# Comfy Cloud MCP
Source: https://docs.comfy.org/agent-tools/cloud

Use Comfy Cloud from Claude Code and Claude Desktop through the Comfy Cloud MCP server — generate images, video, audio, and 3D, search models and nodes, and run workflows.

<Note>
  This is a **Comfy Cloud** feature and is only available in the cloud version. To learn more about Comfy Cloud, see [Comfy Cloud](/get_started/cloud).
</Note>

## Overview

The **Comfy Cloud MCP server** connects AI agents to [Comfy Cloud](https://cloud.comfy.org) over the [Model Context Protocol](https://modelcontextprotocol.io). Once connected, you can generate images, video, audio, and 3D, search models, nodes, and templates, and run ComfyUI workflows — all from a chat with your agent.

Support is currently scoped to **Claude Code** and **Claude Desktop**, which sign in with **OAuth** — a one-time browser sign-in. Support for more clients is coming.

## Install

Pick your client:

<CardGroup>
  <Card title="Claude Code" icon="terminal" href="#claude-code">
    Install the plugin — connection and commands in one step.
  </Card>

  <Card title="Claude Desktop" icon="desktop" href="#claude-desktop">
    Add a custom connector in the app, then sign in.
  </Card>
</CardGroup>

### <span><Icon icon="terminal" /></span> Claude Code

Install the **comfy-cloud** plugin — it adds the MCP connection and the slash commands in one step.

<Steps>
  <Step title="Add the marketplace">
    ```
    /plugin marketplace add Comfy-Org/comfy-skills
    ```
  </Step>

  <Step title="Install the plugin">
    ```
    /plugin install comfy-cloud@comfy-skills
    ```
  </Step>

  <Step title="Sign in">
    Run `/mcp`, select **comfy-cloud** → **Authenticate**. Your browser opens to sign in, and tokens refresh automatically.
  </Step>
</Steps>

The plugin adds these slash commands:

| Command                          | What it does                        |
| -------------------------------- | ----------------------------------- |
| `/comfy-cloud:generate-image`    | Generate, edit, or modify an image  |
| `/comfy-cloud:generate-video`    | Generate, edit, or extend a video   |
| `/comfy-cloud:generate-audio`    | Generate audio                      |
| `/comfy-cloud:generate-3d`       | Generate a 3D model                 |
| `/comfy-cloud:remove-background` | Remove the background from an image |
| `/comfy-cloud:upscale-image`     | Upscale an image                    |
| `/comfy-cloud:search-models`     | Search available models             |
| `/comfy-cloud:search-nodes`      | Search for nodes                    |
| `/comfy-cloud:search-templates`  | Find pre-built workflows            |
| `/comfy-cloud:help`              | See what you can do                 |

<Accordion title="Prefer just the connection, without the plugin?">
  Add the server directly (no slash commands):

  ```bash theme={null}
  claude mcp add --transport http comfy-cloud https://cloud.comfy.org/mcp
  ```

  Then run `/mcp`, select **comfy-cloud** → **Authenticate**. Add `-s user` to make it available in all your projects.
</Accordion>

### <span><Icon icon="desktop" /></span> Claude Desktop

Claude Desktop adds Comfy Cloud as a **custom connector** through its UI, then runs the OAuth sign-in.

<Steps>
  <Step title="Open Connectors">
    In Claude Desktop, open **Customize**, then choose **Connectors**.

    <img alt="Claude Desktop Connectors" />
  </Step>

  <Step title="Add a custom connector">
    Click the **+** button, then choose **Add custom connector**.

    <img alt="Add custom connector" />
  </Step>

  <Step title="Enter the server URL">
    Name it anything (for example, *Comfy Cloud*) and set the **Remote MCP server URL** to:

    ```
    https://cloud.comfy.org/mcp
    ```

    <img alt="Connector details" />
  </Step>

  <Step title="Sign in">
    Click **Add**, then sign in through Claude Desktop when prompted. You are connected.

    <img alt="Sign in through Claude Desktop" />
  </Step>
</Steps>

### Headless / CI (API key)

Claude Code and Claude Desktop use OAuth, so you do not need an API key. For **headless or CI** setups where no browser is available, authenticate with an API key instead:

<Steps>
  <Step title="Create a key">
    Go to [platform.comfy.org/profile/api-keys](https://platform.comfy.org/profile/api-keys), click **New API Key**, and copy it (it starts with `comfyui-`).
  </Step>

  <Step title="Add the server with the key header">
    ```bash theme={null}
    claude mcp add --transport http comfy-cloud https://cloud.comfy.org/mcp -H "X-API-Key: comfyui-…"
    ```
  </Step>
</Steps>

## FAQ

<AccordionGroup>
  <Accordion title="Which clients are supported?">
    Claude Code and Claude Desktop today, both signing in with OAuth. Support for more clients is coming.
  </Accordion>

  <Accordion title="Do I need an API key?">
    Not for Claude Code or Claude Desktop — they use OAuth. An API key is only needed for headless or CI setups with no browser.
  </Accordion>

  <Accordion title="Do the slash commands work in Claude Desktop?">
    No. The slash commands ship in the Claude Code plugin. Claude Desktop connects to the same MCP server (so the tools work — just ask in plain language), but it doesn't support Claude Code plugins or slash commands.
  </Accordion>

  <Accordion title="The sign-in did not open a browser.">
    In Claude Code, run `/mcp`, select **comfy-cloud**, and choose **Authenticate**. In Claude Desktop, reopen the connector from **Customize → Connectors** and trigger sign-in.
  </Accordion>
</AccordionGroup>


# Agent Tools / MCP
Source: https://docs.comfy.org/agent-tools/index

Connect AI agents to ComfyUI via the Model Context Protocol (MCP) for image, video, audio, and 3D content generation.

ComfyUI provides **two MCP servers** that let AI agents (Claude Desktop, Claude Code, Cursor, Amp, and other MCP-compatible clients) generate images, video, audio, and 3D content — with no local ComfyUI installation or GPU required.

<CardGroup>
  <Card title="Comfy Cloud MCP" icon="cloud" href="/agent-tools/cloud">
    Connect to the hosted MCP server at <code>cloud.comfy.org</code>. Runs workflows on Cloud GPUs, uses pre-installed models, and searches the full template library.

    <br />

    <br />

    **Closed beta** — sign up for the waitlist.
  </Card>

  <Card title="Comfy Partner MCP" icon="plug" href="/agent-tools/partner-mcp">
    Run a local MCP server using the Comfy Partner-Node SDK. Provides unified <code>generate\_image</code>, <code>generate\_video</code>, <code>generate\_3d</code>, and more tools across 30+ partner providers.

    <br />

    <br />

    **Waitlist** — sign up for early access.
  </Card>
</CardGroup>

***

## Which One Should I Use?

|               | Comfy Cloud MCP                    | Comfy Partner MCP                                                           |
| ------------- | ---------------------------------- | --------------------------------------------------------------------------- |
| **Type**      | Remote (hosted)                    | Local (runs on your machine)                                                |
| **Requires**  | Comfy Cloud subscription           | [Comfy API key](/development/api-development/getting-an-api-key)            |
| **Models**    | Comfy Cloud models (pre-installed) | 30+ partner providers (BFL, Ideogram, Kling, Runway, Veo, ElevenLabs, etc.) |
| **Workflows** | Full ComfyUI workflow execution    | Partner API generation (no custom workflows)                                |
| **GPU**       | Cloud GPUs (no local GPU needed)   | No GPU needed (API-based)                                                   |
| **Access**    | Closed beta (waitlist)             | Waitlist                                                                    |

***

## What is MCP?

The **Model Context Protocol (MCP)** is an open standard that allows AI assistants to interact with external tools and services through a standardized interface. Instead of an AI agent needing to know custom API formats for every service, MCP provides a uniform way to expose tools.

When you connect an MCP server to Claude Desktop, Claude Code, Cursor, or Amp, the AI assistant can:

* **Generate images** from text descriptions
* **Create videos** from text or images
* **Generate 3D models** from text or images
* **Generate audio and music** using AI models
* **Search models and templates** to find the right tools for your task

...all through natural language conversation, without writing API calls manually.


# Comfy Partner MCP
Source: https://docs.comfy.org/agent-tools/partner-mcp

A local MCP server providing unified generation tools across 30+ partner providers (BFL, Ideogram, Kling, Runway, Veo, Meshy, ElevenLabs, and more).

<Warning>
  **Private preview — waitlist required.** The Comfy Partner MCP server is currently in a private preview. Features and APIs may change. [Sign up for the waitlist](#) to request access.
</Warning>

Comfy Partner MCP is a local MCP server that provides AI agents with unified generation tools across **30+ partner providers**, including BFL, Ideogram, Kling, Runway, Veo, Meshy, ElevenLabs, and more. It uses a single canonical request shape for all generation types.

**Key features:**

* 🎨 **6 generation modalities** — image, video, 3D, SVG, audio, and music
* 🔌 **30+ providers** under one interface
* 💻 **Local server** — runs on your machine, connects to the Comfy API
* 🔍 **Built-in model search** with BM25 text search
* 🧩 **Drop-in compatible** with Claude Desktop, Claude Code, and Amp

***

## Requirements

* **Node.js 20+**
* **pnpm 10**
* **[Comfy API key](/development/api-development/getting-an-api-key)** (starts with `comfyui-`) — get one from the Comfy partner dashboard

***

## Installation

```bash theme={null}
git clone <repo-url> partner-mcp
cd partner-mcp
pnpm install
pnpm build
```

After building, the MCP server launcher is at `packages/mcp/dist/bin.js`.

***

## Configuration

Add the server to your MCP client config. The same JSON format works across Claude Desktop, Claude Code, and Amp:

```json theme={null}
{
  "mcpServers": {
    "comfy-partner": {
      "command": "node",
      "args": ["/ABSOLUTE/PATH/TO/partner-mcp/packages/mcp/dist/bin.js"],
      "env": {
        "COMFY_API_KEY": "comfyui-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
      }
    }
  }
}
```

**Client config locations:**

| Client         | Config file                                                                                                                         |
| -------------- | ----------------------------------------------------------------------------------------------------------------------------------- |
| Claude Desktop | `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) / `%APPDATA%/Claude/claude_desktop_config.json` (Windows) |
| Claude Code    | `~/.claude/mcp.json` (or run `claude mcp add`)                                                                                      |
| Amp            | Settings → MCP Servers, or `~/.config/amp/settings.json`                                                                            |

After adding the config, restart your MCP client. You should see **10 tools** registered under the `comfy-partner` server.

To verify the server starts correctly before wiring it into a client, run it directly — it should print the JSON-RPC handshake and then idle:

```bash theme={null}
COMFY_API_KEY=comfyui-... node /ABSOLUTE/PATH/TO/partner-mcp/packages/mcp/dist/bin.js
```

***

## Environment Variables

| Variable                   | Required | Purpose                                                                                              |
| -------------------------- | -------- | ---------------------------------------------------------------------------------------------------- |
| `COMFY_API_KEY`            | yes      | API key (`comfyui-…`). Sent as `X-API-Key` header.                                                   |
| `COMFY_API_BASE_URL`       | no       | Override the proxy host (defaults to production Comfy API).                                          |
| `COMFY_INLINE_LIMIT_KB`    | no       | Cap (KB) for inlining image bytes in tool results. Default `600`.                                    |
| `COMFY_MCP_RESOURCE_LINKS` | no       | Force `resource_link` content blocks on/off. Defaults to an allowlist (`claude-*`, `mcp-inspector`). |

***

## Available Tools

The MCP server exposes **10 tools**. After a successful install, your MCP client should show all 10 registered under the `comfy-partner` server.

| Tool             | Description                                                                                      |
| ---------------- | ------------------------------------------------------------------------------------------------ |
| `generate_image` | Generate still images — text-to-image, edit, or upscale                                          |
| `generate_video` | Generate video clips — text-to-video, image-to-video, or lipsync                                 |
| `generate_3d`    | Generate 3D meshes (GLB/FBX/OBJ) from text or a reference image                                  |
| `generate_svg`   | Generate SVG vector illustrations from a text prompt                                             |
| `generate_audio` | Generate speech, voice clones, or sound effects from text                                        |
| `generate_music` | Generate instrumental or vocal music from a prompt                                               |
| `media_upload`   | Upload a file (image/video/audio) and get a `media:<id>` reference for use in `generate_*` calls |
| `read_media`     | Fetch and render a media artifact inline — accepts an HTTPS URL or a `media:…` token             |
| `models_explore` | Discover models, search by capability, and read a model's full call shape                        |
| `balance`        | Get the current account's remaining balance in USD                                               |

***

## Example Prompts

After installing, try these in your AI assistant:

```
Generate an image of a cat astronaut floating in space, photorealistic style
```

```
Generate a short video of a sunset over the ocean
```

```
Create a 3D model of a modern chair
```

```
Generate music with a calm, lo-fi vibe, about 30 seconds long
```

***

## Related

* [Comfy Cloud MCP](/agent-tools/cloud) — Hosted MCP server for Comfy Cloud workflow execution
* [Comfy Partner Nodes CLI](/comfy-cli/reference#generate-partner-nodes) — Use partner nodes from the command line


# Import models
Source: https://docs.comfy.org/cloud/import-models

Learn how to import models from Civitai and Hugging Face to Comfy Cloud

<Note>
  This is a **Comfy Cloud** feature and is only available in the cloud version. To learn more about Comfy Cloud, see [Comfy Cloud](/get_started/cloud).
</Note>

## Overview

Comfy Cloud allows you to import models directly from Civitai and Hugging Face. This feature is available for users with a **Creator** subscription or higher.

## Requirements

* **Subscription**: Creator tier or above
* **Supported sources**: Civitai and Hugging Face

## How to import models

### 1. Access the import feature

<img alt="Import" />

1. Click the **Models** button in the left sidebar to open the Model Library.
2. In the Model Library modal, click the **Import** button.

### 2. Paste the link

1. Paste the model link you obtained from Hugging Face or Civitai.
   <img alt="Import Modal" />

2. If the link is valid, you will see a confirmation indicator and can click the `Continue` button to proceed.
   <img alt="Import Modal" />

3. Select the model type and target folder.
   <img alt="Import Modal" />

4. Wait for the model to finish downloading.
   <img alt="Import Modal" />

5. Once downloaded, you can find the model in your Model Library.

## How to view imported models

In the Model Library, select "My Models" in the dropdown filter to filter out the models you imported.

<img alt="Imported Models" />

## How to get model import links

### 1. Get link from Civitai

1. Go to [Civitai](https://civitai.com/) and find the model you want to import.
2. Right-click the download button and select "Copy link address" to get the model download link.

<img alt="Copy Civitai Link" />

### 2. Get link from Hugging Face

1. Go to [Hugging Face](https://huggingface.co/) and find the model repository you want to import.
2. Navigate to the model files page. Supported formats are typically ".safetensor" or ".sft" files. Click on the specific model name to enter its detail page.

<img alt="Copy Huggingface model link" />

3. On the detail page, click the `Copy Download Link` button to get the model download link.

<img alt="Copy Huggingface model link" />

## Import private models

If you want to import private models from Hugging Face or Civitai, you need to configure your API keys first.

### 1. Generate your API keys

First, you need to generate API keys from the respective platforms:

<Tabs>
  <Tab title="Civitai">
    1. Log in to Civitai and visit [https://civitai.com/user/account](https://civitai.com/user/account).
    2. Generate your API key in the account settings.

       <img alt="Civitai API Key" />
  </Tab>

  <Tab title="Hugging Face">
    1. Visit [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens).

    2. Generate your API token.

       <img alt="Hugging Face API Key" />

    3. Make sure your token has read access to the repositories containing the private models you want to import.

       <img alt="Hugging Face Token Permissions" />
  </Tab>
</Tabs>

### 2. Save your API keys

1. Go to [Comfy Cloud Settings](https://cloud.comfy.org) and navigate to the **Secrets** section.

<img alt="Settings Secrets" />

2. Click to add your API keys (you can name the key anything you like):

<img alt="Add Secret Key" />

3. Make sure your API keys have access permissions to the private models you want to import.

### 3. Import the private model

Once your API keys are configured, you can import private models using the same process as public models:

1. Get the model link from Hugging Face or Civitai.
2. Paste the link in the import modal.
3. The system will automatically use your saved API keys to access the private model.

<Note>
  Make sure your API key has the necessary permissions to access the specific private model you want to import.
</Note>

## FAQ

<AccordionGroup>
  <Accordion title="Are there restrictions on what models I can upload?">
    Yes. Only **safetensor** file types are supported. There is effectively no file size limit (up to 100GB).
  </Accordion>

  <Accordion title="Are the models I upload private or shared with everyone?">
    Models you import are **private to you**. Only you can see the models in your library.
  </Accordion>

  <Accordion title="Can I upload my own custom models from my local hard drive?">
    Currently, you need to upload the model to a **public Hugging Face or Civitai repository** first, then import from those platforms.
  </Accordion>

  <Accordion title="Can I upload chunked model files?">
    No. You will need to combine chunked model files into one file before importing.
  </Accordion>

  <Accordion title="Is this feature included in my current cloud subscription?">
    This feature is available for **Creator** and **Pro** plans only.
  </Accordion>

  <Accordion title="Is this feature accessible on the Desktop or portable versions of Comfy?">
    No. This is a **Cloud-only** feature.
  </Accordion>

  <Accordion title="Can I delete a model that I uploaded?">
    Yes. You can delete models you imported. Note that models uploaded by the Comfy internal team cannot be deleted.
  </Accordion>
</AccordionGroup>


# Share workflows
Source: https://docs.comfy.org/cloud/share-workflow

Learn how to share your Comfy Cloud workflows with others via shareable links

<Note>
  This is a **Comfy Cloud** feature and is only available in the cloud version. To learn more about Comfy Cloud, see [Comfy Cloud](/get_started/cloud).
</Note>

## Overview

Comfy Cloud allows you to share your workflows with others by generating a shareable link. Recipients can view the workflow along with all its inputs, outputs, and any assets referenced in the workflow.

<Warning>
  **Shared links include your workflow assets.** Anyone with the link can see not only the workflow layout but also media used in it—such as uploaded images, masks, and other files tied to nodes. Do not share links for workflows that contain private or sensitive content.
</Warning>

## How to share a workflow

<Steps>
  <Step title="Build your workflow">
    Create and finalize the workflow you want to share in Comfy Cloud.
  </Step>

  <Step title="Click the share button">
    In the top-right corner of the workflow page, click the **Share** button.

    <img alt="Share button in the workflow toolbar" />
  </Step>

  <Step title="Save the workflow">
    If your workflow has not been saved yet, you will be prompted to enter a filename and save it before sharing.

    <img alt="Save workflow before sharing" />
  </Step>

  <Step title="Create a shareable link">
    After saving, click **Create a link** to generate a shareable link. The link includes the workflow, its inputs and outputs, and the assets used in the graph.

    <img alt="Create a shareable link" />
  </Step>

  <Step title="Copy and share the link">
    Once the link is generated, copy it and send it to anyone you want to share the workflow with.

    <img alt="Copy the share link" />
  </Step>
</Steps>

## Update a shared workflow

If you make changes to a workflow that has already been shared:

1. Save the updated workflow.
2. Click the **Share** button again.
3. Select **Update** to refresh the existing shared link with your latest changes.

<img alt="Update an existing share link" />

The original link will automatically reflect the updated workflow content. Recipients using the same link will see the latest version.


# Custom Nodes
Source: https://docs.comfy.org/development/core-concepts/custom-nodes

Learn about installing, enabling dependencies, updating, disabling, and uninstalling custom nodes in ComfyUI

## About Custom Nodes

After installing ComfyUI, you'll discover that it includes many built-in nodes. These native nodes are called **Comfy Core** nodes, which are officially maintained by ComfyUI.

Additionally, there are numerous [**custom nodes**](https://registry.comfy.org) created by various authors from the ComfyUI community. These custom nodes bring extensive functionality to ComfyUI, greatly expanding its capabilities and feature boundaries.

In this guide, we'll cover various operations related to custom nodes, including installation, updates, disabling, uninstalling, and dependency installation.

Anyone can develop their own custom extensions for ComfyUI and share them with others. You can find many community custom nodes [here](https://registry.comfy.org). If you want to develop your own custom nodes, visit the section below to get started:

<Card title="Start Developing Custom Nodes" icon="link" href="/custom-nodes/overview">
  Learn how to start developing a custom node
</Card>

## Custom Node Management

In this section we will cover:

* Installing custom nodes
* Installing node dependencies
* Custom node version control
* Uninstalling custom nodes
* Temporarily disabling custom nodes
* Handling custom node dependency conflicts

### 1. Installing Custom Nodes

Currently, ComfyUI supports installing custom nodes through multiple methods, including:

* [Install via ComfyUI Manager (Recommended)](#install-via-comfyui-manager)
* Install via Git
* Manual installation

We recommend installing custom nodes through **ComfyUI Manager**, which is a highly significant tool in the ComfyUI custom node ecosystem. It makes custom node management (such as searching, installing, updating, disabling, and uninstalling) simple - you just need to search for the node you want to install in ComfyUI Manager and click install.

However, since all custom nodes are currently stored on GitHub, for regions that cannot access GitHub normally, we have written detailed instructions for different custom node installation methods in this guide.

Additionally, since we recommend using **ComfyUI Manager** for plugin management, we recommend using this tool for plugin management. You can find its source code [here](https://github.com/Comfy-Org/ComfyUI-Manager).
Therefore, in this documentation, we will use installing ComfyUI Manager as a custom node installation example, and supplement how to use it for node management in the relevant introduction sections.

<Tabs>
  <Tab title="Install via ComfyUI Manager">
    Since ComfyUI Manager has very rich functionality, we will use a separate document to introduce the ComfyUI Manager installation chapter. Please visit the link below to learn how to use ComfyUI Manager to install custom nodes.

    <Card title="Install Custom Nodes with ComfyUI Manager" icon="link" href="/installation/install_custom_node#method-1%3A-comfyui-manager-recommended">
      Learn how to use ComfyUI Manager to install custom nodes
    </Card>
  </Tab>

  <Tab title="Install via Git">
    <Steps>
      <Step title="Ensure Git is Installed">
        First, you need to ensure that Git is installed on your system. You can check if Git is installed by entering the following command in your system terminal:

        ```bash theme={null}
        git --version
        ```

        If Git is installed, you will see output similar to the following:

        <img alt="Windows Terminal" />

        If not yet installed, please visit [git-scm.com](https://git-scm.com/) to download the corresponding installation package. Linux users please refer to [git-scm.com/downloads/linux](https://git-scm.com/downloads/linux) for installation instructions.

        <Tip>
          For ComfyUI Desktop version, you can use the Desktop terminal as shown below to complete the installation.

          <img alt="ComfyUI Desktop Terminal" />
        </Tip>
      </Step>

      <Step title="Clone Custom Node Code to Directory">
        After completing the Git installation, we need the repository address of the custom node. Here we use the ComfyUI-Manager repository address as an example:

        ```bash theme={null}
        https://github.com/Comfy-Org/ComfyUI-Manager
        ```

        <Tip>For regions that cannot access GitHub smoothly, you can try using other code hosting service websites to fork the corresponding repository, then use that repository address to complete the node installation, such as gitee, etc.</Tip>

        First, we need to navigate to the ComfyUI custom nodes directory. Using ComfyUI portable version as an example, if the folder location is `D:\ComfyUI_windows_portable`, then you should be able to find the custom nodes folder at `D:\ComfyUI_windows_portable\ComfyUI\custom_nodes`. First, we need to use the `cd` command to enter the corresponding directory:

        ```bash theme={null}
        cd D:\ComfyUI_windows_portable\ComfyUI\custom_nodes
        ```

        Then we use the `git clone` command to complete the node installation:

        ```bash theme={null}
        git clone https://github.com/Comfy-Org/ComfyUI-Manager
        ```

        If everything goes smoothly, you will see output similar to the following:

        <img alt="Install Custom Nodes via Git" />

        This means you have successfully cloned the custom node code. Next, we need to install the corresponding dependencies.
      </Step>

      <Step title="Install Dependencies">
        Please refer to the instructions in the [Installing Node Dependencies](#installing-node-dependencies) section for dependency installation.
      </Step>
    </Steps>
  </Tab>

  <Tab title="Manual Installation">
    Manual installation is not the recommended installation method, but it serves as a backup option when you cannot install smoothly using git.

    <Warning>
      Plugins installed this way will lose the corresponding git version history information and will not be convenient for subsequent version management.
    </Warning>

    <Steps>
      <Step title="Download Custom Node Code ZIP Package">
        For manual installation, we need to first download the corresponding node code and then extract it to the appropriate directory.

        <img alt="Download Node Code" />

        Visit the corresponding custom node repository page:

        1. Click the `Code` button
        2. Then click the `Download ZIP` button to download the ZIP package
        3. Extract the ZIP package
      </Step>

      <Step title="Copy Files to ComfyUI Custom Nodes Directory">
        Copy the extracted code from the above steps to the ComfyUI custom nodes directory. Using ComfyUI portable version as an example, if the folder location is `D:\ComfyUI_windows_portable`, then you should be able to find the custom nodes folder at `D:\ComfyUI_windows_portable\ComfyUI\custom_nodes`. Copy the extracted code from the above steps to the corresponding directory.
      </Step>

      <Step title="Install Dependencies">
        Please refer to the instructions in the [Installing Node Dependencies](#installing-node-dependencies) section for dependency installation.
      </Step>
    </Steps>
  </Tab>
</Tabs>

### 2. Installing Node Dependencies

Custom nodes all require the installation of related dependencies. For example, for ComfyUI-Manager, you can visit the [requirements.txt](https://github.com/Comfy-Org/ComfyUI-Manager/blob/main/requirements.txt) file to view the dependency package requirements.

In the previous steps, we only cloned the custom node code locally and did not install the corresponding dependencies, so next we need to install the corresponding dependencies.

<Note>
  Actually, if you use ComfyUI-Manager to install plugins, ComfyUI Manager will automatically help you complete the dependency installation. You just need to restart ComfyUI after installing the plugin. This is why we strongly recommend using ComfyUI Manager to install custom nodes.

  But perhaps you may not be able to use ComfyUI Manager to install custom nodes smoothly in some situations, so we provide this more detailed dependency installation guide.
</Note>

In the [Dependencies](/development/core-concepts/dependencies) chapter, we introduced the relevant content about dependencies in ComfyUI. ComfyUI is a **Python**-based project, and we built an independent **Python** runtime environment for running ComfyUI. All related dependencies need to be installed in this independent **Python** runtime environment.

If you run `pip install -r requirements.txt` directly in the system-level terminal, the corresponding dependencies may be installed in the system-level **Python** environment, which will cause the dependencies to still be missing in ComfyUI's environment, preventing the corresponding custom nodes from running normally.

So next we need to use ComfyUI's independent Python runtime environment to complete the dependency installation.

Depending on different ComfyUI versions, we will use different methods to install the corresponding dependencies:

<Tabs>
  <Tab title="ComfyUI Portable">
    For ComfyUI Portable version, it uses an embedded Python located in the `\ComfyUI_windows_portable\python_embeded` directory. We need to use this Python to complete the dependency installation.

    First, start the terminal in the portable version directory, or use the `cd` command to navigate to the `\ComfyUI_windows_portable\` directory after starting the terminal.

    <img alt="Start Terminal" />

    Ensure that the terminal directory is `\ComfyUI_windows_portable\`, as shown below for `D:\ComfyUI_windows_portable\`

    <img alt="Terminal" />

    Then use `python_embeded\python.exe` to complete the dependency installation:

    ```bash theme={null}
    python_embeded\python.exe -m pip install -r ComfyUI\custom_nodes\ComfyUI-Manager\requirements.txt
    ```

    Of course, you can replace ComfyUI-Manager with the name of the custom node you actually installed, but make sure that a `requirements.txt` file exists in the corresponding node directory.
  </Tab>

  <Tab title="ComfyUI Desktop">
    <Tip>
      Since ComfyUI Desktop already has ComfyUI-Manager and its dependencies installed during the installation process, and this guide uses ComfyUI Manager as an example for custom node installation, you don't actually need to perform ComfyUI Manager dependency installation in the desktop version.
      If there are no unexpected issues, we recommend using ComfyUI Manager to install custom nodes, so you don't need to manually install dependencies.
    </Tip>

    <img alt="ComfyUI Desktop Terminal" />

    Then use the following command to install the dependencies for the corresponding plugin:

    ```bash theme={null}
    pip install -r .\custom_nodes\<corresponding_custom_node_name>\requirements.txt
    ```

    As shown below, this is the dependency installation for ComfyUI-Hunyuan3Dwrapper:

    <img alt="ComfyUI Desktop Dependency Installation" />
  </Tab>

  <Tab title="Custom Python Environment Users">
    For users with custom Python environments, we recommend using `pip install -r requirements.txt` to complete the dependency installation.
  </Tab>
</Tabs>

### Custom Node Version Control

Custom node version control is actually based on Git version control. You can manage node versions through Git, but ComfyUI Manager has already integrated this version management functionality very well. Many thanks to [@Dr.Lt.Data](https://github.com/ltdrdata) for bringing us such a convenient tool.

In this section, we will still explain these two different plugin version management methods for you, but if you use ZIP packages for manual installation, the corresponding git version history information will be lost, making it impossible to perform version management.

<Tabs>
  <Tab title="Version Management with ComfyUI Manager">
    <Tip>Since we are iterating on ComfyUI Manager, the actual latest interface and steps may change significantly</Tip>

    <Steps>
      <Step title="Enter Node Management Interface">
        Perform the corresponding operations as shown to enter the ComfyUI Manager interface
      </Step>

      <Step title="Find the Corresponding Custom Node Package">
        You can use the corresponding filters to filter out installed node packages and then perform the corresponding node management
      </Step>

      <Step title="Perform Version Switching">
        Switch to the corresponding version. Manager will help you complete the corresponding dependency updates and installation. Usually, you need to restart ComfyUI after switching versions for the changes to take effect.
      </Step>
    </Steps>
  </Tab>

  <Tab title="Version Management with Git">
    <Steps>
      <Step title="Navigate to Directory Using Command Line">
        Find the directory folder where your corresponding node is located, such as `ComfyUI/custom_nodes/ComfyUI-Manager`
        Use the `cd` command to enter the corresponding folder:

        ```bash theme={null}
        cd <your_installation_directory>/ComfyUI/custom_nodes/ComfyUI-Manager
        ```
      </Step>

      <Step title="View Versions Using Git Commands">
        You can use the following command to view all available tags and releases:

        ```bash theme={null}
        git tag
        ```

        This will list all version tags, and you can choose the version you want to switch to.
      </Step>

      <Step title="Switch to Specified Version">
        Use the following command to switch to a specified tag or release:

        ```bash theme={null}
        git checkout <tag_name>
        ```

        Replace `<tag_name>` with the specific version tag you want to switch to.
      </Step>

      <Step title="Switch to Specific Commit Version">
        If you want to switch to a specific commit version, you can use the following command:

        ```bash theme={null}
        git checkout <commit_hash>
        ```

        Replace `<commit_hash>` with the specific commit hash you want to switch to.
      </Step>

      <Step title="Install Dependencies">
        Since the dependencies of the corresponding custom node package may change after version switching, you need to reinstall the dependencies for the corresponding node. Please refer to the instructions in the [Installing Node Dependencies](#2-installing-node-dependencies) section to enter the corresponding environment for installation.
      </Step>
    </Steps>
  </Tab>
</Tabs>

### Uninstalling Custom Nodes

To be updated

### Temporarily Disabling Custom Nodes

To be updated

### Custom Node Dependency Conflicts

To be updated

## ComfyUI Manager

<img alt="ComfyUI Manager Interface" />

This tool is currently included by default in the [Desktop version](/installation/desktop/windows), while in the [Portable version](/installation/comfyui_portable_windows), you need to refer to the installation instructions in the [Install Manager](#installing-custom-nodes) section of this document.

<Note>
  As ComfyUI continues to develop, ComfyUI Manager plays an increasingly important role in ComfyUI. Currently, ComfyUI-Manager has officially joined the Comfy Org organization, officially becoming part of ComfyUI's core dependencies, and continues to be maintained by the original author [Dr.Lt.Data](https://github.com/ltdrdata). You can read [this blog post](https://blog.comfy.org/p/comfyui-manager-joins-comfy-org) for more information.
  In future iterations, we will greatly optimize the use of ComfyUI Manager, so the interface shown in this documentation may differ from the latest version of ComfyUI Manager.
</Note>

### Installing the Manager

If you are running the ComfyUI server application, you need to install the manager. If ComfyUI is running, please close it before continuing.

The first step is to install Git, which is a command-line application for software version control. Git will download the ComfyUI manager from [github.com](https://github.com). Download and install Git from [git-scm.com](https://git-scm.com/).

After installing Git, navigate to the ComfyUI server program directory and enter the folder labeled **custom\_nodes**. Open a command window or terminal. Make sure the command line shows the current directory path as **custom\_nodes**. Run the following command to clone the ComfyUI-Manager repository:

```bash theme={null}
git clone https://github.com/Comfy-Org/ComfyUI-Manager.git
```

This will download the manager. Technically, this is called *cloning a Git repository*.

### Detecting Missing Nodes

After installing the manager, you can detect missing nodes in the manager.

<img alt="ComfyUI Manager Interface" />

## Developing a Custom Node

If you have some development capabilities, please start with the documentation below to learn how to begin developing a custom node.

<Card title="Start Developing Custom Nodes" icon="link" href="/custom-nodes/overview">
  Learn how to start developing a custom node
</Card>


# Dependencies
Source: https://docs.comfy.org/development/core-concepts/dependencies

Understand dependencies in ComfyUI

## A workflow file depends on other files

We often obtain various workflow files from the community, but frequently find that the workflow cannot run directly after loading. This is because a workflow file depends on other files besides the workflow itself, such as media asset inputs, models, custom nodes, related Python dependencies, etc.
ComfyUI workflows can only run normally when all relevant dependencies are satisfied.

ComfyUI workflow dependencies mainly fall into the following categories:

* Assets (media files including audio, video, images, and other inputs)
* Custom nodes
* Python dependencies
* Models (such as Stable Diffusion models, etc.)

## Assets

An AI model is an example of an ***asset***. In media production, an asset is some media file that supplies input data. For example, a video editing program operates on movie files stored on disk. The editing program's project file holds links to these movie file assets, allowing non-destructive editing that doesn't alter the original movie files.

ComfyUI works the same way. A workflow can only run if all of the required assets are found and loaded. Generative AI models, images, movies, and sounds are some examples of assets that a workflow might depend upon. These are therefore known as ***dependent assets*** or ***asset dependencies***.

## Custom Nodes

Custom nodes are an important component of ComfyUI that extend its functionality. They are created by the community and can be installed to add new capabilities to your workflows.

## Python Dependencies

ComfyUI is a Python-based project. We build a standalone Python environment to run ComfyUI, and all related dependencies are installed in this isolated Python environment.

### ComfyUI Dependencies

You can view ComfyUI's current dependencies in the [requirements.txt](https://github.com/Comfy-Org/ComfyUI/blob/master/requirements.txt) file:

```text theme={null}
comfyui-frontend-package==1.32.9
comfyui-workflow-templates==0.7.25
comfyui-embedded-docs==0.3.1
torch
torchsde
torchvision
torchaudio
numpy>=1.25.0
einops
transformers>=4.50.3
tokenizers>=0.13.3
sentencepiece
safetensors>=0.4.2
aiohttp>=3.11.8
yarl>=1.18.0
pyyaml
Pillow
scipy
tqdm
psutil
alembic
SQLAlchemy
av>=14.2.0

#non essential dependencies:
kornia>=0.7.1
spandrel
pydantic~=2.0
pydantic-settings~=2.0
```

As ComfyUI evolves, we may adjust dependencies accordingly, such as adding new dependencies or removing ones that are no longer needed.
So if you use Git to update ComfyUI, you need to run the following command in the corresponding environment after pulling the latest updates:

```bash theme={null}
pip install -r requirements.txt
```

This ensures that ComfyUI's dependencies are up to date for proper operation. You can also modify specific package dependency versions to upgrade or downgrade certain dependencies.

Additionally, ComfyUI's frontend [ComfyUI\_frontend](https://github.com/Comfy-Org/ComfyUI_frontend) is currently maintained as a separate project. We update the `comfyui-frontend-package` dependency version after the corresponding version stabilizes. If you need to switch to a different frontend version, you can check the version information [here](https://pypi.org/project/comfyui-frontend-package/#history).

### Custom Node Dependencies

Thanks to the efforts of many authors in the ComfyUI community, we can extend ComfyUI's functionality by using different custom nodes, enabling impressive creativity.

Typically, each custom node has its own dependencies and a separate `requirements.txt` file.
If you use [ComfyUI Manager](https://github.com/Comfy-Org/ComfyUI-Manager) to install custom nodes, ComfyUI Manager will usually automatically install the corresponding dependencies.

There are also cases where you need to install dependencies manually. Currently, all custom nodes are installed in the `ComfyUI/custom_nodes` directory.

You need to navigate to the corresponding plugin directory in your ComfyUI Python environment and run `pip install -r requirements.txt` to install the dependencies.

If you're using the [Windows Portable version](/installation/comfyui_portable_windows), you can use the following command in the `ComfyUI_windows_portable` directory:

```
python_embeded\python.exe -m pip install -r ComfyUI\custom_nodes\<custom_node_name>\requirements.txt
```

to install the dependencies for the corresponding node.

### Dependency Conflicts

Dependency conflicts are a common issue when using ComfyUI. You might find that after installing or updating a custom node, previously installed custom nodes can no longer be found in ComfyUI's node library, or error pop-ups appear. One possible reason is dependency conflicts.

There can be many reasons for dependency conflicts, such as:

1. Custom node version locking

Some plugins may fix the exact version of a dependency library (e.g., `open_clip_torch==2.26.1`), while other plugins may require a higher version (e.g., `open_clip_torch>=2.29.0`), making it impossible to satisfy both version requirements simultaneously.

**Solution**: You can try changing the fixed version dependency to a range constraint, such as `open_clip_torch>=2.26.1`, and then reinstall the dependencies to resolve these issues.

2. Environment pollution

During the installation of custom node dependencies, it may overwrite versions of libraries already installed by other plugins. For example, multiple plugins may depend on `PyTorch` but require different CUDA versions, and the later installed plugin will break the existing environment.

**Solutions**:

* You can try manually installing specific versions of dependencies in the Python virtual environment to resolve such issues.
* Or create different Python virtual environments for different plugins to resolve these issues.
* Try installing plugins one by one, restarting ComfyUI after each installation to observe if dependency conflicts occur.

3. Custom node dependency versions incompatible with ComfyUI dependency versions

These types of dependency conflicts may be more difficult to resolve, and you may need to upgrade/downgrade ComfyUI or change the dependency versions of custom nodes to resolve these issues.

**Solution**: These types of dependency conflicts may be more difficult to resolve, and you may need to upgrade/downgrade ComfyUI or change the dependency versions of custom nodes to resolve these issues.

## Models

Models are a significant asset dependency for ComfyUI. Various custom nodes and workflows are built around specific models, such as the Stable Diffusion series, Flux series, Ltxv, and others.
These models are an essential foundation for creation with ComfyUI, so we need to ensure that the models we use are properly available. Typically, our models are saved in the corresponding directory under `ComfyUI/models/`. Of course, you can also create an [extra\_model\_paths.yaml](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example) by modifying the template to make additional model paths recognized by ComfyUI.
This allows multiple ComfyUI instances to share the same model library, reducing disk usage.

## Software

An advanced application like ComfyUI also has ***software dependencies***. These are libraries of programming code and data that are required for the application to run. Custom nodes are examples of software dependencies. On an even more fundamental level, the Python programming environment is the ultimate dependency for ComfyUI. The correct version of Python is required to run a particular version of ComfyUI. Updates to Python, ComfyUI, and custom nodes can all be handled from the **ComfyUI Manager** window.

<img alt="ComfyUI Custom Nodes Manager" />


# Links
Source: https://docs.comfy.org/development/core-concepts/links

Understand connection links in ComfyUI

## Links connect nodes

In ComfyUI, the lines or curves drawn between nodes are called ***links*** (also referred to as ***connections*** or wires). They carry data from one node's output to another node's input, defining the flow of your workflow.

Links can be displayed in several visual styles: curves, right angles, straight lines, or hidden entirely.

<img alt="Link styles" />

To change the link style, go to **Setup Menu** → **Display (Lite Graph)** → **Graph** → **Link Render Mode**.

<img alt="Render mode setting" />

You can also temporarily hide all links from the **Canvas Menu**.

<img alt="Canvas Menu" />

<Tip>
  Showing links is especially useful when learning, sharing, or debugging a workflow — they make the data flow visible at a glance. For finished workflows that aren't meant to be edited, hiding links can reduce visual clutter.
</Tip>

### Reroute node

When a workflow becomes complex, link wires can overlap or pass behind nodes, making it hard to read. The **Reroute** node lets you manually redirect a wire through any point in the 2D graph space, keeping the layout clean and legible.

<img alt="ComfyUI Reroute node" />

ComfyUI also has a built-in native reroute feature in the graph canvas. We recommend using this for new workflows.

<img alt="ComfyUI Native Reroute" />

## Color-coding

Every data type in ComfyUI has a distinct color. Node input and output ports, as well as the link wires connecting them, all share this color scheme. **You can only connect ports of the same color** — this ensures type safety across your workflow.

<img alt="ComfyUI Node Data Types" />

| Data type                 | Color        |
| ------------------------- | ------------ |
| Diffusion model           | Lavender     |
| CLIP model                | Yellow       |
| VAE model                 | Rose         |
| Conditioning              | Orange       |
| Latent Image              | Pink         |
| Pixel image               | Blue         |
| Mask                      | Green        |
| Number (integer or float) | Gray         |
| Mesh                      | Bright green |


# Models
Source: https://docs.comfy.org/development/core-concepts/models

How model files fit into ComfyUI workflows: where they go, how to load them, and common fixes.

## Models in plain terms

In ComfyUI, **models** are the weight files that actually run your workflow—things like **checkpoints**, **VAEs**, **LoRAs**, **ControlNets**, and upscalers. The app install is small; these files are **not** included by default. You usually **download them from the web**, place them under `ComfyUI/models/` (or follow a template’s prompts), then choose the file in the right **loader node** (on the canvas, these often appear as nodes whose names start with **Load**).

### Supported models in ComfyUI

* **Built-in / first-party coverage is intentionally limited** but grows over time as ComfyUI and the open-source ecosystem evolve. When a model gains first-class support, you will **usually see a new entry in the [workflow template library](/interface/features/template)** that shows the expected graph and model pairing.
* **Not every checkpoint or weights file works out of the box.** For **natively supported models and their common companion weights**, keep ComfyUI **[up to date](/installation/update_comfyui)** and confirm the matching workflow exists in the **[template library](/interface/features/template)** before assuming your files are in the wrong place.
* **Many other models are enabled through community custom nodes.** Paths, loader nodes, and graph layout can differ from this page’s generic `ComfyUI/models/` guidance—**always follow each project’s README or docs**. ComfyUI is highly extensible, so implementations vary by author. For installation and troubleshooting, see [How to install custom nodes](/installation/install_custom_node).

## Use models in ComfyUI

1. **Get the files into the right place** — Download from community sites such as [Hugging Face](https://huggingface.co), [Civitai](https://civitai.green), or a project’s page on [GitHub](https://github.com), then put them under `ComfyUI/models/` in the subfolder for that type (for example `checkpoints`, `loras`, `vae`).
2. **Add the matching loader node** — Pick the loader for that model type (checkpoint, LoRA, VAE, etc.); in the node list, titles often begin with **Load**.
3. **Pick the file** in that loader node’s dropdown.
4. **Wire the loader node** into the rest of the graph. If you copied files in by hand while ComfyUI was open, **restart** the app (or refresh as needed) so lists update.

### Expect large downloads

A single generative model is often **many gigabytes**. Budget disk space and time when downloading or syncing.

## Beyond the main checkpoint

The main diffusion checkpoint does a lot, but many workflows add **smaller helper models**, for example:

* **LoRA** — lightweight add-ons tuned for a style, character, or concept
* **ControlNet** — extra guidance from edges, depth, pose, etc.
* **Inpainting** — fill or replace regions inside an existing image

<img alt="auxiliary models" />

## Uninstalling models

There is no “uninstall” button in the UI yet. To remove a model, **delete its file** (or files) from the folder under `ComfyUI/models/` where you put it.

## Adding Extra Model Paths

If you want to manage your model files outside of `ComfyUI/models`, you may have the following reasons:

* You have multiple ComfyUI instances and want them to share model files to save disk space
* You have different types of GUI programs (such as WebUI) and want them to use the same model files
* Model files cannot be recognized or found

We provide a way to add extra model search paths via the `extra_model_paths.yaml` configuration file

### Open Config File

<Tabs>
  <Tab title="Portable/Manual Install">
    For the ComfyUI version such as [portable](/installation/comfyui_portable_windows) and [manual](/installation/manual_install), you can find an example file named `extra_model_paths.yaml.example` in the root directory of ComfyUI:

    ```
    ComfyUI/extra_model_paths.yaml.example
    ```

    Copy and rename it to `extra_model_paths.yaml` for use. Keep it in ComfyUI's root directory at `ComfyUI/extra_model_paths.yaml`.
    You can also find the config example file [here](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example)
  </Tab>

  <Tab title="ComfyUI Desktop">
    If you are using the [ComfyUI Desktop](/installation/desktop/windows) application, you can follow the image below to open the extra model config file:

    <img alt="Open Config File" />

    Or open it directly at:

    <Tabs>
      <Tab title="Windows">
        ```
        C:\Users\YourUsername\AppData\Roaming\ComfyUI\extra_models_config.yaml
        ```
      </Tab>

      <Tab title="macOS">
        ```
        ~/Library/Application Support/ComfyUI/extra_models_config.yaml
        ```
      </Tab>
    </Tabs>

    You should keep the file in the same directory, should not move these files to other places.
  </Tab>
</Tabs>

If the file does not exist, you can create it yourself with any text editor.

### Example Structure

Suppose you want to add the following model paths to ComfyUI:

```
📁 YOUR_PATH/
  ├── 📁models/
  |   ├── 📁 loras/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 checkpoints/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 vae/
  |   │   └── xxxxx.safetensors
  |   └── 📁 controlnet/
  |       └── xxxxx.safetensors
```

Then you can configure the `extra_model_paths.yaml` file like below to let ComfyUI recognize the model paths on your device:

```
my_custom_config:
    base_path: YOUR_PATH
    loras: models/loras/
    checkpoints: models/checkpoints/
    vae: models/vae/
    controlnet: models/controlnet/
```

or

```
my_custom_config:
    base_path: YOUR_PATH/models/
    loras: loras
    checkpoints: checkpoints
    vae: vae
    controlnet: controlnet
```

<Warning>
  For the desktop version, please add the configuration to the existing configuration path without overwriting the path configuration generated during installation. Please back up the corresponding file before modification, so that you can restore it when you make a mistake.
</Warning>

Or you can refer to the default [extra\_model\_paths.yaml.example](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example) for more configuration options. After saving, you need to **restart ComfyUI** for the changes to take effect.

Below is the original config example:

```yaml theme={null}
#Rename this to extra_model_paths.yaml and ComfyUI will load it


#config for a1111 ui
#all you have to do is change the base_path to where yours is installed
a111:
    base_path: path/to/stable-diffusion-webui/

    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet

#config for comfyui
#your base path should be either an existing comfy install or a central folder where you store all of your models, loras, etc.

#comfyui:
#     base_path: path/to/comfyui/
#     # You can use is_default to mark that these folders should be listed first, and used as the default dirs for eg downloads
#     #is_default: true
#     checkpoints: models/checkpoints/
#     clip: models/clip/
#     clip_vision: models/clip_vision/
#     configs: models/configs/
#     controlnet: models/controlnet/
#     diffusion_models: |
#                  models/diffusion_models
#                  models/unet
#     embeddings: models/embeddings/
#     loras: models/loras/
#     upscale_models: models/upscale_models/
#     vae: models/vae/

#other_ui:
#    base_path: path/to/ui
#    checkpoints: models/checkpoints
#    gligen: models/gligen
#    custom_nodes: path/custom_nodes

```

For example, if your WebUI is located at `D:\stable-diffusion-webui\`, you can modify the corresponding configuration to

```yaml theme={null}
a111:
    base_path: D:\stable-diffusion-webui\
    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet
```

### Add Extra Custom Nodes Path

Besides adding external models, you can also add custom nodes paths that are not in the default path of ComfyUI

<Tip>
  Please note that this will not change the default installation path of custom nodes, but will add an extra path search when starting ComfyUI. You still need to complete the installation of custom node dependencies in the corresponding environment to ensure the integrity of the running environment.
</Tip>

Below is a simple configuration example (MacOS), please modify it according to your actual situation and add it to the corresponding configuration file, save it and restart ComfyUI for the changes to take effect:

```yaml theme={null}
my_custom_nodes:
  custom_nodes: /Users/your_username/Documents/extra_custom_nodes
```

## Common issues

<AccordionGroup>
  <Accordion title="Does ComfyUI support GGUF format models?">
    ComfyUI does not natively support GGUF format models. To use GGUF models, you need to install community custom nodes such as [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF).
  </Accordion>

  <Accordion title="Why can't I find my model?">
    If you've installed a model but can't find it in ComfyUI, try these steps:

    * Verify the model is in the correct location:
      * For **ComfyUI Desktop**: Go to **Help** menu → **Open Folder** → **Open Model Folder** to check the model installation path
      * Ensure your model file is placed in the correct subfolder (e.g., `checkpoints`, `loras`, `vae`)
    * Press the `r` key to refresh node definitions so ComfyUI can detect the model
    * Restart ComfyUI
    * Ensure the correct model is selected in the loader node
  </Accordion>
</AccordionGroup>

## Want a bit more background?

<AccordionGroup>
  <Accordion title="What does “model” mean here?">
    Here, a **model** is a data file that encodes what a network learned—enough to turn inputs (like text and noise) into outputs (like an image). Common examples in image workflows are **diffusion** checkpoints, text/image encoders such as **CLIP**, and **upscalers** like RealESRGAN.
  </Accordion>

  <Accordion title="Base models and community variants">
    Large **base** models from labs and open-source projects are general-purpose. The community often **fine-tunes** or merges them into new checkpoints and LoRAs that look better for a given style, run a bit lighter, or add new behavior—same idea as picking a favorite checkpoint on Civitai or Hugging Face.
  </Accordion>
</AccordionGroup>


# Nodes
Source: https://docs.comfy.org/development/core-concepts/nodes

Understand the concept of a node in ComfyUI.

In ComfyUI, nodes are the fundamental building blocks for executing tasks. Each node is an independently built module, whether it's a **Comfy Core** node or a **Custom Node**, with its own unique functionality. Nodes connect to each other through links, allowing us to build complex functionality like assembling LEGO blocks.
The combinations of different nodes create the unlimited possibilities of ComfyUI.

<img alt="Comfy Core K-Sampler Node" />

For example, in the K-Sampler node, you can see it has multiple inputs and outputs, and also includes multiple parameter settings. These parameters determine the logic of node execution. Behind each node is well-written Python logic, allowing you to achieve corresponding functionality without having to write code yourself.

<Note>
  ComfyUI is under active development, so some details here may be outdated. If you spot something that's changed, feel free to [help us update the docs](https://github.com/Comfy-Org/docs).
</Note>

## Nodes perform operations

In computer science, a ***node*** is a container for information, usually including programmed instructions to perform some task. Nodes almost never exist in isolation, they're almost always connected to other nodes in a networked graph. In ComfyUI, nodes take the visual form of boxes that are connected to each other.

ComfyUI nodes are usually ***function operators***. This means that they operate on some data to perform a function. A function is a process that accepts input data, performs some operation on it, and produces output data. In other words, nodes do some work, contributing to the completion of a task such as generating an image. So ComfyUI nodes almost always have at least one input or output, and usually have multiple inputs and outputs.

## Different Node States

<img alt="Node States" />

In ComfyUI, nodes have multiple states. Here are some common node states:

1. **Normal State**: The default state
2. **Running State**: The running state, typically displayed when a node is executing after you start running the workflow
3. **Error State**: Node error, typically displayed after running the workflow if there's a problem with the node's input, indicated by red marking of the erroneous input node. You need to fix the problematic input to ensure the workflow runs correctly
4. **Missing State**: This state usually appears after importing workflows, with two possibilities:
   * Comfy Core native node missing: This usually happens because ComfyUI has been updated, but you're using an older version of ComfyUI. You need to update ComfyUI to resolve this issue
   * Custom node missing: The workflow uses custom nodes developed by third-party authors, but your local ComfyUI version doesn't have these custom nodes installed. You can use [ComfyUI Manager](/manager/overview) to find and install them, or follow [How to install custom nodes](/installation/install_custom_node) for other methods

## Connections Between Nodes

In ComfyUI, nodes are connected through [links](/development/core-concepts/links), allowing data of the same type to flow between different processing units to achieve the final result.

<img alt="ComfyUI Node Links" />

Each node receives some input, processes it through its module, and converts it to corresponding output. Connections between different nodes must conform to the data type requirements. In ComfyUI, we use different colors to distinguish node data types. Below are some basic data types:

<img alt="ComfyUI Node Data Types" />

| Data type                 | Color        |
| ------------------------- | ------------ |
| diffusion model           | lavender     |
| CLIP model                | yellow       |
| VAE model                 | rose         |
| conditioning              | orange       |
| latent image              | pink         |
| pixel image               | blue         |
| mask                      | green        |
| number (integer or float) | light green  |
| mesh                      | bright green |

As ComfyUI evolves, we may expand to more data types to meet the needs of more scenarios.

### Connecting and Disconnecting Nodes

<img alt="ComfyUI Node Connecting" />

**Connecting**: Drag from the output point of one node to the input of the same color on another node to connect them
**Disconnecting**: Click on the input endpoint and drag the mouse left button to disconnect, or cancel the connection through the midpoint menu of the link

## Node Appearance

<img alt="Node Appearance" />

We provide various style settings for you to customize the appearance of nodes:

* Modify styles
* Double-click the node title to modify the node name
* Resize the node by dragging any corner

<video />

### Node Badges

<img alt="Node Badges" />

We provide multiple node badge display features, such as:

* Node ID
* Node source

Currently, **Comfy Core nodes** use a fox icon for display, while custom nodes use their names. This way you can quickly understand which node package a node comes from.

You can set the corresponding display in the menu:

<img alt="Badge Settings" />

## Node Context Menus

Node context menus are mainly divided into two types:

* Context menu for the node itself
* Context menu for inputs/outputs

### Node Context Menu

By right-clicking on a node, you can expand the corresponding node context menu:

<img alt="Node Context Menu" />

In the node's right-click context menu, you can:

* Adjust the node's color style
* Modify the title
* Clone, copy, or delete the node
* Set the node's mode

In this menu, besides appearance-related settings, the following menu operations are important:

* **Mode**: Set the node's mode: Always, Never, Bypass

#### Mode

For modes, you may notice that we currently provide: Always, Never, On Event, On Trigger - four modes, but actually only **Always** and **Never** are effective. **On Event** and **On Trigger** are currently ineffective as we haven't fully implemented this feature. Additionally, you can understand **Bypass** as a mode. Below is an explanation of the available modes:

* **Always**: The default node mode. The node will execute whenever it runs for the first time or when any of its inputs change since the last execution
* **Never**: The node will never execute under any circumstances, as if it's been deleted. Subsequent nodes cannot read or receive any data from it
* **Bypass**: The node will never execute under any circumstances, but subsequent nodes can still try to obtain data that hasn't been processed by this node

Below is a comparison of the `Never` and `Bypass` modes:

<img alt="Never vs Bypass Mode" />

In this comparison example, you can see that both workflows apply two LoRA models simultaneously, with the difference being that one `Load LoRA` node is set to `Never` mode while the other is set to `Bypass` mode.

* The node set to `Never` mode causes subsequent nodes to show errors because they don't receive any input data
* The node set to `Bypass` mode still allows subsequent nodes to receive unprocessed data, so they load the output data from the first `Load LoRA` node, allowing the subsequent workflow to continue running normally

### Input/Output Context Menu

This context menu is mainly related to the data type of the corresponding input/output:

<img alt="Node Input/Output Context Menu" />

When dragging the input/output of a node, if a connection appears but you haven't connected to another node's input or output, releasing the mouse will pop up a context menu for the input/output, used to quickly add related types of nodes.
You can adjust the number of node suggestions in the settings:

<img alt="Node Suggestion Count" />

## Node Selection Toolbox

<video />

The **Node Selection Toolbox** is a floating tool that provides quick operations for nodes. When you select a node, it hovers above the selected node. Through this toolbox, you can:

* Change the node's color
* Quickly set the node to Bypass mode (not execute during runtime)
* Lock the node
* Delete the node

Of course, these functions can also be found in the right-click menu of the corresponding node. The node selection toolbox just provides a shortcut operation. If you want to disable this feature, you can turn it off in the settings.

<img alt="Disable Node Selection Toolbox" />

## Subgraphs

You can collapse a selection of nodes into one reusable subgraph node to tidy complex graphs and reuse the same structure across workflows.

<Card title="Subgraph" icon="share-nodes" href="/interface/features/subgraph">
  Learn how to create, edit, nest, and publish subgraph blueprints to the node library.
</Card>

## Custom Nodes

ComfyUI includes many **Comfy Core** nodes in the base installation. The community also maintains a large catalog of [**custom nodes**](https://registry.comfy.org) for specialized workflows.

For a full summary of how to install custom nodes—**ComfyUI Manager**, Git clone, ZIP download, dependencies, and safety tips—see [How to install custom nodes](/installation/install_custom_node).

### ComfyUI Manager

Use **ComfyUI Manager** for everyday custom node work: search and install from the registry, update or disable packages, detect missing nodes from imported workflows, and manage models and snapshots alongside extensions. Desktop builds ship with it enabled; portable and manual installs may need to turn it on first.

<Card title="ComfyUI Manager" icon="puzzle-piece" href="/manager/overview">
  Overview, enabling the Manager, and node installation workflows
</Card>


# Properties
Source: https://docs.comfy.org/development/core-concepts/properties



## Nodes are containers for properties

Nodes usually have ***properties***. Also known as ***parameters*** or ***attributes***, node properties are variables that can be changed. Some properties can be adjusted manually by the user, using a data entry field called a ***widget***. Other properties can be driven automatically by other nodes connected to the property ***input slot*** or port. Usually, a property can be converted from widget to input and vice versa, allowing users to control property values manually or automatically.

Properties can take many forms and hold many different types of information. For example, a **Load Checkpoint** node has a single property:  the file path to the generative model checkpoint file. A **KSampler** node has multiple properties such as the number of sampling **steps**, **CFG** scale, **sampler\_name**, etc.

<img alt="node properties" />

## Data types

Information can come in many different forms, called ***data types***. For example, alphanumeric text is known as a ***string***, a whole number is an ***integer***, and a number with a decimal point is known as a ***floating point*** number or ***float***. New data types are always being added to ComfyUI.

ComfyUI is written in the Python scripting language, which is very forgiving about data types. By contrast, the ComfyUI environment is very ***strongly typed***. This means that different data types can’t be mixed up. For example, we can’t connect an image output to an integer input. This is a huge benefit to users, guiding them to proper workflow construction and preventing program errors.


# Workflow
Source: https://docs.comfy.org/development/core-concepts/workflow



## A graph of nodes

ComfyUI is an environment for building and running generative content ***workflows***. In this context, a workflow is defined as a collection of program objects called ***nodes*** that are connected to each other, forming a network. This network is also known as a ***graph***.

A ComfyUI workflow can generate any type of media: image, video, audio, AI model, AI agent, and so on.

## Sample workflows

To get started, use the built-in [Workflow Templates](/interface/features/template). Open them via `Workflow` → `Browse Workflow Templates` in the menu. These templates use only the Core nodes included in the ComfyUI installation and will automatically prompt you to download any required models. A thriving community of developers has created a rich [ecosystem](https://registry.comfy.org) of custom nodes to extend the functionality of ComfyUI.

### Simple Example

<img alt="simple workflow" />

## Visual programming

A node-based computer program like ComfyUI provides a level of power and flexibility that can’t be achieved with traditional menu- and button-driven applications. The ComfyUI node graph is not limited by the tools provided in a traditional computer application. It’s a high-level ***visual programming environment*** allowing users to design complex systems without needing to write program code or understand advanced mathematics.

Many other computer applications use this same node graph paradigm. Examples include the compositing application called Nuke, the 3D programs Maya and Blender, the Unreal real-time graphics engine, and the interactive media authoring program called Max.

### More Complex Example

<img alt="complex workflow" />

## Procedural framework

Another term used to describe a node-based application is ***procedural framework***. Procedural means generative: some procedure or algorithm is employed to generate content such as a 3D model or a musical composition.

ComfyUI is all of these things: a node graph, a visual programming environment, and a procedural framework. What makes ComfyUI different (and amazing!) is that its radically open structure allows us to generate any type of media asset such as picture, movie, sound, 3D model, AI model, etc.

In the context of ComfyUI, the term ***workflow*** is a synonym for the node network or graph. It corresponds to the ***scene graph*** in a 3D or multimedia program: the network of all of the nodes within a particular disk file. 3D programs call this a ***scene file***. Video editing, compositing, and multimedia programs usually call it a ***project file***.

## Saving workflows

The ComfyUI workflow is automatically saved in the metadata of any generated image, allowing users to open and use the graph that generated the image. A workflow can also be stored in a human-readable text file that follows the JSON data format. This is necessary for media formats that don’t support metadata. ComfyUI workflows stored as JSON files are very small, allowing convenient versioning, archiving, and sharing of graphs, independently of any generated media.


# Comfy Cloud - Official ComfyUI Cloud Platform Powered by RTX 6000 Pro
Source: https://docs.comfy.org/get_started/cloud

Run ComfyUI workflows online with Comfy Cloud, the official cloud platform powered by NVIDIA RTX 6000 Pro GPUs. No local installation required.

<Card title="Access Comfy Cloud" icon="cloud" href="https://comfy.org/cloud">
  Click here to access ComfyUI Cloud directly
</Card>

## What is Comfy Cloud?

ComfyUI Cloud is the cloud version of ComfyUI with the same features as the local version. Everything is pre-installed and ready to use.

### Key features

<CardGroup>
  <Card title="Zero setup" icon="bolt">
    No installation required. All models and custom nodes are pre-installed and ready to use
  </Card>

  <Card title="Powerful GPUs" icon="microchip">
    Run workflows fast on our powerful server GPUs without needing your own hardware
  </Card>

  <Card title="Always up-to-date" icon="arrows-rotate">
    Automatically stays current with the latest ComfyUI releases and features
  </Card>

  <Card title="Access anywhere" icon="globe">
    Use ComfyUI from any device with an internet connection - no local installation needed
  </Card>
</CardGroup>

## Cloud vs local

ComfyUI offers both an official cloud version, [Comfy Cloud](https://comfy.org/cloud), and an open-source self-hosted version. If you have a powerful GPU, running ComfyUI locally is a great option. The cloud version, on the other hand, is an online service that's ready to use instantly—simply open the URL, no installation or setup required.

| Category                | Comfy Cloud                                                                                               | Self-hosted (local ComfyUI)                                                                                                                        |
| ----------------------- | --------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Cost**                | Monthly Subscription                                                                                      | Free                                                                                                                                               |
| **GPU**                 | Powerful Blackwell RTX 6000 Pros                                                                          | Bring your own GPU                                                                                                                                 |
| **Technical Knowledge** | No technical knowledge required.                                                                          | While desktop and portable give you easy ways to get started, you'll need to troubleshoot custom node installations and local installation issues. |
| **Custom Nodes**        | Use pre-installed custom nodes and never worry about compatibility issues.                                | Install any custom node you want, but you'll need to manage it yourself.                                                                           |
| **Models**              | Use pre-installed models. Import LoRA models from Civitai. Import models from Hugging Face (coming soon). | Use any models you want, but you'll need to download them first.                                                                                   |
| **Notable Differences** | Easy to onboard your team                                                                                 | Works offline, infinitely customizable                                                                                                             |
| **Get started**         | [Run ComfyUI Cloud](https://comfy.org/cloud)                                                              | [Install ComfyUI locally](/installation/system_requirements)                                                                                       |

## Pricing and subscription

<Card title="Check pricing" icon="tag" href="https://www.comfy.org/cloud/pricing">
  View pricing and subscription options for Comfy Cloud
</Card>

## How to use ComfyUI Cloud

Using ComfyUI Cloud is essentially the same as using your local ComfyUI. If this is your first time using ComfyUI, here are some quick tips to get started:

<Steps>
  <Step title="Select a template">
    Click the template icon in the left sidebar to browse available workflows.

    <img alt="Open workflow template" />
  </Step>

  <Step title="Select the workflow you want to run">
    Click on the template you want to run.

    <img alt="Select workflow template" />
  </Step>

  <Step title="Update template inputs">
    1. In the loaded workflow, since we have pre-installed all models in the cloud version, all templates are ready to run immediately after loading.
    2. If you need to make updates, you only need to provide image inputs or text prompts. Check the `Load Image` node or `CLIP Text Encode` node.
       <img alt="Check inputs" />
  </Step>

  <Step title="Run your workflow">
    If everything is correct, click the "Run" icon or use the shortcut "Ctrl + Enter" to run the workflow.

    <img alt="Run workflow" />
  </Step>

  <Step title="View output">
    After clicking run, our service will start allocating a machine for your workflow. You can check the execution status of the corresponding workflow in the queue panel.

    <img alt="View queue" />
  </Step>

  <Step title="Save content locally">
    After the workflow execution is complete, you can save the generated content locally. Depending on the asset type, the save method is as follows:

    <Tabs>
      <Tab title="Save images">
        In the queue panel or on the save image node, right-click on the generated image and select "Save image" to save the image locally.

        <img alt="Save image assets" />
      </Tab>

      <Tab title="Save videos">
        In the queue panel or on the save video node:

        1. Click the three dots on the browser player component to open the menu
        2. Select "Download" to save the video locally.

           <img alt="Save video assets" />
      </Tab>

      <Tab title="Save audio">
        In the queue panel or on the save audio node:

        1. Click the three dots on the browser player component to open the menu
        2. Select "Download" to save the audio file locally.

           <img alt="Save audio assets" />
      </Tab>

      <Tab title="Save 3D assets">
        In the 3D browser node menu, select the "Export" option, choose the format you want to save, and the 3D file will be saved locally.

        <img alt="Save 3D assets" />
      </Tab>
    </Tabs>
  </Step>
</Steps>

## Feedback

If you have any thoughts, suggestions, or run into any issues, simply click the "Feedback" icon. This will directly send your feedback to us.

<img alt="Feedback" />

## Frequently Asked Questions

<Card title="View FAQs" icon="circle-question" href="https://comfy.org/cloud">
  View frequently asked questions and answers about Comfy Cloud, including pricing, features, limitations, and more
</Card>

## Next steps

<CardGroup>
  <Card title="Cloud API" icon="code" href="/development/cloud/overview">
    Programmatically run workflows via the Cloud API
  </Card>

  <Card title="Tutorials" icon="book" href="/tutorials/basic/text-to-image">
    Explore tutorials to learn ComfyUI workflows
  </Card>

  <Card title="Support" icon="life-ring" href="https://discord.com/invite/comfyorg">
    Join our Discord community for help
  </Card>
</CardGroup>


# Getting Started with AI Image Generation
Source: https://docs.comfy.org/get_started/first_generation

This tutorial will guide you through your first image generation with ComfyUI, covering basic interface operations like workflow loading, model installation, and image generation

<Note>
  This guide is intended for **local users** running ComfyUI on their own device. If you'd prefer not to install anything locally, try our official cloud service instead.
</Note>

<Card title="Try Comfy Cloud" icon="cloud" href="http://cloud.comfy.org/?template=image_z_image_turbo&utm_source=docs">
  Run ComfyUI online with zero setup. Sign in with Google to get **400 free credits every month**.
</Card>

This guide aims to help you understand ComfyUI's basic operations and complete your first image generation. We'll cover:

1. Loading example workflows
   * Loading from ComfyUI's workflow templates
   * Loading from images with workflow metadata
2. Model installation guidance
   * Automatic model installation
   * Manual model installation
3. Completing your first text-to-image generation

## About Text-to-Image

Text-to-Image is a fundamental AI drawing feature that generates images from text descriptions. It's one of the most commonly used functions in AI art generation. You can think of the process as telling your requirements (positive and negative prompts) to an artist (the drawing model), who will then create what you want. Detailed explanations about text-to-image will be covered in the [Text to Image](/tutorials/basic/text-to-image) chapter.

## ComfyUI Text-to-Image Workflow Tutorial

### 1. Launch ComfyUI

Make sure you've followed the [installation guide](/installation/system_requirements) to start ComfyUI and can successfully enter the ComfyUI interface. Alternatively, you can use [Comfy Cloud](/get_started/cloud) to use ComfyUI without any installation.

<img alt="ComfyUI Interface" />

If you have not installed ComfyUI, please choose a suitable version to install based on your device.

<AccordionGroup>
  <Accordion title="ComfyUI Desktop">
    ComfyUI Desktop currently supports standalone installation for **Windows and MacOS (ARM)**, currently in Beta

    * Code is open source on [Github](https://github.com/Comfy-Org/desktop)

    <Tip>
      Because Desktop is always built based on the **stable release**, so the latest updates may take some time to experience for Desktop, if you want to always experience the latest version, please use the portable version or manual installation
    </Tip>

    You can choose the appropriate installation for your system and hardware below

    <Tabs>
      <Tab title="Windows">
        <Card title="ComfyUI Desktop (Windows) Installation Guide" icon="link" href="/installation/desktop/windows">
          Suitable for **Windows** version with **Nvidia** GPU
        </Card>
      </Tab>

      <Tab title="MacOS(Apple Silicon)">
        <Card title="ComfyUI Desktop (MacOS) Installation Guide" icon="link" href="/installation/desktop/macos">
          Suitable for MacOS with **Apple Silicon**
        </Card>
      </Tab>

      <Tab title="Linux">
        <Note>ComfyUI Desktop **currently has no Linux prebuilds**, please visit the [Manual Installation](/installation/manual_install) section to install ComfyUI</Note>
      </Tab>
    </Tabs>
  </Accordion>

  <Accordion title="ComfyUI Portable (Windows)">
    Portable version is a ComfyUI version that integrates an independent embedded Python environment, using the portable version you can experience the latest features, currently only supports **Windows** system

    <Card title="ComfyUI Portable (Windows) Installation Guide" icon="link" href="/installation/comfyui_portable_windows">
      Supports **Windows** ComfyUI version running on **Nvidia GPUs** or **CPU-only**, always use the latest commits and completely portable.
    </Card>
  </Accordion>

  <Accordion title="Manual Installation">
    <Card title="ComfyUI Manual Installation Guide" icon="link" href="/installation/manual_install">
      Supports all system types and GPU types (Nvidia, AMD, Intel, Apple Silicon, Ascend NPU, Cambricon MLU)
    </Card>
  </Accordion>
</AccordionGroup>

### 2. Load Default Text-to-Image Workflow

ComfyUI usually loads the default text-to-image workflow automatically when launched. However, you can try different methods to load workflows to familiarize yourself with ComfyUI's basic operations:

<Tabs>
  <Tab title="Load from Workflow Template">
    <img alt="ComfyUI Interface" />

    Follow the numbered steps in the image:

    1. Click the **Fit View** button in the bottom right to ensure any loaded workflow isn't hidden
    2. Click the **folder icon (workflows)** in the sidebar
    3. Click the **Browse example workflows** button at the top of the Workflows panel

    Continue with:

    <img alt="Load Workflow" />

    4. Select the first default workflow **Image Generation** to load it
  </Tab>

  <Tab title="Load from Images with Metadata">
    All images generated by ComfyUI contain metadata including workflow information. You can load workflows by:

    * Dragging and dropping a ComfyUI-generated image into the interface
    * Using menu **Workflows** -> **Open** to open an image

    Try loading the workflow using this example image:
    ![ComfyUI-Text to Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/text-to-image-workflow.png)
  </Tab>

  <Tab title="Load from workflow.json">
    ComfyUI workflows can be stored in JSON format. You can export workflows using menu **Workflows** -> **Export**.

    Try downloading and loading this example workflow:

    <a href="https://github.com/Comfy-Org/docs/blob/main/public/text-to-image.json">
      <p>Download text-to-image.json</p>
    </a>

    After downloading, use menu **Workflows** -> **Open** to load the JSON file.
  </Tab>
</Tabs>

### 3. Model Installation

Most ComfyUI installations don't include base models by default. After loading the workflow, if you don't have the [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors) model installed, you'll see this prompt:

First, ComfyUI will warn you that some models are missing:

<img alt="Missing models warning" />

Click the warning to see which model is missing and the download link:

<img alt="Missing model details" />

All models are stored in `<your ComfyUI installation>/ComfyUI/models/` with subfolders like `checkpoints`, `embeddings`, `vae`, `lora`, `upscale_model`, etc. ComfyUI detects models in these folders and paths configured in `extra_model_paths.yaml` at startup.

<Tabs>
  <Tab title="ComfyUI Desktop (Find models folder)">
    <img alt="Desktop models folder path" />

    On **ComfyUI Desktop**, the models folder location may differ from portable/other installs. Follow these steps:

    1. Click the **logo** at the top-left
    2. Open **Help** → **Open folder**
    3. Choose **Open models folder**

    If your interface is in another language, the exact menu text may differ, but the flow is the same: **Help** → **Open folder** → **Open models folder** (or the closest equivalent in your language).
  </Tab>

  <Tab title="ComfyUI Portable (Find models folder)">
    For the portable version, the models folder is usually located at:

    `ComfyUI_windows_portable/ComfyUI/models/`
  </Tab>
</Tabs>

You can install models through:

<Tabs>
  <Tab title="Automatic Download">
    After you click the **Download** button, ComfyUI will execute the download, and different behaviors will be performed depending on the version you are using.

    <Tabs>
      <Tab title="ComfyUI Desktop">
        The desktop version will automatically complete the model download and save it to the `<your ComfyUI installation location>/ComfyUI/models/checkpoints` directory.
        You can wait for the installation to complete or view the installation progress in the model panel on the sidebar.

        <img alt="Model Download Progress" />

        <Warning>
          Automatic downloads typically fetch models from **Hugging Face**. Make sure your network can reliably reach Hugging Face.

          If the download **does not start** or shows **no progress for a long time**, copy the model link from the missing-model details (or use the manual installation section below) and install the model manually.
        </Warning>
      </Tab>

      <Tab title="ComfyUI Portable">
        The browser will execute file downloads. Please save the file to the `<your ComfyUI installation location>/ComfyUI_windows_portable/ComfyUI/models/checkpoints` directory after the download is complete.
      </Tab>
    </Tabs>
  </Tab>

  <Tab title="Manual Installation">
    Visit [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors) and follow this guide:

    <img alt="Hugging Face Model Download" />

    Save the downloaded file to:

    <Tabs>
      <Tab title="ComfyUI Desktop">
        Save to `<your ComfyUI installation>/ComfyUI/models/checkpoints`

        <img alt="ComfyUI Desktop Model Save Location" />
      </Tab>

      <Tab title="ComfyUI Portable">
        Save to `ComfyUI_windows_portable/ComfyUI/models/checkpoints`

        <img alt="ComfyUI Portable Model Save Location" />
      </Tab>
    </Tabs>

    Refresh or restart ComfyUI after saving.
  </Tab>
</Tabs>

### 4. Load Model and Generate Your First Image

After you install or update models, press **`R`** on your keyboard to refresh object definitions and update model lists in nodes (for example, the dropdown in **Load Checkpoint**). Then continue with the steps below:

<img alt="Run workflow" />

1. In the **Load Checkpoint** node, ensure **v1-5-pruned-emaonly-fp16.safetensors** is selected
2. Click `Run` or press `Ctrl + Enter` to generate

The result will appear in the **Save Image** node. Right-click to save locally.

<img alt="ComfyUI First Image Generation Result" />

For detailed text-to-image instructions, see our comprehensive guide:

<Card title="ComfyUI Text-to-Image Workflow Guide" icon="link" href="/tutorials/basic/text-to-image">
  Click here for detailed text-to-image workflow instructions
</Card>

## Troubleshooting

### Model Loading Issues

If the `Load Checkpoint` node shows no models or displays "null", verify your model installation location and try refreshing or restarting ComfyUI.


# ComfyUI Official Documentation
Source: https://docs.comfy.org/index

ComfyUI Official Documentation

<div>
  <div>
    <div>
      <img />

      <img />
    </div>

    <div>
      <h1>
        ComfyUI Official Documentation
      </h1>
    </div>
  </div>

  <div>
    <div>
      <a href="https://github.com/Comfy-Org/ComfyUI/">
        <Icon icon="github" />
      </a>

      <a href="https://x.com/ComfyUI">
        <Icon icon="x-twitter" />
      </a>

      <a href="https://discord.com/invite/comfyorg">
        <Icon icon="discord" />
      </a>

      <a href="https://www.youtube.com/@comfyorg">
        <Icon icon="youtube" />
      </a>
    </div>
  </div>

  <div>
    <p>
      The most powerful open source node-based application for generative AI
    </p>

    <div>
      <h2>Getting Started</h2>

      <CardGroup>
        <Card title="Download & Install" icon="download" href="/installation/system_requirements">
          Install ComfyUI on Windows, macOS, or Linux
        </Card>

        <Card title="First Generation" icon="rocket" href="/get_started/first_generation">
          Create your first AI-generated image
        </Card>

        <Card title="Basic Concepts" icon="lightbulb" href="/development/core-concepts/workflow">
          Understand workflows, nodes, and links
        </Card>

        <Card title="Comfy Hub" icon="globe" href="https://comfy.org/workflows">
          Discover the world's top creators and workflows
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>Learn & Tutorials</h2>

      <CardGroup>
        <Card title="Interface Guide" icon="window-maximize" href="/interface/overview">
          Navigate the ComfyUI interface
        </Card>

        <Card title="Tutorials" icon="book-open" href="/tutorials/basic/text-to-image">
          Step-by-step guides for common tasks
        </Card>

        <Card title="Built-in Nodes" icon="diagram-project" href="/built-in-nodes/overview">
          Learn about each node in ComfyUI
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>Development & Extension</h2>

      <CardGroup>
        <Card title="Development Guide" icon="code" href="/development/overview">
          Contribute to ComfyUI development
        </Card>

        <Card title="Custom Nodes" icon="puzzle-piece" href="/custom-nodes/overview">
          Create and publish custom nodes
        </Card>

        <Card title="Local API" icon="terminal" href="/development/comfyui-server/comms_overview">
          Integrate with local ComfyUI server
        </Card>

        <Card title="Cloud API" icon="cloud" href="/development/cloud/overview">
          Run workflows via ComfyUI Cloud API
        </Card>

        <Card title="Cloud API Reference" icon="book" href="/development/cloud/api-reference">
          Explore the ComfyUI Cloud API reference
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>AI Agents & MCP</h2>

      <CardGroup>
        <Card title="Agent Tools Overview" icon="robot" href="/agent-tools">
          Connect AI agents via MCP for image, video, audio, and 3D generation
        </Card>

        <Card title="Cloud MCP Server" icon="server" href="/agent-tools/cloud">
          Hosted MCP at cloud.comfy.org — run workflows on Cloud GPUs
        </Card>

        <Card title="Partner MCP" icon="plug" href="/agent-tools/partner-mcp">
          Local MCP with unified generate tools across 30+ partner providers
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>Get Help</h2>

      <CardGroup>
        <Card title="Contact Support" icon="headset" href="/support/contact-support">
          Get help from our support team
        </Card>

        <Card title="Account Management" icon="user-gear" href="/account/create-account">
          Create, login, and manage your account
        </Card>

        <Card title="Billing Support" icon="credit-card" href="/support/subscription/subscribing">
          Manage subscriptions and payments
        </Card>

        <Card title="Troubleshooting" icon="circle-question" href="/troubleshooting/overview">
          Resolve common issues and errors
        </Card>

        <Card title="Community" icon="users" href="/community/links">
          Join the ComfyUI community
        </Card>
      </CardGroup>
    </div>

    <div>
      <h2>About ComfyUI</h2>

      <p>
        Written by <a href="https://github.com/comfyanonymous">comfyanonymous</a> and other <a href="https://github.com/Comfy-Org/ComfyUI/graphs/contributors">contributors</a>.
      </p>

      <ul>
        <li><strong>ComfyUI</strong> is a node-based interface and inference engine for generative AI</li>
        <li>Users can combine various AI models and operations through nodes to achieve highly customizable and controllable content generation</li>
        <li>ComfyUI is completely open source and can run on your local device</li>
      </ul>
    </div>
  </div>
</div>


# ComfyUI(portable) Windows — Local Self-Hosted
Source: https://docs.comfy.org/installation/comfyui_portable_windows

This tutorial will guide you on how to download and start using ComfyUI Portable and run the corresponding programs

**ComfyUI Portable** is a standalone packaged complete ComfyUI Windows version that has integrated an independent **Python (python\_embeded)** required for ComfyUI to run. You only need to extract it to use it.

This guide section will walk you through installing ComfyUI Portable.

## Download ComfyUI Portable

<Note>Choose the download package that matches your GPU type. ComfyUI Portable provides separate packages for different GPU hardware.</Note>

<Tabs>
  <Tab title="Nvidia GPU">
    ### Standard portable for Nvidia GPUs

    <CardGroup>
      <Card title="Nvidia GPU (CUDA 13.0, Python 3.13)" icon="download" href="https://github.com/Comfy-Org/ComfyUI/releases/latest/download/ComfyUI_windows_portable_nvidia.7z">
        For modern Nvidia GPUs (RTX series)
      </Card>

      <Card title="Nvidia GPU (CUDA 12.6, Python 3.12)" icon="download" href="https://github.com/Comfy-Org/ComfyUI/releases/latest/download/ComfyUI_windows_portable_nvidia_cu126.7z">
        For Nvidia 10 series and older GPUs
      </Card>
    </CardGroup>

    Download the file and extract it with [7-ZIP](https://7-zip.org/). The extracted folder structure:

    ```
    ComfyUI_windows_portable
    ├── 📂ComfyUI                   // ComfyUI main program
    ├── 📂python_embeded            // Independent Python environment
    ├── 📂update                    // Batch scripts for upgrading portable version
    ├── README_VERY_IMPORTANT.txt   // ComfyUI Portable usage instructions in English
    ├── run_cpu.bat                 // Double click to start ComfyUI (CPU only)
    └── run_nvidia_gpu.bat          // Double click to start ComfyUI (Nvidia GPU)
    ```

    Double click `run_nvidia_gpu.bat` to launch ComfyUI.
  </Tab>

  <Tab title="AMD GPU">
    ### Portable for AMD GPUs

    <Card title="AMD GPU" icon="download" href="https://github.com/Comfy-Org/ComfyUI/releases/latest/download/ComfyUI_windows_portable_amd.7z">
      Download for AMD GPUs (ROCm)
    </Card>

    Download the file and extract it with [7-ZIP](https://7-zip.org/). The extracted folder structure:

    ```
    ComfyUI_windows_portable_amd
    ├── 📂ComfyUI                   // ComfyUI main program
    ├── 📂python_embeded            // Independent Python environment
    ├── 📂update                    // Batch scripts for upgrading portable version
    ├── README_VERY_IMPORTANT.txt   // ComfyUI Portable usage instructions in English
    ├── run_cpu.bat                 // Double click to start ComfyUI (CPU only)
    └── run_amd_gpu.bat             // Double click to start ComfyUI (AMD GPU)
    ```

    Double click `run_amd_gpu.bat` to launch ComfyUI.
  </Tab>

  <Tab title="Intel GPU">
    ### Portable for Intel GPUs

    <Card title="Intel GPU" icon="download" href="https://github.com/Comfy-Org/ComfyUI/releases/latest/download/ComfyUI_windows_portable_intel.7z">
      Download for Intel GPUs
    </Card>

    Download the file and extract it with [7-ZIP](https://7-zip.org/). The extracted folder structure:

    ```
    ComfyUI_windows_portable_intel
    ├── 📂ComfyUI                   // ComfyUI main program
    ├── 📂python_embeded            // Independent Python environment
    ├── 📂update                    // Batch scripts for upgrading portable version
    ├── README_VERY_IMPORTANT.txt   // ComfyUI Portable usage instructions in English
    ├── run_cpu.bat                 // Double click to start ComfyUI (CPU only)
    └── run_intel_gpu.bat           // Double click to start ComfyUI (Intel GPU)
    ```

    Double click `run_intel_gpu.bat` to launch ComfyUI.
  </Tab>
</Tabs>

After downloading and extracting, you will see the command running as shown in the image below

<img alt="ComfyUI Portable Command Prompt" />

When you see something similar to the image

```
To see the GUI go to: http://127.0.0.1:8188
```

At this point, your ComfyUI service has started. Normally, ComfyUI will automatically open your default browser and navigate to `http://127.0.0.1:8188`. If it doesn't open automatically, please manually open your browser and visit this address.

<Warning>During use, please do not close the corresponding command line window, otherwise ComfyUI will stop running</Warning>

## Adding Extra Model Paths

If you want to manage your model files outside of `ComfyUI/models`, you may have the following reasons:

* You have multiple ComfyUI instances and want them to share model files to save disk space
* You have different types of GUI programs (such as WebUI) and want them to use the same model files
* Model files cannot be recognized or found

We provide a way to add extra model search paths via the `extra_model_paths.yaml` configuration file

### Open Config File

<Tabs>
  <Tab title="Portable/Manual Install">
    For the ComfyUI version such as [portable](/installation/comfyui_portable_windows) and [manual](/installation/manual_install), you can find an example file named `extra_model_paths.yaml.example` in the root directory of ComfyUI:

    ```
    ComfyUI/extra_model_paths.yaml.example
    ```

    Copy and rename it to `extra_model_paths.yaml` for use. Keep it in ComfyUI's root directory at `ComfyUI/extra_model_paths.yaml`.
    You can also find the config example file [here](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example)
  </Tab>

  <Tab title="ComfyUI Desktop">
    If you are using the [ComfyUI Desktop](/installation/desktop/windows) application, you can follow the image below to open the extra model config file:

    <img alt="Open Config File" />

    Or open it directly at:

    <Tabs>
      <Tab title="Windows">
        ```
        C:\Users\YourUsername\AppData\Roaming\ComfyUI\extra_models_config.yaml
        ```
      </Tab>

      <Tab title="macOS">
        ```
        ~/Library/Application Support/ComfyUI/extra_models_config.yaml
        ```
      </Tab>
    </Tabs>

    You should keep the file in the same directory, should not move these files to other places.
  </Tab>
</Tabs>

If the file does not exist, you can create it yourself with any text editor.

### Example Structure

Suppose you want to add the following model paths to ComfyUI:

```
📁 YOUR_PATH/
  ├── 📁models/
  |   ├── 📁 loras/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 checkpoints/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 vae/
  |   │   └── xxxxx.safetensors
  |   └── 📁 controlnet/
  |       └── xxxxx.safetensors
```

Then you can configure the `extra_model_paths.yaml` file like below to let ComfyUI recognize the model paths on your device:

```
my_custom_config:
    base_path: YOUR_PATH
    loras: models/loras/
    checkpoints: models/checkpoints/
    vae: models/vae/
    controlnet: models/controlnet/
```

or

```
my_custom_config:
    base_path: YOUR_PATH/models/
    loras: loras
    checkpoints: checkpoints
    vae: vae
    controlnet: controlnet
```

<Warning>
  For the desktop version, please add the configuration to the existing configuration path without overwriting the path configuration generated during installation. Please back up the corresponding file before modification, so that you can restore it when you make a mistake.
</Warning>

Or you can refer to the default [extra\_model\_paths.yaml.example](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example) for more configuration options. After saving, you need to **restart ComfyUI** for the changes to take effect.

Below is the original config example:

```yaml theme={null}
#Rename this to extra_model_paths.yaml and ComfyUI will load it


#config for a1111 ui
#all you have to do is change the base_path to where yours is installed
a111:
    base_path: path/to/stable-diffusion-webui/

    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet

#config for comfyui
#your base path should be either an existing comfy install or a central folder where you store all of your models, loras, etc.

#comfyui:
#     base_path: path/to/comfyui/
#     # You can use is_default to mark that these folders should be listed first, and used as the default dirs for eg downloads
#     #is_default: true
#     checkpoints: models/checkpoints/
#     clip: models/clip/
#     clip_vision: models/clip_vision/
#     configs: models/configs/
#     controlnet: models/controlnet/
#     diffusion_models: |
#                  models/diffusion_models
#                  models/unet
#     embeddings: models/embeddings/
#     loras: models/loras/
#     upscale_models: models/upscale_models/
#     vae: models/vae/

#other_ui:
#    base_path: path/to/ui
#    checkpoints: models/checkpoints
#    gligen: models/gligen
#    custom_nodes: path/custom_nodes

```

For example, if your WebUI is located at `D:\stable-diffusion-webui\`, you can modify the corresponding configuration to

```yaml theme={null}
a111:
    base_path: D:\stable-diffusion-webui\
    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet
```

### Add Extra Custom Nodes Path

Besides adding external models, you can also add custom nodes paths that are not in the default path of ComfyUI

<Tip>
  Please note that this will not change the default installation path of custom nodes, but will add an extra path search when starting ComfyUI. You still need to complete the installation of custom node dependencies in the corresponding environment to ensure the integrity of the running environment.
</Tip>

Below is a simple configuration example (MacOS), please modify it according to your actual situation and add it to the corresponding configuration file, save it and restart ComfyUI for the changes to take effect:

```yaml theme={null}
my_custom_nodes:
  custom_nodes: /Users/your_username/Documents/extra_custom_nodes
```

## First Image Generation

After successful installation, you can refer to the section below to start your ComfyUI journey\~

<Card title="First Image Generation" icon="link" href="/get_started/first_generation">
  This tutorial will guide you through your first model installation and text-to-image generation
</Card>

## Additional ComfyUI Portable Instructions

### 1. Upgrading ComfyUI Portable

You can use the batch commands in the update folder to upgrade your ComfyUI Portable version

```
ComfyUI_windows_portable
└─ 📂update
   ├── update.py
   ├── update_comfyui.bat                          // Update ComfyUI to the latest commit version
   ├── update_comfyui_and_python_dependencies.bat  // Only use when you have issues with your runtime environment
   └── update_comfyui_stable.bat                   // Update ComfyUI to the latest stable version
```

### 2. Setting Up LAN Access for ComfyUI Portable

If your ComfyUI is running on a local network and you want other devices to access ComfyUI, you can modify the corresponding `.bat` file (e.g. `run_nvidia_gpu.bat`, `run_amd_gpu.bat`, or `run_cpu.bat`) using Notepad to complete the configuration. This is mainly done by adding `--listen` to specify the listening address.
Below is an example of the `run_nvidia_gpu.bat` file command with the `--listen` parameter added

```bat theme={null}
.\python_embeded\python.exe -s ComfyUI\main.py --listen --windows-standalone-build
pause
```

After enabling ComfyUI, you will notice the final running address will become

```
Starting server

To see the GUI go to: http://0.0.0.0:8188
To see the GUI go to: http://[::]:8188
```

You can press `WIN + R` and type `cmd` to open the command prompt, then enter `ipconfig` to view your local IP address. Other devices can then access ComfyUI by entering `http://your-local-IP:8188` in their browser.


# Linux Desktop — Local Self-Hosted
Source: https://docs.comfy.org/installation/desktop/linux

This article introduces how to download, install and use ComfyUI Desktop for Linux

<Warning>Linux pre-built packages are not yet available. Please try [manual installation.](/installation/manual_install)</Warning>

When Linux desktop packages become available, you can configure external model paths:

## Adding External Model Paths

If you have models stored in other locations on your computer outside the ComfyUI installation directory, you can add them to ComfyUI by configuring the `extra_models_config.yaml` file.

For ComfyUI Desktop, this file is located at:

* On Windows: `C:\Users\<YOUR_USERNAME>\AppData\Roaming\ComfyUI\extra_models_config.yaml`
* On macOS: `~/Library/Application Support/ComfyUI/extra_models_config.yaml`
* On Linux: `~/.config/ComfyUI/extra_models_config.yaml`

For detailed instructions, see [Models documentation](/development/core-concepts/models#adding-external-model-paths)


# MacOS Desktop — Local Self-Hosted
Source: https://docs.comfy.org/installation/desktop/macos

This article introduces how to download, install and use ComfyUI Desktop for MacOS

**ComfyUI Desktop** is a standalone installation version that can be installed like regular software.
It supports quick installation and automatic configuration of the **Python environment and dependencies**, and supports one-click import of existing ComfyUI settings, models, workflows, and files.

ComfyUI Desktop is an open source project, please visit the full code [here](https://github.com/Comfy-Org/desktop).

<Note>ComfyUI Desktop (MacOS) only supports Apple Silicon</Note>

This tutorial will guide you through the software installation process and explain related configuration details.

<Warning>As **ComfyUI Desktop** is still in **Beta** status, the actual installation process may change</Warning>

## ComfyUI Desktop (MacOS) Download

Please click the button below to download the installation package for MacOS **ComfyUI Desktop**

<a href="https://download.comfy.org/mac/dmg/arm64">
  <p>Download for MacOS</p>
</a>

## Install via Homebrew

ComfyUI Desktop can also be installed via [Homebrew](https://brew.sh/):

```
brew install comfyui
```

## ComfyUI Desktop Installation Steps

Double-click the downloaded installation package file. As shown in the image, drag the **ComfyUI** application into the **Applications** folder following the arrow

<img alt="ComfyUI Installation Package" />

If your folder shows as below with a prohibition sign on the icon after opening the installation package, it means your current system version is not compatible with **ComfyUI Desktop**

<img alt="ComfyUI logo" />

Then find the **ComfyUI icon** in **Launchpad** and click it to enter ComfyUI initialization settings

<img alt="ComfyUI Lanchpad" />

## ComfyUI Desktop Initialization Process

<Steps>
  <Step title="Start Screen">
    <Tabs>
      <Tab title="Normal Start">
        <img alt="ComfyUI Installation Steps - Start" />

        Click **Get Started** to begin initialization
      </Tab>

      <Tab title="Maintenance Page">
        There are many reasons you might have issues installing ComfyUI. Maybe a network connection failed when installing pytorch (15 GB). Or you don’t have git installed. The maintenance page automatically opens when it detects an issue and provides a way to resolve the issue.

        You can use it to resolve most issues:

        * Create a python virtual environment
        * Reinstall all missing core dependencies to your Python virtual environment that’s managed by Desktop
        * Install git, VC redis
        * Choose a new install location

        The default maintenance page displays the current error content

        <img alt="ComfyUI Maintenance Page" />

        Clicking `All` allows you to view all the content that can be operated on currently

        <img alt="ComfyUI Maintenance Page" />
      </Tab>
    </Tabs>
  </Step>

  <Step title="Select GPU">
    <img alt="ComfyUI Installation Steps - GPU Selection" />

    The three options are:

    1. **MPS (Recommended):** Metal Performance Shaders (MPS) is an Apple framework that uses GPUs to accelerate computing and machine learning tasks on Apple devices, supporting frameworks like PyTorch.
    2. **Manual Configuration:** You need to manually install and configure the python runtime environment. Don't select this unless you know how to configure
    3. **Enable CPU Mode:** For developers and special cases only. Don't select this unless you're sure you need it

    Unless there are special circumstances, please select **MPS** as shown and click **Next** to proceed
  </Step>

  <Step title="Install location">
    <img alt="ComfyUI Installation Steps - Installation Location" />

    In this step, you will select the installation location for the following related content of ComfyUI:

    * **Python Environment**
    * **Models Model Files**
    * **Custom Nodes Custom Nodes**

    Recommendations:

    * Please create a separate empty folder as the installation directory for ComfyUI
    * Please ensure that the disk has at least **5G** of disk space to ensure the normal installation of **ComfyUI Desktop**

    <Note>Not all files are installed in this directory, some files will be located in the MacOS system directory, you can refer to the uninstallation section of this guide to complete the uninstallation of the ComfyUI desktop version</Note>
  </Step>

  <Step title="Migrate from Existing Installation (Optional)">
    <img alt="ComfyUI Installation Steps - File Migration" />

    In this step you can migrate your existing ComfyUI installation content to ComfyUI Desktop. Select your existing ComfyUI installation directory, and the installer will automatically recognize:

    * **User Files**
    * **Models:** Will not be copied, only linked with desktop version
    * **Custom Nodes:** Nodes will be reinstalled

    Don't worry, this step won't copy model files. You can check or uncheck options as needed. Click **Next** to continue
  </Step>

  <Step title="Desktop Settings">
    <img alt="ComfyUI Installation Steps - Desktop Settings" />

    These are preference settings:

    1. **Automatic Updates:** Whether to set automatic updates when ComfyUI updates are available
    2. **Usage Metrics:** If enabled, we will collect **anonymous usage data** to help improve ComfyUI
    3. **Mirror Settings:** Since the program needs internet access to download Python and complete environment installation, if you see a red ❌ during installation indicating this may cause installation failure, please follow the steps below

    <img alt="ComfyUI Installation Steps - Mirror Settings" />

    Expand the mirror settings to find the specific failing mirror. In this screenshot the error is **Python Install Mirror** failure.

    For different mirror errors, you can refer to the following content to try to manually find different mirrors and replace them

    The following cases mainly apply to users in China.

    #### Python Installation Mirror

    If the default mirror is unavailable, please try using the mirror below.

    ```
    https://python-standalone.org/mirror/astral-sh/python-build-standalone
    ```

    If you need to find other alternative GitHub mirror addresses, please look for and construct a mirror address pointing to the releases of the `python-build-standalone` repository.

    ```
    https://github.com/astral-sh/python-build-standalone/releases/download
    ```

    Build a link in the following pattern

    ```
    https://xxx/astral-sh/python-build-standalone/releases/download
    ```

    <info>Since most of the Github mirror services are provided by third parties, please pay attention to the security during use.</info>

    #### PyPI Mirror

    * Alibaba Cloud: [https://mirrors.aliyun.com/pypi/simple/](https://mirrors.aliyun.com/pypi/simple/)
    * Tencent Cloud: [https://mirrors.cloud.tencent.com/pypi/simple/](https://mirrors.cloud.tencent.com/pypi/simple/)
    * University of Science and Technology of China: [https://pypi.mirrors.ustc.edu.cn/simple/](https://pypi.mirrors.ustc.edu.cn/simple/)
    * Shanghai Jiao Tong University: [https://pypi.sjtu.edu.cn/simple/](https://pypi.sjtu.edu.cn/simple/)

    #### Torch Mirror

    * Aliyun: [https://mirrors.aliyun.com/pytorch-wheels/cu130/](https://mirrors.aliyun.com/pytorch-wheels/cu130/)
  </Step>

  <Step title="Complete the installation">
    If everything is correct, the installer will complete and automatically enter the ComfyUI Desktop interface, then the installation is successful

    <img alt="ComfyUI Desktop Interface" />
  </Step>
</Steps>

## Important: Do not modify the resource/ComfyUI folder

<Warning>
  Do not add or modify any content in the `/resource/ComfyUI` folder. All content in this folder will be reset when ComfyUI Desktop updates.

  Unlike other ComfyUI versions, the Desktop version manages this folder automatically. During installation, you chose a custom location for your models, custom nodes, and other user files - please use that location instead.
</Warning>

## First Image Generation

After successful installation, you can refer to the section below to start your ComfyUI journey\~

<Card title="First Image Generation" icon="link" href="/get_started/first_generation">
  This tutorial will guide you through your first model installation and text-to-image generation
</Card>

## How to Update ComfyUI Desktop

Currently, ComfyUI Desktop updates use automatic detection updates, please ensure that automatic updates are enabled in the settings

<img alt="ComfyUI Desktop Settings" />

You can also choose to manually check for available updates in the `Menu` --> `Help` --> `Check for Updates`

<img alt="ComfyUI Desktop Check for Updates" />

## Adding Extra Model Paths

If you want to manage your model files outside of `ComfyUI/models`, you may have the following reasons:

* You have multiple ComfyUI instances and want them to share model files to save disk space
* You have different types of GUI programs (such as WebUI) and want them to use the same model files
* Model files cannot be recognized or found

We provide a way to add extra model search paths via the `extra_model_paths.yaml` configuration file

### Open Config File

<Tabs>
  <Tab title="Portable/Manual Install">
    For the ComfyUI version such as [portable](/installation/comfyui_portable_windows) and [manual](/installation/manual_install), you can find an example file named `extra_model_paths.yaml.example` in the root directory of ComfyUI:

    ```
    ComfyUI/extra_model_paths.yaml.example
    ```

    Copy and rename it to `extra_model_paths.yaml` for use. Keep it in ComfyUI's root directory at `ComfyUI/extra_model_paths.yaml`.
    You can also find the config example file [here](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example)
  </Tab>

  <Tab title="ComfyUI Desktop">
    If you are using the [ComfyUI Desktop](/installation/desktop/windows) application, you can follow the image below to open the extra model config file:

    <img alt="Open Config File" />

    Or open it directly at:

    <Tabs>
      <Tab title="Windows">
        ```
        C:\Users\YourUsername\AppData\Roaming\ComfyUI\extra_models_config.yaml
        ```
      </Tab>

      <Tab title="macOS">
        ```
        ~/Library/Application Support/ComfyUI/extra_models_config.yaml
        ```
      </Tab>
    </Tabs>

    You should keep the file in the same directory, should not move these files to other places.
  </Tab>
</Tabs>

If the file does not exist, you can create it yourself with any text editor.

### Example Structure

Suppose you want to add the following model paths to ComfyUI:

```
📁 YOUR_PATH/
  ├── 📁models/
  |   ├── 📁 loras/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 checkpoints/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 vae/
  |   │   └── xxxxx.safetensors
  |   └── 📁 controlnet/
  |       └── xxxxx.safetensors
```

Then you can configure the `extra_model_paths.yaml` file like below to let ComfyUI recognize the model paths on your device:

```
my_custom_config:
    base_path: YOUR_PATH
    loras: models/loras/
    checkpoints: models/checkpoints/
    vae: models/vae/
    controlnet: models/controlnet/
```

or

```
my_custom_config:
    base_path: YOUR_PATH/models/
    loras: loras
    checkpoints: checkpoints
    vae: vae
    controlnet: controlnet
```

<Warning>
  For the desktop version, please add the configuration to the existing configuration path without overwriting the path configuration generated during installation. Please back up the corresponding file before modification, so that you can restore it when you make a mistake.
</Warning>

Or you can refer to the default [extra\_model\_paths.yaml.example](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example) for more configuration options. After saving, you need to **restart ComfyUI** for the changes to take effect.

Below is the original config example:

```yaml theme={null}
#Rename this to extra_model_paths.yaml and ComfyUI will load it


#config for a1111 ui
#all you have to do is change the base_path to where yours is installed
a111:
    base_path: path/to/stable-diffusion-webui/

    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet

#config for comfyui
#your base path should be either an existing comfy install or a central folder where you store all of your models, loras, etc.

#comfyui:
#     base_path: path/to/comfyui/
#     # You can use is_default to mark that these folders should be listed first, and used as the default dirs for eg downloads
#     #is_default: true
#     checkpoints: models/checkpoints/
#     clip: models/clip/
#     clip_vision: models/clip_vision/
#     configs: models/configs/
#     controlnet: models/controlnet/
#     diffusion_models: |
#                  models/diffusion_models
#                  models/unet
#     embeddings: models/embeddings/
#     loras: models/loras/
#     upscale_models: models/upscale_models/
#     vae: models/vae/

#other_ui:
#    base_path: path/to/ui
#    checkpoints: models/checkpoints
#    gligen: models/gligen
#    custom_nodes: path/custom_nodes

```

For example, if your WebUI is located at `D:\stable-diffusion-webui\`, you can modify the corresponding configuration to

```yaml theme={null}
a111:
    base_path: D:\stable-diffusion-webui\
    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet
```

### Add Extra Custom Nodes Path

Besides adding external models, you can also add custom nodes paths that are not in the default path of ComfyUI

<Tip>
  Please note that this will not change the default installation path of custom nodes, but will add an extra path search when starting ComfyUI. You still need to complete the installation of custom node dependencies in the corresponding environment to ensure the integrity of the running environment.
</Tip>

Below is a simple configuration example (MacOS), please modify it according to your actual situation and add it to the corresponding configuration file, save it and restart ComfyUI for the changes to take effect:

```yaml theme={null}
my_custom_nodes:
  custom_nodes: /Users/your_username/Documents/extra_custom_nodes
```

## Desktop Python Environment

The desktop installation will create a Python virtual environment in your chosen installation directory, typically a hidden `.venv` folder.

If you need to handle dependencies for ComfyUI plugins, you'll need to do so within this environment. Using the system command line directly risks installing dependencies to the system environment, so please follow the instructions below to activate the appropriate environment.

### How to use the Desktop Python environment?

<Tabs>
  <Tab title="Desktop (Recommended)">
    You can use the built-in terminal in the desktop app to access the Python environment.

    <img alt="ComfyUI Desktop Terminal" />

    1. Click the icon in the menu bar to open the bottom panel
    2. Click `Terminal` to open the terminal
    3. If you want to check the Python installation location for the corresponding environment, you can use the following command

    <Tabs>
      <Tab title="Windows">
        ```
          python -c "import sys; print(sys.executable)"
        ```
      </Tab>

      <Tab title="macOS">
        ```
        which python
        ```
      </Tab>
    </Tabs>

    <Warning>
      Unless you understand the meaning of your current operations, your actions may cause dependency issues in the corresponding environment. Please use this method with caution.
    </Warning>
  </Tab>

  <Tab title="Terminal">
    You can also use your preferred terminal to access the Python environment, but you'll need to activate the virtual environment first.

    <Warning>
      When using other terminals, if you're not familiar with the operations, you may accidentally install dependencies to the system environment. Please use this method with caution.
    </Warning>

    <img alt="Using system to activate environment" />

    <Warning>
      In the screenshot, it shows a macOS terminal. If you are using Windows, please refer to the following steps to activate the virtual environment on your system.
    </Warning>

    <Steps>
      <Step title="Open Terminal">
        Open your preferred terminal and use the `cd` command to navigate to your ComfyUI installation directory, for example:

        ```
        cd <your comfyui install directory>/ComfyUI
        ```
      </Step>

      <Step title="Activate Virtual Environment">
        Type the following command in the terminal to activate the virtual environment

        <Tabs>
          <Tab title="Windows">
            ```
            .venv/Scripts/activate
            ```
          </Tab>

          <Tab title="macOS">
            ```
            source .venv/bin/activate
            ```
          </Tab>
        </Tabs>

        After activation, you should see a prompt like `(ComfyUI)` in the terminal, indicating that you've activated the virtual environment.
      </Step>

      <Step title="Confirm Current Python Environment">
        Use `which python` to check the current Python installation location and confirm it's not the system environment.
      </Step>

      After completing these steps, you've activated the corresponding Python environment, and you can continue to perform dependency installation operations in this environment.
    </Steps>
  </Tab>
</Tabs>

## How to Uninstall ComfyUI Desktop

For **ComfyUI Desktop**, you can directly delete **ComfyUI** from the **Applications** folder

If you want to completely remove all **ComfyUI Desktop** files, you can manually delete these folders:

```
~/Library/Application Support/ComfyUI
```

The above operations will not delete your following folders. If you need to delete corresponding files, please delete manually:

* models files
* custom nodes
* input/output directories

## Troubleshooting

### ​Error identification​

If installation fails, you should see the following screen

<img alt="ComfyUI Installation Failed" />

It is recommended to take these steps to find the error cause:

1. Click `Show Terminal` to view error output
2. Click `Open Logs` to view installation logs
3. Visit official forum to search for error reports
4. Click `Reinstall` to try reinstalling

Before submitting feedback, it's recommended to provide the **error output** and **log files** to tools like **GPT**

<img alt="ComfyUI Installation Failed - Error Log" />

<img alt="ComfyUI Installation Failed - GPT Feedback" />

As shown above, ask the GPT for the cause of the corresponding error, or remove ComfyUI completely and retry the installation.

### Feedback Installation Failure

If you encounter any errors during installation, please check if there are similar error reports or submit errors to us through:

* Github Issues: [https://github.com/Comfy-Org/desktop/issues](https://github.com/Comfy-Org/desktop/issues)
* Comfy Official Forum: [https://forum.comfy.org/](https://forum.comfy.org/)

When submitting error reports, please ensure you include the following logs and configuration files to help us locate and investigate the issue:

1. Log Files

| Filename    | Description                                                                                     | Location |
| ----------- | ----------------------------------------------------------------------------------------------- | -------- |
| main.log    | Contains logs related to desktop application and server startup from the Electron process       |          |
| comfyui.log | Contains logs related to ComfyUI normal operation, such as core ComfyUI process terminal output |          |

<img alt="ComfyUI Log Files Location" />

2. Configuration Files

| Filename                 | Description                                                                     | Location |
| ------------------------ | ------------------------------------------------------------------------------- | -------- |
| extra\_model\_paths.yaml | Contains additional paths where ComfyUI will search for models and custom nodes |          |
| config.json              | Contains application configuration. This file should not be edited directly     |          |

<img alt="ComfyUI Config Files Location" />


# Windows Desktop — Local Self-Hosted
Source: https://docs.comfy.org/installation/desktop/windows

This article introduces how to download, install and use ComfyUI Desktop for Windows

**ComfyUI Desktop** is a standalone installation version that can be installed like regular software. It supports quick installation and automatic configuration of the **Python environment and dependencies**, and supports one-click import of existing ComfyUI settings, models, workflows, and files. You can quickly migrate from an existing [ComfyUI Portable version](/installation/comfyui_portable_windows) to the Desktop version.

ComfyUI Desktop is an open source project, please visit the full code [here](https://github.com/Comfy-Org/desktop)

ComfyUI Desktop hardware requirements:

* NVIDIA GPU (with CUDA)
* AMD GPU (with ROCm support)

This tutorial will guide you through the software installation process and explain related configuration details.

<Warning>As **ComfyUI Desktop** is still in **Beta** status, the actual installation process may change</Warning>

## ComfyUI Desktop (Windows) Download

Please click the button below to download the installation package for Windows **ComfyUI Desktop**

<a href="https://download.comfy.org/windows/nsis/x64">
  <p>Download for Windows</p>
</a>

## ComfyUI Desktop Installation Steps

Double-click the downloaded installation package file, which will first perform an automatic installation and create a **ComfyUI Desktop** shortcut on the desktop

<img alt="ComfyUI logo" />

Double-click the corresponding shortcut to enter ComfyUI initialization settings

### ComfyUI Desktop Initialization Process

<Steps>
  <Step title="Start Screen">
    <Tabs>
      <Tab title="Normal Start">
        <img alt="ComfyUI Installation Steps - Start" />

        Click **Get Started** to begin initialization
      </Tab>

      <Tab title="Maintenance Page">
        There are many reasons you might have issues installing ComfyUI. Maybe a network connection failed when installing pytorch (15 GB). Or you don’t have git installed. The maintenance page automatically opens when it detects an issue and provides a way to resolve the issue.

        You can use it to resolve most issues:

        * Create a python virtual environment
        * Reinstall all missing core dependencies to your Python virtual environment that’s managed by Desktop
        * Install git, VC redis
        * Choose a new install location

        The default maintenance page displays the current error content

        <img alt="ComfyUI Maintenance Page" />

        Clicking `All` allows you to view all the content that can be operated on currently

        <img alt="ComfyUI Maintenance Page" />
      </Tab>
    </Tabs>
  </Step>

  <Step title="Select GPU">
    <img alt="ComfyUI Installation Steps - GPU Selection" />

    The available options are:

    1. **Nvidia GPU (Recommended for NVIDIA users):** Direct support for pytorch and CUDA
    2. **AMD GPU:** Direct support for pytorch and ROCm
    3. **Manual Configuration:** You need to manually install and configure the python runtime environment. Don't select this unless you know how to configure
    4. **Enable CPU Mode:** For developers and special cases only. Don't select this unless you're sure you need it

    Select the option that matches your GPU type and click **Next** to proceed
  </Step>

  <Step title="Install location">
    <img alt="ComfyUI Installation Steps - Installation Location" />

    In this step, you will select the installation location for the following ComfyUI content:

    * **Python Environment**
    * **Models Model Files**
    * **Custom Nodes Custom Nodes**

    Recommendations:

    * Please select a **solid-state drive** as the installation location, which will increase ComfyUI's performance when accessing models.
    * Please create a separate empty folder as the ComfyUI installation directory
    * Please ensure that the corresponding disk has at least around **15G** of disk space to ensure the installation of ComfyUI Desktop

    <Note>Not all files are installed in this directory, some files will still be installed on the C drive, and if you need to uninstall in the future, you can refer to the uninstallation section of this guide to complete the full uninstallation of ComfyUI Desktop</Note>

    After completing this step, click **Next** to proceed to the next step
  </Step>

  <Step title="Migrate from Existing Installation (Optional)">
    <img alt="ComfyUI Installation Steps - File Migration" />

    In this step you can migrate your existing ComfyUI installation content to ComfyUI Desktop. As shown, I selected my original **D:\ComfyUI\_windows\_portable\ComfyUI** installation directory. The installer will automatically recognize:

    * **User Files**
    * **Models:** Will not be copied, only linked with desktop version
    * **Custom Nodes:** Nodes will be reinstalled

    Don't worry, this step won't copy model files. You can check or uncheck options as needed. Click **Next** to continue
  </Step>

  <Step title="Desktop Settings">
    <img alt="ComfyUI Installation Steps - Desktop Settings" />

    These are preference settings:

    1. **Automatic Updates:** Whether to set automatic updates when ComfyUI updates are available
    2. **Usage Metrics:** If enabled, we will collect **anonymous usage data** to help improve ComfyUI
    3. **Mirror Settings:** Since the program needs internet access to download Python and complete environment installation, if you see a red ❌ during installation indicating this may cause installation failure, please follow the steps below

    <img alt="ComfyUI Installation Steps - Mirror Settings" />

    Expand the mirror settings to find the specific failing mirror. In this screenshot the error is **Python Install Mirror** failure.

    For different mirror errors, you can refer to the following content to try to manually find different mirrors and replace them

    The following cases mainly apply to users in China.

    #### Python Installation Mirror

    If the default mirror is unavailable, please try using the mirror below.

    ```
    https://python-standalone.org/mirror/astral-sh/python-build-standalone
    ```

    If you need to find other alternative GitHub mirror addresses, please look for and construct a mirror address pointing to the releases of the `python-build-standalone` repository.

    ```
    https://github.com/astral-sh/python-build-standalone/releases/download
    ```

    Build a link in the following pattern

    ```
    https://xxx/astral-sh/python-build-standalone/releases/download
    ```

    <info>Since most of the Github mirror services are provided by third parties, please pay attention to the security during use.</info>

    #### PyPI Mirror

    * Alibaba Cloud: [https://mirrors.aliyun.com/pypi/simple/](https://mirrors.aliyun.com/pypi/simple/)
    * Tencent Cloud: [https://mirrors.cloud.tencent.com/pypi/simple/](https://mirrors.cloud.tencent.com/pypi/simple/)
    * University of Science and Technology of China: [https://pypi.mirrors.ustc.edu.cn/simple/](https://pypi.mirrors.ustc.edu.cn/simple/)
    * Shanghai Jiao Tong University: [https://pypi.sjtu.edu.cn/simple/](https://pypi.sjtu.edu.cn/simple/)

    #### Torch Mirror

    * Aliyun: [https://mirrors.aliyun.com/pytorch-wheels/cu130/](https://mirrors.aliyun.com/pytorch-wheels/cu130/)
  </Step>

  <Step title="Complete the installation">
    If everything is correct, the installer will complete and automatically enter the ComfyUI Desktop interface, then the installation is successful

    <img alt="ComfyUI Desktop Interface" />
  </Step>
</Steps>

## Important: Do not modify the resource/ComfyUI folder

<Warning>
  Do not add or modify any content in the `/resource/ComfyUI` folder. All content in this folder will be reset when ComfyUI Desktop updates.

  Unlike other ComfyUI versions, the Desktop version manages this folder automatically. During installation, you chose a custom location for your models, custom nodes, and other user files - please use that location instead.
</Warning>

## First Image Generation

After successful installation, you can refer to the section below to start your ComfyUI journey\~

<Card title="First Image Generation" icon="link" href="/get_started/first_generation">
  This tutorial will guide you through your first model installation and text-to-image generation
</Card>

## How to Update ComfyUI Desktop

Currently, ComfyUI Desktop updates use automatic detection updates, please ensure that automatic updates are enabled in the settings

<img alt="ComfyUI Desktop Settings" />

You can also choose to manually check for available updates in the `Menu` --> `Help` --> `Check for Updates`

<img alt="ComfyUI Desktop Check for Updates" />

## Adding Extra Model Paths

If you want to manage your model files outside of `ComfyUI/models`, you may have the following reasons:

* You have multiple ComfyUI instances and want them to share model files to save disk space
* You have different types of GUI programs (such as WebUI) and want them to use the same model files
* Model files cannot be recognized or found

We provide a way to add extra model search paths via the `extra_model_paths.yaml` configuration file

### Open Config File

<Tabs>
  <Tab title="Portable/Manual Install">
    For the ComfyUI version such as [portable](/installation/comfyui_portable_windows) and [manual](/installation/manual_install), you can find an example file named `extra_model_paths.yaml.example` in the root directory of ComfyUI:

    ```
    ComfyUI/extra_model_paths.yaml.example
    ```

    Copy and rename it to `extra_model_paths.yaml` for use. Keep it in ComfyUI's root directory at `ComfyUI/extra_model_paths.yaml`.
    You can also find the config example file [here](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example)
  </Tab>

  <Tab title="ComfyUI Desktop">
    If you are using the [ComfyUI Desktop](/installation/desktop/windows) application, you can follow the image below to open the extra model config file:

    <img alt="Open Config File" />

    Or open it directly at:

    <Tabs>
      <Tab title="Windows">
        ```
        C:\Users\YourUsername\AppData\Roaming\ComfyUI\extra_models_config.yaml
        ```
      </Tab>

      <Tab title="macOS">
        ```
        ~/Library/Application Support/ComfyUI/extra_models_config.yaml
        ```
      </Tab>
    </Tabs>

    You should keep the file in the same directory, should not move these files to other places.
  </Tab>
</Tabs>

If the file does not exist, you can create it yourself with any text editor.

### Example Structure

Suppose you want to add the following model paths to ComfyUI:

```
📁 YOUR_PATH/
  ├── 📁models/
  |   ├── 📁 loras/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 checkpoints/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 vae/
  |   │   └── xxxxx.safetensors
  |   └── 📁 controlnet/
  |       └── xxxxx.safetensors
```

Then you can configure the `extra_model_paths.yaml` file like below to let ComfyUI recognize the model paths on your device:

```
my_custom_config:
    base_path: YOUR_PATH
    loras: models/loras/
    checkpoints: models/checkpoints/
    vae: models/vae/
    controlnet: models/controlnet/
```

or

```
my_custom_config:
    base_path: YOUR_PATH/models/
    loras: loras
    checkpoints: checkpoints
    vae: vae
    controlnet: controlnet
```

<Warning>
  For the desktop version, please add the configuration to the existing configuration path without overwriting the path configuration generated during installation. Please back up the corresponding file before modification, so that you can restore it when you make a mistake.
</Warning>

Or you can refer to the default [extra\_model\_paths.yaml.example](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example) for more configuration options. After saving, you need to **restart ComfyUI** for the changes to take effect.

Below is the original config example:

```yaml theme={null}
#Rename this to extra_model_paths.yaml and ComfyUI will load it


#config for a1111 ui
#all you have to do is change the base_path to where yours is installed
a111:
    base_path: path/to/stable-diffusion-webui/

    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet

#config for comfyui
#your base path should be either an existing comfy install or a central folder where you store all of your models, loras, etc.

#comfyui:
#     base_path: path/to/comfyui/
#     # You can use is_default to mark that these folders should be listed first, and used as the default dirs for eg downloads
#     #is_default: true
#     checkpoints: models/checkpoints/
#     clip: models/clip/
#     clip_vision: models/clip_vision/
#     configs: models/configs/
#     controlnet: models/controlnet/
#     diffusion_models: |
#                  models/diffusion_models
#                  models/unet
#     embeddings: models/embeddings/
#     loras: models/loras/
#     upscale_models: models/upscale_models/
#     vae: models/vae/

#other_ui:
#    base_path: path/to/ui
#    checkpoints: models/checkpoints
#    gligen: models/gligen
#    custom_nodes: path/custom_nodes

```

For example, if your WebUI is located at `D:\stable-diffusion-webui\`, you can modify the corresponding configuration to

```yaml theme={null}
a111:
    base_path: D:\stable-diffusion-webui\
    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet
```

### Add Extra Custom Nodes Path

Besides adding external models, you can also add custom nodes paths that are not in the default path of ComfyUI

<Tip>
  Please note that this will not change the default installation path of custom nodes, but will add an extra path search when starting ComfyUI. You still need to complete the installation of custom node dependencies in the corresponding environment to ensure the integrity of the running environment.
</Tip>

Below is a simple configuration example (MacOS), please modify it according to your actual situation and add it to the corresponding configuration file, save it and restart ComfyUI for the changes to take effect:

```yaml theme={null}
my_custom_nodes:
  custom_nodes: /Users/your_username/Documents/extra_custom_nodes
```

## Desktop Python Environment

The desktop installation will create a Python virtual environment in your chosen installation directory, typically a hidden `.venv` folder.

If you need to handle dependencies for ComfyUI plugins, you'll need to do so within this environment. Using the system command line directly risks installing dependencies to the system environment, so please follow the instructions below to activate the appropriate environment.

### How to use the Desktop Python environment?

<Tabs>
  <Tab title="Desktop (Recommended)">
    You can use the built-in terminal in the desktop app to access the Python environment.

    <img alt="ComfyUI Desktop Terminal" />

    1. Click the icon in the menu bar to open the bottom panel
    2. Click `Terminal` to open the terminal
    3. If you want to check the Python installation location for the corresponding environment, you can use the following command

    <Tabs>
      <Tab title="Windows">
        ```
          python -c "import sys; print(sys.executable)"
        ```
      </Tab>

      <Tab title="macOS">
        ```
        which python
        ```
      </Tab>
    </Tabs>

    <Warning>
      Unless you understand the meaning of your current operations, your actions may cause dependency issues in the corresponding environment. Please use this method with caution.
    </Warning>
  </Tab>

  <Tab title="Terminal">
    You can also use your preferred terminal to access the Python environment, but you'll need to activate the virtual environment first.

    <Warning>
      When using other terminals, if you're not familiar with the operations, you may accidentally install dependencies to the system environment. Please use this method with caution.
    </Warning>

    <img alt="Using system to activate environment" />

    <Warning>
      In the screenshot, it shows a macOS terminal. If you are using Windows, please refer to the following steps to activate the virtual environment on your system.
    </Warning>

    <Steps>
      <Step title="Open Terminal">
        Open your preferred terminal and use the `cd` command to navigate to your ComfyUI installation directory, for example:

        ```
        cd <your comfyui install directory>/ComfyUI
        ```
      </Step>

      <Step title="Activate Virtual Environment">
        Type the following command in the terminal to activate the virtual environment

        <Tabs>
          <Tab title="Windows">
            ```
            .venv/Scripts/activate
            ```
          </Tab>

          <Tab title="macOS">
            ```
            source .venv/bin/activate
            ```
          </Tab>
        </Tabs>

        After activation, you should see a prompt like `(ComfyUI)` in the terminal, indicating that you've activated the virtual environment.
      </Step>

      <Step title="Confirm Current Python Environment">
        Use `which python` to check the current Python installation location and confirm it's not the system environment.
      </Step>

      After completing these steps, you've activated the corresponding Python environment, and you can continue to perform dependency installation operations in this environment.
    </Steps>
  </Tab>
</Tabs>

## How to Uninstall ComfyUI Desktop

For **ComfyUI Desktop** you can use the system uninstall function in Windows Settings to complete software uninstallation

<img alt="ComfyUI Desktop Uninstallation" />

If you want to completely remove all **ComfyUI Desktop** files, you can manually delete these folders:

* C:\Users\<YOUR\_USERNAME>\AppData\Local\@comfyorgcomfyui-electron-updater
* C:\Users\<YOUR\_USERNAME>\AppData\Local\Programs\@comfyorgcomfyui-electron
* C:\Users\<YOUR\_USERNAME>\AppData\Roaming\ComfyUI

The above operations will not delete your following folders. If you need to delete corresponding files, please delete manually:

* models files
* custom nodes
* input/output directories

## Troubleshooting

### Display unsupported devices

<img alt="ComfyUI Installation Steps - Unsupported Device" />

ComfyUI Desktop supports **NVIDIA GPUs** and **AMD GPUs** on Windows. You may see this screen if your device is not a supported GPU type.

* Please switch to a supported device
* Or consider using [ComfyUI Portable](/installation/comfyui_portable_windows) or through [manual installation](/installation/manual_install) to use ComfyUI

### Antivirus flags `uv.exe` as malicious

ComfyUI Desktop bundles [`uv`](https://github.com/astral-sh/uv) (from Astral) to manage the Python environment. Some antivirus products — including **360 Total Security**, **Windows Defender**, **BitDefender**, and **DeepInstinct** — occasionally flag `uv.exe` as malicious. This is a **known false positive** affecting `uv` itself, not ComfyUI.

**Symptoms:**

* Antivirus quarantines or deletes `uv.exe` during installation or updates
* Installation fails partway through Python environment setup
* "Python environment failed to install" or similar errors after antivirus warnings

**Solution:** Add the ComfyUI installation directory to your antivirus's trusted list / whitelist, then reinstall or repair the installation. The directories to whitelist are:

* Your selected ComfyUI install directory (chosen during the [installation steps](#install-location))
* `C:\Users\<YOUR_USERNAME>\AppData\Local\Programs\@comfyorgcomfyui-electron`
* `C:\Users\<YOUR_USERNAME>\AppData\Roaming\ComfyUI`

**Reference:** Tracked upstream in the `uv` project — see [astral-sh/uv#1587](https://github.com/astral-sh/uv/issues/1587), [#10079](https://github.com/astral-sh/uv/issues/10079), [#12621](https://github.com/astral-sh/uv/issues/12621), and [#15011](https://github.com/astral-sh/uv/issues/15011).

### ​Error identification​

If installation fails, you should see the following screen

<img alt="ComfyUI Installation Failed" />

It is recommended to take these steps to find the error cause:

1. Click `Show Terminal` to view error output
2. Click `Open Logs` to view installation logs
3. Visit official forum to search for error reports
4. Click `Reinstall` to try reinstalling

Before submitting feedback, it's recommended to provide the **error output** and **log files** to tools like **GPT**

<img alt="ComfyUI Installation Failed - Error Log" />

<img alt="ComfyUI Installation Failed - GPT Feedback" />

As shown above, ask the GPT for the cause of the corresponding error, or remove ComfyUI completely and retry the installation.

### Feedback Installation Failure

If you encounter any errors during installation, please check if there are similar error reports or submit errors to us through:

* Github Issues: [https://github.com/Comfy-Org/desktop/issues](https://github.com/Comfy-Org/desktop/issues)
* Comfy Official Forum: [https://forum.comfy.org/](https://forum.comfy.org/)

When submitting error reports, please ensure you include the following logs and configuration files to help us locate and investigate the issue:

1. Log Files

| Filename    | Description                                                                                     | Location |
| ----------- | ----------------------------------------------------------------------------------------------- | -------- |
| main.log    | Contains logs related to desktop application and server startup from the Electron process       |          |
| comfyui.log | Contains logs related to ComfyUI normal operation, such as core ComfyUI process terminal output |          |

<img alt="ComfyUI Log Files Location" />

2. Configuration Files

| Filename                 | Description                                                                     | Location |
| ------------------------ | ------------------------------------------------------------------------------- | -------- |
| extra\_model\_paths.yaml | Contains additional paths where ComfyUI will search for models and custom nodes |          |
| config.json              | Contains application configuration. This file should not be edited directly     |          |

<img alt="ComfyUI Config Files Location" />


# How to Install Custom Nodes in ComfyUI
Source: https://docs.comfy.org/installation/install_custom_node

This guide will show you different methods to install custom nodes in ComfyUI

## What are Custom Nodes ?

Custom nodes are extensions for ComfyUI that add new functionality like advanced image processing, machine learning fine-tuning, color adjustments, and more. These community-developed nodes can significantly expand ComfyUI's core capabilities.

<Warning>
  Before installing custom nodes, it's important to review them carefully. Since ComfyUI is an open-source project, malicious plugins could potentially exploit custom nodes:

  1. Only install custom nodes from trusted authors and those commonly used by the community
  2. Understand the plugin's functionality before installing and avoid unknown sources to ensure system security
  3. Avoid installing obscure or suspicious plugins - unverified plugins may pose security risks that could lead to system compromise
</Warning>

All custom node installations require completing these two steps:

1. Clone the node code to the `ComfyUI/custom_nodes` directory
2. Install the required Python dependencies

This guide compares three installation approaches. **ComfyUI Manager** is built into current ComfyUI releases for most setups—start from the [ComfyUI Manager overview](/manager/overview) for what it does and how to enable it. Use **Git clone** or **ZIP** when a node is not on the registry or you need a specific revision.

| Method                            | Advantages                                                                  | Disadvantages                                                                           |
| --------------------------------- | --------------------------------------------------------------------------- | --------------------------------------------------------------------------------------- |
| **ComfyUI Manager** (Recommended) | 1. Automated installation<br />2. Dependency handling<br />3. GUI interface | Cannot directly search for nodes not registered in the registry                         |
| **Git Clone**                     | Can install nodes not registered in the registry                            | 1. Requires Git knowledge<br />2. Manual dependency handling<br />3. Installation risks |
| **Repository ZIP Download**       | 1. No Git required<br />2. Manual control                                   | 1. Manual dependency handling<br />2. No version control<br />3. Installation risks     |

Tip: Before installing custom nodes, check the plugin's README file to understand installation methods, usage, and requirements like specific models, dependency versions, and common issue solutions.

## Method 1: ComfyUI Manager (Recommended)

<Note>
  You need ComfyUI Manager available in your environment before using this method. If it is missing or disabled, see the [ComfyUI Manager overview](/manager/overview) and [installation guide](/manager/install).
</Note>

ComfyUI Manager provides two UI versions for managing custom nodes. Choose the guide that matches your interface:

<Columns>
  <Card title="New UI (default for Desktop)" icon="sparkles" href="/manager/pack-management">
    The new node management interface, enabled by default for Desktop users.
  </Card>

  <Card title="Legacy UI" icon="rectangle-history" href="/manager/legacy-ui">
    The classic Manager interface for custom node installation.
  </Card>
</Columns>

## Method 2: Manual Installation Using Git

Suitable for new nodes not found in Manager or when specific versions are needed. Requires [Git](https://git-scm.com/) installed on your system.

<Steps>
  <Step title="Get the repository URL">
    Click the "Code" button on GitHub and copy the HTTPS link
  </Step>

  <Step title="Navigate to custom_nodes directory">
    ```bash theme={null}
    cd /path/to/ComfyUI/custom_nodes
    ```
  </Step>

  <Step title="Clone the repository">
    ```bash theme={null}
    git clone [repository URL]
    ```
  </Step>

  <Step title="Install dependencies">
    Dependencies must be installed in your ComfyUI environment - be careful not to mix with your system environment to avoid contamination

    <Tabs>
      <Tab title="Windows Portable">
        For Windows portable version, install dependencies in the embedded Python environment

        ```bash theme={null}
        python_embeded\python.exe -m pip install -r ComfyUI\custom_nodes\[node directory]\requirements.txt
        ```
      </Tab>

      <Tab title="Manual Install">
        Install dependencies in your ComfyUI environment

        ```bash theme={null}
        cd [node directory]
        pip install -r requirements.txt
        ```
      </Tab>
    </Tabs>
  </Step>

  <Step title="Restart ComfyUI and refresh browser">
    Restart ComfyUI and refresh your browser. Check startup logs for any `import failed` errors
  </Step>
</Steps>

## Method 3: ZIP Download Installation

Suitable for users who cannot use Git or Manager

<Warning>
  We don't recommend this installation method as it loses version control capabilities
</Warning>

<Steps>
  <Step title="Click `Code` → `Download ZIP` on GitHub">
    Click `Code` → `Download ZIP` on the GitHub page

    <img alt="Click Code → Download ZIP on GitHub" />
  </Step>

  <Step title="Extract the ZIP file">
    Extract the downloaded ZIP file
  </Step>

  <Step title="Copy extracted folder to `ComfyUI/custom_nodes/` directory">
    Copy the extracted folder to `ComfyUI/custom_nodes/` directory
  </Step>

  <Step title="Install dependencies manually (same as Git method step 4)">
    Restart ComfyUI and refresh browser
  </Step>

  <Step title="Verify successful installation">
    Check ComfyUI Manager after restart to confirm the plugin installed successfully and there are no `import failed` errors
  </Step>
</Steps>

## Custom Node Resources

In ComfyUI, besides the basic node extension functionality, custom nodes can also include the following additional resources:

* [Node Documentation](/custom-nodes/help_page): This feature supports all custom and basic nodes. You can use it to view node documentation, understand the purpose and usage of nodes, and contribute documentation via PRs to the author.
* [Custom Node Workflow Templates](/custom-nodes/workflow_templates): Workflow templates provided by node authors as example workflows, which can be browsed and loaded from the ComfyUI templates.
* [Multi-language Support](/custom-nodes/i18n)

If you are a custom node developer, you can add these resources to make your custom node more user-friendly.


# Manual Installation — Local Self-Hosted
Source: https://docs.comfy.org/installation/manual_install

This section will guide you through the manual installation process on Windows, MacOS and Linux

For the installation of ComfyUI, it is mainly divided into several steps:

1. Create a virtual environment(avoid polluting the system-level Python environment)
2. Clone the ComfyUI code repository
3. Install dependencies
4. Start ComfyUI

You can also refer to [ComfyUI CLI](/comfy-cli/getting-started) to install ComfyUI, it is a command line tool that can easily install ComfyUI and manage its dependencies.

## Create a virtual environment

<Tip>
  Independent virtual environments are necessary because ComfyUI's dependencies may conflict with other dependencies on the system, and it can also avoid polluting the system-level Python environment.
</Tip>

[Install Miniconda](https://docs.anaconda.com/free/miniconda/index.html#latest-miniconda-installer-links). This will help you install the correct versions of Python and other libraries needed by ComfyUI.

Create an environment with Conda.

```
conda create -n comfyenv
conda activate comfyenv
```

## Clone the ComfyUI code repository

You need to ensure that you have installed [Git](https://git-scm.com/downloads) on your system. First, you need to open the terminal (command line), then clone the code repository.

<Tabs>
  <Tab title="Windows">
    <Warning>If you have not installed Microsoft Visual C++ Redistributable, please install it [here.](https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170)</Warning>
  </Tab>

  <Tab title="Linux">
    Open Terminal application.
  </Tab>

  <Tab title="MacOS">
    Open [Terminal application](https://support.apple.com/guide/terminal/open-or-quit-terminal-apd5265185d-f365-44cb-8b09-71a064a42125/mac).
  </Tab>
</Tabs>

```bash theme={null}
git clone https://github.com/Comfy-Org/ComfyUI.git
```

## Install GPU and ComfyUI dependencies

<Steps>
  <Step title="Install GPU dependencies">
    Install GPU Dependencies

    <Accordion title="Nvidia">
      ```
      pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu130
      ```

      Alternatively, you can install the nightly version of PyTorch.

      <Accordion title="Install Nightly">
        <Warning>Install Nightly version (might be more risky)</Warning>

        ```
        pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu132
        ```
      </Accordion>
    </Accordion>

    <Accordion title="AMD">
      ```
      pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.2
      ```

      Alternatively, you can install the nightly version of PyTorch (ROCm 7.2).

      <Accordion title="Install Nightly">
        <Warning>Install Nightly version (might be more risky)</Warning>

        ```
        pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.2
        ```
      </Accordion>
    </Accordion>

    <Accordion title="Mac ARM Silicon">
      ```bash theme={null}
      conda install pytorch-nightly::pytorch torchvision torchaudio -c pytorch-nightly
      ```
    </Accordion>
  </Step>

  <Step title="Install ComfyUI dependencies">
    ```bash theme={null}
    cd ComfyUI
    pip install -r requirements.txt
    ```
  </Step>

  <Step title="Start ComfyUI">
    Start the application

    ```
    cd ComfyUI
    python main.py
    ```
  </Step>
</Steps>

## How to update ComfyUI

<Steps>
  <Step title="pull the latest code">
    Use the command line to enter the installation path of ComfyUI, then pull the latest code.

    ```bash theme={null}
    cd <installation path>/ComfyUI
    git pull
    ```
  </Step>

  <Step title="install the dependencies">
    Use the command line to enter the installation path of ComfyUI, then install the dependencies.

    <Warning>
      You need to ensure that the current Python environment is the ComfyUI virtual environment, otherwise the dependencies will be installed to the system-level Python environment, polluting the system-level Python environment.
    </Warning>

    ```bash theme={null}
        pip install -r requirements.txt
    ```
  </Step>
</Steps>

## Adding Extra Model Paths

If you want to manage your model files outside of `ComfyUI/models`, you may have the following reasons:

* You have multiple ComfyUI instances and want them to share model files to save disk space
* You have different types of GUI programs (such as WebUI) and want them to use the same model files
* Model files cannot be recognized or found

We provide a way to add extra model search paths via the `extra_model_paths.yaml` configuration file

### Open Config File

<Tabs>
  <Tab title="Portable/Manual Install">
    For the ComfyUI version such as [portable](/installation/comfyui_portable_windows) and [manual](/installation/manual_install), you can find an example file named `extra_model_paths.yaml.example` in the root directory of ComfyUI:

    ```
    ComfyUI/extra_model_paths.yaml.example
    ```

    Copy and rename it to `extra_model_paths.yaml` for use. Keep it in ComfyUI's root directory at `ComfyUI/extra_model_paths.yaml`.
    You can also find the config example file [here](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example)
  </Tab>

  <Tab title="ComfyUI Desktop">
    If you are using the [ComfyUI Desktop](/installation/desktop/windows) application, you can follow the image below to open the extra model config file:

    <img alt="Open Config File" />

    Or open it directly at:

    <Tabs>
      <Tab title="Windows">
        ```
        C:\Users\YourUsername\AppData\Roaming\ComfyUI\extra_models_config.yaml
        ```
      </Tab>

      <Tab title="macOS">
        ```
        ~/Library/Application Support/ComfyUI/extra_models_config.yaml
        ```
      </Tab>
    </Tabs>

    You should keep the file in the same directory, should not move these files to other places.
  </Tab>
</Tabs>

If the file does not exist, you can create it yourself with any text editor.

### Example Structure

Suppose you want to add the following model paths to ComfyUI:

```
📁 YOUR_PATH/
  ├── 📁models/
  |   ├── 📁 loras/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 checkpoints/
  |   │   └── xxxxx.safetensors
  |   ├── 📁 vae/
  |   │   └── xxxxx.safetensors
  |   └── 📁 controlnet/
  |       └── xxxxx.safetensors
```

Then you can configure the `extra_model_paths.yaml` file like below to let ComfyUI recognize the model paths on your device:

```
my_custom_config:
    base_path: YOUR_PATH
    loras: models/loras/
    checkpoints: models/checkpoints/
    vae: models/vae/
    controlnet: models/controlnet/
```

or

```
my_custom_config:
    base_path: YOUR_PATH/models/
    loras: loras
    checkpoints: checkpoints
    vae: vae
    controlnet: controlnet
```

<Warning>
  For the desktop version, please add the configuration to the existing configuration path without overwriting the path configuration generated during installation. Please back up the corresponding file before modification, so that you can restore it when you make a mistake.
</Warning>

Or you can refer to the default [extra\_model\_paths.yaml.example](https://github.com/Comfy-Org/ComfyUI/blob/master/extra_model_paths.yaml.example) for more configuration options. After saving, you need to **restart ComfyUI** for the changes to take effect.

Below is the original config example:

```yaml theme={null}
#Rename this to extra_model_paths.yaml and ComfyUI will load it


#config for a1111 ui
#all you have to do is change the base_path to where yours is installed
a111:
    base_path: path/to/stable-diffusion-webui/

    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet

#config for comfyui
#your base path should be either an existing comfy install or a central folder where you store all of your models, loras, etc.

#comfyui:
#     base_path: path/to/comfyui/
#     # You can use is_default to mark that these folders should be listed first, and used as the default dirs for eg downloads
#     #is_default: true
#     checkpoints: models/checkpoints/
#     clip: models/clip/
#     clip_vision: models/clip_vision/
#     configs: models/configs/
#     controlnet: models/controlnet/
#     diffusion_models: |
#                  models/diffusion_models
#                  models/unet
#     embeddings: models/embeddings/
#     loras: models/loras/
#     upscale_models: models/upscale_models/
#     vae: models/vae/

#other_ui:
#    base_path: path/to/ui
#    checkpoints: models/checkpoints
#    gligen: models/gligen
#    custom_nodes: path/custom_nodes

```

For example, if your WebUI is located at `D:\stable-diffusion-webui\`, you can modify the corresponding configuration to

```yaml theme={null}
a111:
    base_path: D:\stable-diffusion-webui\
    checkpoints: models/Stable-diffusion
    configs: models/Stable-diffusion
    vae: models/VAE
    loras: |
         models/Lora
         models/LyCORIS
    upscale_models: |
                  models/ESRGAN
                  models/RealESRGAN
                  models/SwinIR
    embeddings: embeddings
    hypernetworks: models/hypernetworks
    controlnet: models/ControlNet
```

### Add Extra Custom Nodes Path

Besides adding external models, you can also add custom nodes paths that are not in the default path of ComfyUI

<Tip>
  Please note that this will not change the default installation path of custom nodes, but will add an extra path search when starting ComfyUI. You still need to complete the installation of custom node dependencies in the corresponding environment to ensure the integrity of the running environment.
</Tip>

Below is a simple configuration example (MacOS), please modify it according to your actual situation and add it to the corresponding configuration file, save it and restart ComfyUI for the changes to take effect:

```yaml theme={null}
my_custom_nodes:
  custom_nodes: /Users/your_username/Documents/extra_custom_nodes
```


# System Requirements
Source: https://docs.comfy.org/installation/system_requirements

This guide introduces some system requirements for ComfyUI, including hardware and software requirements

In this guide, we will introduce the system requirements for installing ComfyUI. Due to frequent updates of ComfyUI, this document may not be updated in a timely manner. Please refer to the relevant instructions in [ComfyUI](https://github.com/Comfy-Org/ComfyUI).

Regardless of which version of ComfyUI you use, it runs in a separate Python environment.

### System Requirements

Currently, we support the following operating systems:

* Windows
* Linux
* macOS (supports Apple Silicon, such as the M series)

You can refer to the following sections to learn about the installation methods for different systems and versions of ComfyUI. In the installation of different versions, we have simply described the system requirements.

<AccordionGroup>
  <Accordion title="ComfyUI Desktop">
    ComfyUI Desktop currently supports standalone installation for **Windows and MacOS (ARM)**, currently in Beta

    * Code is open source on [Github](https://github.com/Comfy-Org/desktop)

    <Tip>
      Because Desktop is always built based on the **stable release**, so the latest updates may take some time to experience for Desktop, if you want to always experience the latest version, please use the portable version or manual installation
    </Tip>

    You can choose the appropriate installation for your system and hardware below

    <Tabs>
      <Tab title="Windows">
        <Card title="ComfyUI Desktop (Windows) Installation Guide" icon="link" href="/installation/desktop/windows">
          Suitable for **Windows** version with **Nvidia** GPU
        </Card>
      </Tab>

      <Tab title="MacOS(Apple Silicon)">
        <Card title="ComfyUI Desktop (MacOS) Installation Guide" icon="link" href="/installation/desktop/macos">
          Suitable for MacOS with **Apple Silicon**
        </Card>
      </Tab>

      <Tab title="Linux">
        <Note>ComfyUI Desktop **currently has no Linux prebuilds**, please visit the [Manual Installation](/installation/manual_install) section to install ComfyUI</Note>
      </Tab>
    </Tabs>
  </Accordion>

  <Accordion title="ComfyUI Portable (Windows)">
    Portable version is a ComfyUI version that integrates an independent embedded Python environment, using the portable version you can experience the latest features, currently only supports **Windows** system

    <Card title="ComfyUI Portable (Windows) Installation Guide" icon="link" href="/installation/comfyui_portable_windows">
      Supports **Windows** ComfyUI version running on **Nvidia GPUs** or **CPU-only**, always use the latest commits and completely portable.
    </Card>
  </Accordion>

  <Accordion title="Manual Installation">
    <Card title="ComfyUI Manual Installation Guide" icon="link" href="/installation/manual_install">
      Supports all system types and GPU types (Nvidia, AMD, Intel, Apple Silicon, Ascend NPU, Cambricon MLU)
    </Card>
  </Accordion>
</AccordionGroup>

### Python Version

* **Python 3.13** is very well supported and recommended
* Python 3.14 works but some custom nodes may have issues. The free threaded variant works but some dependencies will enable the GIL so it's not fully supported
* Python 3.12 is a good fallback if you have trouble with some custom node dependencies on 3.13

### Browser Requirements

For the best experience, use **Google Chrome version 143 or later**. Earlier versions of Chrome (142 and below) have known issues that can cause visual glitches and performance problems in ComfyUI.

### Supported Hardware

* **NVIDIA GPU** - Install stable pytorch with CUDA 13.0: `pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu130`
* **AMD GPU (Linux)** - ROCm 7.2 stable or nightly
* **AMD GPU (Windows/Linux, RDNA 3/3.5/4 only)** - Experimental support for RX 7000 series (RDNA 3), Strix Halo/Ryzen AI Max+ 365 (RDNA 3.5), and RX 9000 series (RDNA 4)
* **Intel GPU** - Arc series with native PyTorch torch.xpu support
* **Apple Silicon** - M1/M2/M3/M4 series with Metal acceleration
* **Ascend NPU** - Via torch\_npu extension
* **Cambricon MLU** - Via torch\_mlu extension
* **Iluvatar Corex** - Via Iluvatar Extension for PyTorch
* **CPU** - Use the `--cpu` parameter (slower)

Please refer to the [ComfyUI Windows and Linux manual installation section](https://github.com/Comfy-Org/ComfyUI?tab=readme-ov-file#manual-install-windows-linux) for detailed installation steps.

<Note>
  PyTorch 2.4 and above is supported, but some features and optimizations might only work on newer versions. We generally recommend using the latest major version of PyTorch with the latest CUDA version unless it is less than 2 weeks old.

  The Windows portable build currently comes with Python 3.13 and PyTorch CUDA 13.0. Update your Nvidia drivers if it doesn't start.
</Note>

### Dependencies

* Install PyTorch (version specific to your hardware)
* Install all dependencies in the requirements.txt of ComfyUI: `pip install -r requirements.txt`

<Card title="Manual Installation" icon="book" href="/installation/manual_install">
  Please refer to the manual installation section for detailed installation steps.
</Card>


# How to Update ComfyUI
Source: https://docs.comfy.org/installation/update_comfyui

This section provides a comprehensive guide to updating ComfyUI

While we've covered ComfyUI updates across different installation methods in various sections, this comprehensive guide consolidates all update procedures to help users clearly understand how to update ComfyUI.

## How to Update ComfyUI?

<Tabs>
  <Tab title="Portable">
    ComfyUI Portable provides convenient batch scripts for easy updates.

    ### Update Script Location

    In the `update` folder within your portable installation directory, you'll find the following update scripts:

    ```
    ComfyUI_windows_portable
    └─ 📂update
       ├── update.py
       ├── update_comfyui.bat                           // Update to latest development version
       ├── update_comfyui_stable.bat                    // Update to latest stable version
       └── update_comfyui_and_python_dependencies.bat   // ⚠️ DANGER: Reinstalls dependencies - may cause conflicts
    ```

    <Warning>Ensure a stable internet connection during updates.</Warning>

    <Warning>
      **⚠️ DANGER: Use `update_comfyui_and_python_dependencies.bat` with extreme caution!**

      This script is more thorough than regular updates and will:

      * ✅ Update ComfyUI code itself
      * ✅ Update PyTorch (for NVIDIA GPU CUDA 12.9)
      * ✅ Reinstall ALL Python dependencies

      **Risks:**

      * May cause dependency conflicts with your existing setup
      * Can break custom nodes that rely on specific package versions
      * May overwrite manually configured packages

      **⚠️ Only use this script when:**

      * You need to fix dependency issues
      * Performing major version updates
      * For daily updates, use `update_comfyui.bat` instead

      **Before running this script:**

      1. **Back up your entire ComfyUI installation**
      2. Document any custom package versions you've installed
      3. Be prepared to reinstall custom nodes if needed
    </Warning>
  </Tab>

  <Tab title="Desktop">
    ComfyUI Desktop features automatic updates to ensure you're always running the latest version. However, since the Desktop version is built on stable releases, feature updates may lag behind. You can also visit the [download page](https://www.comfy.org/download) to get the latest version.

    ### Auto-Update Settings

    Ensure automatic updates are enabled in your settings:

    <img alt="ComfyUI Desktop Settings" />

    ### Manual Update Check

    You can also manually check for available updates:

    1. Click `Menu` in the menu bar
    2. Select `Help`
    3. Click `Check for Updates`
       <img alt="ComfyUI Desktop Check Updates" />

    <Note>Desktop version automatically handles all update processes, including ComfyUI core code and dependency updates</Note>
  </Tab>

  <Tab title="Manual Installation">
    Manually installed ComfyUI requires Git commands to complete updates.

    ### Pre-Update Requirements

    Ensure your system has [Git](https://git-scm.com/downloads) installed and ComfyUI was installed via Git clone.

    ### Update Steps

    <Steps>
      <Step title="Activate Virtual Environment">
        First, activate ComfyUI's Python virtual environment (if using one):

        ```bash theme={null}
        # For conda environment
        conda activate comfyui

        # For venv environment
        # Windows
        venv\Scripts\activate
        # macOS/Linux  
        source venv/bin/activate
        ```
      </Step>

      <Step title="Pull Latest Code">
        Navigate to your ComfyUI installation directory and pull the latest code:

        ```bash theme={null}
        cd <ComfyUI-installation-path>
        git pull
        ```
      </Step>

      <Step title="Update Dependencies">
        Install or update ComfyUI's dependency packages:

        ```bash theme={null}
        pip install -r requirements.txt
        ```

        <Warning>
          Ensure you're in ComfyUI's virtual environment to avoid contaminating the system-level Python environment
        </Warning>
      </Step>

      <Step title="Restart ComfyUI">
        After updating, restart ComfyUI:

        ```bash theme={null}
        python main.py
        ```
      </Step>
    </Steps>

    ### Version Switching (Optional)

    To switch to a specific version, use these commands:

    ```bash theme={null}
    # View commit history
    git log --oneline

    # Switch to specific commit
    git checkout <commit-hash>

    # Return to latest version
    git checkout master
    ```

    <Tip>Regular updates are recommended for the latest features and security fixes, while stable versions are recommended for system stability</Tip>
  </Tab>
</Tabs>

## ComfyUI Version Types

Depending on your installation method, ComfyUI offers several installation versions. The links below contain update instructions for each version.

<AccordionGroup>
  <Accordion title="ComfyUI Desktop">
    ComfyUI Desktop currently supports standalone installation for **Windows and MacOS (ARM)**, currently in Beta

    * Code is open source on [Github](https://github.com/Comfy-Org/desktop)

    <Tip>
      Because Desktop is always built based on the **stable release**, so the latest updates may take some time to experience for Desktop, if you want to always experience the latest version, please use the portable version or manual installation
    </Tip>

    You can choose the appropriate installation for your system and hardware below

    <Tabs>
      <Tab title="Windows">
        <Card title="ComfyUI Desktop (Windows) Installation Guide" icon="link" href="/installation/desktop/windows">
          Suitable for **Windows** version with **Nvidia** GPU
        </Card>
      </Tab>

      <Tab title="MacOS(Apple Silicon)">
        <Card title="ComfyUI Desktop (MacOS) Installation Guide" icon="link" href="/installation/desktop/macos">
          Suitable for MacOS with **Apple Silicon**
        </Card>
      </Tab>

      <Tab title="Linux">
        <Note>ComfyUI Desktop **currently has no Linux prebuilds**, please visit the [Manual Installation](/installation/manual_install) section to install ComfyUI</Note>
      </Tab>
    </Tabs>
  </Accordion>

  <Accordion title="ComfyUI Portable (Windows)">
    Portable version is a ComfyUI version that integrates an independent embedded Python environment, using the portable version you can experience the latest features, currently only supports **Windows** system

    <Card title="ComfyUI Portable (Windows) Installation Guide" icon="link" href="/installation/comfyui_portable_windows">
      Supports **Windows** ComfyUI version running on **Nvidia GPUs** or **CPU-only**, always use the latest commits and completely portable.
    </Card>
  </Accordion>

  <Accordion title="Manual Installation">
    <Card title="ComfyUI Manual Installation Guide" icon="link" href="/installation/manual_install">
      Supports all system types and GPU types (Nvidia, AMD, Intel, Apple Silicon, Ascend NPU, Cambricon MLU)
    </Card>
  </Accordion>
</AccordionGroup>

## What Needs to Be Updated When Updating ComfyUI?

ComfyUI updates primarily consist of two components:

1. Update ComfyUI's core code
2. Update ComfyUI's core dependencies, including necessary Python dependencies and ComfyUI functional dependency packages

**Core Code**: New nodes, new model support, new features, etc.
**Core Dependencies**: Mainly includes ComfyUI's frontend functionality, workflow templates, node help documentation, etc.

```
comfyui-frontend-package   # ComfyUI frontend functionality
comfyui-workflow-templates # ComfyUI workflow templates  
comfyui-embedded-docs      # ComfyUI node help documentation
comfy-kitchen              # ComfyUI core utilities
comfy-aimdo                # ComfyUI core utilities
```

These core dependencies are maintained in separate repositories:

* [ComfyUI\_frontend](https://github.com/Comfy-Org/ComfyUI_frontend/) - Frontend interface and interactive features
* [workflow\_templates](https://github.com/Comfy-Org/workflow_templates) - Pre-built workflow templates
* [comfyui-embedded-docs](https://github.com/Comfy-Org/embedded-docs) - Node help documentation
* [comfy-kitchen](https://github.com/Comfy-Org/comfy-kitchen) - Fast kernel library for Diffusion inference with multiple compute backends
* [comfy-aimdo](https://github.com/Comfy-Org/comfy-aimdo) - AI Model Demand Offloading Allocator

It's important to understand the difference between development (nightly) and stable (release) versions:

* **Development version (nightly)**: Latest commit code, giving you access to the newest features, but may contain potential issues
* **Stable version (release)**: Built on stable releases, usually lags behind development versions but offers higher stability. We support stable versions after features are tested and stabilized

Many users often find themselves on release versions or desktop versions during updates, but discover that needed features are only available in development versions. In such cases, check if your local `ComfyUI/requirements.txt` matches the [nightly version dependencies](https://github.com/Comfy-Org/ComfyUI/blob/master/requirements.txt) to determine if all dependencies support the latest features.

## Common Update Issues

### Missing or Outdated Frontend, Workflow Templates, Node  After Updates

<Tabs>
  <Tab title="Dependencies Not Properly Updated">
    Users often only use the `git pull` command to update ComfyUI code but **neglect core dependency updates**, leading to the following issues:

    * Missing or abnormal frontend functionality
    * Cannot find newly added workflow templates
    * Outdated or missing node help documentation
    * New features lack corresponding frontend support

    After using the `git pull` command, use the corresponding ComfyUI environment to use `pip install -r requirements.txt` to update dependencies.
  </Tab>

  <Tab title="Dependency Update Failures">
    If dependency updates fail, it's commonly due to network or computer permission issues. When core dependency failures occur during updates, the system falls back to older versions. You'll typically see logs like this during startup:

    ```
    Falling back to the default frontend.
    ComfyUI frontend version: xxx
    ```

    Follow these troubleshooting steps:

    1. Use `pip list` in the appropriate environment to view currently installed dependency packages. If you find version inconsistencies, use `pip install -r requirements.txt` in the ComfyUI environment to attempt dependency updates again.
    2. If issues persist after updating, check your network connection. Users in mainland China may need to configure a proxy to reliably access GitHub repositories.
    3. If problems continue, check computer permissions. If administrator privileges are required, run the command line with administrator rights.
  </Tab>
</Tabs>

### How to Properly Update Core Dependencies

<Tabs>
  <Tab title="Portable">
    **Recommended Method**: Use the `ComfyUI_windows_portable\update\update_comfyui.bat` batch script, which will update both ComfyUI code and all Python dependencies.

    **Manual Dependency Update**:
    If you need to manually update dependencies, use the following command:

    ```bash theme={null}
    # Open command line in portable version directory
    .\python_embeded\python.exe -m pip install -r ComfyUI\requirements.txt
    ```
  </Tab>

  <Tab title="Manual Installation">
    <Steps>
      <Step title="Activate Python Environment">
        If you use Conda to manage Python environments, activate your environment first:

        ```bash theme={null}
        conda activate comfyui  # or other environment name
        ```
      </Step>

      <Step title="Update Code">
        Navigate to the ComfyUI root directory and update the code using Git:

        ```
        cd <ComfyUI_ROOT_PATH>
        git pull
        ```
      </Step>

      <Step title="Update Dependencies">
        Update ComfyUI dependencies - this step is crucial, especially for the `comfyui-frontend-package`:

        ```
        pip install -r requirements.txt
        ```
      </Step>
    </Steps>
  </Tab>

  <Tab title="Desktop">
    Desktop version usually handles dependency updates automatically. If you encounter issues:

    1. **Check if auto-update** is enabled
    2. **Manually trigger update**: Menu → Help → Check for Updates
    3. **Reinstall desktop version** (in extreme cases)
  </Tab>
</Tabs>

### Core Dependency Update Troubleshooting

If core dependency updates fail, follow these troubleshooting steps:

<Steps>
  <Step title="Check Network Connection">
    If located in mainland China, ensure you can access PyPI or configure a domestic mirror:

    ```bash theme={null}
    # Using Tsinghua University mirror
    pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
    ```
  </Step>

  <Step title="Install Core Packages Individually">
    If batch installation fails, try installing packages individually. **First check version requirements in `ComfyUI/requirements.txt`**:

    **Then install according to specified versions (use version numbers from your requirements.txt):**

    ```bash theme={null}
    pip install comfyui-frontend-package==<version> 
    pip install comfyui-workflow-templates==<version>
    pip install comfyui-embedded-docs==<version>
    pip install comfy-kitchen==<version>
    pip install comfy-aimdo==<version>
    ```

    <Warning>
      It's recommended to use the exact version numbers specified in `ComfyUI/requirements.txt`. Don't upgrade to the latest versions independently, as this may cause compatibility issues.
    </Warning>
  </Step>
</Steps>

### Why Can't I Find New Features After Updating?

This is one of the most common issues:

* If you're using the **Desktop version**, features may lag behind because the desktop version is built on stable releases
* Ensure you're using the **development version (nightly)**, not the **stable version (release)**

Additionally, ensure that corresponding dependencies have been successfully updated during the update process. If issues persist after updating, refer to the [Dependency Update Troubleshooting](#dependency-update-troubleshooting) section to diagnose problems.

### How to Switch Between Development (Nightly) and Stable (Release) Versions?

Differences between versions:

<Tabs>
  <Tab title="Development Version (Nightly)">
    * **Characteristics**: Contains the latest commit code
    * **Advantages**: Experience the latest features and improvements first
    * **Risks**: May contain undiscovered bugs or unstable factors
    * **Suitable for**: Developers, testers, users wanting to experience the latest features
  </Tab>

  <Tab title="Stable Version (Release)">
    * **Characteristics**: Tested and verified stable code
    * **Advantages**: High stability, suitable for production environments
    * **Disadvantages**: Feature updates have delays, may lag behind development versions by weeks or months
    * **Suitable for**: Users requiring stability, production environment users
  </Tab>
</Tabs>

<Tabs>
  <Tab title="Portable">
    Use `update_comfyui.bat` instead of `update_comfyui_stable.bat`:

    ```
    # Development version (latest features)
    double-click: update_comfyui.bat

    # Stable version
    double-click: update_comfyui_stable.bat
    ```
  </Tab>

  <Tab title="Manual Installation">
    ```bash theme={null}
    # Switch to development version
    git checkout master
    git pull

    # Switch to latest stable version
    git fetch --tags
    git checkout $(git describe --tags `git rev-list --tags --max-count=1`)
    ```
  </Tab>

  <Tab title="Desktop">
    Desktop version is typically built on stable releases and doesn't currently support version switching. If you need the latest features, we recommend:

    1. Wait for desktop version updates
    2. Or use portable/manual installation to experience the latest features
  </Tab>
</Tabs>

### What to Do When Errors Occur After Updates?

1. **Check Dependencies**: Run `pip install -r requirements.txt` to ensure all dependencies are updated
2. **Check Custom Nodes**: Some custom nodes may be incompatible with new versions
3. **Roll Back Version**: If issues are severe, you can roll back to a previous stable version

If problems occur, refer to our troubleshooting page for solutions.

<Card title="Troubleshooting" icon="bug" href="/troubleshooting/overview">
  Learn how to troubleshoot ComfyUI issues
</Card>

### How to Stay Updated on New Features?

* **GitHub Releases**: Check [ComfyUI Releases](https://github.com/Comfy-Org/ComfyUI/releases) for stable version updates
* **GitHub Commits**: View [latest commits](https://github.com/Comfy-Org/ComfyUI/commits/master) to understand development progress
* **Community Discussion**: Follow our [blog](https://blog.comfy.org) and [Twitter](https://x.com/comfyui) for the latest updates


# ComfyUI APP mode guide
Source: https://docs.comfy.org/interface/app-mode

Learn how to build and use APP mode in ComfyUI to simplify workflow interaction by defining custom input/output interfaces.

APP mode simplifies workflow interaction by allowing you to define custom input/output interfaces, making it easier to share and use workflows without editing nodes.

<iframe title="ComfyUI APP Mode Guide" />

<Note>
  APP mode is officially supported from ComfyUI front-end version 1.41.13. Earlier versions are in early test phase.
</Note>

## Enter APP mode

There are two ways to enter APP mode: click the top-left icon (**1**) and select **Enter app mode** from the dropdown, or use the breadcrumb navigation dropdown (**2**) at the top of the interface.

<img alt="Enter APP mode via top-left menu" />

1. Click the top-left icon (marked **1**) to open the dropdown menu and select **Enter app mode**.
2. Alternatively, use the breadcrumb navigation dropdown (marked **2**) at the top to enter APP mode.

## Build an APP mode workflow

<iframe title="How to Create APP Mode Workflows" />

If the workflow has never been configured for APP mode, entering APP mode will automatically open the APP mode builder.

<img alt="APP mode builder entry screen" />

1. If the workflow has no existing APP mode configuration, the APP mode builder opens by default.
2. Click **Build app** to enter the APP builder and start configuring.

### Step 1: Select inputs

The builder interface displays four guided steps (marked **1**, **2**, **3**, **4**) at the top. The bottom bar lets you exit the builder or navigate between steps.

<img alt="APP builder interface overview" />

1. The numbers **1 2 3 4** at the top correspond to the four build steps: selecting inputs, selecting outputs, previewing, and setting the default view.
2. The buttons at the bottom let you exit the builder or move between steps.
3. Areas marked in the canvas are selectable input/output parameters.
4. The right panel shows a live preview of the current configuration.

Click the **Inputs** step at the top. The canvas highlights selectable input nodes. Click a node to select it as an input parameter — options include image uploads, text prompt inputs, and model selection. Selected parameters appear in the right sidebar.

### Step 2: Select outputs

Click the **Outputs** step. Choose which output nodes to display in the APP, such as a Preview node or Save Image node.

<img alt="Selecting output nodes with right-panel preview" />

1. Select the output nodes to display in the APP.
2. Similar to inputs, the right sidebar displays a live preview of the selected output nodes.

### Step 3: Preview

Click the **Preview** step to review the final APP layout. The selected inputs appear on the right panel, and the output area is shown in the canvas.

<img alt="Preview mode showing input and output layout" />

1. This is the preview mode — check that all input and output configurations appear as expected.
2. If any adjustments are needed, click **Back** to return to the previous step.

### Step 4: Set a default view

Click the **Set a default view** step. Choose whether the workflow should open in **App** mode or **Node Graph** mode by default. Click **Apply** to confirm.

<img alt="Set default view step with App/Node Graph options" />

1. Choose whether the workflow defaults to **App** mode or **Node Graph** mode when opened.
2. Select **App** and click **Apply** to confirm. The workflow will then open in APP mode by default.

After applying, a confirmation prompt will appear.

<img alt="Confirmation prompt with View app button" />

Click **View app** to enter APP mode and start using the workflow.

## Use APP mode

In APP mode, the right panel shows all configured input options. Adjust the inputs as needed, then click **Run** to execute the workflow.

<img alt="APP mode interface with inputs panel and Run button" />

1. The right **Input** panel lets you adjust input parameters before running.
2. Click **Run** to execute the workflow.
3. The left sidebar provides additional controls, such as rebuilding the APP, viewing assets, and opening the workflow panel.

APP mode is also optimized for mobile and narrow-screen layouts. The interface adapts into a tab-based view, letting you switch between the input panel, output view, and Media Assets panel.

<img alt="APP mode mobile layout with inputs, outputs, and assets tabs" />

While running, a **Cancel this run** button appears at the top to stop the current execution.

<img alt="Running state with cancel option and results panel" />

1. Click **Cancel this run** at the top to stop the current run.
2. Switch between the queue view and the results view in the bottom panel.
3. Click the relevant area to open the assets panel.

## Save and share the workflow

### Save workflow

Use `Ctrl + S` (or `Cmd + S` on Mac) to save the workflow for future use.

Click the left sidebar button to open the saved workflows panel.

<img alt="Left sidebar showing saved APP workflows" />

1. Click the left sidebar button to open the panel, which displays all saved APP workflows.
2. Switch between saved APP workflows from this panel.

### Share workflow

<iframe title="How to Share Workflows" />

In APP mode, click the **Share** button in the left sidebar. If the workflow has not been saved yet, a dialog will prompt you to save it first before a link can be created.

<img alt="Share dialog prompting to save the workflow" />

1. Click the Share button in the left sidebar to open the Share dialog.
2. If the workflow is unsaved, enter a workflow name and click **Save workflow** to continue.

Once saved, the Share dialog shows the option to generate a link.

<img alt="Share dialog with Create a link button" />

Click **Create a link** to generate a shareable URL for the workflow.

<img alt="Share dialog showing the generated link with Copy button" />

Click **Copy** to copy the link. Recipients can open it and run the workflow directly — the full workflow configuration is included in the link.

<Note>
  Share links are only supported on Comfy Cloud.
</Note>


# Customizing ComfyUI Appearance
Source: https://docs.comfy.org/interface/appearance

Learn how to customize the appearance of ComfyUI using color palettes and advanced CSS options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

ComfyUI offers flexible appearance customization options that allow you to personalize the interface to your preferences.

## Color Palette System

The primary way to customize ComfyUI's appearance is through the built-in color palette system.

<img alt="Color Palette" />

This allows you to:

1. Switch ComfyUI themes
2. Export the currently selected theme as JSON format
3. Load custom theme configuration from JSON file
4. Delete custom theme configuration

<Note>
  For appearance needs that cannot be satisfied by the color palette, you can perform advanced appearance customization through the [user.css](#advanced-customization-with-user-css) file
</Note>

### How to Customize Color Themes

The color palette allows you to modify many specific properties. Here are some of the most commonly customized elements, with colors represented in hexadecimal format:

<Tip>
  1. The JSON comments below are for illustration only. Do not copy the content below for modification as it will cause the theme to malfunction.
  2. Since we are still iterating frequently, the content below may change with ComfyUI frontend updates. If you need to modify, please export the theme configuration from settings and then modify it.
</Tip>

```json theme={null}
{
  "id": "dark",                     // Must be unique, cannot be the same as other theme IDs
  "name": "Dark (Default)",         // Theme name, displayed in theme selector
  "colors": {
    "node_slot": {                  // Node connection slot color configuration
      "CLIP": "#FFD500",            // CLIP model connection slot color
      "CLIP_VISION": "#A8DADC",     // CLIP Vision model connection slot color
      "CLIP_VISION_OUTPUT": "#ad7452", // CLIP Vision output connection slot color
      "CONDITIONING": "#FFA931",     // Conditioning control connection slot color
      "CONTROL_NET": "#6EE7B7",     // ControlNet model connection slot color
      "IMAGE": "#64B5F6",           // Image data connection slot color
      "LATENT": "#FF9CF9",          // Latent space connection slot color
      "MASK": "#81C784",            // Mask data connection slot color
      "MODEL": "#B39DDB",           // Model connection slot color
      "STYLE_MODEL": "#C2FFAE",     // Style model connection slot color
      "VAE": "#FF6E6E",             // VAE model connection slot color
      "NOISE": "#B0B0B0",           // Noise data connection slot color
      "GUIDER": "#66FFFF",          // Guider connection slot color
      "SAMPLER": "#ECB4B4",         // Sampler connection slot color
      "SIGMAS": "#CDFFCD",          // Sigmas data connection slot color
      "TAESD": "#DCC274"            // TAESD model connection slot color
    },
    "litegraph_base": {             // LiteGraph base interface configuration
      "BACKGROUND_IMAGE": "",        // Background image, default is empty
      "CLEAR_BACKGROUND_COLOR": "#222", // Main canvas background color
      "NODE_TITLE_COLOR": "#999",    // Node title text color
      "NODE_SELECTED_TITLE_COLOR": "#FFF", // Selected node title color
      "NODE_TEXT_SIZE": 14,          // Node text size
      "NODE_TEXT_COLOR": "#AAA",     // Node text color
      "NODE_TEXT_HIGHLIGHT_COLOR": "#FFF", // Node text highlight color
      "NODE_SUBTEXT_SIZE": 12,       // Node subtext size
      "NODE_DEFAULT_COLOR": "#333",   // Node default color
      "NODE_DEFAULT_BGCOLOR": "#353535", // Node default background color
      "NODE_DEFAULT_BOXCOLOR": "#666", // Node default border color
      "NODE_DEFAULT_SHAPE": 2,        // Node default shape
      "NODE_BOX_OUTLINE_COLOR": "#FFF", // Node border outline color
      "NODE_BYPASS_BGCOLOR": "#FF00FF", // Node bypass background color
      "NODE_ERROR_COLOUR": "#E00",    // Node error state color
      "DEFAULT_SHADOW_COLOR": "rgba(0,0,0,0.5)", // Default shadow color
      "DEFAULT_GROUP_FONT": 24,       // Group default font size
      "WIDGET_BGCOLOR": "#222",       // Widget background color
      "WIDGET_OUTLINE_COLOR": "#666", // Widget outline color
      "WIDGET_TEXT_COLOR": "#DDD",    // Widget text color
      "WIDGET_SECONDARY_TEXT_COLOR": "#999", // Widget secondary text color
      "WIDGET_DISABLED_TEXT_COLOR": "#666", // Widget disabled state text color
      "LINK_COLOR": "#9A9",          // Connection line color
      "EVENT_LINK_COLOR": "#A86",    // Event connection line color
      "CONNECTING_LINK_COLOR": "#AFA", // Connecting line color
      "BADGE_FG_COLOR": "#FFF",      // Badge foreground color
      "BADGE_BG_COLOR": "#0F1F0F"    // Badge background color
    },
    "comfy_base": {                  // ComfyUI base interface configuration
      "fg-color": "#fff",            // Foreground color
      "bg-color": "#202020",         // Background color
      "comfy-menu-bg": "#353535",    // Menu background color
      "comfy-menu-secondary-bg": "#303030", // Secondary menu background color
      "comfy-input-bg": "#222",      // Input field background color
      "input-text": "#ddd",          // Input text color
      "descrip-text": "#999",        // Description text color
      "drag-text": "#ccc",           // Drag text color
      "error-text": "#ff4444",       // Error text color
      "border-color": "#4e4e4e",     // Border color
      "tr-even-bg-color": "#222",    // Table even row background color
      "tr-odd-bg-color": "#353535",  // Table odd row background color
      "content-bg": "#4e4e4e",       // Content area background color
      "content-fg": "#fff",          // Content area foreground color
      "content-hover-bg": "#222",    // Content area hover background color
      "content-hover-fg": "#fff",    // Content area hover foreground color
      "bar-shadow": "rgba(16, 16, 16, 0.5) 0 0 0.5rem" // Bar shadow effect
    }
  }
}
```

## Canvas

### Background Image

* **Requirements**: ComfyUI frontend version 1.20.5 or newer
* **Function**: Set a custom background image for the canvas to provide a more personalized workspace. You can upload images or use web images to set the background for the canvas.

<img alt="Set Background Image" />

## Node

### Node Opacity

* **Function**: Set the opacity of nodes, where 0 represents completely transparent and 1 represents completely opaque.

<img alt="Node Opacity" />

## Node Widget

### Textarea Widget Font Size

* **Range**: 8 - 24
* **Function**: Set the font size in textarea widgets. Adjusts the text display size in text input boxes to improve readability.

<img alt="Textarea Widget Font Size" />

## Sidebar

### Unified Sidebar Width

* **Function**: When enabled, the sidebar width will be unified to a consistent width when switching between different sidebars. If disabled, different sidebars can maintain their custom widths when switching.

### Sidebar Size

* **Function**: Control the size of the sidebar, can be set to normal or small.

### Sidebar Location

* **Function**: Control whether the sidebar is displayed on the left or right side of the interface, allowing users to adjust the sidebar position according to their usage habits.

### Sidebar Style

* **Function**: Control the visual style of the sidebar. Options include:
  * **Connected**: The sidebar appears connected to the edge of the interface.
  * **Floating**: The sidebar appears as a floating panel with visual separation from the interface edge.

<img alt="Sidebar Style" />

## Tree Explorer

### Tree Explorer Item Padding

* **Function**: Set the padding of items in the tree explorer (sidebar panel), adjusting the spacing between items in the tree structure.

<img alt="Tree Explorer Item Padding" />

## Advanced Customization with user.css

For cases where the color palette doesn't provide enough control, you can use custom CSS via a user.css file. This method is recommended for advanced users who need to customize elements that aren't available in the color palette system.

### Requirements

* ComfyUI frontend version 1.20.5 or newer

### Setting Up user.css

1. Create a file named `user.css` in your ComfyUI user directory (same location as your workflows and settings - see location details below)
2. Add your custom CSS rules to this file
3. Restart ComfyUI or refresh the page to apply changes

### User Directory Location

The ComfyUI user directory is where your personal settings, workflows, and customizations are stored. The location depends on your installation type:

<Tabs>
  <Tab title="Desktop - Windows">
    ```
    C:\Users\<your username>\AppData\Roaming\ComfyUI\user
    ```
  </Tab>

  <Tab title="Desktop - macOS">
    ```
    ~/<ComfyUI installation path>/ComfyUI/user
    ```
  </Tab>

  <Tab title="Desktop - Linux">
    ```
    ~/.config/ComfyUI/user
    ```
  </Tab>

  <Tab title="Manual Install">
    The user directory is located in your ComfyUI installation folder:

    ```
    <ComfyUI installation path>/user
    ```

    For example, if you cloned ComfyUI to `C:\ComfyUI`, your user directory would be `C:\ComfyUI\user\default` (or `C:\ComfyUI\user\john` if you've set up a custom username).

    <Note>
      ComfyUI supports multiple users per installation. If you haven't configured a custom username, it defaults to "default". Each user gets their own subdirectory within the `user` folder.
    </Note>
  </Tab>

  <Tab title="Portable">
    The user directory is located in your ComfyUI portable folder:

    ```
    <ComfyUI_windows_portable>/ComfyUI/user
    ```

    For example: `ComfyUI_windows_portable/ComfyUI/user/default`

    <Note>
      ComfyUI supports multiple users per installation. If you haven't configured a custom username, it defaults to "default". Each user gets their own subdirectory within the `user` folder.
    </Note>
  </Tab>
</Tabs>

This location contains your workflows, settings, and other user-specific files.

After finding the above folder location, please copy the corresponding CSS file to the corresponding user directory, such as the default user folder being `ComfyUI/user/default`, then restart ComfyUI or refresh the page to apply changes.

### user.css Examples and Related Instructions

The `user.css` file is loaded early in the application startup process. So you may need to use `!important` in your CSS rules to ensure they override the default styles.

**user.css Customization Examples**

```css theme={null}
/* Increase font size in inputs and menus for better readability */
.comfy-multiline-input, .litecontextmenu .litemenu-entry {
    font-size: 20px !important;
}

/* Make context menu entries larger for easier selection */
.litegraph .litemenu-entry,
.litemenu-title {
  font-size: 24px !important; 
}

/* Custom styling for specific elements not available in the color palette */
.comfy-menu {
    border: 1px solid rgb(126, 179, 189) !important;
    border-radius: 0px 0px 0px 10px !important;
    backdrop-filter: blur(2px);
}
```

**Best Practices**

1. **Start with the color palette** for most customizations
2. Use **user.css only when necessary** for elements not covered by the color palette
3. **Export your theme** before making significant changes so you can revert if needed
4. **Share your themes** with the community to inspire others

**Troubleshooting**

* If your color palette changes don't appear, try refreshing the page
* If CSS customizations don't work, check that you're using frontend version 1.20.5+
* Try adding `!important` to user.css rules that aren't being applied
* Keep backups of your customizations to easily restore them


# Credits Management
Source: https://docs.comfy.org/interface/credits

In this article, we will introduce ComfyUI's credit management features, including how to obtain, use, and view credits.

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

The credit system was added to support the `Partner Nodes`, as calling closed-source AI models requires token consumption, so proper credit management is necessary. By default, the credits interface is not displayed. Please first log in to your ComfyUI account in `Settings` -> `User`, and then you can view your associated account's credit information in `Settings` -> `Credits`.

<img alt="ComfyUI Credits Interface" />

<Note>
  ComfyUI will always remain fully open-source and free for local users.
</Note>

## How to Purchase Credits?

Below is a demonstration video for purchasing credits:

<video />

Detailed steps are as follows:

<Steps>
  <Step title="Log in to your ComfyUI account">
    Log in to your ComfyUI account in `Settings` -> `User`

    <img alt="Login Interface" />
  </Step>

  <Step title="Go to `Settings` -> `Credits` to purchase credits">
    After logging in, you should see the `Credits` option added to the menu

    Go to `Settings` -> `Credits` to purchase credits

    <img alt="Credits Interface" />
  </Step>

  <Step title="Set the amount of credits to purchase">
    <img alt="Set Purchase Amount" />

    In the popup, set the purchase amount and click the `Buy` button
  </Step>

  <Step title="Make payment through Stripe">
    <img alt="Stripe Payment Page" />

    On the payment page, please follow these steps:

    1. Select the currency for payment
    2. Confirm that the email is the same as your ComfyUI registration email
    3. Choose your payment method

    * Credit Card
    * WeChat (only supported when paying in Comfy Credits)
    * Alipay (only supported when paying in Comfy Credits)

    4. Click the `Pay` button or the `Generate QR Code` button to complete the payment process
  </Step>

  <Step title="Complete payment and check your credit balance">
    <img alt="Payment Successful" />

    After completing the payment, please return to `Menu` -> `Credits` to check if your balance has been updated. Try refreshing the interface or restarting if necessary
  </Step>
</Steps>

## Frequently Asked Questions

<AccordionGroup>
  <Accordion title="Can credits go negative?">
    Credits are not intended to be used as a negative balance or credit line. However, due to race conditions where partner nodes don't always report costs before execution, a single execution may consume more credits than your remaining balance and temporarily result in a negative balance after completion. When your balance is negative, you will not be able to run Partner Nodes until you top up and restore a positive balance. Please ensure you have enough credits before making API calls.
  </Accordion>

  <Accordion title="Can I get a refund for unused credits?">
    Currently, we do not support refunds
  </Accordion>

  <Accordion title="How do I check my current balance and usage?">
    Click on `Settings` -> `Credits` to see your current balance and access the `Credit History` entry
  </Accordion>

  <Accordion title="Can I share my credits with other users?">
    You can log into the same account on multiple devices, but we do not support sharing credits with other users
  </Accordion>

  <Accordion title="How do I know how many credits I've consumed each time?">
    Due to different image sizes and generation quantities, the `Tokens` and `Credits` consumed each time vary. In `Settings` -> `Credits`, you can see the credits consumed each time and the corresponding credit history
  </Accordion>

  <Accordion title="Why don't I see WeChat or Alipay payment options?">
    Please ensure you are paying in Comfy Credits, as WeChat and Alipay are only supported when paying in Comfy Credits
  </Accordion>

  <Accordion title="Do credits expire?">
    Yes, the expiration depends on the type of credits:

    * **Monthly credits**: Expire at the end of your billing period
    * **Top-up credits**: Expire 1 year from the date of purchase
  </Accordion>
</AccordionGroup>


# Node docs - View documentation for any node
Source: https://docs.comfy.org/interface/features/node-docs

Learn how to access built-in documentation for nodes in ComfyUI, including both built-in and custom nodes.

Node docs provide quick access to documentation for any node in your workflow. You can view detailed information about a node's functionality, parameters, and usage examples directly within ComfyUI.

## How to view node docs

<img alt="Node docs" />

1. **Select a node:**\
   Click on any node in your workflow to select it.

2. **Open node docs:**\
   Click the node info icon in the selection toolbox to open the node documentation page.

3. **Exit node docs:**\
   If you want to exit the node docs, you can click the arrow icon in the top left corner to exit the node docs.

You can also access the node docs via the node library, hover on a node then click the "?" icon to open the node docs.

<img alt="Node docs" />

## Built-in node documentation

Documentation for ComfyUI's built-in nodes is maintained in the [embedded-docs repository](https://github.com/Comfy-Org/embedded-docs).

**Contributing to built-in node docs:**

* Users can contribute improvements and additions to built-in node documentation
* Submit pull requests to the [embedded-docs repository](https://github.com/Comfy-Org/embedded-docs)
* Help improve documentation quality for the entire ComfyUI community

## Custom node documentation

Custom nodes can also include their own documentation. When custom node authors provide documentation, it will automatically appear in the node docs panel when you select their nodes.

<Card title="Developer guide: Adding node docs" icon="code" href="/custom-nodes/help_page">
  Learn how to create rich documentation for your custom nodes
</Card>


# Partial Execution - Run Only Part of Your workflow in ComfyUI
Source: https://docs.comfy.org/interface/features/partial-execution

How to use and the requirements for the Partial Execution feature in ComfyUI

<img alt="Partial Execution Feature" />

The Partial Execution feature is located in the ComfyUI node selection toolbox. It allows you to run only a part of your workflow instead of executing all nodes. This feature is only available when the selected node is an output node, and when available, it appears as a green triangle icon.

## What is Partial Execution?

Partial Execution, as the name suggests, lets you run only a part of your workflow instead of executing all nodes in the workflow.

<img alt="Partial Execution" />

The diagram above compares Partial Execution and running the entire workflow:

1. Partial Execution (left): Only runs the branch of the workflow from the starting node to the output node.
2. Run Workflow (right): Runs all nodes in the workflow.

This feature allows you to flexibly execute specific parts of your workflow, rather than running the entire workflow every time.

## How to Use the Partial Execution Feature?

<img alt="Partial Execution Requirements" />

To use the Partial Execution feature, the currently selected node must be an output node, such as preview or save nodes. When the corresponding node meets the criteria, after selecting the node, the button in the toolbox will display as a green triangle icon. Click this icon to run the partial workflow.

## Common Issues

Q: Why do all nodes run when I use this feature?
A: Please ensure your ComfyUI frontend version is after v1.23.4, or possibly requires v1.24.x version. The corresponding bug was fixed around version 1.24.x, so please update your ComfyUI to the latest version to ensure the frontend version meets the requirements.


# Subgraph - Simplify your workflow
Source: https://docs.comfy.org/interface/features/subgraph

An introduction to the Subgraph feature in ComfyUI, including how to create, navigate, and manage subgraphs.

<Note>
  The subgraph feature requires ComfyUI frontend version 1.24.3 or later. If you don't see this feature, please refer to: [How to Update ComfyUI](/installation/update_comfyui)

  * Images in this document are made with nightly version frontend, please refer to the actual interface
  * Some features like converting subgraph back to nodes will be supported in the future
</Note>

<Tip>
  For developer documentation on working with subgraphs programmatically, see the [Subgraph Developer Guide](/custom-nodes/js/subgraphs).
</Tip>

<iframe title="ComfyUI Selection Toolbox New Features" />

A subgraph is a powerful ComfyUI feature that lets you package complex workflows into a single reusable subgraph node, making them easier to manage and share.

<img alt="Subgraph" />

Think of a subgraph as a "folder" for your workflow – you can group related nodes together and use the entire collection as one unified subgraph node.

**Use subgraphs to:**

* Simplify complex workflows
* Reuse common node combinations
* Build more efficient workflows with modular components

## Creating a Subgraph

<Steps>
  <Step title="Select nodes">
    Select the nodes you want to group in ComfyUI
  </Step>

  <Step title="Click the subgraph icon">
    <img alt="Subgraph icon" />

    Find the subgraph icon in the toolbar
  </Step>

  <Step title="Subgraph created">
    <img alt="Workflow using subgraph" />

    ComfyUI automatically creates a subgraph based on your selected nodes' inputs and outputs
  </Step>

  <Step title="Customize your subgraph">
    Refer to [Editing Subgraphs](#editing-subgraphs), you can edit and organize the subgraph to create a fully functional node

    <img alt="Workflow using subgraph" />
  </Step>
</Steps>

## Working with Subgraphs

### Basic Operations

Subgraphs work just like regular nodes. You can:

* Change colors and names
* Use bypass to disable
* Apply all standard node operations

### Editing Subgraphs

**To enter edit mode:**

* Double-click the empty area inside the subgraph (not on widgets), or
* Click the subgraph edit button

<img alt="Subgraph editing mode" />

**In edit mode you'll see:**

1. **Navigation bar**: Exit the current subgraph and return to the parent level
2. **Input slots**: Internal node inputs exposed to the outside
   * Connect outputs to slots like normal nodes
   * **Right-click** connection points to rename/delete exposed slots
3. **Output slots**: Outputs exposed to the outside (same functionality as input slots)

<img alt="Subgraph slots" />

**Working with slots:**

1. **Default slot** (labeled 1): Use this to add new input/output connections
2. **Right-click** existing slots to rename, delete, or disconnect from original nodes

> Note: Slot connections follow standard data type validation rules

### Parameters Panel

With ComfyUI v0.3.66 or later, you can edit the subgraph parameters directly from the parameters panel without entering the subgraph.

You can select any subgraph and use the "Edit Subgraph Widgets" button to open the parameters panel.

<img alt="Open Parameters Panel" />

After it is opened, you can edit the order and visibility of the subgraph widgets directly in the parameters panel.

<img alt="Open Parameters Panel" />

1. Reordering: you use right-click and hold the widget to drag it to the desired position
2. Visibility: you can check the visibility of the widget by clicking the eye icon

### Nested Subgraphs

Create even more complex workflows by nesting subgraphs within subgraphs.

<img alt="Nested subgraph" />

The navigation bar shows your current level and lets you easily move between nested subgraphs.

<img alt="Nested subgraph navigation" />

### Exit subgraph

To exit a subgraph and return to the parent level:

* Use the **Navigation bar** (labeled 1 in the image) at the top of the canvas, or
* Press the **Esc** key

<img alt="Subgraph editing mode" />

Click on the navigation bar or press Esc to exit the current subgraph and return to the parent workflow.

## Unpack Subgraphs to Nodes

When you're done creating a subgraph, you can convert it back to nodes if you need to.

<img alt="Subgraph to node" />

1. You can select the subgraph node then use right-click menu "Unpack subgraph" to convert it back to nodes.
2. Click the "Unpack subgraph" button in the select toolbox to convert it back to nodes.

## Subgraph Blueprint

With ComfyUI frontend version 1.27.7 or later, you can publish your subgraph to the node library.

This feature allows you to convert a subgraph to a `Subgraph Blueprints` node, which means it's a reusable subgraph node.

### Publish Subgraph to Node Library

<img alt="Publish Subgraph" />

Currently, you have two ways to publish subgraph to node library, both are in the selection toolbox:

1. Click the `book(publish)` icon on the selection toolbox
2. Open the selection toolbox menu, use the `Add Subgraph to Library` menu to publish subgraph

After you click on the `book(publish)` icon or `Add Subgraph to Library` menu, you will see the following dialog:

<img alt="Subgraph naming" />

By default, the subgraph will use the name of the subgraph node as the name of the subgraph blueprint.

After publishing, you will see the subgraph blueprint node in the node library.

<img alt="Subgraph blueprint node" />

Now, you can drag or search the subgraph just like a normal node. The new subgraph node that has been added from Subgraph Blueprints is still isolated, which means after adding it to the workflow, it can be edited independently, they will not affect each other.

### Edit Subgraph Blueprint

If you want to edit the subgraph blueprint, you can click the edit button just like the image below, you can delete it as well.

<img alt="Edit Subgraph Blueprint" />

This will enable the subgraph editing mode

<img alt="Subgraph editing mode" />

After editing the subgraph blueprint, you can go to the parent level to preview the subgraph.

<img alt="Update Subgraph Blueprint" />

If you want to save the updated subgraph blueprint, you can click the save button or use the shortcut key Ctrl + S.


# Templates - ComfyUI Built-in Workflow Templates
Source: https://docs.comfy.org/interface/features/template

Templates provide model workflows natively supported by ComfyUI and example workflows from custom nodes. You can find and use workflows for currently supported models here.

Workflow Templates is the browser for ComfyUI's natively supported model workflows and also some example workflows from custom nodes.

In ComfyUI’s Workflow Templates, you can find:

* Natively supported model workflows
* Example workflows from custom nodes

<img alt="Template" />

## How to open Templates in ComfyUI

Click the **Templates** icon in the sidebar to open Workflow Templates. You can also open it from the menu **Workflow** → **Browse Workflow Templates**.

<img alt="Template" />

## How to use templates

1. Load a template: Click any template you want to load its workflow.
2. Download models: When loading a template, ComfyUI automatically checks whether all required model files exist. If anything is missing, it will prompt you to download the models.
3. Run the workflow: Once all requirements—such as models, input images, and prompts—are ready, click the Run button to start using the workflow.

### Model storage location

Each workflow template embeds links to the required models. On first use, if the corresponding model files are not detected, you will see a download prompt.

<img alt="Missing Models" />

1. For desktop version, when you click the `Download` button, the desktop program will automatically download the model files for you.
2. For other versions, the browser will be used to download the corresponding model. You need to download the model and save it to the corresponding folder under `ComfyUI/models`. For example, the model in the screenshot should be saved in the following location:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── qwen_image_fp8_e4m3fn.safetensors
│   ├── 📂 vae/
│   │   └── qwen_image_vae.safetensors
│   └── 📂 text_encoders/
│       └── qwen_2.5_vl_7b_fp8_scaled.safetensors
```

In the current version, missing-file detection only checks whether there is a file with the same name in the corresponding top-level directory. For example, the file must exist directly under `ComfyUI/models/diffusion_models`.
If you have already downloaded the model into a subfolder such as `ComfyUI/models/diffusion_models/wan_video`, you can ignore the popup and simply ensure the correct model is selected in the corresponding model loader node.

If you're curious how model links are embedded, we add a `models` field under the node’s `properties`. Below is a complete snippet of a `DualCLIPLoader` node with embedded model information:

```json theme={null}
    {
      "id": 40,
      "type": "DualCLIPLoader",
      "pos": [
        -320,
        290
      ],
      "size": [
        270,
        130
      ],
      "flags": {},
      "order": 0,
      "mode": 0,
      "inputs": [],
      "outputs": [
        {
          "name": "CLIP",
          "type": "CLIP",
          "links": [
            64
          ]
        }
      ],
      "properties": {
        "Node name for S&R": "DualCLIPLoader",
        "cnr_id": "comfy-core",
        "ver": "0.3.40",
        "models": [
          {
            "name": "clip_l.safetensors",
            "url": "https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors",
            "directory": "text_encoders"
          },
          {
            "name": "t5xxl_fp16.safetensors",
            "url": "https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors",
            "directory": "text_encoders"
          }
        ]
      },
      "widgets_values": [
        "clip_l.safetensors",
        "t5xxl_fp16.safetensors",
        "flux",
        "default"
      ]
    }
```

The `models` field inside `properties` includes `name`, `url`, and `directory`.

* `name`: the model file name
* `url`: a direct download link to the file (not a repository page)
* `directory`: which subfolder under `ComfyUI/models` to store the file, e.g. `vae` means `ComfyUI/models/vae`

Currently, only links from Hugging Face and Civitai are supported. The model format must be a safe format such as `.safetensors` or `.sft`. Formats like `.gguf` are considered unsafe; when embedded they will be flagged as unsafe and the link will not be shown.

You can use [this tool](https://comfyui-wiki.github.io/ComfyUI-Workflow-JSON-Editor/) to edit the model information in workflow templates. At the moment, [@ComfyUI-Wiki](https://github.com/ComfyUI-Wiki) only adds support for native nodes.

## How to update templates?

Templates are managed and updated as a separate dependency: [`comfyui-workflow-templates`](https://pypi.org/project/comfyui-workflow-templates/).

If, after updating ComfyUI, you don’t see the documentation or newly announced templates, you may need to update the corresponding dependency. You can check versions in [`ComfyUI/requirements.txt`](https://github.com/Comfy-Org/ComfyUI/blob/master/requirements.txt).

Typically, the following three dependencies may be upgraded together when ComfyUI is updated:

```
comfyui-frontend-package==1.24.4
comfyui-workflow-templates==0.1.52
comfyui-embedded-docs==0.2.4
```

If you’re not sure how to update correctly, see [Update ComfyUI](/installation/update_comfyui) for how to update ComfyUI and its dependencies.

## How to contribute templates to the ComfyUI repository?

All templates are hosted in the [workflow\_templates](https://github.com/Comfy-Org/workflow_templates/) repository. You can contribute templates by submitting a PR. For official templates, we require the following:

1. Do not use any third-party nodes (to avoid extra installations for users who lack those nodes).
2. The template must not duplicate existing ones and should target supported model capabilities.
3. You may open an issue in the repository to ask questions.

## Custom node templates

If a custom node author provides templates and example workflows, you can also find them in the Templates browser. Usually, you can locate all templates by finding the category named after the node.

If you are a custom node author, note that we currently only support a single directory level under the `templates` folder (no nested subdirectories), and only JSON-format templates are supported.

## How to add templates for custom nodes?

See [Custom Node Templates](/custom-nodes/workflow_templates) for how to add workflow templates for your custom nodes.


# Mask Editor - Create and Edit Masks in ComfyUI
Source: https://docs.comfy.org/interface/maskeditor

Learn how to use the Mask Editor in ComfyUI, including tools, layers, settings, and shortcuts

The Mask Editor is a built-in tool in ComfyUI that lets you create and edit masks directly on your images — no external image editor needed. It supports multiple drawing tools, layer management, undo/redo, canvas transformations, and GPU-accelerated brush rendering.

***

## How to Open

There are three ways to open the Mask Editor:

1. **Selection Toolbox** — Select a Load Image node, then click the Mask icon button in the selection toolbar above the node.
2. **Image Overlay** — Hover over the image preview (gallery mode), then click the **Edit or mask image** button (mask icon) that appears in the top-left corner.
3. **Right-Click Menu** — Right-click a Load Image node and select `Open in Mask Editor` from the context menu.

> The Mask Editor is available in both **Graph Mode** and **App Mode**.

<img alt="Three ways to open the Mask Editor: Selection Toolbox, Image Overlay, and Right-Click Menu" />

***

## Interface Overview

<img alt="Mask Editor main interface with tool panel, canvas, and settings side panel" />

The Mask Editor opens as a modal dialog with four main areas:

| # | Area             | Location | Description                                                         |
| - | ---------------- | -------- | ------------------------------------------------------------------- |
| 1 | **Top Bar**      | Top      | Header with undo/redo, canvas transforms, invert/clear, save/cancel |
| 2 | **Tool Panel**   | Left     | Tool selection and zoom info                                        |
| — | **Pointer Zone** | Center   | The main canvas area for drawing and editing                        |
| 3 | **Side Panel**   | Right    | Tool-specific settings and layer controls                           |

***

## Tools

The tool panel on the left side offers five tools. Select a tool to activate it, and the right panel will show its settings.

<img alt="Mask Editor tool panel with 5 numbered tools" />

| # | Tool             | Layer       | Description                                                                                                                                                                                              |
| - | ---------------- | ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| 1 | **Mask Pen**     | Mask        | Primary tool for drawing mask regions. Left-click and drag to paint mask on the image.                                                                                                                   |
| 2 | **Paint Pen**    | RGB (Paint) | Paint directly onto the image's RGB layer. Useful for inpainting or touching up the base image.                                                                                                          |
| 3 | **Eraser**       | Mask / RGB  | Erase parts of an existing mask or paint layer.                                                                                                                                                          |
| 4 | **Paint Bucket** | Mask        | Flood-fill tool based on color similarity. Click a pixel to fill the connected region with a mask; click an already-masked area to erase from the mask. Tolerance controls how broadly the fill spreads. |
| 5 | **Color Select** | Mask        | Selectively mask all pixels matching a target color, with advanced matching algorithms (Simple HSL / LAB).                                                                                               |

***

## TopBar Actions

<img alt="Mask Editor TopBar actions labeled 1–10" />

The top bar provides canvas-wide operations:

| #  | Action                           | Description                             |
| -- | -------------------------------- | --------------------------------------- |
| 1  | **Undo** (Ctrl+Z)                | Revert the last action                  |
| 2  | **Redo** (Ctrl+Shift+Z / Ctrl+Y) | Reapply a reverted action               |
| 3  | **Rotate Left**                  | Rotate all layers 90° counter-clockwise |
| 4  | **Rotate Right**                 | Rotate all layers 90° clockwise         |
| 5  | **Mirror Horizontal**            | Flip all layers horizontally            |
| 6  | **Mirror Vertical**              | Flip all layers vertically              |
| 7  | **Invert**                       | Invert the mask (black ↔ white)         |
| 8  | **Clear**                        | Clear the entire mask                   |
| 9  | **Save**                         | Save the mask and close the editor      |
| 10 | **Cancel**                       | Close without saving                    |

> **Note**: Rotate and mirror operations affect all three layers (mask, paint, and base image) simultaneously. GPU-accelerated textures are recreated after transforms.

***

## Layers

The right panel includes a **Layers** section where you can toggle visibility of each layer independently:

* **Mask Layer**: The mask overlay. You can adjust its **opacity** and **blending mode**:
  * `Black` — Mask renders as black overlay
  * `White` — Mask renders as white overlay
  * `Negative` — Inverted mask rendering
* **Paint Layer**: The RGB paint layer (visible when using Paint Pen)
* **Base Image Layer**: The original source image

Click **Activate Layer** on a layer to switch drawing focus to it.

Refer to the main editor screenshot above — the right panel includes brush settings and the Layers section at the bottom.

***

## Brush Settings

When a brush-based tool (Mask Pen, Paint Pen, or Eraser) is active, the side panel shows brush settings:

| Setting       | Range         | Description                                                    |
| ------------- | ------------- | -------------------------------------------------------------- |
| **Shape**     | Arc / Rect    | Round brush or square brush                                    |
| **Color**     | Any hex color | The paint color (for Paint Pen) or mask color                  |
| **Thickness** | 1–250         | Brush diameter in pixels                                       |
| **Opacity**   | 0–1           | Brush stroke transparency                                      |
| **Hardness**  | 0–1           | Edge softness. 1 = hard edge, 0 = very soft                    |
| **Step Size** | 1–100         | Spacing between brush dabs. Lower values give smoother strokes |

Use **Reset to Default** to restore the default brush parameters.

***

## Canvas Navigation & Shortcuts

| Shortcut                             | Action                                                                  |
| ------------------------------------ | ----------------------------------------------------------------------- |
| **Space + Drag**                     | Pan the canvas                                                          |
| **Ctrl + Scroll**                    | Zoom in/out                                                             |
| **Click zoom %**                     | Reset zoom to 100%                                                      |
| **Ctrl + Z**                         | Undo                                                                    |
| **Ctrl + Shift + Z** or **Ctrl + Y** | Redo                                                                    |
| **Alt + Right-click + Drag**         | Adjust brush: left/right changes **size**, up/down changes **hardness** |

***

## Settings

In the ComfyUI Settings panel, you can configure the following Mask Editor options:

| Setting                                    | Category                                           | Default       | Description                                                                                          |
| ------------------------------------------ | -------------------------------------------------- | ------------- | ---------------------------------------------------------------------------------------------------- |
| **Brush adjustment speed multiplier**      | Mask Editor → Brush Adjustment → Sensitivity       | 1.0 (0.1–2.0) | How quickly the brush size and hardness change when using Alt+Right-click drag                       |
| **Lock brush adjustment to dominant axis** | Mask Editor → Brush Adjustment → Use Dominant Axis | On            | When enabled, the adjustment affects only size OR hardness based on your dominant movement direction |

***

## Video Tutorial

<video>
  <source type="video/mp4" />

  Your browser does not support the video tag.
</video>

> **Note**: This video demonstrates an older version of the Mask Editor (Nodes 1.0 UI) showing brush size adjustment and mask preview creation. The overall workflow remains the same in the current version.


# Nodes 2.0
Source: https://docs.comfy.org/interface/nodes-2

Learn about Nodes 2.0, the new Vue-based node rendering system in ComfyUI that enables faster development and richer interactions.

Nodes 2.0 is now available in ComfyUI Desktop, portable, and stable releases. This update transitions the node system from LiteGraph.js Canvas rendering to a Vue-based architecture, unlocking faster iteration and richer interactions.

## Why this change?

The previous Canvas rendering system had become a development bottleneck. Even small UI changes often required deep modifications and could take days to implement. This slowed the ability to respond to community feedback and made node customization difficult for developers.

The new Vue-based system enables:

* **Faster feature development** - UI changes can be implemented more quickly
* **Richer interactions** - Dynamic widgets, expandable nodes, and better components
* **A more flexible foundation** - Better support for future tools and customization

## Current status and known issues

We're actively working on improvements and want to be transparent about current limitations:

| Area              | Status                                                                                      |
| ----------------- | ------------------------------------------------------------------------------------------- |
| **Performance**   | Still optimizing toward Canvas-level performance. Certain scenarios may behave differently. |
| **Compatibility** | Some custom nodes may require updates to be fully supported.                                |
| **Edge cases**    | At extreme zoom levels or within very large workflows, minor visual issues may appear.      |

We're gathering feedback to prioritize improvements. The LiteGraph.js rendering system remains available, and you can toggle between systems at any time.

## How to try it

### Enable Nodes 2.0

1. Visit [cloud.comfy.org](https://cloud.comfy.org) or update to the latest version of ComfyUI Desktop, portable, or stable release
2. Click **Try it out** on the top banner when you launch ComfyUI

### What to test

Use Nodes 2.0 in your daily workflows and share feedback with us:

* **Basic interactions** - Dragging, resizing, selecting
* **Daily workflows** - Execution, parameters, custom nodes
* **Performance** - Especially with complex workflows

## How to provide feedback

Encountered issues or have suggestions for interaction improvements?

* **Support center** - [ComfyUI Help Center](https://support.comfy.org)
* **GitHub issues** - [Create an issue in ComfyUI\_frontend](https://github.com/Comfy-Org/ComfyUI_frontend/issues)

<Tip>
  Including reproduction steps, screenshots, and system info is extremely helpful when reporting issues.
</Tip>

## Switching back

If you encounter issues:

1. Click on the **ComfyUI logo** to open the menu
2. Toggle **Nodes 2.0** to switch back to the previous interface

<img alt="Nodes 2.0 toggle location in ComfyUI menu" />

Your feedback helps us prioritize improvements. Enable Nodes 2.0 in settings and start exploring the new node design!


# ComfyUI Interface Overview
Source: https://docs.comfy.org/interface/overview

In this article, we will briefly introduce the basic user interface of ComfyUI, familiarizing you with the various parts of the ComfyUI interface.

The visual interface is currently the way most users utilize ComfyUI to call the [ComfyUI Server](/development/comfyui-server/comms_overview) to generate corresponding media resources. It provides a visual interface for users to operate and organize workflows, debug workflows, and create amazing works.

Typically, when you start the ComfyUI server, you will see an interface like this:

<img alt="ComfyUI Basic Interface" />

Currently, the [ComfyUI frontend](https://github.com/Comfy-Org/ComfyUI_frontend) is a separate project, released and maintained as an independent pip package. If you want to contribute, you can fork this [repository](https://github.com/Comfy-Org/ComfyUI_frontend) and submit a pull request.

## Localization Support

Currently, ComfyUI supports: English, Chinese, Russian, French, Japanese, and Korean.
If you need to switch the interface language to your preferred language, you can click the **Settings gear icon** and then select your desired language under `Comfy` --> `Locale`.

<img alt="ComfyUI Localization Support" />

## New Menu Interface

### Workspace Areas

Below are the main interface areas of ComfyUI and a brief introduction to each part.

<img alt="ComfyUI Workspace" />

Currently, apart from the main workflow interface, the ComfyUI interface is mainly divided into the following parts:

1. **Main Menu**: Click to expand the function menu, including file operations, help menu, etc.

**Left Navigation Sidebar:**
2\. **Left Panel Entries**:

* **ASSETS**: Displays generated images, videos, and other assets.
* **Nodes**: Lists ComfyUI native and third-party nodes.
* **Models**: Shows model information detected after ComfyUI starts. After startup, if models are downloaded, press the `r` key to refresh node definitions and get the latest models.
* **Workflows**: Displays locally saved workflows.
* **Templates**: Provides ComfyUI built-in workflow templates.

**Bottom Left Toolbar:**
3\. **Bottom Toolbar**: Contains buttons for Help (opens runtime logs), Console (opens runtime logs), Shortcuts (displays shortcut panel), and Settings (opens settings panel).

**Top Header Bar:**
4\. **Top Area**: Displays the currently opened workflow.
5\. **New Workflow Button**: Click to create a new blank workflow file.
6\. **Right Control Area**: Run and queue control management, where you can run workflows and view the queue.
7\. **Login Status**: Not displayed by default, only shown after login, used when closed-source Partner Nodes are required.
8\. **Quick Access Button**: Opens the right-side panel.

**Bottom Right Canvas Controls:**
9\. **Canvas Navigation Tools**: Can switch between move or pan modes, open the minimap, and toggle node connection display.

### Sidebar Panel Buttons

<img alt="ComfyUI Sidebar Panel" />

In the current ComfyUI, we provide four side panels with the following functions:

1. Workflow History Queue (Queue): All queue information for ComfyUI executing media content generation
2. Node Library: All nodes in ComfyUI, including `Comfy Core` and your installed custom nodes, can be found here
3. Model Library: Models in your local `ComfyUI/models` directory can be found here
4. Local User Workflows (Workflows): Your locally saved workflows can be found here

## Old Menu Version

Currently, ComfyUI enables the new interface by default. If you prefer to use the old interface, you can click the **Settings gear icon** and then set `Use new menu` to `disabled` under `Comfy` --> `Menu` to switch to the old menu version.

<Note>
  The old menu interface only supports English.
</Note>

The function annotations for the old menu interface are explained below:

<img alt="ComfyUI Old Menu" />


# ComfyUI 3D Settings
Source: https://docs.comfy.org/interface/settings/3d

Detailed description of ComfyUI 3D setting options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

This section of settings is mainly used to control the initialization settings of 3D-related components in ComfyUI, including camera, lighting, scene, etc. When creating new 3D components, they will be initialized according to these settings. After creation, these settings can still be adjusted individually.

## Camera

### Initial Camera Type

* **Options**:
  * `perspective`
  * `orthographic`
* **Function**: Controls whether the default camera is perspective or orthographic when creating new 3D components. This default setting can still be switched individually for each component after creation

<img alt="摄像机类型" />

## Light

The light settings in this section are used to set the default lighting settings for 3D components. The corresponding settings in the 3D settings in ComfyUI can also be modified.

<img alt="light" />

### Light Adjustment Increment

* **Default Value**: 0.5
* **Function**: Controls the step size when adjusting light intensity in 3D scenes. Smaller step values allow for finer light adjustments, while larger values make each adjustment more noticeable

### Light Intensity Minimum

* **Default Value**: 1
* **Function**: Sets the minimum light intensity value allowed in 3D scenes. This defines the lowest brightness that can be set when adjusting the lighting of any 3D control

### Light Intensity Maximum

* **Default Value**: 10
* **Function**: Sets the maximum light intensity value allowed in 3D scenes. This defines the upper limit of brightness that can be set when adjusting the lighting of any 3D control

### Initial Light Intensity

* **Default Value**: 3
* **Function**: Sets the default brightness level of lights in 3D scenes. This value determines the intensity with which lights illuminate objects when creating new 3D controls, but each control can be adjusted individually after creation

## Scene

### Initial Background Color

* **Function**: Controls the default background color of 3D scenes. This setting determines the background appearance when creating new 3D components, but each component can be adjusted individually after creation
* **Default Value**: `282828` (dark gray)

Change the background color, which can also be adjusted in the canvas.

<img alt="Initial Background Color vs Modified" />

### Initial Preview Visibility

* **Function**: Controls whether the preview screen is displayed by default when creating new 3D components. This default setting can still be toggled individually for each component after creation
* **Default Value**: true (enabled)

<img alt="Preview vs hide preview" />

### Initial Grid Visibility

* **Function**: Controls whether the grid is displayed by default when creating new 3D components. This default setting can still be toggled individually for each component after creation
* **Default Value**: true (enabled)

Hide or show the grid on initialization

<img alt="Show grid vs hide grid" />


# About Page
Source: https://docs.comfy.org/interface/settings/about

Detailed description of ComfyUI About settings page

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

The About page is an information display panel in the ComfyUI settings system, used to show application version information, related links, and system statistics. These settings can provide us with critical information when you submit feedback or report issues.

<img alt="about" />

### Version Information Badges

The About page displays the following core version information:

* **ComfyUI Version**: Shows the backend ComfyUI version number, linked to the official GitHub repository
* **ComfyUI\_frontend Version**: Shows the frontend interface version number, linked to the frontend GitHub repository
* **Discord Community**: Provides a link to the ComfyOrg Discord server
* **Official Website**: Links to the ComfyOrg official website

<Tip>
  Since the version information here mainly corresponds to stable version information, if you are using the nightly version, the corresponding commit hash will not be displayed here. If you are using the nightly version, you can use the `git log` command in the corresponding ComfyUI main directory to view the corresponding commit hash and other information.
  Another common issue is that different dependency packages may fail and rollback during updates.
</Tip>

### Custom Node Badges

If custom nodes are installed, the About page will also display additional badge information provided by custom nodes. These badges are registered by each custom node through the `aboutPageBadges` property.

### System Info

The bottom of the page displays detailed system statistics, including:

* Hardware configuration information
* Software environment information
* System performance data

## Extension Developer Guide

Extension developers can add custom badges to the About page by adding the `aboutPageBadges` property to their extension configuration:

```javascript theme={null}
app.registerExtension({
  name: 'MyExtension',
  aboutPageBadges: [
    {
      label: 'My Extension v1.0.0',
      url: 'https://github.com/myuser/myextension',
      icon: 'pi pi-github'
    }
  ]
})
```


# Comfy Settings
Source: https://docs.comfy.org/interface/settings/comfy

Detailed description of ComfyUI core setting options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

## Partner Nodes

### Show Partner Node pricing badge

* **Default Value**: Enabled
* **Function**: Controls whether to display pricing badges on Partner Nodes, helping users identify the usage cost of Partner Nodes

<img alt="Show Partner Node pricing badge" />

> For more information about Partner Nodes, please refer to [Partner Nodes](/tutorials/partner-nodes/overview)

## Dev Mode

### Enable dev mode options (API save, etc.)

* **Default Value**: Disabled
* **Function**: Enables development mode options (such as API save, etc.)

## Edit Token Weight

### Ctrl+up/down precision

* **Default Value**: 0.01
* **Function**: When using CLIPTextEncode type nodes or text input node widgets, use Ctrl+up/down to quickly adjust weights. This option changes the weight value for each adjustment

<video>
  <source type="video/mp4" />
</video>

## Locale

### Language

* **Options**: English, 中文 (Chinese),日本語 (Japanese), 한국어 (Korean), Русский (Russian), Español (Spanish), Français (French)
* **Default Value**: Auto-detect browser language
* **Function**: Modify the display language of ComfyUI interface

## Menu

### Use new menu

* **Default Value**: Top
* **Function**: Select menu interface and position, currently only supports Top, Bottom, Disabled

<Tabs>
  <Tab title="Top">
    The menu interface will be displayed at the top of the workspace

    <img alt="Top Menu" />
  </Tab>

  <Tab title="Bottom">
    The menu bar interface will be displayed at the bottom of the workspace

    <img alt="Bottom Menu" />
  </Tab>

  <Tab title="Disabled">
    If you prefer the early legacy menu, you can try this option.

    <Tip>
      Since we are constantly updating, some new features will not be synchronized and supported in the legacy menu.
    </Tip>

    <img alt="Legacy Menu" />
  </Tab>
</Tabs>

## Model Library

Model Library refers to the model management function in the ComfyUI sidebar menu. You can use this function to view models in your `ComfyUI/models` and additionally configured model folders.

<img alt="Model Library" />

### What name to display in the model library tree view

* **Default Value**: title
* **Function**: Select the name format to display in the model library tree view, currently only supports filename and title

### Automatically load all model folders

* **Default Value**: Disabled
* **Function**: Whether to automatically detect model files in all folders when clicking the model library. Enabling may cause loading delays (requires traversing all folders). When disabled, files in the corresponding folder will only be loaded when clicking the folder name.

## Node

During the iteration process of ComfyUI, we will adjust some nodes and enable some nodes. These nodes may undergo major changes or be removed in future versions. However, to ensure compatibility, deprecated nodes have not been removed. You can use the settings below to enable whether to display **experimental nodes** and **deprecated nodes**.

### Show deprecated nodes in search

* **Default Value**: Disabled
* **Function**: Controls whether to display deprecated nodes in search. Deprecated nodes are hidden by default in the UI, but remain effective in existing workflows.

<img alt="Show deprecated nodes in search" />

### Show experimental nodes in search

* **Default Value**: Enabled
* **Function**: Controls whether to display experimental nodes in search. Experimental nodes are some new feature support, but are not fully stable and may change or be removed in future versions.

<img alt="Show experimental nodes in search" />

## Node Search Box

### Number of nodes suggestions

* **Default Value**: 5
* **Function**: Used to modify the number of recommended nodes in the related node context menu. The larger the value, the more related recommended nodes are displayed.

<img alt="Number of nodes suggestions" />

### Show node frequency in search results

* **Default Value**: Disabled
* **Function**: Controls whether to display node usage frequency in search results

<img alt="Show node frequency in search results" />

### Show node id name in search results

* **Default Value**: Disabled
* **Function**: Controls whether to display node ID names in search results

<img alt="Show node id name in search results" />

### Show node category in search results

* **Default Value**: Enabled
* **Function**: Controls whether to display node categories in search results, helping users understand node classification information

### Node preview

* **Default Value**: Enabled
* **Function**: Controls whether to display node previews in search results, making it convenient for you to quickly preview nodes

### Node search box implementation

* **Default Value**: default
* **Function**: Select the implementation method of the node search box (experimental feature). If you select `litegraph (legacy)`, it will switch to the early ComfyUI search box

## Node Widget

### Widget control mode

* **Options**: before, after
* **Function**: Controls whether the timing of node widget value updates is before or after workflow execution, such as updating seed values

### Textarea widget spellcheck

* **Default Value**: Disabled
* **Function**: Controls whether text area widgets enable spellcheck, providing spellcheck functionality during text input. This functionality is implemented through the browser's spellcheck attribute

## Queue

### Queue history size

* **Default Value**: 100
* **Function**: Controls the queue history size recorded in the sidebar queue history panel. The larger the value, the more queue history is recorded. When the number is large, loading the page will also consume more memory

## Queue Button

### Batch count limit

* **Default Value**: 100
* **Function**: Sets the maximum number of tasks added to the queue in a single click, preventing accidentally adding too many tasks to the queue

## Validation

### Validate node definitions (slow)

* **Default Value**: Disabled
* **Function**: Controls whether to validate all node definitions at startup (slow). Only recommended for node developers. When enabled, the system will use Zod schemas to strictly validate each node definition. This functionality will consume more memory and time
* **Error Handling**: Failed node definitions will be skipped and warning information will be output to the console

<Tip>
  Since detailed schema validation needs to be performed on all node definitions, this feature will significantly increase startup time, so it is disabled by default and only recommended for node developers
</Tip>

### Validate workflows

* **Default Value**: Enabled
* **Function**: Ensures the structural and connection correctness of workflows. If enabled, the system will call `useWorkflowValidation().validateWorkflow()` to validate workflow data
* **Validation Process**: The validation process includes two steps:
  * Schema validation: Use Zod schemas to validate workflow structure
  * Link repair: Check and repair connection issues between nodes
* **Error Handling**: When validation fails, error prompts will be displayed, but workflow loading will not be blocked

## Window

### Show confirmation when closing window

* **Default Value**: Enabled
* **Function**: When there are modified but unsaved workflows, controls whether to display confirmation when closing the browser window or tab, preventing accidental window closure that leads to loss of unsaved workflows

## Workflow

### Persist workflow state and restore on page (re)load

* **Default Value**: Enabled
* **Function**: Controls whether to restore workflow state on page (re)load, maintaining workflow content after page refresh

### Auto Save

* **Default Value**: off
* **Function**: Controls the auto-save behavior of workflows, automatically saving workflow changes to avoid data loss

### Auto Save Delay (ms)

* **Default Value**: 1000
* **Function**: Sets the delay time for auto-save, only effective when auto-save is set to "after delay"

### Show confirmation when deleting workflows

* **Default Value**: Enabled
* **Function**: Controls whether to display a confirmation dialog when deleting workflows in the sidebar, preventing accidental deletion of important workflows

### Save and restore canvas position and zoom level in workflows

* **Default Value**: Enabled
* **Function**: Controls whether to save and restore canvas position and zoom level in workflows, restoring the previous view state when reopening workflows

### Opened workflows position

* **Options**: Sidebar, Topbar, Topbar (Second Row)
* **Default Value**: Topbar
* **Function**: Controls the display position of opened workflow tabs, currently only supports Sidebar, Topbar, Topbar (Second Row)

### Prompt for filename when saving workflow

* **Default Value**: Enabled
* **Function**: Controls whether to prompt for filename input when saving workflows, allowing users to customize workflow filenames

### Sort node IDs when saving workflow

* **Default Value**: Disabled
* **Function**: Determines whether to sort node IDs when saving workflows, making workflow file format more standardized and convenient for version control

### Show missing nodes warning

* **Default Value**: Enabled
* **Function**: Controls whether to display warnings for missing nodes in workflows, helping users identify unavailable nodes in workflows

### Show missing models warning

* **Default Value**: Enabled
* **Function**: We support adding model link information to widget values in workflow files for prompts when loading model files. When enabled, if you don't have the corresponding model files locally, warnings for missing models in workflows will be displayed

### Require confirmation when clearing workflow

* **Default Value**: Enabled
* **Function**: Controls whether to display a confirmation dialog when clearing workflows, preventing accidental clearing of workflow content

### Save node IDs to workflow

* **Default Value**: Enabled
* **Function**: Controls whether to save node IDs when saving workflows, making workflow file format more standardized and convenient for version control


# Comfy Desktop General Settings
Source: https://docs.comfy.org/interface/settings/comfy-desktop

Detailed description of ComfyUI Desktop general setting options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

## General

### Window Style

**Function**: Controls the title bar style of the application window

### Automatically check for updates

**Function**: Automatically checks for ComfyUI Desktop updates and will remind you to update when updates are available

### Send anonymous usage metrics

**Function**: Sends anonymous usage statistics to help improve the software. Changes to this setting require a restart to take effect

## UV

This section is mainly for users in China, because many of the original mirrors used by Desktop are outside of China, so access may not be friendly for domestic users. You can set your own mirror sources here to improve access speed and ensure that corresponding packages can be accessed and downloaded normally.

### Python Install Mirror

**Function**:

* Managed Python installation packages are downloaded from the Astral python-build-standalone project
* Can set mirror URL to use different Python installation sources
* The provided URL will replace the default GitHub download address
* Supports using file:// protocol to read distribution packages from local directories\
  **Validation**: Automatically checks mirror reachability

### Pypi Install Mirror

**Function**: Default pip package installation mirror source

### Torch Install Mirror

**Function**: PyTorch-specific pip installation mirror source


# Extension Settings
Source: https://docs.comfy.org/interface/settings/extension

Detailed description of ComfyUI extension management and setting options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

The Extension settings panel is a special management panel in the ComfyUI frontend settings system, specifically used to manage the enable/disable status of frontend extension plugins. Unlike Custom Nodes, this panel is only used to manage frontend extensions registered by custom nodes, not to disable custom nodes themselves.

<img alt="extension" />

These frontend extension plugins are used to enhance the ComfyUI experience, such as providing shortcuts, settings, UI components, menu items, and other features.

Extension status changes require a page reload to take effect:

## Extension Settings Panel Features

### 1. Extension List Management

Displays all registered extensions, including:

* Extension Name
* Core extension identification (displays "Core" label)
* Enable/disable status

### 2. Search Functionality

Provides a search box to quickly find specific extensions:

### 3. Enable/Disable Control

Each extension has an independent toggle switch:

### 4. Batch Operations

Provides right-click menu for batch operations:

* Enable All extensions
* Disable All extensions
* Disable 3rd Party extensions (keep core extensions)

## Notes

* Extension status changes require a page reload to take effect
* Some core extensions cannot be disabled
* The system will automatically disable known problematic extensions
* Extension settings are automatically saved to the user configuration file

This Extension settings panel is essentially a "frontend plugin manager" that allows users to flexibly control ComfyUI's functional modules.


# ComfyUI LiteGraph (Canvas) Settings
Source: https://docs.comfy.org/interface/settings/lite-graph

Detailed description of ComfyUI graphics rendering engine LiteGraph setting options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

LiteGraph is the underlying graphics rendering engine of ComfyUI. The settings in this category mainly control the behavior and appearance of graphical interfaces such as canvas, nodes, and links.

## Canvas

### Show selection toolbox

* **Default Value**: Enabled
* **Function**: The selection toolbox is a floating quick action toolbar that appears on nodes after they are selected, providing common quick operations such as partial execution, pinning, deletion, color modification, etc.

<img alt="Show selection toolbox" />

### Low quality rendering zoom threshold

* **Default Value**: 0.6
* **Range**: 0.1 - 1.0
* **Function**: When rendering the interface, especially when the workflow is particularly complex and the entire canvas is particularly large, the frontend rendering of corresponding elements will consume a lot of memory and cause lag. By lowering this threshold, you can control elements to enter low quality rendering mode when scaled to a specific percentage, thereby reducing memory consumption. The corresponding different rendering modes are shown below

<img alt="Low quality rendering" />

### Maximum FPS

* **Default Value**: 0 (use screen refresh rate)
* **Range**: 0 - 120
* **Function**: Limits the rendering frame rate of the canvas. 0 means using the screen refresh rate. Higher FPS will make the canvas rendering smoother, but will also consume more performance. Too low values will cause more obvious stuttering.

### Always snap to grid

* **Default Value**: Disabled
* **Function**: When this option is not enabled, you can hold the `Shift` key to align node edges with the grid. When enabled, node edges will automatically align with the grid without holding the `Shift` key.

<video>
  <source type="video/mp4" />
</video>

### Snap to grid size

* **Range**: 1 - 500
* **Function**: When auto-snap is enabled or when moving nodes while holding the `Shift` key, this parameter determines the grid size for snapping. The default value is 10, and you can adjust it according to your needs.

### Enable fast-zoom shortcut (Ctrl + Shift + Drag)

* **Default Value**: Enabled
* **Function**: Enables the `Ctrl + Shift + Left Mouse Button Drag` fast zoom function, providing a faster zoom operation method

<video>
  <source type="video/mp4" />
</video>

### Show graph canvas menu

* **Default Value**: Enabled
* **Function**: Controls whether to display the canvas menu in the bottom right corner

The canvas menu is located in the bottom right corner of the entire ComfyUI interface, containing operations such as canvas zooming, temporarily hiding all connections, quickly scaling the workflow to fit the canvas, etc., as shown in the image below

<img alt="Show graph canvas menu" />

### Canvas zoom speed

* **Default Value**: 1.1
* **Range**: 1.01 - 2.5
* **Function**: Controls the speed of canvas zooming, adjusts the sensitivity of mouse wheel zooming

### Show canvas info on bottom left corner (fps, etc.)

* **Default Value**: Enabled
* **Function**: Controls whether to display canvas information in the bottom left corner, showing performance metrics like FPS

<img alt="Canvas info" />

## Context Menu

### Scale node combo widget menus (lists) when zoomed in

* **Default Value**: Enabled
* **Function**: Controls whether to scale node combo widget menus (lists) when zoomed in, allowing users to select node combo widgets

## Graph

### Link Render Mode

* **Default Value**: 2 (Spline)
* **Options**: Straight, Linear, Spline, Hidden
* **Function**: Sets the rendering style of connections, controlling the visual style of links between nodes

<img alt="Link Render Mode" />

## Group

This section of settings is mainly related to node group functionality

<img alt="Node Group" />

### Double click group title to edit

* **Default Value**: Enabled
* **Function**: Controls whether you can double-click the node title to edit it, allowing users to rename nodes, marked as part `1` in the image

### Group selected nodes padding

* **Default Value**: 10
* **Range**: 0 - 100
* **Function**: Sets the inner padding when grouping selected nodes, controlling the spacing between the group frame and nodes, marked as the arrow annotation part `2` in the image

## Link

### Link midpoint markers

* **Default Value**: Circle
* **Options**: None, Circle, Arrow
* **Function**: Sets the marker style at link midpoints, displaying direction indicators at link midpoints

<img alt="Link midpoint markers" />

## Link Release

This menu section currently mainly controls related operations when link connections are released. The current two related operations are:

**A node recommendation list related to the current input/output will appear after release**

<video>
  <source type="video/mp4" />
</video>

**A search box will be launched after release**

<video>
  <source type="video/mp4" />
</video>

### Action on link release (Shift)

* **Default Value**: search box
* **Options**: context menu, search box, no action
* **Function**: Sets the action when releasing links while holding the Shift key, special behavior when releasing links while holding Shift

### Action on link release (No modifier)

* **Default Value**: context menu
* **Options**: context menu, search box, no action
* **Function**: Sets the default action when releasing links, controls the behavior after dragging and releasing links

## Node

### Always shrink new nodes

* **Default Value**: Enabled
* **Function**: Controls whether to automatically shrink when creating new nodes, so nodes can always display the minimum size, but may cause some text display to be truncated when adding, requiring manual adjustment of node size

### Enable DOM element clipping (enabling may reduce performance)

* **Default Value**: Enabled
* **Function**: Enables DOM element clipping (may affect performance), optimizes rendering but may reduce performance

### Middle-click creates a new Reroute node

* **Default Value**: Enabled
* **Function**: Creates a new reroute node when middle-clicking, quickly creates reroute nodes for organizing connections

### Keep all links when deleting nodes

* **Default Value**: Enabled
* **Function**: Automatically bypasses connections when deleting intermediate nodes, attempts to reconnect input and output links when deleting nodes

### Snap highlights node

* **Default Value**: Enabled
* **Function**: Highlights nodes when dragging links to them, provides visual feedback, shows connectable nodes. When enabled, the effect is as shown in the image below, the corresponding side of the link will display highlighted style

<img alt="Snap highlights node" />

### Auto snap link to node slot

* **Default Value**: Enabled
* **Function**: Automatically snaps to available slots when dragging links to nodes, simplifies connection operations, automatically finds suitable input slots

<video>
  <source type="video/mp4" />
</video>

### Enable Tooltips

* **Default Value**: Enabled
* **Function**: Some node information will contain tooltips, including parameter descriptions, etc. When enabled, these tooltips will be displayed when hovering the mouse, as shown in the image below

<img alt="Enable Tooltips" />

### Tooltip Delay

* **Default Value**: 500
* **Function**: Controls the delay time for tooltips, in milliseconds. Setting to 0 means displaying tooltips immediately

### Node life cycle badge mode

* **Default Value**: Show all
* **Function**: Controls the display of node lifecycle markers, showing node status information

### Node ID badge mode

* **Default Value**: Show all
* **Function**: Controls the display of node ID markers, showing node unique identifiers

<img alt="Node ID badge mode" />

### Node source badge mode

* **Options**:
  * None
  * Hide built-in
  * Show all
* **Function**: Controls the display mode of node source markers, showing node source information. The corresponding display effect is shown in the image below. If show all is selected, it will display labels for both custom nodes and built-in nodes, making it convenient for you to determine the corresponding node source. The corresponding fox logo represents ComfyUI built-in nodes

<img alt="Node source badge mode" />

### Double click node title to edit

* **Default Value**: Enabled
* **Function**: Controls whether you can double-click the node title to edit it, allowing users to rename nodes

## Node Widget

### Float widget rounding decimal places \[0 = auto]

* **Default Value**: 0 (auto)
* **Range**: 0 - 6
* **Function**: Sets the decimal places for float widget rounding, 0 means auto, requires page reload

### Disable default float widget rounding

* **Default Value**: Disabled
* **Function**: Controls whether to disable default float widget rounding, requires page reload, cannot be disabled when the node backend has set rounding

### Disable node widget sliders

* **Default Value**: Disabled
* **Function**: Controls whether to disable slider controls in node widgets, forcing text input instead of sliders

### Preview image format

* **Default Value**: Empty string (use original format)
* **Function**: Sets the format for preview images in image widgets, converts to lightweight formats like webp, jpeg, etc.

### Show width × height below the image preview

* **Default Value**: Enabled
* **Function**: Displays width × height information below image previews, showing image dimension information

<img alt="Show width × height below the image preview" />

## Pointer

### Enable trackpad gestures

* **Default Value**: Enabled
* **Function**: This setting enables trackpad mode for the canvas, allowing two-finger pinch zoom and drag.

### Double click interval (maximum)

* **Default Value**: 300
* **Function**: Maximum time (milliseconds) between two clicks of a double-click. Increasing this value helps solve issues where double-clicks are sometimes not recognized.

### Pointer click drift delay

* **Default Value**: 150
* **Function**: Maximum time (milliseconds) to ignore pointer movement after pressing the pointer button. Helps prevent accidental mouse movement when clicking.

### Pointer click drift (maximum distance)

* **Default Value**: 6
* **Function**: If the pointer moves more than this distance while holding the button, it is considered a drag (rather than a click). Helps prevent accidental mouse movement when clicking.

## Reroute

### Reroute spline offset

* **Default Value**: 20
* **Function**: Used to determine the smoothness of curves on both sides of reroute nodes. Larger values make curves smoother, smaller values make curves sharper.

<img alt="Reroute spline offset" />


# ComfyUI Mask Editor Settings
Source: https://docs.comfy.org/interface/settings/mask-editor

Detailed description of ComfyUI mask editor setting options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

## Brush Adjustment

### Brush adjustment speed multiplier

* **Function**: Controls the speed of brush size and hardness changes during adjustment
* **Description**: Higher values mean faster changes

### Lock brush adjustment to dominant axis

* **Function**: When enabled, brush adjustment will only affect size or hardness based on the direction you move
* **Description**: This feature allows users to more precisely control brush property adjustments

## New Editor

### Use new mask editor

* **Function**: Switch to the new brush editor interface
* **Description**: Allows users to switch between new and old editor interfaces

<Tabs>
  <Tab title="New Editor">
    The new version has a better UI interface and interaction, with more complete functionality

    <img alt="new" />
  </Tab>

  <Tab title="Old Editor">
    The old version is an early version with relatively simple functionality, but can meet basic needs. It will not be updated in the future.

    <img alt="old" />
  </Tab>
</Tabs>


# ComfyUI Settings Overview
Source: https://docs.comfy.org/interface/settings/overview

Detailed description of ComfyUI settings overview

This section covers detailed setting descriptions in the ComfyUI frontend settings menu. All user settings are automatically saved to the `ComfyUI/user/default/comfy.settings.json` file.

You can use the `Ctrl + ,` keyboard shortcut to open the settings panel, then click on the corresponding setting options to configure them.

Since custom nodes can also register corresponding setting categories in the menu, our official documentation currently only includes native setting content. Additionally, some setting options are **only effective for ComfyUI Desktop**, which we have noted on the corresponding pages.

## ComfyUI Settings Menu

<Columns>
  <Card title="User" icon="user" href="/interface/user">
    User settings related to ComfyUI account, mainly used for logging into ComfyUI account to use Partner Nodes
  </Card>

  <Card title="Credits" icon="credit-card" href="/interface/credits">
    Entry for purchasing credits and credit balance history, only visible after logging into ComfyUI account
  </Card>

  <Card title="Comfy" icon="sliders" href="/interface/settings/comfy">
    Detailed description of ComfyUI core setting options
  </Card>

  <Card title="Lite Graph" icon="diagram-project" href="/interface/settings/lite-graph">
    Detailed description of Canvas (Lite Graph) setting options in ComfyUI
  </Card>

  <Card title="Appearance" icon="palette" href="/interface/appearance">
    Modify ComfyUI appearance options such as themes, background colors, sidebar position, etc.
  </Card>

  <Card title="Extension" icon="puzzle-piece" href="/interface/settings/extension">
    Manage the enable/disable status of frontend extension plugins in ComfyUI
  </Card>

  <Card title="3D" icon="cube" href="/interface/settings/3d">
    Some setting options for 3D node initialization
  </Card>

  <Card title="Comfy Desktop" icon="desktop" href="/interface/settings/comfy-desktop">
    Desktop update settings, mirror settings, etc. (only effective for ComfyUI Desktop)
  </Card>

  <Card title="Mask Editor" icon="brush" href="/interface/settings/mask-editor">
    Adjust mask editor usage preferences
  </Card>

  <Card title="Keybinding" icon="keyboard" href="/interface/shortcuts">
    Modify ComfyUI keyboard shortcut settings
  </Card>

  <Card title="About" icon="info" href="/interface/settings/about">
    Learn about current ComfyUI version information, device runtime information, etc., which is very useful for daily feedback
  </Card>

  <Card title="Server Config" icon="server" href="/interface/settings/server-config">
    Modify ComfyUI configuration file, this setting is only effective for ComfyUI Desktop
  </Card>
</Columns>


# Server Config
Source: https://docs.comfy.org/interface/settings/server-config

Detailed description of ComfyUI server configuration options

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

<Note>
  Currently the `Server Config` settings menu only exists in the Desktop version, and this settings menu item does not exist in other versions
</Note>

## Network

### Host: The IP address to listen on

* **Function**: Sets the IP address the server binds to. Default `127.0.0.1` means only local access is allowed. If you need LAN access, you can set it to `0.0.0.0`

<Tip>
  Although we provide LAN listening settings for the Desktop version, as a desktop application, it is not suitable for use as a server. We recommend that if you need to use ComfyUI as a public service within the LAN, please refer to the manual deployment tutorial to deploy the corresponding ComfyUI service.
</Tip>

### Port: The port to listen on

**Function**: The port number the server listens on. Desktop version defaults to port 8000, Web version typically uses port 8188

### TLS Key File: Path to TLS key file for HTTPS

**Function**: The private key file path required for HTTPS encryption, used to establish secure connections

### TLS Certificate File: Path to TLS certificate file for HTTPS

**Function**: The certificate file path required for HTTPS encryption, used in conjunction with the private key

### Enable CORS header: Use "\*" for all origins or specify domain

**Function**: Cross-Origin Resource Sharing settings, allowing web browsers to access the server from different domains

### Maximum upload size (MB)

**Function**: Limits the maximum size of single file uploads, in MB, default 100MB. Affects upload limits for images, models and other files

## CUDA

### CUDA device index to use

**Function**: Specifies which NVIDIA graphics card to use. 0 represents the first graphics card, 1 represents the second, and so on. Important for multi-GPU systems

### Use CUDA malloc for memory allocation

**Function**: Controls whether to use CUDA's memory allocator. Can improve memory management efficiency in certain situations

## Inference

### Global floating point precision

**Function**: Sets the numerical precision for model calculations. FP16 saves VRAM but may affect quality, FP32 is more precise but uses more VRAM

### UNET precision

**Options**:

* `auto`: Automatically selects the most suitable precision
* `fp64`: 64-bit floating point precision, highest precision but largest VRAM usage
* `fp32`: 32-bit floating point precision, standard precision
* `fp16`: 16-bit floating point precision, can save VRAM
* `bf16`: 16-bit brain floating point precision, between fp16 and fp32
* `fp8_e4m3fn`: 8-bit floating point precision (e4m3), minimal VRAM usage
* `fp8_e5m2`: 8-bit floating point precision (e5m2), minimal VRAM usage

**Function**: Specifically controls the computational precision of the UNET core component of diffusion models. Higher precision can provide better image generation quality but uses more VRAM. Lower precision can significantly save VRAM but may affect the quality of generated results.

### VAE precision

**Options and Recommendations**:

* `auto`: Automatically selects the most suitable precision, recommended for users with 8-12GB VRAM
* `fp16`: 16-bit floating point precision, recommended for users with 6GB or less VRAM, can save VRAM but may affect quality
* `fp32`: 32-bit floating point precision, recommended for users with 16GB or more VRAM who pursue the best quality
* `bf16`: 16-bit brain floating point precision, recommended for newer graphics cards that support this format, can achieve better performance balance

**Function**: Controls the computational precision of the Variational Autoencoder (VAE), affecting the quality and speed of image encoding/decoding. Higher precision can provide better image reconstruction quality but uses more VRAM. Lower precision can save VRAM but may affect image detail restoration.

### Run VAE on CPU

**Function**: Forces VAE to run on CPU, can save VRAM but will reduce processing speed

### Text Encoder precision

**Options**:

* `auto`: Automatically selects the most suitable precision
* `fp8_e4m3fn`: 8-bit floating point precision (e4m3), minimal VRAM usage
* `fp8_e5m2`: 8-bit floating point precision (e5m2), minimal VRAM usage
* `fp16`: 16-bit floating point precision, can save VRAM
* `fp32`: 32-bit floating point precision, standard precision

**Function**: Controls the computational precision of the text prompt encoder, affecting the accuracy of text understanding and VRAM usage. Higher precision can provide more accurate text understanding but uses more VRAM. Lower precision can save VRAM but may affect prompt parsing effectiveness.

## Memory

### Force channels-last memory format

**Function**: Changes the data arrangement in memory, may improve performance on certain hardware

### DirectML device index

**Function**: Specifies the device when using DirectML acceleration on Windows, mainly for AMD graphics cards

### Disable IPEX optimization

**Function**: Disables Intel CPU optimization, mainly affects Intel processor performance

### VRAM management mode

**Options**:

* `auto`: Automatically manages VRAM, allocating VRAM based on model size and requirements
* `lowvram`: Low VRAM mode, uses minimal VRAM, may affect generation quality
* `normalvram`: Standard VRAM mode, balances VRAM usage and performance
* `highvram`: High VRAM mode, uses more VRAM for better performance
* `novram`: No VRAM usage, runs entirely on system memory
* `cpu`: CPU-only mode, doesn't use graphics card

**Function**: Controls VRAM usage strategy, such as automatic management, low VRAM mode, etc.

### Reserved VRAM (GB)

**Function**: Amount of VRAM reserved for the operating system and other programs, prevents system freezing

### Disable smart memory management

**Function**: Disables automatic memory optimization, forces models to move to system memory to free VRAM

## Preview

### Method used for latent previews

**Options**:

* `none`: No preview images displayed, only shows progress bar during generation
* `auto`: Automatically selects the most suitable preview method, dynamically adjusts based on system performance and VRAM
* `latent2rgb`: Directly converts latent space data to RGB images for preview, faster but average quality
* `taesd`: Uses lightweight TAESD model for preview, balances speed and quality

**Function**: Controls how to preview intermediate results during generation. Different preview methods affect preview quality and performance consumption. Choosing the right preview method can find a balance between preview effects and system resource usage.

### Size of preview images

**Function**: Sets the resolution of preview images, affects preview clarity and performance. Larger sizes provide higher preview quality but also consume more VRAM

## Cache

### Use classic cache system

**Function**: Uses traditional caching strategy, more conservative but stable

### Use LRU caching with a maximum of N node results cached

**Function**: Uses Least Recently Used (LRU) algorithm caching system, can cache a specified number of node computation results

**Description**:

* Set a specific number to control maximum cache count, such as 10, 50, 100, etc.
* Caching can avoid repeated computation of the same node operations, improving workflow execution speed
* When cache reaches the limit, automatically clears the least recently used results
* Cached results occupy system memory (RAM/VRAM), larger values use more memory

**Usage Recommendations**:

* Default value is null, meaning LRU caching is not enabled
* Set appropriate cache count based on system memory capacity and usage requirements
* Recommended for workflows that frequently reuse the same node configurations
* If system memory is sufficient, larger values can be set for better performance improvement

## Attention

### Cross attention method

**Options**:

* `auto`: Automatically selects the most suitable attention computation method
* `split`: Block-wise attention computation, can save VRAM but slower speed
* `quad`: Uses quad attention algorithm, balances speed and VRAM usage
* `pytorch`: Uses PyTorch native attention computation, faster but higher VRAM usage

**Function**: Controls the specific algorithm used when the model computes attention. Different algorithms make different trade-offs between generation quality, speed, and VRAM usage. Usually recommended to use auto for automatic selection.

### Force attention upcast

**Function**: Forces high-precision attention computation, improves quality but increases VRAM usage

### Prevent attention upcast

**Function**: Disables high-precision attention computation, saves VRAM

## General

### Disable xFormers optimization

**Function**: Disables the optimization features of the xFormers library. xFormers is a library specifically designed to optimize the attention mechanisms of Transformer models, typically improving computational efficiency, reducing memory usage, and accelerating inference speed. Disabling this optimization will:

* Fall back to standard attention computation methods
* May increase memory usage and computation time
* Provide a more stable runtime environment in certain situations

**Use Cases**:

* When encountering compatibility issues related to xFormers
* When more precise computation results are needed (some optimizations may affect numerical precision)
* When debugging or troubleshooting requires using standard implementations

### Default hashing function for model files

**Options**:

* `sha256`: Uses SHA-256 algorithm for hash verification, high security but slower computation
* `sha1`: Uses SHA-1 algorithm, faster but slightly lower security
* `sha512`: Uses SHA-512 algorithm, provides highest security but slowest computation
* `md5`: Uses MD5 algorithm, fastest but lowest security

**Function**: Sets the hash algorithm for model file verification, used to verify file integrity. Different hash algorithms have different trade-offs between computation speed and security. Usually recommended to use sha256 as the default option, which achieves a good balance between security and performance.

### Make pytorch use slower deterministic algorithms when it can

**Function**: Forces PyTorch to use deterministic algorithms when possible to improve result reproducibility.

**Description**:

* When enabled, PyTorch will prioritize deterministic algorithms over faster non-deterministic algorithms
* Same inputs will produce same outputs, helpful for debugging and result verification
* Deterministic algorithms typically run slower than non-deterministic algorithms
* Even with this setting enabled, completely identical image results cannot be guaranteed in all situations

**Use Cases**:

* Scientific research requiring strict result reproducibility
* Debugging processes requiring stable output results
* Production environments requiring result consistency

### Enable some untested and potentially quality deteriorating optimizations

**Function**: Enables experimental optimizations that may improve speed but could potentially affect generation quality

### Don't print server output to console

**Function**: Prevents displaying server runtime information in the console, keeping the interface clean.

**Description**:

* When enabled, ComfyUI server logs and runtime information will not be displayed
* Can reduce console information interference, making the interface cleaner
* May slightly improve system performance when there's heavy log output
* Default is disabled (false), meaning server output is displayed by default

**Use Cases**:

* Production environments where debugging information is not needed
* When wanting to keep the console interface clean
* When the system runs stably and log monitoring is not required

**Note**: It's recommended to keep this option disabled during development and debugging to promptly view server runtime status and error information.

### Disable saving prompt metadata in files

**Function**: Does not save workflow information in generated images, reducing file size, but also means the loss of corresponding workflow information, preventing you from using workflow output files to reproduce the corresponding generation results

### Disable loading all custom nodes

**Function**: Prevents loading all third-party extension nodes, typically used when troubleshooting issues to locate whether errors are caused by third-party extension nodes

### Logging verbosity level

**Function**: Controls the verbosity level of log output, used for debugging and monitoring system runtime status.

**Options**:

* `CRITICAL`: Only outputs critical error information that may cause the program to stop running
* `ERROR`: Outputs error information indicating some functions cannot work properly
* `WARNING`: Outputs warning information indicating possible issues that don't affect main functionality
* `INFO`: Outputs general information including system runtime status and important operation records
* `DEBUG`: Outputs the most detailed debugging information including system internal runtime details

**Description**:

* Log levels increase in verbosity from top to bottom
* Each level includes all log information from higher levels
* Recommended to set to INFO level for normal use
* Can be set to DEBUG level when troubleshooting for more information
* Can be set to WARNING or ERROR level in production environments to reduce log volume

## Directories

### Input directory

**Function**: Sets the default storage path for input files (such as images, models)

### Output directory

**Function**: Sets the save path for generation results


# ComfyUI Keyboard Shortcuts and Custom Settings
Source: https://docs.comfy.org/interface/shortcuts

Keyboard and mouse shortcuts for ComfyUI and related settings

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

Currently, ComfyUI supports custom keyboard shortcuts. You can set the shortcuts by clicking on `Settings (gear icon)` --> `Keybinding`.

<img alt="ComfyUI Shortcut Settings" />

In the corresponding menu, you can see all the current shortcut settings for ComfyUI. Click the `edit icon` before the corresponding command to customize the shortcut.

Below is the current list of shortcuts for ComfyUI, which you can customize as needed.

<Tabs>
  <Tab title="Windows/Linux">
    | Shortcut                        | Command                                                                                                            |
    | ------------------------------- | ------------------------------------------------------------------------------------------------------------------ |
    | Ctrl + Enter                    | Queue prompt                                                                                                       |
    | Ctrl + Shift + Enter            | Queue prompt (Front)                                                                                               |
    | Ctrl + Alt + Enter              | Interrupt                                                                                                          |
    | Ctrl + Z / Ctrl + Y             | Undo/Redo                                                                                                          |
    | Ctrl + S                        | Save workflow                                                                                                      |
    | Ctrl + O                        | Load workflow                                                                                                      |
    | Ctrl + A                        | Select all nodes                                                                                                   |
    | Alt + C                         | Collapse/uncollapse selected nodes                                                                                 |
    | Ctrl + M                        | Mute/unmute selected nodes                                                                                         |
    | Ctrl + B                        | Bypass/unbypass selected nodes                                                                                     |
    | Delete<br />Backspace           | Delete selected nodes                                                                                              |
    | Backspace                       | Clear workflow                                                                                                     |
    | Space                           | Move canvas when holding and moving cursor                                                                         |
    | Ctrl + Click<br />Shift + Click | Add clicked node to selection                                                                                      |
    | Ctrl + C/Ctrl + V               | Copy and paste selected nodes (without maintaining connections to outputs of unselected nodes)                     |
    | Ctrl + C/Ctrl + Shift + V       | Copy and paste selected nodes (maintaining connections from outputs of unselected nodes to inputs of pasted nodes) |
    | Shift + Drag                    | Move multiple selected nodes at the same time                                                                      |
    | Ctrl + G                        | Add frame to selected nodes                                                                                        |
    | Ctrl + ,                        | Show settings dialog                                                                                               |
    | Alt + =                         | Zoom in (canvas)                                                                                                   |
    | Alt + -                         | Zoom out (canvas)                                                                                                  |
    | .                               | Fit view to selected nodes                                                                                         |
    | P                               | Pin/unpin selected items                                                                                           |
    | Q                               | Toggle queue sidebar                                                                                               |
    | W                               | Toggle workflow sidebar                                                                                            |
    | N                               | Toggle node library sidebar                                                                                        |
    | M                               | Toggle model library sidebar                                                                                       |
    | Ctrl + \`                       | Toggle log bottom panel                                                                                            |
    | F                               | Toggle focus mode (full screen)                                                                                    |
    | R                               | Refresh node definitions                                                                                           |
    | Double-Click LMB                | Quick search for nodes to add                                                                                      |
  </Tab>

  <Tab title="MacOS">
    | Shortcut                         | Command                                                                                                            |
    | -------------------------------- | ------------------------------------------------------------------------------------------------------------------ |
    | Cmd ⌘ + Enter                    | Queue prompt                                                                                                       |
    | Cmd ⌘ + Shift + Enter            | Queue prompt (Front)                                                                                               |
    | Cmd ⌘ + Alt + Enter              | Interrupt                                                                                                          |
    | Cmd ⌘ + Z/Cmd ⌘ + Y              | Undo/Redo                                                                                                          |
    | Cmd ⌘ + S                        | Save workflow                                                                                                      |
    | Cmd ⌘ + O                        | Load workflow                                                                                                      |
    | Cmd ⌘ + A                        | Select all nodes                                                                                                   |
    | Opt ⌥ + C                        | Collapse/uncollapse selected nodes                                                                                 |
    | Cmd ⌘ + M                        | Mute/unmute selected nodes                                                                                         |
    | Cmd ⌘ + B                        | Bypass/unbypass selected nodes                                                                                     |
    | Delete<br />Backspace            | Delete selected nodes                                                                                              |
    | Backspace                        | Clear workflow                                                                                                     |
    | Space                            | Move canvas when holding and moving cursor                                                                         |
    | Cmd ⌘ + Click<br />Shift + Click | Add clicked node to selection                                                                                      |
    | Cmd ⌘ + C / Cmd ⌘ + V            | Copy and paste selected nodes (without maintaining connections to outputs of unselected nodes)                     |
    | Cmd ⌘ + C / Cmd ⌘ + Shift + V    | Copy and paste selected nodes (maintaining connections from outputs of unselected nodes to inputs of pasted nodes) |
    | Shift + Drag                     | Move multiple selected nodes at the same time                                                                      |
    | Cmd ⌘ + G                        | Add frame to selected nodes                                                                                        |
    | Cmd ⌘ + ,                        | Show settings dialog                                                                                               |
    | Opt ⌥ + =                        | Zoom in (canvas)                                                                                                   |
    | Opt ⌥ + -                        | Zoom out (canvas)                                                                                                  |
    | .                                | Fit view to selected nodes                                                                                         |
    | P                                | Pin/unpin selected items                                                                                           |
    | Q                                | Toggle queue sidebar                                                                                               |
    | W                                | Toggle workflow sidebar                                                                                            |
    | N                                | Toggle node library sidebar                                                                                        |
    | M                                | Toggle model library sidebar                                                                                       |
    | Cmd ⌘ + \`                       | Toggle log bottom panel                                                                                            |
    | F                                | Toggle focus mode (full screen)                                                                                    |
    | R                                | Refresh node definitions                                                                                           |
    | Double-Click LMB                 | Quick search for nodes to add                                                                                      |
  </Tab>
</Tabs>


# Account Management
Source: https://docs.comfy.org/interface/user

In this document, we will introduce the account management features of ComfyUI, including account login, registration, and logout operations.

<Info>
  The settings described on this page are located in the **ComfyUI in-app settings menu**. You can open it by navigating to **Settings** (gear icon) or using the `Ctrl + ,` keyboard shortcut, then select the corresponding category to view and configure these options.
</Info>

Using `Partner Nodes` requires credits, so the account system provides credit management and authentication support, enabling users to conveniently access cutting-edge closed-source model APIs.

Currently, we support the following login methods:

* Email login
* Google login
* Github login
* API Key login (for non-whitelisted site authorization)

We will provide relevant login requirements and explanations in this document.

## ComfyUI Version Requirements

You may need to use at least [ComfyUI v0.3.0](https://github.com/Comfy-Org/ComfyUI/releases/tag/v0.3.30) to use the account system. Ensure that the corresponding frontend version is at least `1.17.11`. Sometimes the frontend may fail to install and revert to an older version, so please check if the frontend version is greater than `1.17.11` in `Settings` -> `About`.

In some regions, network restrictions may prevent normal access to the login API, causing timeouts or failures. Before logging in, please **ensure that your network environment does not restrict access to the corresponding API**, and make sure you can access sites like Google or Github.

<Tip>
  Since we are still in rapid iterative updates, related functions may change. If there are no special circumstances, please try to update to the latest version to get support for relevant functions.
</Tip>

## Network Requirements

To login to ComfyUI account, you must be in a secure network environment:

* Only allow access from `127.0.0.1` or `localhost`.
* Do not support using the `--listen` parameter to access the Partner Node through a local network.
* If you are using a non-SSL certificate or a site that does not start with `https`, you may not be able to successfully log in.
* You may not be able to log in on a site that is not in our whitelist (but you can log in using an API Key now).
* Ensure you can connect to our service normally (some regions may require a proxy).

## How to Log In

Log in via `Settings` -> `User`:

<img alt="ComfyUI User Interface" />

## Login Methods

<img alt="user-login" />

If this is your first login, please create an account first.

<Card title="Logging in with an API Key" icon="key" href="/account/login#logging-in-with-an-api-key">
  For non-whitelisted sites or LAN environments, you can use API Key login. See the detailed guide in the account login documentation.
</Card>

## Post-Login Status

After logging in, a login button is displayed in the top menu bar of the ComfyUI interface. You can open the corresponding login interface through this button and log out of the corresponding account in the settings menu.

<img alt="user-logged" />

<img alt="menu-user-logged" />

## Frequently Asked Questions

<AccordionGroup>
  <Accordion title="Are there any login device restrictions?">
    We do not restrict login devices. You can log in to your account on any device, but please note that your account information may be accessed by other devices, so do not log in to your account on public devices.
  </Accordion>

  <Accordion title="How to log in in a LAN environment?">
    Currently, only API Key login is supported in a LAN environment. If you are accessing ComfyUI services through a LAN, please use API Key to log in.
  </Accordion>

  <Accordion title="Why can't I log in on some websites?">
    Our login service has a whitelist, so you may not be able to log in to ComfyUI deployed on some servers, for this case, you can use API Key login to solve it.
  </Accordion>
</AccordionGroup>


# Configuration
Source: https://docs.comfy.org/manager/configuration

Configure ComfyUI-Manager settings

## Configuration paths

Starting from V3.38, Manager uses a protected system path for enhanced security.

| ComfyUI Version                 | Manager Path                                |
| ------------------------------- | ------------------------------------------- |
| v0.3.76+ (with System User API) | `<USER_DIRECTORY>/__manager/`               |
| Older versions                  | `<USER_DIRECTORY>/default/ComfyUI-Manager/` |

<Note>
  If executed without any options, the `<USER_DIRECTORY>` path defaults to `ComfyUI/user`. It can be set using `--user-directory <USER_DIRECTORY>`.
</Note>

### Configuration files

| File                 | Description                      |
| -------------------- | -------------------------------- |
| `config.ini`         | Basic configuration              |
| `channels.list`      | Configurable channel lists       |
| `pip_overrides.json` | Custom pip package mappings      |
| `pip_blacklist.list` | Packages to prevent installation |
| `pip_auto_fix.list`  | Packages to auto-restore         |
| `snapshots/`         | Saved snapshot files             |
| `startup-scripts/`   | Startup script files             |
| `components/`        | Component files                  |

## Config.ini options

Modify the `config.ini` file to apply settings. The path is displayed in startup log messages.

```ini theme={null}
[default]
git_exe = <path to git executable>
use_uv = <True/False - use uv instead of pip>
default_cache_as_channel_url = <True/False - retrieve DB designated as channel_url at startup>
bypass_ssl = <True/False - disable SSL if errors occur>
file_logging = <True/False - create log file>
windows_selector_event_loop_policy = <True/False - fix event loop errors on Windows>
model_download_by_agent = <True/False - use agent for model downloads>
downgrade_blacklist = <comma-separated list of packages to prevent downgrades>
security_level = <strong|normal|normal-|weak>
always_lazy_install = <True/False - perform dependency installation on restart>
network_mode = <public|private|offline>
```

### Network modes

| Mode      | Description                                                                                |
| --------- | ------------------------------------------------------------------------------------------ |
| `public`  | Standard public network environment                                                        |
| `private` | Closed network with private node DB configured via `channel_url` (uses cache if available) |
| `offline` | No external connections (uses cache if available)                                          |

### Security levels

| Level     | Description                                                                                                                    |
| --------- | ------------------------------------------------------------------------------------------------------------------------------ |
| `strong`  | Doesn't allow high and middle level risky features                                                                             |
| `normal`  | Doesn't allow high level risky features; middle level features available                                                       |
| `normal-` | Doesn't allow high level risky features if `--listen` is specified and not starts with `127.`; middle level features available |
| `weak`    | All features available                                                                                                         |

#### Risk levels for features

| Risk Level | Features                                                                                                |
| ---------- | ------------------------------------------------------------------------------------------------------- |
| **High**   | Install via git url, pip install, installation of custom nodes not in default channel, fix custom nodes |
| **Middle** | Uninstall/Update, installation of custom nodes in default channel, restore/remove snapshot, restart     |
| **Low**    | Update ComfyUI                                                                                          |

## Environment variables

| Variable          | Description                           |
| ----------------- | ------------------------------------- |
| `COMFYUI_PATH`    | Installation path of ComfyUI          |
| `GITHUB_ENDPOINT` | Reverse proxy for GitHub access       |
| `HF_ENDPOINT`     | Reverse proxy for Hugging Face access |

### Examples

Redirecting GitHub requests through a proxy:

```bash theme={null}
GITHUB_ENDPOINT=https://mirror.ghproxy.com/https://github.com
```

Changing Hugging Face endpoint:

```bash theme={null}
HF_ENDPOINT=https://some-hf-mirror.com
```

## Advanced configuration

### Prevent downgrade of specific packages

List package names in the `downgrade_blacklist` section of `config.ini`, separated by commas:

```ini theme={null}
downgrade_blacklist = diffusers, kornia
```

### Custom pip mapping

Create a `pip_overrides.json` file to change the installation of specific pip packages to user-defined installations. Refer to `pip_overrides.json.template` for the format.

### Prevent installation of specific pip packages

List package names one per line in the `pip_blacklist.list` file.

### Automatically restore pip installation

List pip spec requirements in `pip_auto_fix.list` (similar to `requirements.txt`). It will automatically restore specified versions when starting ComfyUI or when versions get mismatched during custom node installations. `--index-url` can be used.

### Use aria2 as downloader

For faster downloads, you can configure ComfyUI-Manager to use aria2. See the [aria2 setup guide](https://github.com/Comfy-Org/ComfyUI-Manager/blob/main/docs/en/use_aria2.md).

## extra\_model\_paths.yaml configuration

The following settings are applied based on the section marked as `is_default`:

* `custom_nodes`: Path for installing custom nodes
* `download_model_base`: Path for downloading models

## CLI tools

ComfyUI-Manager provides `cm-cli`, a command line tool that allows you to use Manager features without running ComfyUI. This is useful for automating custom node installation and managing installations in headless environments.

For detailed cm-cli documentation, see the [official cm-cli guide](https://github.com/Comfy-Org/ComfyUI-Manager/blob/main/docs/en/cm-cli.md).

For a more comprehensive CLI experience, consider using [comfy-cli](/comfy-cli/getting-started).


# ComfyUI-Manager Installation
Source: https://docs.comfy.org/manager/install

How to install ComfyUI-Manager for different setups

## Desktop users

If you're using [ComfyUI Desktop](/installation/desktop/windows), ComfyUI-Manager is already included and enabled by default. No additional installation is required.

## Portable users

For users running the [Windows Portable](/installation/comfyui_portable_windows) version, the new ComfyUI-Manager is built into ComfyUI core but needs to be enabled.

1. Install the manager dependencies:
   ```bash theme={null}
   .\python_embeded\python.exe -m pip install -r ComfyUI\manager_requirements.txt
   ```

2. Launch ComfyUI with the manager enabled:
   ```bash theme={null}
   .\python_embeded\python.exe -s ComfyUI\main.py --windows-standalone-build --enable-manager
   pause
   ```

## Manual install users

For users with a [manual installation](/installation/manual_install), the new ComfyUI-Manager is built into ComfyUI core but needs to be enabled.

1. Activate your virtual environment:
   ```bash theme={null}
   # Windows
   venv\Scripts\activate

   # Linux/macOS
   source venv/bin/activate
   ```

2. Install the manager dependencies:
   ```bash theme={null}
   pip install -r manager_requirements.txt
   ```

3. Enable the manager with the `--enable-manager` flag when running ComfyUI:
   ```bash theme={null}
   python main.py --enable-manager
   ```

### Command line options

| Flag                         | Description                                                                                          |
| ---------------------------- | ---------------------------------------------------------------------------------------------------- |
| `--enable-manager`           | Enable ComfyUI-Manager                                                                               |
| `--enable-manager-legacy-ui` | Use the legacy manager UI instead of the new UI (requires `--enable-manager`)                        |
| `--disable-manager-ui`       | Disable the manager UI and endpoints while keeping background features (requires `--enable-manager`) |

### Switch between new and legacy UI

The following version updates only support pip installations. Versions installed via custom nodes do not support switching to the new UI.

<Tabs>
  <Tab title="Non-Desktop users">
    To use the new UI:

    ```bash theme={null}
    python main.py --enable-manager
    ```

    To use the legacy UI:

    ```bash theme={null}
    python main.py --enable-manager --enable-manager-legacy-ui
    ```
  </Tab>

  <Tab title="Desktop users">
    Desktop users can switch to the legacy UI in **Server Settings → UI Settings → Use legacy manager interface**

    <img alt="Switch to legacy UI" />
  </Tab>
</Tabs>

## Legacy installation methods

<Accordion title="Method 1: Git clone (general installation)">
  To install ComfyUI-Manager in addition to an existing installation of ComfyUI:

  1. Navigate to `ComfyUI/custom_nodes` directory in terminal
  2. Clone the repository:
     ```bash theme={null}
     git clone https://github.com/Comfy-Org/ComfyUI-Manager comfyui-manager
     ```
  3. Install the manager dependencies:
     ```bash theme={null}
     cd comfyui-manager
     pip install -r requirements.txt
     ```
  4. Restart ComfyUI
</Accordion>

<Accordion title="Method 2: Portable version (Windows)">
  1. Install [Git for Windows](https://git-scm.com/download/win) (standalone version, select "use windows default console window")
  2. Download [install-manager-for-portable-version.bat](https://github.com/Comfy-Org/ComfyUI-Manager/raw/main/scripts/install-manager-for-portable-version.bat) into your `ComfyUI_windows_portable` directory
  3. Double-click the batch file to install
</Accordion>

<Accordion title="Method 3: comfy-cli (recommended for new installations)">
  comfy-cli provides various features to manage ComfyUI from the CLI.

  **Prerequisites**: Python 3, Git

  **Windows:**

  ```bash theme={null}
  python -m venv venv
  venv\Scripts\activate
  pip install comfy-cli
  comfy install
  ```

  **Linux/macOS:**

  ```bash theme={null}
  python -m venv venv
  . venv/bin/activate
  pip install comfy-cli
  comfy install
  ```

  See also: [comfy-cli documentation](/comfy-cli/getting-started)
</Accordion>

<Accordion title="Method 4: Linux + venv">
  **Prerequisites**: python-is-python3, python3-venv, git

  1. Download [install-comfyui-venv-linux.sh](https://github.com/comfy-org/ComfyUI-Manager/raw/main/scripts/install-comfyui-venv-linux.sh) into an empty install directory
  2. Run:
     ```bash theme={null}
     chmod +x install-comfyui-venv-linux.sh
     ./install-comfyui-venv-linux.sh
     ```
  3. Execute ComfyUI with `./run_gpu.sh` or `./run_cpu.sh`
</Accordion>

<Warning>
  **Installation precautions:**

  * ComfyUI-Manager files must be accurately located in the path `ComfyUI/custom_nodes/comfyui-manager`
  * Do not decompress directly into `ComfyUI/custom_nodes` (files like `__init__.py` should not be in that directory)
  * Do not install in paths like `ComfyUI/custom_nodes/ComfyUI-Manager/ComfyUI-Manager` or `ComfyUI/custom_nodes/ComfyUI-Manager-main`
</Warning>


# Managing custom nodes with ComfyUI-Manager (legacy UI)
Source: https://docs.comfy.org/manager/legacy-ui

Install, update, and manage custom nodes with ComfyUI-Manager using the legacy interface

## ComfyUI custom node management

Learn how to install custom nodes through Manager

### Install nodes

<Steps>
  <Step title="Click the Manager button in the ComfyUI interface">
    Click the **Manager** button on the main menu (top bar).

    <img alt="Manager button" />
  </Step>

  <Step title="Select Install Nodes">
    <img alt="Manager entry" />
  </Step>

  <Step title="Browse or search for the node you want to install">
    <img alt="Manager list" />
  </Step>

  <Step title="Click **Install** to install the node">
    <img alt="Node install dialog" />

    1. Prefer **latest** version if available
    2. Click **Select** to install the node

    <Note>
      * Version numbers with digits are versions published by authors to [registry](https://registry.comfy.org/), equivalent to stable releases
      * nightly is the latest version updated by authors to github, equivalent to development version, usually not security scanned, with unstable factors

      ComfyUI's default security settings do not allow direct installation of **nightly** versions. You can refer to [Security Policy](/manager/troubleshooting#security-policy) for details
    </Note>
  </Step>

  <Step title="Wait for dependency installation to complete, then restart ComfyUI">
    After clicking install, Manager will automatically complete dependency installation and prompt you to restart ComfyUI after installation is complete

    <img alt="Restart ComfyUI and refresh browser after installation" />

    <img alt="Restart ComfyUI and refresh browser after installation" />
  </Step>

  <Step title="Check if the plugin was installed successfully">
    After restarting, check in ComfyUI Manager whether the corresponding plugin was installed successfully, and whether there are `import failed` error messages

    <img alt="Check if plugin was installed successfully" />
  </Step>
</Steps>

### Install missing nodes

Missing nodes are a common situation when loading workflows. There are usually two types of missing nodes:

1. Core node missing: ComfyUI version is not the latest version, please refer to [Update ComfyUI](/installation/update_comfyui) to update ComfyUI
2. Custom node missing: Third-party custom nodes are missing, you can refer to this guide for installation

After ComfyUI-Manager is installed, if there are missing custom nodes when importing workflows, you will be alerted about the missing node information

<img alt="Missing nodes prompt" />

1. Click **Open Manager** to activate the corresponding option

<img alt="Missing nodes prompt" />

2\. Click **Install Missing Custom Nodes** in the Manager menu to enter the missing nodes list interface

<img alt="Missing nodes prompt" />

3\. View and install the corresponding nodes in the node list

<Note>
  If you find that the missing nodes list cannot find the corresponding node, there are usually several situations:

  1. The corresponding node author has not submitted and registered the custom node to [registry](/registry/overview)
  2. The corresponding node is not open source, it may be a restricted node from certain authors or limited platforms
  3. The original author changed the version and deleted the corresponding node
</Note>

### Update nodes

<img alt="Node version" />

1. Switch the filter to **Update** filter to filter nodes that can be updated in the current node list
2. Click the **Update** button to update the node

### Uninstall nodes

<img alt="Uninstall nodes" />

1. Select the "Installed" filter in the node list to filter installed nodes in the current node list
2. Right-click the corresponding node and select **Uninstall** to uninstall

> Uninstalling the corresponding node will not remove the corresponding dependency installation

For other methods of installing plugins, please refer to the article below

<Card title="Install custom nodes" icon="download" href="/installation/install_custom_node">
  Learn how to manually install custom nodes
</Card>

## Snapshot manager

Snapshots save your current installation status, allowing you to restore to a previous state.

![Snapshot manager](https://raw.githubusercontent.com/ltdrdata/ComfyUI-extension-tutorials/Main/ComfyUI-Manager/images/snapshot.jpg)

Snapshots are automatically saved when you press **Save snapshot** or use **Update All**. Snapshot files are stored in: `<USER_DIRECTORY>/default/ComfyUI-Manager/snapshots`

To restore: Open the Snapshot Manager, select a snapshot, and press **Restore**.

<Note>
  Restoration takes effect on the next ComfyUI startup. For custom nodes not managed by Git, snapshot support is incomplete.
</Note>


# Overview
Source: https://docs.comfy.org/manager/overview

An extension to manage custom nodes, models, and more in ComfyUI

**ComfyUI-Manager** is an extension designed to enhance the usability of [ComfyUI](https://github.com/Comfy-Org/ComfyUI). It offers management functions to **install, remove, disable, and enable** various custom nodes of ComfyUI. Furthermore, this extension provides a hub feature and convenience functions to access a wide range of information within ComfyUI.

<img alt="ComfyUI-Manager dialog" />

## Key features

* **Custom node management**: Install, update, remove, and disable custom nodes
* **Model management**: Download and manage models from various sources
* **Snapshot management**: Save and restore installation states
* **Missing node detection**: Automatically detect and install missing nodes from workflows

## Next steps

<CardGroup>
  <Card title="Installation" icon="download" href="/manager/install">
    Install ComfyUI-Manager for your setup
  </Card>

  <Card title="New UI" icon="puzzle-piece" href="/manager/pack-management">
    Manage custom nodes and models with the new UI
  </Card>

  <Card title="Legacy UI" icon="puzzle-piece" href="/manager/legacy-ui">
    Manage custom nodes and models with the legacy UI
  </Card>

  <Card title="Configuration" icon="gear" href="/manager/configuration">
    Configure settings and options
  </Card>

  <Card title="Troubleshooting" icon="bug" href="/manager/troubleshooting">
    Resolve common issues
  </Card>
</CardGroup>


# Custom nodes (new UI)
Source: https://docs.comfy.org/manager/pack-management

Install, update, and manage custom nodes with ComfyUI-Manager using the new interface

<Note>
  If you're not using the new UI, refer to the [Switch between new and legacy UI](/manager/install) section to learn how to switch.
</Note>

## New UI overview

<img alt="New UI" />

1. **Left sidebar (Filters)**: Filter installed nodes, nodes in workflow, missing nodes, updatable nodes, etc.
2. **Top search bar**: Search node packs (Node Pack) or individual nodes (Node), switch search type using the Filter dropdown
3. **Right detail panel**: Click a node to display detailed information including description, enable status, version information, etc. The Description tab contains repository information, and the Nodes tab previews all nodes

## Node management

Learn how to use the new ComfyUI Manager to manage custom nodes

### Search nodes

<img alt="Filter" />

The Manager supports searching for node packs and individual nodes separately. As shown above, you can switch search types by toggling the filter.

* Node Pack: A complete custom node pack
* Individual Node: Search for individual nodes within node packs

### Install nodes

<img alt="Install nodes" />

1. Select the corresponding node card
2. Click **Install** in the expanded node information
3. Or select a specific version in **Version** to install

### Update nodes

Under the **Update available** filter, you can filter nodes that have updates available in the current node list

<img alt="Update nodes" />

1. Updatable nodes will display an update arrow indicator
2. Select a specific version in **Version**
3. Click the **Update** button after selecting a version to update

### Find missing nodes

<img alt="Find missing nodes" />

If your ComfyUI Manager is properly installed, a prompt will appear when loading a workflow with missing nodes

1. You can choose **Install All** to install all nodes at once
2. Or choose **Open Manager** to open the manager and browse details before installing

<img alt="Find missing nodes" />

To find missing nodes in a workflow, select the corresponding node, then click the **Missing** button in the preview panel to find missing nodes

### Uninstall nodes

<img alt="Uninstall nodes" />

To uninstall an installed node, select the corresponding node, then click the **Uninstall** button in the preview panel to uninstall

## Common questions

1. Why can't I find the node I need?
   The new Manager only supports installing nodes from the [registry](/registry/overview). If your node is not registered in the registry, please register it in the Manager first.

2. Why can't I find the option to install via git?
   For security and stability of the ComfyUI user system, the new UI does not support installing nodes via git. Please refer to [Manually install custom nodes](/installation/install_custom_node) to learn how to manually install custom nodes.


# Troubleshooting
Source: https://docs.comfy.org/manager/troubleshooting

Resolve common ComfyUI-Manager issues

## Common issues

### Custom git executable path

If your `git.exe` is installed in a specific location other than the system default:

1. Install ComfyUI-Manager and run ComfyUI once
2. Open `<USER_DIRECTORY>/default/ComfyUI-Manager/config.ini`
3. Specify the full path including the file name in `git_exe =`

```ini theme={null}
git_exe = C:\Program Files\Git\bin\git.exe
```

### ComfyUI-Manager update fails

If updating ComfyUI-Manager itself fails, go to the ComfyUI-Manager directory and run:

```bash theme={null}
git update-ref refs/remotes/origin/main a361cc1 && git fetch --all && git pull
```

### Windows: Overlapped Object error

If you encounter `Overlapped Object has pending operation at deallocation on ComfyUI Manager load`:

Edit `config.ini` and add:

```ini theme={null}
windows_selector_event_loop_policy = True
```

### SSL certificate verification failed

If you encounter `SSL: CERTIFICATE_VERIFY_FAILED` error:

Edit `config.ini` and add:

```ini theme={null}
bypass_ssl = True
```

## Installation issues

### Incorrect installation path

ComfyUI-Manager files must be located in `ComfyUI/custom_nodes/comfyui-manager`.

**Common mistakes to avoid:**

| Issue                   | Problem                                                                      |
| ----------------------- | ---------------------------------------------------------------------------- |
| Files in wrong location | Manager files like `__init__.py` placed directly in `custom_nodes` directory |
| Double nested folder    | Installed as `custom_nodes/ComfyUI-Manager/ComfyUI-Manager`                  |
| Wrong folder name       | Installed as `custom_nodes/ComfyUI-Manager-main`                             |
| Compressed format       | Installing from a compressed file without proper extraction                  |

<Warning>
  If installed incorrectly, ComfyUI-Manager may appear to work but won't be recognized for updates and may cause duplicate installations. Remove it and reinstall properly via `git clone`.
</Warning>

## Network issues

### GitHub access problems

If you have limited access to GitHub, set the `GITHUB_ENDPOINT` environment variable:

```bash theme={null}
GITHUB_ENDPOINT=https://mirror.ghproxy.com/https://github.com
```

### Hugging Face access problems

If you have limited access to Hugging Face, set the `HF_ENDPOINT` environment variable:

```bash theme={null}
HF_ENDPOINT=https://some-hf-mirror.com
```

## Scanner troubleshooting

When running the `scan.sh` script:

* It updates `extension-node-map.json` by pulling or cloning custom nodes listed in `custom-node-list.json` into `~/.tmp/default`
* It updates `github-stats.json` using the GitHub API

| Option               | Description                           |
| -------------------- | ------------------------------------- |
| `--skip-update`      | Skip updating extension-node-map.json |
| `--skip-stat-update` | Skip updating github-stats.json       |
| `--skip-all`         | Skip both update steps                |

<Tip>
  To avoid GitHub API rate limits, set your token: `export GITHUB_TOKEN=your_token_here`
</Tip>

If you want to specify a different path instead of `~/.tmp/default`, run `python scanner.py [path]` directly instead of `scan.sh`.

## Security policy

If you encounter the error `This action is not allowed with this security level configuration` when installing custom nodes via git URL or using the nightly version, you need to adjust the security level in your `config.ini` file.

The `config.ini` file is located at:

* **ComfyUI v0.3.76+**: `<USER_DIRECTORY>/__manager/config.ini`
* **Older versions**: `<USER_DIRECTORY>/default/ComfyUI-Manager/config.ini`

Where `<USER_DIRECTORY>` defaults to `ComfyUI/user`. See [Configuration](/manager/configuration) for more details.

Configure security levels in `config.ini`:

```ini theme={null}
security_level = normal
```

| Level     | Description                                                                                                                    |
| --------- | ------------------------------------------------------------------------------------------------------------------------------ |
| `strong`  | Doesn't allow high and middle level risky features                                                                             |
| `normal`  | Doesn't allow high level risky features; middle level features available                                                       |
| `normal-` | Doesn't allow high level risky features if `--listen` is specified and not starts with `127.`; middle level features available |
| `weak`    | All features available                                                                                                         |

### Risk levels for features

| Risk Level | Features                                                                                                |
| ---------- | ------------------------------------------------------------------------------------------------------- |
| **High**   | Install via git url, pip install, installation of custom nodes not in default channel, fix custom nodes |
| **Middle** | Uninstall/Update, installation of custom nodes in default channel, restore/remove snapshot, restart     |
| **Low**    | Update ComfyUI                                                                                          |

<Tip>
  To install custom nodes via git URL or nightly versions, set `security_level = weak` in your `config.ini`.
</Tip>

## Getting help

If you're still experiencing issues:

1. Check the [ComfyUI-Manager GitHub issues](https://github.com/Comfy-Org/ComfyUI-Manager/issues) for similar problems
2. Review the startup log messages for error details
3. Join the [ComfyUI Discord](https://discord.com/invite/comfyorg) for community support


# ComfyUI Hunyuan3D-2 Examples
Source: https://docs.comfy.org/tutorials/3d/hunyuan3D-2

This guide will demonstrate how to use Hunyuan3D-2 in ComfyUI to generate 3D assets.

# Hunyuan3D 2.0 Introduction

![Hunyuan 3D 2](https://raw.githubusercontent.com/Tencent/Hunyuan3D-2/main/assets/images/e2e-1.gif)
![Hunyuan 3D 2](https://raw.githubusercontent.com/Tencent/Hunyuan3D-2/main/assets/images/e2e-2.gif)
[Hunyuan3D 2.0](https://github.com/Tencent/Hunyuan3D-2) is an open-source 3D asset generation model released by Tencent, capable of generating high-fidelity 3D models with high-resolution texture maps through text or images.

Hunyuan3D 2.0 adopts a two-stage generation approach, first generating a geometry model without textures, then synthesizing high-resolution texture maps. This effectively separates the complexity of shape and texture generation. Below are the two core components of Hunyuan3D 2.0:

1. **Geometry Generation Model (Hunyuan3D-DiT)**: Based on a flow diffusion Transformer architecture, it generates untextured geometric models that precisely match input conditions.
2. **Texture Generation Model (Hunyuan3D-Paint)**: Combines geometric conditions and multi-view diffusion techniques to add high-resolution textures to models, supporting PBR materials.

**Key Advantages**

* **High-Precision Generation**: Sharp geometric structures, rich texture colors, support for PBR material generation, achieving near-realistic lighting effects.
* **Diverse Usage Methods**: Provides code calls, Blender plugins, Gradio applications, and online experience through the official website, suitable for different user needs.
* **Lightweight and Compatibility**: The Hunyuan3D-2mini model requires only 5GB VRAM, the standard version needs 6GB VRAM for shape generation, and the complete process (shape + texture) requires only 12GB VRAM.

Recently (March 18, 2025), Hunyuan3D 2.0 also introduced a multi-view shape generation model (Hunyuan3D-2mv), which supports generating more detailed geometric structures from inputs at different angles.

This example includes three workflows:

* Using Hunyuan3D-2mv with multiple view inputs to generate 3D models
* Using Hunyuan3D-2mv-turbo with multiple view inputs to generate 3D models
* Using Hunyuan3D-2 with a single view input to generate 3D models

<Tip>
  ComfyUI now natively supports Hunyuan3D-2mv, but does not yet support texture and material generation. Please make sure you have updated to the latest version of [ComfyUI](https://github.com/Comfy-Org/ComfyUI) before starting.

  The workflow example PNG images in this tutorial contain workflow JSON in their metadata:

  * You can drag them directly into ComfyUI
  * Or use the menu `Workflows` -> `Open (ctrl+o)`

  This will load the corresponding workflow and prompt you to download the required models. The generated `.glb` format models will be output to the `ComfyUI/output/mesh` folder.
</Tip>

## ComfyUI Hunyuan3D-2mv Workflow Example

In the Hunyuan3D-2mv workflow, we'll use multi-view images to generate a 3D model. Note that multiple view images are not mandatory in this workflow - you can use only the `front` view image to generate a 3D model.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<a href="https://cloud.comfy.org/?template=3d_hunyuan3d_multiview_to_model&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 1. Workflow

Please download the images below and drag  into ComfyUI to load the workflow.
![Hunyuan3D-2mv workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/hunyuan-3d-multiview-elf.webp)

Download the images below we will use them as input images.

![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/front.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/left.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/back.png)

<Tip>
  In this example, the input images have already been preprocessed to remove excess background. In actual use, you can use custom nodes like [ComfyUI\_essentials](https://github.com/cubiq/ComfyUI_essentials) to automatically remove excess background.
</Tip>

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-mv: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2mv/resolve/main/hunyuan3d-dit-v2-mv/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2-mv.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2-mv.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2mv" />

1. Ensure that the Image Only Checkpoint Loader(img2vid model) has loaded our downloaded and renamed `hunyuan3d-dit-v2-mv.safetensors` model
2. Load the corresponding view images in each of the `Load Image` nodes
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

If you need to add more views, make sure to load other view images in the `Hunyuan3Dv2ConditioningMultiView` node, and ensure that you load the corresponding view images in the `Load Image` nodes.

## Hunyuan3D-2mv-turbo Workflow

In the Hunyuan3D-2mv-turbo workflow, we'll use the Hunyuan3D-2mv-turbo model to generate 3D models. This model is a step distillation version of Hunyuan3D-2mv, allowing for faster 3D model generation. In this version of the workflow, we set `cfg` to 1.0 and add a `flux guidance` node to control the `distilled cfg` generation.

<a href="https://cloud.comfy.org/?template=3d_hunyuan3d_multiview_to_model_turbo&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 1. Workflow

Please download the images below and drag into ComfyUI to load the workflow.

![Hunyuan3D-2mv-turbo workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/hunyuan-3d-turbo.webp)

Download the images below we will use them as input images.

![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/front.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/right.png)

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-mv-turbo: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2mv/resolve/main/hunyuan3d-dit-v2-mv-turbo/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2-mv-turbo.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2-mv-turbo.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2mv_turbo" />

1. Ensure that the `Image Only Checkpoint Loader(img2vid model)` node has loaded our renamed `hunyuan3d-dit-v2-mv-turbo.safetensors` model
2. Load the corresponding view images in each of the `Load Image` nodes
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Hunyuan3D-2 Single View Workflow

In the Hunyuan3D-2 workflow, we'll use the Hunyuan3D-2 model to generate 3D models. This model is not a multi-view model. In this workflow, we use the `Hunyuan3Dv2Conditioning` node instead of the `Hunyuan3Dv2ConditioningMultiView` node.

<a href="https://cloud.comfy.org/?template=3d_hunyuan3d_image_to_model&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 1. Workflow

Please download the image below and drag it into ComfyUI to load the workflow.

![Hunyuan3D-2 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d-non-multiview-train.webp)

Download the image below we will use it as input image.
![ComfyUI Hunyuan 3D 2 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan_3d_v2_non_multiview_train.png)

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-0: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2/resolve/main/hunyuan3d-dit-v2-0/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2" />

1. Ensure that the `Image Only Checkpoint Loader(img2vid model)` node has loaded our renamed `hunyuan3d-dit-v2.safetensors` model
2. Load the image in the `Load Image` node
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Community Resources

Below are ComfyUI community resources related to Hunyuan3D-2

* [ComfyUI-Hunyuan3DWrapper](https://github.com/kijai/ComfyUI-Hunyuan3DWrapper)
* [Kijai/Hunyuan3D-2\_safetensors](https://huggingface.co/Kijai/Hunyuan3D-2_safetensors/tree/main)
* [ComfyUI-3D-Pack](https://github.com/MrForExample/ComfyUI-3D-Pack)

## Hunyuan3D 2.0 Open-Source Model Series

Currently, Hunyuan3D 2.0 has open-sourced multiple models covering the complete 3D generation process. You can visit [Hunyuan3D-2](https://github.com/Tencent/Hunyuan3D-2) for more information.

**Hunyuan3D-2mini Series**

| Model                 | Description               | Date       | Parameters | Huggingface                                                                             |
| --------------------- | ------------------------- | ---------- | ---------- | --------------------------------------------------------------------------------------- |
| Hunyuan3D-DiT-v2-mini | Mini Image to Shape Model | 2025-03-18 | 0.6B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mini/tree/main/hunyuan3d-dit-v2-mini) |

**Hunyuan3D-2mv Series**

| Model                    | Description                                                                                                 | Date       | Parameters | Huggingface                                                                              |
| ------------------------ | ----------------------------------------------------------------------------------------------------------- | ---------- | ---------- | ---------------------------------------------------------------------------------------- |
| Hunyuan3D-DiT-v2-mv-Fast | Guidance Distillation Version, can halve DIT inference time                                                 | 2025-03-18 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mv/tree/main/hunyuan3d-dit-v2-mv-fast) |
| Hunyuan3D-DiT-v2-mv      | Multi-view Image to Shape Model, suitable for 3D creation requiring multiple angles to understand the scene | 2025-03-18 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mv/tree/main/hunyuan3d-dit-v2-mv)      |

**Hunyuan3D-2 Series**

| Model                   | Description                 | Date       | Parameters | Huggingface                                                                           |
| ----------------------- | --------------------------- | ---------- | ---------- | ------------------------------------------------------------------------------------- |
| Hunyuan3D-DiT-v2-0-Fast | Guidance Distillation Model | 2025-02-03 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-dit-v2-0-fast) |
| Hunyuan3D-DiT-v2-0      | Image to Shape Model        | 2025-01-21 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-dit-v2-0)      |
| Hunyuan3D-Paint-v2-0    | Texture Generation Model    | 2025-01-21 | 1.3B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-paint-v2-0)    |
| Hunyuan3D-Delight-v2-0  | Image Delight Model         | 2025-01-21 | 1.3B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-delight-v2-0)  |


# TripoSplat Image to Gaussian Splat ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/3d/triposplat

Generate high-quality 3D Gaussian splat representations from a single 2D image using TripoSplat, with controllable density and budget for rendering.

**TripoSplat** is an open-source model that generates **3D Gaussian splat** representations directly from a single 2D image. It was developed by VAST-AI and released under an open-source license.

Unlike traditional 3D reconstruction methods that require multiple views or generate meshes as the primary output, TripoSplat creates **Gaussian splat** representations — a rendering technique where thousands of colored 3D Gaussians are placed in space to represent a scene. This approach enables fast, high-quality rendering with controllable density and budget.

<img alt="TripoSplat workflow" />

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_triposplat_image_to_gaussian_splat.json">
  Download JSON or search "TripoSplat" in Template Library
</Card>

## How it works

TripoSplat uses a **feed-forward architecture** that takes a single RGB image and directly predicts a set of 3D Gaussian primitives. The pipeline involves:

1. **Image encoding** — the input image is processed by a vision encoder (DINOv2)
2. **Triplane generation** — features are decoded into a triplane representation
3. **Gaussian prediction** — the triplane is sampled to produce Gaussian parameters (position, scale, rotation, opacity, color)
4. **Rendering** — Gaussians are rendered from arbitrary viewpoints using differentiable splatting

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses a Subgraph node for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Workflow node guide

### LoadImage

* Loads your input image (PNG/JPG)
* Sample image: `white-hotel-on-rocky-island.png` (available in Template Library)

### TripoSplat (subgraph)

The main subgraph node processes the image and generates the 3D Gaussian splat. Exposed parameters:

| Parameter         | Default | Description                                                                      |
| ----------------- | ------- | -------------------------------------------------------------------------------- |
| `switch`          | —       | Enable/disable the subgraph                                                      |
| `num_gaussians`   | —       | Number of Gaussian primitives to generate (controls quality/performance)         |
| `seed`            | —       | Random seed for reproducibility                                                  |
| `unet_name`       | —       | TripoSplat diffusion model checkpoint                                            |
| `clip_name`       | —       | CLIP vision encoder model                                                        |
| `vae_name`        | —       | VAE for encoding/decoding (2 entries: one for the main VAE, one for the encoder) |
| `bg_removal_name` | —       | Background removal model                                                         |

### CreateCameraInfo

* Defines the camera orbit for rendering the result
* Parameters: orbit type, angle, distance, field of view, etc.
* Default: orbit at 35° elevation, 30 distance, 2.5 zoom

### RenderSplat

* Renders the Gaussian splat into a 2D image from the defined camera angle
* Parameters: output resolution (default 1024×1024), image quality settings

### SplatToMesh

* Converts the Gaussian splat to a mesh (optional)
* Parameters: mesh density, smoothing, simplification

### SaveGLB

* Saves the result as a GLB 3D file

### SaveVideo

* Saves a video of the rendered 3D scene

### SplatToFile3D

* Exports the Gaussian splat in SPZ format

### CreateVideo

* Creates a video from rendered frames

## Steps to run

1. **Load an image** — use the **LoadImage** node to load a single 2D image
2. **Run the TripoSplat subgraph** — the model will generate a Gaussian splat representation
3. **Choose output format** — export as GLB, SPZ, video, or render to mesh
4. **View results** — use the created 3D file or rendered preview

## Output options

| Node              | Format   | Use case                                               |
| ----------------- | -------- | ------------------------------------------------------ |
| **SaveGLB**       | `.glb`   | Standard 3D file format, importable into 3D software   |
| **SplatToFile3D** | `.spz`   | Compressed Gaussian splat format for efficient storage |
| **RenderSplat**   | 2D image | Quick preview of the result from any angle             |
| **SplatToMesh**   | Mesh     | Convert to traditional mesh for further editing        |

## Model downloads

Download the TripoSplat model and required files. Place them in the corresponding `models/` subdirectories.

<Card title="TripoSplat diffusion" icon="download" href="https://huggingface.co/VAST-AI/TripoSplat/resolve/main/diffusion_models/triposplat_fp16.safetensors">
  triposplat\_fp16.safetensors — TripoSplat diffusion model checkpoint
</Card>

<Card title="TripoSplat VAE decoder" icon="download" href="https://huggingface.co/VAST-AI/TripoSplat/resolve/main/vae/triposplat_vae_decoder_fp16.safetensors">
  triposplat\_vae\_decoder\_fp16.safetensors — VAE decoder
</Card>

<Card title="Flux2 VAE" icon="download" href="https://huggingface.co/VAST-AI/TripoSplat/resolve/main/vae/flux2-vae.safetensors">
  flux2-vae.safetensors — Flux.2 VAE for latent encoding
</Card>

<Card title="DINOv2 CLIP" icon="download" href="https://huggingface.co/VAST-AI/TripoSplat/resolve/main/clip_vision/dino_v3_vit_h.safetensors">
  dino\_v3\_vit\_h.safetensors — CLIP vision encoder (DINOv2)
</Card>

<Card title="BiRefNet bg removal" icon="download" href="https://huggingface.co/VAST-AI/TripoSplat/resolve/main/background_removal/birefnet.safetensors">
  birefnet.safetensors — Background removal model for preprocessing
</Card>

### Model storage location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │      └── triposplat_fp16.safetensors
│   ├── 📂 vae/
│   │      ├── triposplat_vae_decoder_fp16.safetensors
│   │      └── flux2-vae.safetensors
│   ├── 📂 clip_vision/
│   │      └── dino_v3_vit_h.safetensors
│   └── 📂 background_removal/
│          └── birefnet.safetensors
```


# ComfyUI Image to Image Workflow
Source: https://docs.comfy.org/tutorials/basic/image-to-image

This guide will help you understand and complete an image to image workflow

## What is Image to Image

Image to Image is a workflow in ComfyUI that allows users to input an image and generate a new image based on it.

Image to Image can be used in scenarios such as:

* Converting original image styles, like transforming realistic photos into artistic styles
* Converting line art into realistic images
* Image restoration
* Colorizing old photos
* ... and other scenarios

To explain it with an analogy:
It's like asking an artist to create a specific piece based on your reference image.

If you carefully compare this tutorial with the [Text to Image](/tutorials/basic/text-to-image) tutorial,
you'll notice that the Image to Image process is very similar to Text to Image,
just with an additional input reference image as a condition. In Text to Image, we let the artist (image model) create freely based on our prompts,
while in Image to Image, we let the artist create based on both our reference image and prompts.

## ComfyUI Image to Image Workflow Example Guide

### Model Installation

Download the [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors) file and put it in your `ComfyUI/models/checkpoints` folder.

### Image to Image Workflow and Input Image

Download the image below and **drag it into ComfyUI** to load the workflow:
![Image to Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image_to_image/workflow.png)

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

Download the image below and we will use it as the input image:

<img alt="Example Image" />

### Complete the Workflow Step by Step

Follow the steps in the diagram below to ensure the workflow runs correctly.

<img alt="ComfyUI Image to Image Workflow - Steps" />

1. Ensure `Load Checkpoint` loads  **v1-5-pruned-emaonly-fp16.safetensors**
2. Upload the input image to the `Load Image` node
3. Click `Queue` or press `Ctrl/Cmd + Enter` to generate

## Key Points of Image to Image Workflow

The key to the Image to Image workflow lies in the `denoise` parameter in the `KSampler` node, which should be **less than 1**

If you've adjusted the `denoise` parameter and generated images, you'll notice:

* The smaller the `denoise` value, the smaller the difference between the generated image and the reference image
* The larger the `denoise` value, the larger the difference between the generated image and the reference image

This is because `denoise` determines the strength of noise added to the latent space image after converting the reference image. If `denoise` is 1, the latent space image will become completely random noise, making it the same as the latent space generated by the `empty latent image` node, losing all characteristics of the reference image.

For the corresponding principles, please refer to the principle explanation in the [Text to Image](/tutorials/basic/text-to-image) tutorial.

## Try It Yourself

1. Try modifying the `denoise` parameter in the **KSampler** node, gradually changing it from 1 to 0, and observe the changes in the generated images
2. Replace with your own prompts and reference images to generate your own image effects


# ComfyUI Inpainting Workflow
Source: https://docs.comfy.org/tutorials/basic/inpaint

This guide will introduce you to the inpainting workflow in ComfyUI, walk you through an inpainting example, and cover topics like using the mask editor

This article will introduce the concept of inpainting in AI image generation and guide you through creating an inpainting workflow in ComfyUI. We'll cover:

* Using inpainting workflows to modify images
* Using the ComfyUI mask editor to draw masks
* `VAE Encoder (for Inpainting)` node

## About Inpainting

In AI image generation, we often encounter situations where we're satisfied with the overall image but there are elements we don't want or that contain errors. Simply regenerating might produce a completely different image, so using inpainting to fix specific parts becomes very useful.

It's like having an **artist (AI model)** paint a picture, but we're still not satisfied with the specific details. We need to tell the artist **which areas to adjust (mask)**, and then let them **repaint (inpaint)** according to our requirements.

Common inpainting scenarios include:

* **Defect Repair:** Removing unwanted objects, fixing incorrect AI-generated body parts, etc.
* **Detail Optimization:** Precisely adjusting local elements (like modifying clothing textures, adjusting facial expressions)
* And other scenarios

## ComfyUI Inpainting Workflow Example

### Model and Resource Preparation

#### 1. Model Installation

Download the [512-inpainting-ema.safetensors](https://huggingface.co/Comfy-Org/stable_diffusion_2.1_repackaged/resolve/main/512-inpainting-ema.safetensors)  file and put it in your `ComfyUI/models/checkpoints` folder:

#### 2. Inpainting Asset

Please download the following image which we'll use as input:

<img alt="ComfyUI Inpainting Input Image" />

<Note>This image already contains an alpha channel (transparency mask), so you don't need to manually draw a mask. This tutorial will also cover how to use the mask editor to draw masks.</Note>

#### 3. Inpainting Workflow

Download the image below and **drag it into ComfyUI** to load the workflow:

![ComfyUI Inpainting Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/basic/sd1.5_inpaint.png)

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

### ComfyUI Inpainting Workflow Example Explanation

Follow the steps in the diagram below to ensure the workflow runs correctly.

<img alt="ComfyUI Inpainting Workflow" />

1. Ensure `Load Checkpoint` loads `512-inpainting-ema.safetensors`
2. Upload the input image to the `Load Image` node
3. Click `Queue` or use `Ctrl + Enter` to generate

For comparison, here's the result using the [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors) model:

<img alt="SD1.5 Inpainting Result" />

You will find that the results generated by the [512-inpainting-ema.safetensors](https://huggingface.co/Comfy-Org/stable_diffusion_2.1_repackaged/resolve/main/512-inpainting-ema.safetensors) model have better inpainting effects and more natural transitions.
This is because this model is specifically designed for inpainting, which helps us better control the generation area, resulting in improved inpainting effects.

Do you remember the analogy we've been using? Different models are like artists with varying abilities, but each artist has their own limits. Choosing the right model can help you achieve better generation results.

You can try these approaches to achieve better results:

1. Modify positive and negative prompts with more specific descriptions
2. Try multiple runs using different seeds in the `KSampler` for different generation results
3. After learning about the mask editor in this tutorial, you can re-inpaint the generated results to achieve satisfactory outcomes.

Next, we'll learn about using the **Mask Editor**. While our input image already includes an `alpha` transparency channel (the area we want to edit),
so manual mask drawing isn't necessary, you'll often use the Mask Editor to create masks in practical applications.

### Using the Mask Editor

First right-click the `Save Image` node and select `Copy(Clipspace)`:

<img alt="Copy Image to Clipboard" />

Then right-click the **Load Image** node and select `Paste(Clipspace)`:

<img alt="Paste Image" />

Right-click the **Load Image** node again and select `Open in MaskEditor`:

<img alt="Open Mask Editor" />

<img alt="Mask Editor Demo" />

1. Adjust brush parameters on the right panel
2. Use eraser to correct mistakes
3. Click `Save` when finished

The drawn content will be used as a Mask input to the VAE Encoder (for Inpainting) node for encoding

Then try adjusting your prompts and generating again until you achieve satisfactory results.

## VAE Encoder (for Inpainting) Node

Comparing this workflow with [Text-to-Image](/tutorials/basic/text-to-image) and [Image-to-Image](/tutorials/basic/image-to-image), you'll notice the main differences are in the VAE section's conditional inputs.
In this workflow, we use the **VAE Encoder (for Inpainting)** node, specifically designed for inpainting to help us better control the generation area and achieve better results.

<img alt="VAE Encoder (for Inpainting) Node" />

**Input Types**

| Parameter Name | Function                                                                                                                                              |
| -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- |
| `pixels`       | Input image to be encoded into latent space.                                                                                                          |
| `vae`          | VAE model used to encode the image from pixel space to latent space.                                                                                  |
| `mask`         | Image mask specifying which areas need modification.                                                                                                  |
| `grow_mask_by` | Pixel value to expand the original mask outward, ensuring a transition area around the mask to avoid hard edges between inpainted and original areas. |

**Output Types**

| Parameter Name | Function                                    |
| -------------- | ------------------------------------------- |
| `latent`       | Image encoded into latent space by the VAE. |


# ComfyUI LoRA Example
Source: https://docs.comfy.org/tutorials/basic/lora

This guide will help you understand and use a single LoRA model

**LoRA (Low-Rank Adaptation)** is an efficient technique for fine-tuning large generative models like Stable Diffusion.
It introduces trainable low-rank matrices to the pre-trained model, adjusting only a portion of parameters rather than retraining the entire model,
thus achieving optimization for specific tasks at a lower computational cost.
Compared to base models like SD1.5, LoRA models are smaller and easier to train.

<img alt="LoRA Model vs Base Model Comparison" />

The image above compares generation with the same parameters using [dreamshaper\_8](https://civitai.com/models/4384?modelVersionId=128713) directly versus using the [blindbox\_V1Mix](https://civitai.com/models/25995/blindbox) LoRA model.
As you can see, by using a LoRA model, we can generate images in different styles without adjusting the base model.

We will demonstrate how to use a LoRA model. All LoRA variants: Lycoris, loha, lokr, locon, etc... are used in the same way.

In this example, we will learn how to load and use a LoRA model in [ComfyUI](https://github.com/Comfy-Org/ComfyUI), covering the following topics:

1. Installing a LoRA model
2. Generating images using a LoRA model
3. A simple introduction to the `Load LoRA` node

## Required Model Installation

Download the [dreamshaper\_8.safetensors](https://civitai.com/api/download/models/128713?type=Model\&format=SafeTensor\&size=pruned\&fp=fp16) file and put it in your `ComfyUI/models/checkpoints` folder.

Download the [blindbox\_V1Mix.safetensors](https://civitai.com/api/download/models/32988?type=Model\&format=SafeTensor\&size=full\&fp=fp16) file and put it in your `ComfyUI/models/loras` folder.

## LoRA Workflow File

Download the image below and **drag it into ComfyUI** to load the workflow.

<img alt="ComfyUI Workflow - LoRA" />

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

## Complete the Workflow Step by Step

Follow the steps in the diagram below to ensure the workflow runs correctly.

![ComfyUI Workflow - LoRA Flow Diagram](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/lora.png)

1. Ensure `Load Checkpoint` loads `dreamshaper_8.safetensors`
2. Ensure `Load LoRA` loads `blindbox_V1Mix.safetensors`
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to generate the image

## Load LoRA Node Introduction

<img alt="Load LoRA Node" />

Models in the `ComfyUI\models\loras` folder will be detected by ComfyUI and can be loaded using this node.

### Input Types

| Parameter Name   | Function                                                                                               |
| ---------------- | ------------------------------------------------------------------------------------------------------ |
| `model`          | Connect to the base model                                                                              |
| `clip`           | Connect to the CLIP model                                                                              |
| `lora_name`      | Select the LoRA model to load and use                                                                  |
| `strength_model` | Affects how strongly the LoRA influences the model weights; higher values make the LoRA style stronger |
| `strength_clip`  | Affects how strongly the LoRA influences the CLIP text embeddings                                      |

### Output Types

| Parameter Name | Function                                             |
| -------------- | ---------------------------------------------------- |
| `model`        | Outputs the model with LoRA adjustments applied      |
| `clip`         | Outputs the CLIP model with LoRA adjustments applied |

This node supports chain connections, allowing multiple `Load LoRA` nodes to be linked in series to apply multiple LoRA models. For more details, please refer to [ComfyUI Multiple LoRAs Example](/tutorials/basic/multiple-loras)

<img alt="LoRA Node Chain Connection" />

## Try It Yourself

1. Try modifying the prompt or adjusting different parameters of the `Load LoRA` node, such as `strength_model`, to observe changes in the generated images and become familiar with the `Load LoRA` node.
2. Visit [CivitAI](https://civitai.com/models) to download other kinds of LoRA models and try using them.


# ComfyUI Multiple LoRAs Example
Source: https://docs.comfy.org/tutorials/basic/multiple-loras

This guide demonstrates how to apply multiple LoRA models simultaneously in ComfyUI

In our [ComfyUI LoRA Example](/tutorials/basic/lora), we introduced how to load and use a single LoRA model, mentioning the node's chain connection capability.

<img alt="LoRA Node Chaining" />

This tutorial demonstrates chaining multiple `Load LoRA` nodes to apply two LoRA models simultaneously: [blindbox\_V1Mix](https://civitai.com/models/25995?modelVersionId=32988) and [MoXinV1](https://civitai.com/models/12597?modelVersionId=14856).

The comparison below shows individual effects of these LoRAs using identical parameters:

<img alt="Single LoRA Effects Comparison" />

By chaining multiple LoRA models, we achieve a blended style in the final output:

<img alt="Multi-LoRA Application Result" />

## Model Installation

Download the [dreamshaper\_8.safetensors](https://civitai.com/api/download/models/128713?type=Model\&format=SafeTensor\&size=pruned\&fp=fp16) file and put it in your `ComfyUI/models/checkpoints` folder.

Download the [blindbox\_V1Mix.safetensors](https://civitai.com/api/download/models/32988?type=Model\&format=SafeTensor\&size=full\&fp=fp16) file and put it in your `ComfyUI/models/loras` folder.

Download the [MoXinV1.safetensors](https://civitai.com/api/download/models/14856?type=Model\&format=SafeTensor\&size=full\&fp=fp16) file and put it in your `ComfyUI/models/loras` folder.

## Multi-LoRA Workflow

Download the image below and **drag it into ComfyUI** to load the workflow:
![ComfyUI Workflow - Multiple LoRAs](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/multiple_loras.png)

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

## Complete the Workflow Step by Step

Follow the steps in the diagram below to ensure the workflow runs correctly.

<img alt="Multi-LoRA Workflow Diagram" />

1. Ensure `Load Checkpoint` loads  **dreamshaper\_8.safetensors**
2. Ensure first `Load LoRA` loads **blindbox\_V1Mix.safetensors**
3. Ensure second `Load LoRA` loads **MoXinV1.safetensors**
4. Click `Queue` or press `Ctrl/Cmd + Enter` to generate

## Try It Yourself

1. Adjust `strength_model` values in both `Load LoRA` nodes to control each LoRA's influence
2. Explore [CivitAI](https://civitai.com/models) for additional LoRAs and create custom combinations


# ComfyUI Outpainting Workflow Example
Source: https://docs.comfy.org/tutorials/basic/outpaint

This guide will introduce you to the outpainting workflow in ComfyUI and walk you through an outpainting example

This guide will introduce you to the concept of outpainting in AI image generation and how to create an outpainting workflow in ComfyUI. We will cover:

* Using outpainting workflow to extend an image
* Understanding and using outpainting-related nodes in ComfyUI
* Mastering the basic outpainting process

## About Outpainting

In AI image generation, we often encounter situations where an existing image has good composition but the canvas area is too small, requiring us to extend the canvas to get a larger scene. This is where outpainting comes in.

Basically, it requires similar content to [Inpainting](/tutorials/basic/inpaint), but we use different nodes to **build the mask**.

Outpainting applications include:

* **Scene Extension:** Expand the scene range of the original image to show a more complete environment
* **Composition Adjustment:** Optimize the overall composition by extending the canvas
* **Content Addition:** Add more related scene elements to the original image

## ComfyUI Outpainting Workflow Example Explanation

### Preparation

#### 1. Model Installation

Download the following model file and save it to `ComfyUI/models/checkpoints` directory:

* [512-inpainting-ema.safetensors](https://huggingface.co/Comfy-Org/stable_diffusion_2.1_repackaged/resolve/main/512-inpainting-ema.safetensors)

#### 2. Input Image

Prepare an image you want to extend. In this example, we will use the following image:

<img alt="ComfyUI Outpainting Input Image" />

#### 3. Outpainting Workflow

Download the image below and **drag it into ComfyUI** to load the workflow:

![ComfyUI Outpainting Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/basic/outpaint.png)

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

### Outpainting Workflow Usage Explanation

<img alt="ComfyUI Outpainting Workflow Diagram" />

The key steps of the outpainting workflow are as follows:

1. Load the locally installed model file in the `Load Checkpoint` node
2. Click the `Upload` button in the `Load Image` node to upload your image
3. Click the `Queue` button or use the shortcut `Ctrl + Enter` to execute the image generation

In this workflow, we mainly use the `Pad Image for outpainting` node to control the direction and range of image extension. This is actually an [Inpaint](/tutorials/basic/inpaint) workflow, but we use different nodes to build the mask.

### Pad Image for outpainting Node

<img alt="Pad Image for outpainting Node" />

This node accepts an input image and outputs an extended image with a corresponding mask, where the mask is built based on the node parameters.

#### Input Parameters

| Parameter Name | Function                                                                                                                              |
| -------------- | ------------------------------------------------------------------------------------------------------------------------------------- |
| `image`        | Input image                                                                                                                           |
| `left`         | Left padding amount                                                                                                                   |
| `top`          | Top padding amount                                                                                                                    |
| `right`        | Right padding amount                                                                                                                  |
| `bottom`       | Bottom padding amount                                                                                                                 |
| `feathering`   | Controls the smoothness of the transition between the original image and the added padding, higher values create smoother transitions |

#### Output Parameters

| Parameter Name | Function                                                                   |
| -------------- | -------------------------------------------------------------------------- |
| `image`        | Output `image` represents the padded image                                 |
| `mask`         | Output `mask` indicates the original image area and the added padding area |

#### Node Output Content

After processing by the `Pad Image for outpainting` node, the output image and mask preview are as follows:

<img alt="Pad Image for outpainting Node Results" />

You can see the corresponding output results:

* The `Image` output is the extended image
* The `Mask` output is the mask marking the extension areas


# ComfyUI Text to Image Workflow
Source: https://docs.comfy.org/tutorials/basic/text-to-image

This guide will help you understand the concept of text-to-image in AI art generation and complete a text-to-image workflow in ComfyUI

This guide aims to introduce you to ComfyUI's text-to-image workflow and help you understand the functionality and usage of various ComfyUI nodes.

In this document, we will:

* Complete a text-to-image workflow
* Gain a basic understanding of diffusion model principles
* Learn about the functions and roles of workflow nodes
* Get an initial understanding of the SD1.5 model

We'll start by running a text-to-image workflow, followed by explanations of related concepts. Please choose the relevant sections based on your needs.

## About Text to Image

**Text to Image** is a fundamental process in AI art generation that creates images from text descriptions, with **diffusion models** at its core.

The text-to-image process requires the following elements:

* **Artist:** The image generation model
* **Canvas:** The latent space
* **Image Requirements (Prompts):** Including positive prompts (elements you want in the image) and negative prompts (elements you don't want)

This text-to-image generation process can be simply understood as telling your requirements (positive and negative prompts) to an **artist (the image model)**, who then creates what you want based on these requirements.

## ComfyUI Text to Image Workflow Example Guide

### 1. Preparation

Ensure you have at least one SD1.5 model file in your `ComfyUI/models/checkpoints` folder, such as [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors)

If you haven't installed it yet, please refer to the model installation section in [Getting Started with ComfyUI AI Art Generation](/get_started/first_generation).

### 2. Loading the Text to Image Workflow

Download the image below and **drag it into ComfyUI** to load the workflow:

<img alt="ComfyUI-Text to Image Workflow" />

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

### 3. Loading the Model and Generating Your First Image

After installing the image model, follow the steps in the image below to load the model and generate your first image

![Image Generation](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/basic/text-to-image-workflow.png)

Follow these steps according to the image numbers:

1. In the **Load Checkpoint** node, use the arrows or click the text area to ensure **v1-5-pruned-emaonly-fp16.safetensors** is selected, and the left/right arrows don't show **null** text
2. Click the `Queue` button or use the shortcut `Ctrl + Enter` to execute image generation

After the process completes, you should see the resulting image in the **Save Image** node interface, which you can right-click to save locally

<img alt="ComfyUI First Image Generation Result" />

<Tip>If you're not satisfied with the result, try running the generation multiple times. Each time you run it, **KSampler** will use a different random seed based on the `seed` parameter, so each generation will produce different results</Tip>

### 4. Start Experimenting

Try modifying the text in the **CLIP Text Encoder**

<img alt="CLIP Text Encoder" />

The `Positive` connection to the KSampler node represents positive prompts, while the `Negative` connection represents negative prompts

Here are some basic prompting principles for the SD1.5 model:

* Use English whenever possible
* Separate prompts with English commas `,`
* Use phrases rather than long sentences
* Use specific descriptions
* Use expressions like `(golden hour:1.2)` to increase the weight of specific keywords, making them more likely to appear in the image. `1.2` is the weight, `golden hour` is the keyword
* Use keywords like `masterpiece, best quality, 4k` to improve generation quality

Here are several prompt examples you can try, or use your own prompts for generation:

**1. Anime Style**

Positive prompts:

```
anime style, 1girl with long pink hair, cherry blossom background, studio ghibli aesthetic, soft lighting, intricate details

masterpiece, best quality, 4k
```

Negative prompts:

```
low quality, blurry, deformed hands, extra fingers
```

**2. Realistic Style**

Positive prompts:

```
(ultra realistic portrait:1.3), (elegant woman in crimson silk dress:1.2), 
full body, soft cinematic lighting, (golden hour:1.2), 
(fujifilm XT4:1.1), shallow depth of field, 
(skin texture details:1.3), (film grain:1.1), 
gentle wind flow, warm color grading, (perfect facial symmetry:1.3)
```

Negative prompts:

```
(deformed, cartoon, anime, doll, plastic skin, overexposed, blurry, extra fingers)
```

**3. Specific Artist Style**

Positive prompts:

```
fantasy elf, detailed character, glowing magic, vibrant colors, long flowing hair, elegant armor, ethereal beauty, mystical forest, magical aura, high detail, soft lighting, fantasy portrait, Artgerm style
```

Negative prompts:

```
blurry, low detail, cartoonish, unrealistic anatomy, out of focus, cluttered, flat lighting
```

## Text to Image Working Principles

The entire text-to-image process can be understood as a **reverse diffusion process**. The [v1-5-pruned-emaonly-fp16.safetensors](https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly-fp16.safetensors) we downloaded is a pre-trained model that can **generate target images from pure Gaussian noise**. We only need to input our prompts, and it can generate target images through denoising random noise.

```mermaid theme={null}
graph LR
A[Pure Gaussian Noise] --> B[Iterative Denoising]
B --> C[Intermediate Latents]
C --> D[Final Generated Image]
E[Text Prompts] --> F[CLIP Encoder]
F --> G[Semantic Vectors]
G --> B
```

We need to understand two concepts:

1. **Latent Space:** Latent Space is an abstract data representation method in diffusion models. Converting images from pixel space to latent space reduces storage space and makes it easier to train diffusion models and reduce denoising complexity. It's like architects using blueprints (latent space) for design rather than designing directly on the building (pixel space), maintaining structural features while significantly reducing modification costs
2. **Pixel Space:** Pixel Space is the storage space for images, which is the final image we see, used to store pixel values.

If you want to learn more about diffusion models, you can read these papers:

* [Denoising Diffusion Probabilistic Models (DDPM)](https://arxiv.org/pdf/2006.11239)
* [Denoising Diffusion Implicit Models (DDIM)](https://arxiv.org/pdf/2010.02502)
* [High-Resolution Image Synthesis with Latent Diffusion Models](https://arxiv.org/pdf/2112.10752)

## ComfyUI Text to Image Workflow Node Explanation

<img alt="ComfyUI Text to Image Workflow Explanation" />

### A. Load Checkpoint Node

<img alt="Load Checkpoint" />

This node is typically used to load the image generation model. A `checkpoint` usually contains three components: `MODEL (UNet)`, `CLIP`, and `VAE`

* `MODEL (UNet)`: The UNet model responsible for noise prediction and image generation during the diffusion process
* `CLIP`: The text encoder that converts our text prompts into vectors that the model can understand, as the model cannot directly understand text prompts
* `VAE`: The Variational AutoEncoder that converts images between pixel space and latent space, as diffusion models work in latent space while our images are in pixel space

### B. Empty Latent Image Node

<img alt="Empty Latent Image" />

Defines a latent space that outputs to the KSampler node. The Empty Latent Image node constructs a **pure noise latent space**

You can think of its function as defining the canvas size, which determines the dimensions of our final generated image

### C. CLIP Text Encoder Node

<img alt="CLIP Text Encoder" />

Used to encode prompts, which are your requirements for the image

* The `Positive` condition input connected to the KSampler node represents positive prompts (elements you want in the image)
* The `Negative` condition input connected to the KSampler node represents negative prompts (elements you don't want in the image)

The prompts are encoded into semantic vectors by the `CLIP` component from the `Load Checkpoint` node and output as conditions to the KSampler node

### D. KSampler Node

<img alt="KSampler" />

The **KSampler** is the core of the entire workflow, where the entire noise denoising process occurs, ultimately outputting a latent space image

```mermaid theme={null}
graph LR
A[Diffusion Model] --> B{KSampler}
C[Random Noise<br>Latent Space] --> B
D[CLIP Semantic Vectors] --> B
B --> E[Denoised Latent]
```

Here's an explanation of the KSampler node parameters:

| Parameter Name               | Description                        | Function                                                                                                    |
| ---------------------------- | ---------------------------------- | ----------------------------------------------------------------------------------------------------------- |
| **model**                    | Diffusion model used for denoising | Determines the style and quality of generated images                                                        |
| **positive**                 | Positive prompt condition encoding | Guides generation to include specified elements                                                             |
| **negative**                 | Negative prompt condition encoding | Suppresses unwanted content                                                                                 |
| **latent\_image**            | Latent space image to be denoised  | Serves as the input carrier for noise initialization                                                        |
| **seed**                     | Random seed for noise generation   | Controls generation randomness                                                                              |
| **control\_after\_generate** | Seed control mode after generation | Determines seed variation pattern in batch generation                                                       |
| **steps**                    | Number of denoising iterations     | More steps mean finer details but longer processing time                                                    |
| **cfg**                      | Classifier-free guidance scale     | Controls prompt constraint strength (too high leads to overfitting)                                         |
| **sampler\_name**            | Sampling algorithm name            | Determines the mathematical method for denoising path                                                       |
| **scheduler**                | Scheduler type                     | Controls noise decay rate and step size allocation                                                          |
| **denoise**                  | Denoising strength coefficient     | Controls noise strength added to latent space, 0.0 preserves original input features, 1.0 is complete noise |

In the KSampler node, the latent space uses `seed` as an initialization parameter to construct random noise, and semantic vectors `Positive` and `Negative` are input as conditions to the diffusion model

Then, based on the number of denoising steps specified by the `steps` parameter, denoising is performed. Each denoising step uses the denoising strength coefficient specified by the `denoise` parameter to denoise the latent space and generate a new latent space image

### E. VAE Decode Node

<img alt="VAE Decode" />

Converts the latent space image output from the **KSampler** into a pixel space image

### F. Save Image Node

<img alt="Save Image" />

Previews and saves the decoded image from latent space to the local `ComfyUI/output` folder

## Introduction to SD1.5 Model

**SD1.5 (Stable Diffusion 1.5)** is an AI image generation model developed by [Stability AI](https://stability.ai/). It's the foundational version of the Stable Diffusion series, trained on **512×512** resolution images, making it particularly good at generating images at this resolution. With a size of about 4GB, it runs smoothly on **consumer-grade GPUs (e.g., 6GB VRAM)**. Currently, SD1.5 has a rich ecosystem, supporting various plugins (like ControlNet, LoRA) and optimization tools.
As a milestone model in AI art generation, SD1.5 remains the best entry-level choice thanks to its open-source nature, lightweight architecture, and rich ecosystem. Although newer versions like SDXL/SD3 have been released, its value for consumer-grade hardware remains unmatched.

### Basic Information

* **Release Date**: October 2022
* **Core Architecture**: Based on Latent Diffusion Model (LDM)
* **Training Data**: LAION-Aesthetics v2.5 dataset (approximately 590M training steps)
* **Open Source Features**: Fully open-source model/code/training data

### Advantages and Limitations

Model Advantages:

* Lightweight: Small size, only about 4GB, runs smoothly on consumer GPUs
* Low Entry Barrier: Supports a wide range of plugins and optimization tools
* Mature Ecosystem: Extensive plugin and tool support
* Fast Generation: Smooth operation on consumer GPUs

Model Limitations:

* Detail Handling: Hands/complex lighting prone to distortion
* Resolution Limits: Quality degrades for direct 1024x1024 generation
* Prompt Dependency: Requires precise English descriptions for control


# ComfyUI Image Upscale Workflow
Source: https://docs.comfy.org/tutorials/basic/upscale

This guide explains the concept of image upscaling in AI drawing and demonstrates how to implement an image upscaling workflow in ComfyUI

## What is Image Upscaling?

Image Upscaling is the process of converting low-resolution images to high-resolution using algorithms.
Unlike traditional interpolation methods, AI upscaling models (like ESRGAN) can intelligently reconstruct details while maintaining image quality.

For instance, the default SD1.5 model often struggles with large-size image generation.
To achieve high-resolution results,we typically generate smaller images first and then use upscaling techniques.

This article covers one of many upscaling methods in ComfyUI. In this tutorial, we'll guide you through:

1. Downloading and installing upscaling models
2. Performing basic image upscaling
3. Combining text-to-image workflows with upscaling

<Note>
  Looking for more advanced upscaling options? Check out our comprehensive [Image Upscaling Guide](/tutorials/utility/image-upscale) which covers various models and use cases including portrait enhancement, product photography, and more.
</Note>

## Upscaling Workflow

### Model Installation

Required ESRGAN models download:

<Steps>
  <Step title="Visit OpenModelDB">
    Visit [OpenModelDB](https://openmodeldb.info/) to search and download upscaling models (e.g., RealESRGAN)

    <img alt="openmodeldb" />

    As shown:

    1. Filter models by image type using the category selector
    2. The model's magnification factor is indicated in the top-right corner (e.g., 2x in the screenshot)

    We'll use the [4x-ESRGAN](https://openmodeldb.info/models/4x-ESRGAN) model for this tutorial. Click the `Download` button on the model detail page.

    <img alt="OpenModelDB_download" />
  </Step>

  <Step title="Save Model Files in Directory">
    Save the model file (.pth) in `ComfyUI/models/upscale_models` directory
  </Step>
</Steps>

### Workflow and Assets

Download and drag the following image into ComfyUI to load the basic upscaling workflow:
![Upscale workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/basic/upscale_workflow.png)

<Tip>
  Images containing workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
</Tip>

Use this image in smaller size as input:

<img alt="Upscale-input" />

### Complete the Workflow Step by Step

Follow the steps in the diagram below to ensure the workflow runs correctly.

<img alt="Upscale workflow" />

1. Ensure `Load Upscale Model` loads `4x-ESRGAN.pth`
2. Upload the input image to the `Load Image` node
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to generate the image

The core components are the `Load Upscale Model` and `Upscale Image (Using Model)` nodes, which receive an image input and upscale it using the selected model.

## Text-to-Image Combined Workflow

After mastering basic upscaling, we can combine it with the [text-to-image](/tutorials/basic/text-to-image) workflow. For text-to-image basics, refer to the [text-to-image tutorial](/tutorials/basic/text-to-image).

Download and drag this image into ComfyUI to load the combined workflow:

<img alt="Text-to-image upscale workflow" />

This workflow connects the text-to-image output image directly to the upscaling nodes for final processing.

## Additional Tips

<Tip>
  Model characteristics:

  * **RealESRGAN**: General-purpose upscaling
  * **BSRGAN**: Excels with text and sharp edges
  * **SwinIR**: Preserves natural textures, ideal for landscapes
</Tip>

1. **Chained Upscaling**: Combine multiple upscale nodes (e.g., 2x → 4x) for ultra-high magnification
2. **Hybrid Workflow**: Connect upscale nodes after generation for "generate+enhance" pipelines
3. **Comparative Testing**: Different models perform better on specific image types - test multiple options


# ComfyUI ControlNet Usage Example
Source: https://docs.comfy.org/tutorials/controlnet/controlnet

This guide will introduce you to the basic concepts of ControlNet and demonstrate how to generate corresponding images in ComfyUI

Achieving precise control over image creation in AI image generation cannot be done with just one click.
It typically requires numerous generation attempts to produce a satisfactory image. However, the emergence of **ControlNet** has effectively addressed this challenge.

ControlNet is a conditional control generation model based on diffusion models (such as Stable Diffusion),
first proposed by [Lvmin Zhang](https://lllyasviel.github.io/) and Maneesh Agrawala et al. in 2023 in the paper [Adding Conditional Control to Text-to-Image Diffusion Models](https://arxiv.org/abs/2302.05543).

ControlNet models significantly enhance the controllability of image generation and the ability to reproduce details by introducing multimodal input conditions,
such as edge detection maps, depth maps, and pose keypoints.

These conditioning constraints make image generation more controllable, allowing multiple ControlNet models to be used simultaneously during the drawing process for better results.

Before ControlNet, we could only rely on the model to generate images repeatedly until we were satisfied with the results, which involved a lot of randomness.

<img alt="Images generated with random seeds in ComfyUI" />

With the advent of ControlNet, we can control image generation by introducing additional conditions.
For example, we can use a simple sketch to guide the image generation process, producing images that closely align with our sketch.

<img alt="Sketch-controlled image generation in ComfyUI" />

In this example, we will guide you through installing and using ControlNet models in [ComfyUI](https://github.com/Comfy-Org/ComfyUI), and complete a sketch-controlled image generation example.

![ComfyUI ControlNet Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/scribble_controlnet.png)

<Tip>
  The workflows for other types of ControlNet V1.1 models are similar to this example. You only need to select the appropriate model and upload the corresponding reference image based on your needs.
</Tip>

## ControlNet Image Preprocessing Information

Different types of ControlNet models typically require different types of reference images:

![Reference Images](https://github.com/Fannovel16/comfyui_controlnet_aux/blob/main/examples/CNAuxBanner.jpg?raw=true)

> Image source: [ComfyUI ControlNet aux](https://github.com/Fannovel16/comfyui_controlnet_aux)

Since the current **Comfy Core** nodes do not include all types of **preprocessors**, in the actual examples in this documentation, we will provide pre-processed images.
However, in practical use, you may need to use custom nodes to preprocess images to meet the requirements of different ControlNet models. Below are some relevant custom nodes:

* [ComfyUI-Advanced-ControlNet](https://github.com/Kosinkadink/ComfyUI-Advanced-ControlNet)
* [ComfyUI ControlNet aux](https://github.com/Fannovel16/comfyui_controlnet_aux)

## ComfyUI ControlNet Workflow Example Explanation

### 1. ControlNet Workflow Assets

Please download the workflow image below and drag it into ComfyUI to load the workflow:

![ComfyUI Workflow - ControlNet](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/scribble_controlnet.png)

<Tip>
  Images with workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
  This image already includes download links for the corresponding models, and dragging it into ComfyUI will automatically prompt for downloads.
</Tip>

Please download the image below, which we will use as input:

![ComfyUI Sketch Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/scribble_input.png)

### 2. Manual Model Installation

<Note>
  If your network cannot successfully complete the automatic download of the corresponding models, please try manually downloading the models below and placing them in the specified directories:
</Note>

* [dreamCreationVirtual3DECommerce\_v10.safetensors](https://civitai.com/api/download/models/731340?type=Model\&format=SafeTensor\&size=full\&fp=fp16)
* [vae-ft-mse-840000-ema-pruned.safetensors](https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.safetensors?download=true)
* [control\_v11p\_sd15\_scribble\_fp16.safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_scribble_fp16.safetensors?download=true)

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── dreamCreationVirtual3DECommerce_v10.safetensors
│   ├── vae/
│   │   └── vae-ft-mse-840000-ema-pruned.safetensors
│   └── controlnet/
│       └── control_v11p_sd15_scribble_fp16.safetensors
```

<Note>
  In this example, you could also use the VAE model embedded in dreamCreationVirtual3DECommerce\_v10.safetensors, but we're following the model author's recommendation to use a separate VAE model.
</Note>

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Workflow - ControlNet Flow Diagram" />

1. Ensure that `Load Checkpoint` can load **dreamCreationVirtual3DECommerce\_v10.safetensors**
2. Ensure that `Load VAE` can load **vae-ft-mse-840000-ema-pruned.safetensors**
3. Click `Upload` in the `Load Image` node to upload the input image provided earlier
4. Ensure that `Load ControlNet` can load **control\_v11p\_sd15\_scribble\_fp16.safetensors**
5. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## Related Node Explanations

### Load ControlNet Node Explanation

<img alt="load controlnet" />

Models located in `ComfyUI\models\controlnet` will be detected by ComfyUI and can be loaded through this node.

### Apply ControlNet Node Explanation

<img alt="apply controlnet" />

This node accepts the ControlNet model loaded by `load controlnet` and generates corresponding control conditions based on the input image.

**Input Types**

| Parameter Name  | Function                                                                                                                                   |
| --------------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
| `positive`      | Positive conditioning                                                                                                                      |
| `negative`      | Negative conditioning                                                                                                                      |
| `control_net`   | The ControlNet model to be applied                                                                                                         |
| `image`         | Preprocessed image used as reference for ControlNet application                                                                            |
| `vae`           | VAE model input                                                                                                                            |
| `strength`      | Strength of ControlNet application; higher values increase ControlNet's influence on the generated image                                   |
| `start_percent` | Determines when to start applying ControlNet as a percentage; e.g., 0.2 means ControlNet guidance begins when 20% of diffusion is complete |
| `end_percent`   | Determines when to stop applying ControlNet as a percentage; e.g., 0.8 means ControlNet guidance stops when 80% of diffusion is complete   |

**Output Types**

| Parameter Name | Function                                           |
| -------------- | -------------------------------------------------- |
| `positive`     | Positive conditioning data processed by ControlNet |
| `negative`     | Negative conditioning data processed by ControlNet |

You can use chain connections to apply multiple ControlNet models, as shown in the image below. You can also refer to the [Mixing ControlNet Models](/tutorials/controlnet/mixing-controlnets) guide to learn more about combining multiple ControlNet models.

<img alt="apply controlnet chain link" />

<Note>
  You might see the `Apply ControlNet(Old)` node in some early workflows, which is an early version of the ControlNet node. It is currently deprecated and not visible by default in search and node lists.

  <img alt="apply controlnet old" />

  To enable it, go to **Settings** --> **comfy** --> **Node** and enable the `Show deprecated nodes in search` option. However, it's recommended to use the new node.
</Note>

## Start Your Exploration

1. Try creating similar sketches, or even draw your own, and use ControlNet models to generate images to experience the benefits of ControlNet.
2. Adjust the `Control Strength` parameter in the Apply ControlNet node to control the influence of the ControlNet model on the generated image.
3. Visit the [ControlNet-v1-1\_fp16\_safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/tree/main) repository to download other types of ControlNet models and try using them to generate images.


# ComfyUI Depth ControlNet Usage Example
Source: https://docs.comfy.org/tutorials/controlnet/depth-controlnet

This guide will introduce you to the basic concepts of Depth ControlNet and demonstrate how to generate corresponding images in ComfyUI

## Introduction to Depth Maps and Depth ControlNet

A depth map is a special type of image that uses grayscale values to represent the distance between objects in a scene and the observer or camera. In a depth map, the grayscale value is inversely proportional to distance: brighter areas (closer to white) indicate objects that are closer, while darker areas (closer to black) indicate objects that are farther away.

![Depth Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth_input.png)

Depth ControlNet is a ControlNet model specifically trained to understand and utilize depth map information. It helps AI correctly interpret spatial relationships, ensuring that generated images conform to the spatial structure specified by the depth map, thereby enabling precise control over three-dimensional spatial layouts.

### Application Scenarios for Depth Maps with ControlNet

Depth maps have numerous applications in various scenarios:

1. **Portrait Scenes**: Control the spatial relationship between subjects and backgrounds, avoiding distortion in critical areas such as faces
2. **Landscape Scenes**: Control the hierarchical relationships between foreground, middle ground, and background
3. **Architectural Scenes**: Control the spatial structure and perspective relationships of buildings
4. **Product Showcase**: Control the separation and spatial positioning of products against their backgrounds

In this example, we will use a depth map to generate an architectural visualization scene.

## ComfyUI ControlNet Workflow Example Explanation

### 1. ControlNet Workflow Assets

Please download the workflow image below and drag it into ComfyUI to load the workflow:

![Depth Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth_controlnet.png)

<Tip>
  Images with workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
  This image already includes download links for the corresponding models, and dragging it into ComfyUI will automatically prompt for downloads.
</Tip>

Please download the image below, which we will use as input:

![Depth Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth_input.png)

### 2. Model Installation

<Note>
  If your network cannot successfully complete the automatic download of the corresponding models, please try manually downloading the models below and placing them in the specified directories:
</Note>

* [architecturerealmix\_v11.safetensors](https://civitai.com/api/download/models/431755?type=Model\&format=SafeTensor\&size=full\&fp=fp16)
* [control\_v11f1p\_sd15\_depth\_fp16.safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11f1p_sd15_depth_fp16.safetensors?download=true)

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── architecturerealmix_v11.safetensors
│   └── controlnet/
│       └── control_v11f1p_sd15_depth_fp16.safetensors
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Workflow - Depth ControlNet Flow Diagram" />

1. Ensure that `Load Checkpoint` can load **architecturerealmix\_v11.safetensors**
2. Ensure that `Load ControlNet` can load **control\_v11f1p\_sd15\_depth\_fp16.safetensors**
3. Click `Upload` in the `Load Image` node to upload the depth image provided earlier
4. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## Combining Depth Control with Other Techniques

Based on different creative needs, you can combine Depth ControlNet with other types of ControlNet to achieve better results:

1. **Depth + Lineart**: Maintain spatial relationships while reinforcing outlines, suitable for architecture, products, and character design
2. **Depth + Pose**: Control character posture while maintaining correct spatial relationships, suitable for character scenes

For more information on using multiple ControlNet models together, please refer to the [Mixing ControlNet](/tutorials/controlnet/mixing-controlnets) example.


# ComfyUI Depth T2I Adapter Usage Example
Source: https://docs.comfy.org/tutorials/controlnet/depth-t2i-adapter

This guide will introduce you to the basic concepts of Depth T2I Adapter and demonstrate how to generate corresponding images in ComfyUI

## Introduction to T2I Adapter

[T2I-Adapter](https://huggingface.co/TencentARC/T2I-Adapter) is a lightweight adapter developed by [Tencent ARC Lab](https://github.com/TencentARC) designed to enhance the structural, color, and style control capabilities of text-to-image generation models (such as Stable Diffusion).
It works by aligning external conditions (such as edge detection maps, depth maps, sketches, or color reference images) with the model's internal features, achieving high-precision control without modifying the original model structure. With only about 77M parameters (approximately 300MB in size), its inference speed is about 3 times faster than [ControlNet](https://github.com/lllyasviel/ControlNet-v1-1-nightly), and it supports multiple condition combinations (such as sketch + color grid). Application scenarios include line art to image conversion, color style transfer, multi-element scene generation, and more.

### Comparison Between T2I Adapter and ControlNet

Although their functions are similar, there are notable differences in implementation and application:

1. **Lightweight Design**: T2I Adapter has fewer parameters and a smaller memory footprint
2. **Inference Speed**: T2I Adapter is typically about 3 times faster than ControlNet
3. **Control Precision**: ControlNet offers more precise control in certain scenarios, while T2I Adapter is more suitable for lightweight control
4. **Multi-condition Combination**: T2I Adapter shows more significant resource advantages when combining multiple conditions

### Main Types of T2I Adapter

T2I Adapter provides various types to control different aspects:

* **Depth**: Controls the spatial structure and depth relationships in images
* **Line Art (Canny/Sketch)**: Controls image edges and lines
* **Keypose**: Controls character poses and actions
* **Segmentation (Seg)**: Controls scene layout through semantic segmentation
* **Color**: Controls the overall color scheme of images

In ComfyUI, using T2I Adapter is similar to [ControlNet](/tutorials/controlnet/controlnet) in terms of interface and workflow. In this example, we will demonstrate how to use a depth T2I Adapter to control an interior scene.

![ComfyUI Depth T2I Adapter Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth-t2i-adapter.png)

## Value of Depth T2I Adapter Applications

Depth maps have several important applications in image generation:

1. **Spatial Layout Control**: Accurately describes three-dimensional spatial structures, suitable for interior design and architectural visualization
2. **Object Positioning**: Controls the relative position and size of objects in a scene, suitable for product showcases and scene construction
3. **Perspective Relationships**: Maintains reasonable perspective and proportions, suitable for landscape and urban scene generation
4. **Light and Shadow Layout**: Natural light and shadow distribution based on depth information, enhancing realism

We will use interior design as an example to demonstrate how to use the depth T2I Adapter, but these techniques are applicable to other scenarios as well.

## ComfyUI Depth T2I Adapter Workflow Example Explanation

### 1. Depth T2I Adapter Workflow Assets

Please download the workflow image below and drag it into ComfyUI to load the workflow:

![ComfyUI Workflow - Depth T2I Adapter](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth-t2i-adapter.png)

<Tip>
  Images with workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
  This image already includes download links for the corresponding models, and dragging it into ComfyUI will automatically prompt for downloads.
</Tip>

Please download the image below, which we will use as input:

![ComfyUI Interior Depth Map](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth-t2i-adapter_input.png)

### 2. Model Installation

<Note>
  If your network cannot successfully complete the automatic download of the corresponding models, please try manually downloading the models below and placing them in the specified directories:
</Note>

* [interiordesignsuperm\_v2.safetensors](https://civitai.com/api/download/models/93152?type=Model\&format=SafeTensor\&size=full\&fp=fp16)
* [t2iadapter\_depth\_sd15v2.pth](https://huggingface.co/TencentARC/T2I-Adapter/resolve/main/models/t2iadapter_depth_sd15v2.pth?download=true)

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── interiordesignsuperm_v2.safetensors
│   └── controlnet/
│       └── t2iadapter_depth_sd15v2.pth
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Workflow - Depth T2I Adapter Flow Diagram" />

1. Ensure that `Load Checkpoint` can load **interiordesignsuperm\_v2.safetensors**
2. Ensure that `Load ControlNet` can load **t2iadapter\_depth\_sd15v2.pth**
3. Click `Upload` in the `Load Image` node to upload the input image provided earlier
4. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## General Tips for Using T2I Adapter

### Input Image Quality Optimization

Regardless of the application scenario, high-quality input images are key to successfully using T2I Adapter:

1. **Moderate Contrast**: Control images (such as depth maps, line art) should have clear contrast, but not excessively extreme
2. **Clear Boundaries**: Ensure that major structures and element boundaries are clearly distinguishable in the control image
3. **Noise Control**: Try to avoid excessive noise in control images, especially for depth maps and line art
4. **Reasonable Layout**: Control images should have a reasonable spatial layout and element distribution

## Characteristics of T2I Adapter Usage

One major advantage of T2I Adapter is its ability to easily combine multiple conditions for complex control effects:

1. **Depth + Edge**: Control spatial layout while maintaining clear structural edges, suitable for architecture and interior design
2. **Line Art + Color**: Control shapes while specifying color schemes, suitable for character design and illustrations
3. **Pose + Segmentation**: Control character actions while defining scene areas, suitable for complex narrative scenes

Mixing different T2I Adapters, or combining them with other control methods (such as ControlNet, regional prompts, etc.), can further expand creative possibilities. To achieve mixing, simply chain multiple `Apply ControlNet` nodes together in the same way as described in [Mixing ControlNet](/tutorials/controlnet/mixing-controlnets).


# ComfyUI Mixing ControlNet Examples
Source: https://docs.comfy.org/tutorials/controlnet/mixing-controlnets

In this example, we will demonstrate how to mix multiple ControlNets and learn to use multiple ControlNet models to control image generation

In AI image generation, a single control condition often fails to meet the requirements of complex scenes. Mixing multiple ControlNets allows you to control different regions or aspects of an image simultaneously, achieving more precise control over image generation.

In certain scenarios, mixing ControlNets can leverage the characteristics of different control conditions to achieve more refined conditional control:

1. **Scene Complexity**: Complex scenes require multiple control conditions working together
2. **Fine-grained Control**: By adjusting the strength parameter of each ControlNet, you can precisely control the degree of influence for each part
3. **Complementary Effects**: Different types of ControlNets can complement each other, compensating for the limitations of single controls
4. **Creative Expression**: Combining different controls can produce unique creative effects

### How to Mix ControlNets

When mixing multiple ControlNets, each ControlNet influences the image generation process according to its applied area. ComfyUI enables multiple ControlNet conditions to be applied sequentially in a layered manner through chain connections in the `Apply ControlNet` node:

<img alt="apply controlnet chain link" />

## ComfyUI ControlNet Regional Division Mixing Example

In this example, we will use a combination of **Pose ControlNet** and **Scribble ControlNet** to generate a scene containing multiple elements: a character on the left controlled by Pose ControlNet and a cat on a scooter on the right controlled by Scribble ControlNet.

### 1. ControlNet Mixing Workflow Assets

Please download the workflow image below and drag it into ComfyUI to load the workflow:
![ComfyUI Workflow - Mixing ControlNet](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/mixing_controlnets.png)

<Tip>
  This workflow image contains Metadata, and can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`. The system will automatically detect and prompt to download the required models.
</Tip>

Input pose image (controls the character pose on the left):

![ComfyUI Workflow - Mixing ControlNet Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/mixing_controlnets_input.png)

Input scribble image (controls the cat and scooter on the right):

![ComfyUI Workflow - Mixing ControlNet Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/mixing_controlnets_input_scribble.png)

### 2. Manual Model Installation

<Note>
  If your network cannot successfully complete the automatic download of the corresponding models, please try manually downloading the models below and placing them in the specified directories:
</Note>

* [awpainting\_v14.safetensors](https://civitai.com/api/download/models/624939?type=Model\&format=SafeTensor\&size=full\&fp=fp16)
* [control\_v11p\_sd15\_scribble\_fp16.safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_scribble_fp16.safetensors?download=true)
* [control\_v11p\_sd15\_openpose\_fp16.safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_openpose_fp16.safetensors?download=true)
* [vae-ft-mse-840000-ema-pruned.safetensors](https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.safetensors?download=true)

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── awpainting_v14.safetensors
│   ├── controlnet/
│   │   └── control_v11p_sd15_scribble_fp16.safetensors
│   │   └── control_v11p_sd15_openpose_fp16.safetensors
│   ├── vae/
│   │   └── vae-ft-mse-840000-ema-pruned.safetensors
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Workflow - Mixing ControlNet Flow Diagram" />

Follow these steps according to the numbered markers in the image:

1. Ensure that `Load Checkpoint` can load **awpainting\_v14.safetensors**
2. Ensure that `Load VAE` can load **vae-ft-mse-840000-ema-pruned.safetensors**

First ControlNet group using the Openpose model:
3\. Ensure that `Load ControlNet Model` loads **control\_v11p\_sd15\_openpose\_fp16.safetensors**
4\. Click `Upload` in the `Load Image` node to upload the pose image provided earlier

Second ControlNet group using the Scribble model:
5\. Ensure that `Load ControlNet Model` loads **control\_v11p\_sd15\_scribble\_fp16.safetensors**
6\. Click `Upload` in the `Load Image` node to upload the scribble image provided earlier
7\. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## Workflow Explanation

#### Strength Balance

When controlling different regions of an image, balancing the strength parameters is particularly important:

* If the ControlNet strength for one region is significantly higher than another, it may cause that region's control effect to overpower and suppress the other region
* It's recommended to set similar strength values for ControlNets controlling different regions, for example, both set to 1.0

#### Prompt Techniques

For regional division mixing, the prompt needs to include descriptions of both regions:

```
"A woman in red dress, a cat riding a scooter, detailed background, high quality"
```

Such a prompt covers both the character and the cat on the scooter, ensuring the model pays attention to both control regions.

## Multi-dimensional Control Applications for a Single Subject

In addition to the regional division mixing shown in this example, another common mixing approach is to apply multi-dimensional control to the same subject. For example:

* **Pose + Depth**: Control character posture and spatial sense
* **Pose + Canny**: Control character posture and edge details
* **Pose + Reference**: Control character posture while referencing a specific style

In this type of application, reference images for multiple ControlNets should be aligned to the same subject, and their strengths should be adjusted to ensure proper balance.

By combining different types of ControlNets and specifying their control regions, you can achieve precise control over elements in your image.


# ComfyUI Pose ControlNet Usage Example
Source: https://docs.comfy.org/tutorials/controlnet/pose-controlnet-2-pass

This guide will introduce you to the basic concepts of Pose ControlNet, and demonstrate how to generate large-sized images in ComfyUI using a two-pass generation approach

## Introduction to OpenPose

[OpenPose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) is an open-source real-time multi-person pose estimation system developed by Carnegie Mellon University (CMU), representing a significant breakthrough in the field of computer vision. The system can simultaneously detect multiple people in an image, capturing:

* **Body skeleton**: 18 keypoints, including head, shoulders, elbows, wrists, hips, knees, and ankles
* **Facial expressions**: 70 facial keypoints for capturing micro-expressions and facial contours
* **Hand details**: 21 hand keypoints for precisely expressing finger positions and gestures
* **Foot posture**: 6 foot keypoints, recording standing postures and movement details

<img alt="OpenPose Example" />

In AI image generation, skeleton structure maps generated by OpenPose serve as conditional inputs for ControlNet, enabling precise control over the posture, actions, and expressions of generated characters. This allows us to generate realistic human figures with expected poses and actions, greatly improving the controllability and practical value of AI-generated content.
Particularly for early Stable Diffusion 1.5 series models, skeletal maps generated by OpenPose can effectively prevent issues with distorted character actions, limbs, and expressions.

## ComfyUI 2-Pass Pose ControlNet Usage Example

### 1. Pose ControlNet Workflow Assets

Please download the workflow image below and drag it into ComfyUI to load the workflow:

![ComfyUI Workflow - Pose ControlNet](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/pose_controlnet_2_pass.png)

<Tip>
  Images with workflow JSON in their metadata can be directly dragged into ComfyUI or loaded using the menu `Workflows` -> `Open (ctrl+o)`.
  This image already includes download links for the corresponding models, and dragging it into ComfyUI will automatically prompt for downloads.
</Tip>

Please download the image below, which we will use as input:

![ComfyUI Pose Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/pose_controlnet_2_pass_input.png)

### 2. Manual Model Installation

<Note>
  If your network cannot successfully complete the automatic download of the corresponding models, please try manually downloading the models below and placing them in the specified directories:
</Note>

* [control\_v11p\_sd15\_openpose\_fp16.safetensors](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_openpose_fp16.safetensors?download=true)
* [majicmixRealistic\_v7.safetensors](https://civitai.com/api/download/models/176425?type=Model\&format=SafeTensor\&size=pruned\&fp=fp16)
* [japaneseStyleRealistic\_v20.safetensors](https://civitai.com/api/download/models/85426?type=Model\&format=SafeTensor\&size=pruned\&fp=fp16)
* [vae-ft-mse-840000-ema-pruned.safetensors](https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.safetensors?download=true)

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── majicmixRealistic_v7.safetensors
│   │   └── japaneseStyleRealistic_v20.safetensors
│   ├── vae/
│   │   └── vae-ft-mse-840000-ema-pruned.safetensors
│   └── controlnet/
│       └── control_v11p_sd15_openpose_fp16.safetensors
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Workflow - Pose ControlNet Flow Diagram" />

Follow these steps according to the numbered markers in the image:

1. Ensure that `Load Checkpoint` can load **majicmixRealistic\_v7.safetensors**
2. Ensure that `Load VAE` can load **vae-ft-mse-840000-ema-pruned.safetensors**
3. Ensure that `Load ControlNet Model` can load **control\_v11p\_sd15\_openpose\_fp16.safetensors**
4. Click the select button in the `Load Image` node to upload the pose input image provided earlier, or use your own OpenPose skeleton map
5. Ensure that `Load Checkpoint` can load **japaneseStyleRealistic\_v20.safetensors**
6. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## Explanation of the Pose ControlNet 2-Pass Workflow

This workflow uses a two-pass image generation approach, dividing the image creation process into two phases:

### First Phase: Basic Pose Image Generation

In the first phase, the **majicmixRealistic\_v7** model is combined with Pose ControlNet to generate an initial character pose image:

1. First, load the majicmixRealistic\_v7 model via the `Load Checkpoint` node
2. Load the pose control model through the `Load ControlNet Model` node
3. The input pose image is fed into the `Apply ControlNet` node and combined with positive and negative prompt conditions
4. The first `KSampler` node (typically using 20-30 steps) generates a basic character pose image
5. The pixel-space image for the first phase is obtained through `VAE Decode`

This phase primarily focuses on correct character posture, pose, and basic structure, ensuring that the generated character conforms to the input skeletal pose.

### Second Phase: Style Optimization and Detail Enhancement

In the second phase, the output image from the first phase is used as a reference, with the **japaneseStyleRealistic\_v20** model performing stylization and detail enhancement:

1. The image generated in the first phase creates a larger resolution latent space through the `Upscale latent` node
2. The second `Load Checkpoint` loads the japaneseStyleRealistic\_v20 model, which focuses on details and style
3. The second `KSampler` node uses a lower `denoise` strength (typically 0.4-0.6) for refinement, preserving the basic structure from the first phase
4. Finally, a higher quality, larger resolution image is output through the second `VAE Decode` and `Save Image` nodes

This phase primarily focuses on style consistency, detail richness, and enhancing overall image quality.

## Advantages of 2-Pass Image Generation

Compared to single-pass generation, the two-pass image generation method offers the following advantages:

1. **Higher Resolution**: Two-pass processing can generate high-resolution images beyond the capabilities of single-pass generation
2. **Style Blending**: Can combine advantages of different models, such as using a realistic model in the first phase and a stylized model in the second phase
3. **Better Details**: The second phase can focus on optimizing details without having to worry about overall structure
4. **Precise Control**: Once pose control is completed in the first phase, the second phase can focus on refining style and details
5. **Reduced GPU Load**: Generating in two passes allows for high-quality large images with limited GPU resources

<Tip>
  To learn more about techniques for mixing multiple ControlNets, please refer to the [Mixing ControlNet Models](/tutorials/controlnet/mixing-controlnets) tutorial.
</Tip>


# ComfyUI Flux.1 ControlNet Examples
Source: https://docs.comfy.org/tutorials/flux/flux-1-controlnet

This guide will demonstrate workflow examples using Flux.1 ControlNet.

<img alt="Flux.1 Canny Controlnet" />

<img alt="Flux.1 Depth Controlnet" />

## FLUX.1 ControlNet Model Introduction

FLUX.1 Canny and Depth are two powerful models from the [FLUX.1 Tools](https://blackforestlabs.ai/flux-1-tools/) launched by [Black Forest Labs](https://blackforestlabs.ai/). This toolkit is designed to add control and guidance capabilities to FLUX.1, enabling users to modify and recreate real or generated images.

**FLUX.1-Depth-dev** and **FLUX.1-Canny-dev** are both 12B parameter Rectified Flow Transformer models that can generate images based on text descriptions while maintaining the structural features of the input image.
The Depth version maintains the spatial structure of the source image through depth map extraction techniques, while the Canny version uses edge detection techniques to preserve the structural features of the source image, allowing users to choose the appropriate control method based on different needs.

Both models have the following features:

* Top-tier output quality and detail representation
* Excellent prompt following ability while maintaining consistency with the original image
* Trained using guided distillation techniques for improved efficiency
* Open weights for the research community
* API interfaces (pro version) and open-source weights (dev version)

Additionally, Black Forest Labs also provides **FLUX.1-Depth-dev-lora** and **FLUX.1-Canny-dev-lora** adapter versions extracted from the complete models.
These can be applied to the FLUX.1 \[dev] base model to provide similar functionality with smaller file size, especially suitable for resource-constrained environments.

We will use the full version of **FLUX.1-Canny-dev** and **FLUX.1-Depth-dev-lora** to complete the workflow examples.

<Tip>
  All workflow images's Metadata contains the corresponding model download information. You can load the workflows by:

  * Dragging them directly into ComfyUI
  * Or using the menu `Workflows` -> `Open（ctrl+o）`

  If you're not using the Desktop Version or some models can't be downloaded automatically, please refer to the manual installation sections to save the model files to the corresponding folder.

  For image preprocessors, you can use the following custom nodes to complete image preprocessing. In this example, we will provide processed images as input.

  * [ComfyUI-Advanced-ControlNet](https://github.com/Kosinkadink/ComfyUI-Advanced-ControlNet)
  * [ComfyUI ControlNet aux](https://github.com/Fannovel16/comfyui_controlnet_aux)
</Tip>

## FLUX.1-Canny-dev Complete Version Workflow

<a href="https://cloud.comfy.org/?template=flux_canny_model_example&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 1. Workflow and Asset

Please download the workflow image below and drag it into ComfyUI to load the workflow

![ComfyUI Workflow - ControlNet](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/controlnet/flux-1-canny-dev.png)

Please download the image below, which we will use as the input image

![ComfyUI Flux.1 Canny Controlnet input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/controlnet/flux-1-canny-dev-input.png)

### 2. Manual Models Installation

<Note>
  If you have previously used the [complete version of Flux related workflows](/tutorials/flux/flux-1-text-to-image), then you only need to download the **flux1-canny-dev.safetensors** model file.
  Since you need to first agree to the terms of [black-forest-labs/FLUX.1-Canny-dev](https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev), please visit the [black-forest-labs/FLUX.1-Canny-dev](https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev) page and make sure you have agreed to the corresponding terms as shown in the image below.

  <img alt="Flux Agreement" />
</Note>

Complete model list:

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors?download=true)
* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors?download=true)
* [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/ae.safetensors?download=true)
* [flux1-canny-dev.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev/resolve/main/flux1-canny-dev.safetensors?download=true) (Please ensure you have agreed to the corresponding repo's terms)

File storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── t5xxl_fp16.safetensors
│   ├── vae/
│   │   └── ae.safetensors
│   └── diffusion_models/
│       └── flux1-canny-dev.safetensors
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Flux.1 Canny Controlnet Step Process" />

1. Make sure `ae.safetensors` is loaded in the `Load VAE` node
2. Make sure `flux1-canny-dev.safetensors` is loaded in the `Load Diffusion Model` node
3. Make sure the following models are loaded in the `DualCLIPLoader` node:
   * clip\_name1: t5xxl\_fp16.safetensors
   * clip\_name2: clip\_l.safetensors
4. Upload the provided input image in the `Load Image` node
5. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

### 4. Start Your Experimentation

Try using the [FLUX.1-Depth-dev](https://huggingface.co/black-forest-labs/FLUX.1-Depth-dev) model to complete the Depth version of the workflow

You can use the image below as input
![ComfyUI Indoor Depth Map](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/controlnet/depth-t2i-adapter_input.png)

Or use the following custom nodes to complete image preprocessing:

* [ComfyUI-Advanced-ControlNet](https://github.com/Kosinkadink/ComfyUI-Advanced-ControlNet)
* [ComfyUI ControlNet aux](https://github.com/Fannovel16/comfyui_controlnet_aux)

## FLUX.1-Depth-dev-lora Workflow

<a href="https://cloud.comfy.org/?template=flux_depth_lora_example&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

The LoRA version workflow builds on the complete version by adding the LoRA model. Compared to the [complete version of the Flux workflow](/tutorials/flux/flux-1-text-to-image), it adds nodes for loading and using the corresponding LoRA model.

### 1. Workflow and Asset

Please download the workflow image below and drag it into ComfyUI to load the workflow

![ComfyUI Workflow - ControlNet](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/controlnet/flux-1-depth-dev-lora.png)

Please download the image below, which we will use as the input image

![ComfyUI Flux.1 Depth Controlnet input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/controlnet/flux-1-depth-dev-lora-input.png)

### 2. Manual Model Download

<Tip>
  If you have previously used the [complete version of Flux related workflows](/tutorials/flux/flux-1-text-to-image), then you only need to download the **flux1-depth-dev-lora.safetensors** model file.
</Tip>

Complete model list:

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors?download=true)
* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors?download=true)
* [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/ae.safetensors?download=true)
* [flux1-dev.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-dev/resolve/main/flux1-dev.safetensors?download=true)
* [flux1-depth-dev-lora.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-Depth-dev-lora/resolve/main/flux1-depth-dev-lora.safetensors?download=true)

File storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── t5xxl_fp16.safetensors
│   ├── vae/
│   │   └── ae.safetensors
│   ├── diffusion_models/
│   │   └── flux1-dev.safetensors
│   └── loras/
│       └── flux1-depth-dev-lora.safetensors
```

### 3. Step-by-Step Workflow Execution

<img alt="ComfyUI Flux.1 Depth Controlnet Step Process" />

1. Make sure `flux1-dev.safetensors` is loaded in the `Load Diffusion Model` node
2. Make sure `flux1-depth-dev-lora.safetensors` is loaded in the `LoraLoaderModelOnly` node
3. Make sure the following models are loaded in the `DualCLIPLoader` node:
   * clip\_name1: t5xxl\_fp16.safetensors
   * clip\_name2: clip\_l.safetensors
4. Upload the provided input image in the `Load Image` node
5. Make sure `ae.safetensors` is loaded in the `Load VAE` node
6. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

### 4. Start Your Experimentation

Try using the [FLUX.1-Canny-dev-lora](https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev-lora) model to complete the Canny version of the workflow

Use [ComfyUI-Advanced-ControlNet](https://github.com/Kosinkadink/ComfyUI-Advanced-ControlNet) or [ComfyUI ControlNet aux](https://github.com/Fannovel16/comfyui_controlnet_aux) to complete image preprocessing

## Community Versions of Flux Controlnets

XLab and InstantX + Shakker Labs have released Controlnets for Flux.

**InstantX:**

* [FLUX.1-dev-Controlnet-Canny](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Canny/blob/main/diffusion_pytorch_model.safetensors)
* [FLUX.1-dev-ControlNet-Depth](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Depth/blob/main/diffusion_pytorch_model.safetensors)
* [FLUX.1-dev-ControlNet-Union-Pro](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro/blob/main/diffusion_pytorch_model.safetensors)

**XLab**: [flux-controlnet-collections](https://huggingface.co/XLabs-AI/flux-controlnet-collections)

Place these files in the `ComfyUI/models/controlnet` directory.

You can visit [Flux Controlnet Example](https://raw.githubusercontent.com/comfyanonymous/ComfyUI_examples/refs/heads/master/flux/flux_controlnet_example.png) to get the corresponding workflow image, and use the image from [here](https://raw.githubusercontent.com/comfyanonymous/ComfyUI_examples/refs/heads/master/flux/girl_in_field.png) as the input image.


# ComfyUI Flux.1 fill dev Example
Source: https://docs.comfy.org/tutorials/flux/flux-1-fill-dev

This guide demonstrates how to use Flux.1 fill dev to create Inpainting and Outpainting workflows.

<img alt="Flux.1 fill dev" />

## Introduction to Flux.1 fill dev Model

Flux.1 fill dev is one of the core tools in the [FLUX.1 Tools suite](https://blackforestlabs.ai/flux-1-tools/) launched by [Black Forest Labs](https://blackforestlabs.ai/), specifically designed for image inpainting and outpainting.

Key features of Flux.1 fill dev:

* Powerful image inpainting and outpainting capabilities, with results second only to the commercial version FLUX.1 Fill \[pro].
* Excellent prompt understanding and following ability, precisely capturing user intent while maintaining high consistency with the original image.
* Advanced guided distillation training technology, making the model more efficient while maintaining high-quality output.
* Friendly licensing terms, with generated outputs usable for personal, scientific, and commercial purposes, please refer to the [FLUX.1 \[dev\] non-commercial license](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md) for details.

Open Source Repository: [FLUX.1 \[dev\]](https://huggingface.co/black-forest-labs/FLUX.1-dev)

This guide will demonstrate inpainting and outpainting workflows based on the Flux.1 fill dev model.
If you're not familiar with inpainting and outpainting workflows, you can refer to [ComfyUI Layout Inpainting Example](/tutorials/basic/inpaint) and [ComfyUI Image Extension Example](/tutorials/basic/outpaint) for some related explanations.

## Flux.1 Fill dev and related models installation

Before we begin, let's complete the installation of the Flux.1 Fill dev model files. The inpainting and outpainting workflows will use exactly the same model files.
If you've previously used the full version of the [Flux.1 Text-to-Image workflow](/tutorials/flux/flux-1-text-to-image),
then you only need to download the **flux1-fill-dev.safetensors** model file in this section.

However, since downloading the corresponding model requires agreeing to the corresponding usage agreement, please visit the [black-forest-labs/FLUX.1-Fill-dev](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev) page and make sure you have agreed to the corresponding agreement as shown in the image below.

<img alt="Flux Agreement" />

Complete model list:

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors?download=true)
* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors?download=true)
* [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/ae.safetensors?download=true)
* [flux1-fill-dev.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev/resolve/main/flux1-fill-dev.safetensors?download=true)

File storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │    ├── clip_l.safetensors
│   │    └── t5xxl_fp16.safetensors
│   ├── vae/
│   │    └── ae.safetensors
│   └── diffusion_models/
│        └── flux1-fill-dev.safetensors
```

## Flux.1 Fill dev inpainting workflow

### 1. Inpainting workflow and asset

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/inpaint/flux_fill_inpaint.png">
  <p>Download Workflow Image</p>
</a>

<a href="https://cloud.comfy.org/?template=flux_fill_inpaint_example&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

Please download the image below and drag it into ComfyUI to load the corresponding workflow
![ComfyUI Flux.1 inpaint](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/inpaint/flux_fill_inpaint.png)

Please download the image below, we will use it as the input image
![ComfyUI Flux.1 inpaint input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/inpaint/flux_fill_inpaint_input.png)

<Note>
  The corresponding image already contains an alpha channel, so you don't need to draw a mask separately.
  If you want to draw your own mask, please [click here](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/inpaint/flux_fill_inpaint_input_original.png) to get the image without a mask, and refer to the MaskEditor usage section in the [ComfyUI Layout Inpainting Example](/tutorials/basic/inpaint#using-the-mask-editor) to learn how to draw a mask in the `Load Image` node.
</Note>

### 2. Steps to run the workflow

<img alt="ComfyUI Flux.1 Fill dev Inpainting Workflow" />

1. Ensure the `Load Diffusion Model` node has `flux1-fill-dev.safetensors` loaded.
2. Ensure the `DualCLIPLoader` node has the following models loaded:
   * clip\_name1: `t5xxl_fp16.safetensors`
   * clip\_name2: `clip_l.safetensors`
3. Ensure the `Load VAE` node has `ae.safetensors` loaded.
4. Upload the input image provided in the document to the `Load Image` node; if you're using the version without a mask, remember to complete the mask drawing using the mask editor
5. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Flux.1 Fill dev Outpainting Workflow

### 1. Outpainting workflow and asset

Please download the image below and drag it into ComfyUI to load the corresponding workflow
![ComfyUI Flux.1 outpaint](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/outpaint/flux_fill_dev_outpaint.png)

Please download the image below, we will use it as the input image
![ComfyUI Flux.1 outpaint input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/outpaint/flux_fill_dev_outpaint_input.png)

### 2. Steps to run the workflow

<img alt="ComfyUI Flux.1 Fill dev Outpainting Workflow" />

1. Ensure the `Load Diffusion Model` node has `flux1-fill-dev.safetensors` loaded.
2. Ensure the `DualCLIPLoader` node has the following models loaded:
   * clip\_name1: `t5xxl_fp16.safetensors`
   * clip\_name2: `clip_l.safetensors`
3. Ensure the `Load VAE` node has `ae.safetensors` loaded.
4. Upload the input image provided in the document to the `Load Image` node
5. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow


# ComfyUI Flux Kontext Dev Native Workflow Example
Source: https://docs.comfy.org/tutorials/flux/flux-1-kontext-dev

ComfyUI Flux Kontext Dev Native Workflow Example.

<iframe title="ComfyUI Selection Toolbox New Features" />

## About FLUX.1 Kontext Dev

FLUX.1 Kontext is a breakthrough multimodal image editing model from Black Forest Labs that supports simultaneous text and image input, intelligently understanding image context and performing precise editing. Its development version is an open-source diffusion transformer model with 12 billion parameters, featuring excellent context understanding and character consistency maintenance, ensuring that key elements such as character features and composition layout remain stable even after multiple iterative edits.

It shares the same core capabilities as the FLUX.1 Kontext suite:

* Character Consistency: Preserves unique elements in images across multiple scenes and environments, such as reference characters or objects in the image.
* Editing: Makes targeted modifications to specific elements in the image without affecting other parts.
* Style Reference: Generates novel scenes while preserving the unique style of the reference image according to text prompts.
* Interactive Speed: Minimal latency in image generation and editing.

While the previously released API version offers the highest fidelity and speed, FLUX.1 Kontext \[Dev] runs entirely on local machines, providing unparalleled flexibility for developers, researchers, and advanced users who wish to experiment.

### Version Information

* **\[FLUX.1 Kontext \[pro]** - Commercial version, focused on rapid iterative editing
* **FLUX.1 Kontext \[max]** - Experimental version with stronger prompt adherence
* **FLUX.1 Kontext \[dev]** - Open source version (used in this tutorial), 12B parameters, mainly for research

Currently in ComfyUI, you can use all these versions, where [Pro and Max versions](/tutorials/partner-nodes/black-forest-labs/flux-1-kontext) can be called through Partner Nodes, while the Dev open source version please refer to the instructions in this guide.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model Download

To run the workflows in this guide successfully, you first need to download the following model files. You can also directly get the model download links from the corresponding workflows, which already contain the model file download information.

**Diffusion Model**

* [flux1-dev-kontext\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/flux1-kontext-dev_ComfyUI/resolve/main/split_files/diffusion_models/flux1-dev-kontext_fp8_scaled.safetensors)

<Tip>
  If you want to use the original weights, you can visit Black Forest Labs' related repository to obtain and use the original model weights.
</Tip>

**VAE**

* [ae.safetensors](https://huggingface.co/Comfy-Org/Lumina_Image_2.0_Repackaged/blob/main/split_files/vae/ae.safetensors)

**Text Encoder**

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors)
* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors) or [t5xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp8_e4m3fn_scaled.safetensors)

Model save location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── flux1-dev-kontext_fp8_scaled.safetensors
│   ├── 📂 vae/
│   │   └── ae.safetensor
│   └── 📂 text_encoders/
│       ├── clip_l.safetensors
│       └── t5xxl_fp16.safetensors or t5xxl_fp8_e4m3fn_scaled.safetensors
```

## Flux.1 Kontext Dev Workflow

<a href="https://cloud.comfy.org/?template=flux_kontext_dev_basic&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

This workflow uses the `Load Image(from output)` node to load the image to be edited, making it more convenient for you to access the edited image for multiple rounds of editing.

### 1. Workflow and Input Image Download

Download the following files and drag them into ComfyUI to load the corresponding workflow

![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/kontext/dev/flux_1_kontext_dev_basic.png)

**Input Image**

![ComfyUI Flux Kontext Native Workflow Input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/kontext/dev/rabbit.jpg)

### 2. Complete the workflow step by step

<img alt="Workflow Step Guide" />

You can refer to the numbers in the image to complete the workflow run:

1. In the `Load Diffusion Model` node, load the `flux1-dev-kontext_fp8_scaled.safetensors` model
2. In the `DualCLIP Load` node, ensure that `clip_l.safetensors` and `t5xxl_fp16.safetensors` or `t5xxl_fp8_e4m3fn_scaled.safetensors` are loaded
3. In the `Load VAE` node, ensure that `ae.safetensors` model is loaded
4. In the `Load Image(from output)` node, load the provided input image
5. In the `CLIP Text Encode` node, modify the prompts, only English is supported
6. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Flux Kontext Prompt Techniques

### 1. Basic Modifications

* Simple and direct: `"Change the car color to red"`
* Maintain style: `"Change to daytime while maintaining the same style of the painting"`

### 2. Style Transfer

**Principles:**

* Clearly name style: `"Transform to Bauhaus art style"`
* Describe characteristics: `"Transform to oil painting with visible brushstrokes, thick paint texture"`
* Preserve composition: `"Change to Bauhaus style while maintaining the original composition"`

### 3. Character Consistency

**Framework:**

* Specific description: `"The woman with short black hair"` instead of "she"
* Preserve features: `"while maintaining the same facial features, hairstyle, and expression"`
* Step-by-step modifications: Change background first, then actions

### 4. Text Editing

* Use quotes: `"Replace 'joy' with 'BFL'"`
* Maintain format: `"Replace text while maintaining the same font style"`

## Common Problem Solutions

### Character Changes Too Much

❌ Wrong: `"Transform the person into a Viking"`
✅ Correct: `"Change the clothes to be a viking warrior while preserving facial features"`

### Composition Position Changes

❌ Wrong: `"Put him on a beach"`
✅ Correct: `"Change the background to a beach while keeping the person in the exact same position, scale, and pose"`

### Style Application Inaccuracy

❌ Wrong: `"Make it a sketch"`
✅ Correct: `"Convert to pencil sketch with natural graphite lines, cross-hatching, and visible paper texture"`

## Core Principles

1. **Be Specific and Clear** - Use precise descriptions, avoid vague terms
2. **Step-by-step Editing** - Break complex modifications into multiple simple steps
3. **Explicit Preservation** - State what should remain unchanged
4. **Verb Selection** - Use "change", "replace" rather than "transform"

## Best Practice Templates

**Object Modification:**
`"Change [object] to [new state], keep [content to preserve] unchanged"`

**Style Transfer:**
`"Transform to [specific style], while maintaining [composition/character/other] unchanged"`

**Background Replacement:**
`"Change the background to [new background], keep the subject in the exact same position and pose"`

**Text Editing:**
`"Replace '[original text]' with '[new text]', maintain the same font style"`

> **Remember:** The more specific, the better. Kontext excels at understanding detailed instructions and maintaining consistency.


# ComfyUI Flux.1 Text-to-Image Workflow Example
Source: https://docs.comfy.org/tutorials/flux/flux-1-text-to-image

This guide provides a brief introduction to the Flux.1 model and guides you through using the Flux.1 model for text-to-image generation with examples including the full version and the FP8 Checkpoint version.

<img alt="Flux" />

Flux is one of the largest open-source text-to-image generation models, with 12B parameters and an original file size of approximately 23GB. It was developed by [Black Forest Labs](https://blackforestlabs.ai/), a team founded by former Stable Diffusion team members.
Flux is known for its excellent image quality and flexibility, capable of generating high-quality, diverse images.

Currently, the Flux.1 model has several main versions:

* **Flux.1 Pro:** The best performing model, closed-source, only available through API calls.
* **[Flux.1 \[dev\]：](https://huggingface.co/black-forest-labs/FLUX.1-dev)** Open-source but limited to non-commercial use, distilled from the Pro version, with performance close to the Pro version.
* **[Flux.1 \[schnell\]：](https://huggingface.co/black-forest-labs/FLUX.1-schnell)** Uses the Apache2.0 license, requires only 4 steps to generate images, suitable for low-spec hardware.

**Flux.1 Model Features**

* **Hybrid Architecture:** Combines the advantages of Transformer networks and diffusion models, effectively integrating text and image information, improving the alignment accuracy between generated images and prompts, with excellent fidelity to complex prompts.
* **Parameter Scale:** Flux has 12B parameters, capturing more complex pattern relationships and generating more realistic, diverse images.
* **Supports Multiple Styles:** Supports diverse styles, with excellent performance for various types of images.

In this example, we'll introduce text-to-image examples using both Flux.1 Dev and Flux.1 Schnell versions, including the full version model and the simplified FP8 Checkpoint version.

* **Flux Full Version:** Best performance, but requires larger VRAM resources and installation of multiple model files.
* **Flux FP8 Checkpoint:** Requires only one fp8 version of the model, but quality is slightly reduced compared to the full version.

<Tip>
  All workflow images's Metadata contains the corresponding model download information. You can load the workflows by:

  * Dragging them directly into ComfyUI
  * Or using the menu `Workflows` -> `Open（ctrl+o）`

  If you're not using the Desktop Version or some models can't be downloaded automatically, please refer to the manual installation sections to save the model files to the corresponding folder.
  Make sure your ComfyUI is updated to the latest version before starting.
</Tip>

## Flux.1 Full Version Text-to-Image Example

<Note>
  If you can't download models from [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev), make sure you've logged into Huggingface and agreed to the corresponding repository's license agreement.

  <img alt="Flux Agreement" />
</Note>

### Flux.1 Dev

#### 1. Workflow File

Please download the image below and drag it into ComfyUI to load the workflow.
![Flux Dev Original Version Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/text-to-image/flux_dev_t5fp16.png)

<a href="https://cloud.comfy.org/?template=flux_dev_checkpoint_example&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

#### 2. Manual Model Installation

<Note>
  * The `flux1-dev.safetensors` file requires agreeing to the [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) agreement before downloading via browser.
  * If your VRAM is low, you can try using [t5xxl\_fp8\_e4m3fn.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp8_e4m3fn.safetensors?download=true) to replace the `t5xxl_fp16.safetensors` file.
</Note>

Please download the following model files:

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors?download=true)
* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors?download=true) Recommended when your VRAM is greater than 32GB.
* [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/ae.safetensors?download=true)
* [flux1-dev.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-dev/resolve/main/flux1-dev.safetensors)

Storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── t5xxl_fp16.safetensors
│   ├── vae/
│   │   └── ae.safetensors
│   └── diffusion_models/
│       └── flux1-dev.safetensors
```

#### 3. Steps to Run the Workflow

Please refer to the image below to ensure all model files are loaded correctly

<img alt="ComfyUI Flux Dev Workflow" />

1. Ensure the `DualCLIPLoader` node has the following models loaded:
   * clip\_name1: t5xxl\_fp16.safetensors
   * clip\_name2: clip\_l.safetensors
2. Ensure the `Load Diffusion Model` node has `flux1-dev.safetensors` loaded
3. Make sure the `Load VAE` node has `ae.safetensors` loaded
4. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

<Tip>
  Thanks to Flux's excellent prompt following capability, we don't need any negative prompts
</Tip>

### Flux.1 Schnell

#### 1. Workflow File

Please download the image below and drag it into ComfyUI to load the workflow.

![Flux Schnell Version Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/text-to-image/flux_schnell_t5fp8.png)

<a href="https://cloud.comfy.org/?template=flux_schnell&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

#### 2. Manual Models Installation

<Note>
  In this workflow, only two model files are different from the Flux1 Dev version workflow. For t5xxl, you can still use the fp16 version for better results.

  * **t5xxl\_fp16.safetensors** -> **t5xxl\_fp8.safetensors**
  * **flux1-dev.safetensors** -> **flux1-schnell.safetensors**
</Note>

Complete model file list:

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors?download=true)
* [t5xxl\_fp8\_e4m3fn.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp8_e4m3fn.safetensors?download=true)
* [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/ae.safetensors?download=true)
* [flux1-schnell.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/flux1-schnell.safetensors)

File storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── t5xxl_fp8_e4m3fn.safetensors
│   ├── vae/
│   │   └── ae.safetensors
│   └── diffusion_models/
│       └── flux1-schnell.safetensors
```

#### 3. Steps to Run the Workflow

<img alt="Flux Schnell Version Workflow" />

1. Ensure the `DualCLIPLoader` node has the following models loaded:
   * clip\_name1: t5xxl\_fp8\_e4m3fn.safetensors
   * clip\_name2: clip\_l.safetensors
2. Ensure the `Load Diffusion Model` node has `flux1-schnell.safetensors` loaded
3. Ensure the `Load VAE` node has `ae.safetensors` loaded
4. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Flux.1 FP8 Checkpoint Version Text-to-Image Example

The fp8 version is a quantized version of the original Flux.1 fp16 version.
To some extent, the quality of this version will be lower than that of the fp16 version,
but it also requires less VRAM, and you only need to install one model file to try running it.

### Flux.1 Dev

Please download the image below and drag it into ComfyUI to load the workflow.

![Flux Dev fp8 Checkpoint Version Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/text-to-image/flux_dev_fp8.png)

<a href="https://cloud.comfy.org/?template=flux_dev_full_text_to_image&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

Please download [flux1-dev-fp8.safetensors](https://huggingface.co/Comfy-Org/flux1-dev/resolve/main/flux1-dev-fp8.safetensors?download=true) and save it to the `ComfyUI/models/checkpoints/` directory.

Ensure that the corresponding `Load Checkpoint` node loads `flux1-dev-fp8.safetensors`, and you can try to run the workflow.

### Flux.1 Schnell

Please download the image below and drag it into ComfyUI to load the workflow.

![Flux Schnell fp8 Checkpoint Version Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/text-to-image/flux_schnell_fp8.png)

Please download [flux1-schnell-fp8.safetensors](https://huggingface.co/Comfy-Org/flux1-schnell/resolve/main/flux1-schnell-fp8.safetensors?download=true) and save it to the `ComfyUI/models/checkpoints/` directory.

Ensure that the corresponding `Load Checkpoint` node loads `flux1-schnell-fp8.safetensors`, and you can try to run the workflow.


# ByteDance USO ComfyUI Native Workflow example
Source: https://docs.comfy.org/tutorials/flux/flux-1-uso

Unified Style and Subject-Driven Generation with ByteDance's USO model

**USO (Unified Style-Subject Optimized)** is a model developed by ByteDance's UXO Team that unifies style-driven and subject-driven generation tasks.
Built on FLUX.1-dev architecture, the model achieves both style similarity and subject consistency through disentangled learning and style reward learning (SRL).

USO supports three main approaches:

* **Subject-Driven**: Place subjects into new scenes while maintaining identity consistency
* **Style-Driven**: Apply artistic styles to new content based on reference images
* **Combined**: Use both subject and style references simultaneously

**Related Links**

* [Project Page](https://bytedance.github.io/USO/)
* [GitHub](https://github.com/bytedance/USO)
* [Model Weights](https://huggingface.co/bytedance-research/USO)

## ByteDance USO ComfyUI Native Workflow

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### 1. Workflow and input

Download the image below and drag it into ComfyUI to load the corresponding workflow.

![Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/flux/bytedance-uso/bytedance-uso.png)

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/flux1_dev_uso_reference_image_gen.json">
  <p>Download JSON Workflow</p>
</a>

<a href="https://cloud.comfy.org/?template=flux1_dev_uso_reference_image_gen&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

Use the image below as an input image.

![input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/flux/bytedance-uso/input.png)

### 2. Model links

**checkpoints**

* [flux1-dev-fp8.safetensors](https://huggingface.co/Comfy-Org/flux1-dev/resolve/main/flux1-dev-fp8.safetensors)

**loras**

* [uso-flux1-dit-lora-v1.safetensors](https://huggingface.co/Comfy-Org/USO_1.0_Repackaged/resolve/main/split_files/loras/uso-flux1-dit-lora-v1.safetensors)

**model\_patches**

* [uso-flux1-projector-v1.safetensors](https://huggingface.co/Comfy-Org/USO_1.0_Repackaged/resolve/main/split_files/model_patches/uso-flux1-projector-v1.safetensors)

**clip\_visions**

* [sigclip\_vision\_patch14\_384.safetensors](https://huggingface.co/Comfy-Org/sigclip_vision_384/resolve/main/sigclip_vision_patch14_384.safetensors)

Please download all models and place them in the following directories:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   └── flux1-dev-fp8.safetensors
│   ├── 📂 loras/
│   │   └── uso-flux1-dit-lora-v1.safetensors
│   ├── 📂 model_patches/
│   │   └── uso-flux1-projector-v1.safetensors
│   ├── 📂 clip_visions/
│   │   └── sigclip_vision_patch14_384.safetensors
```

### 3. Workflow instructions

<img alt="Workflow instructions" />

1. Load models:
   * 1.1 Ensure the `Load Checkpoint` node has `flux1-dev-fp8.safetensors` loaded
   * 1.2 Ensure the `LoraLoaderModelOnly` node has `dit_lora.safetensors` loaded
   * 1.3 Ensure the `ModelPatchLoader` node has `projector.safetensors` loaded
   * 1.4 Ensure the `Load CLIP Vision` node has `sigclip_vision_patch14_384.safetensors` loaded
2. Content Reference:
   * 2.1 Click `Upload` to upload the input image we provided
   * 2.2 The `ImageScaleToMaxDimension` node will scale your input image for content reference, 512px will keep more character features, but if you only use the character's head as input, the final output image often has issues like the character taking up too much space. Setting it to 1024px gives much better results.
3. In the example, we only use the `content reference` image input. If you want to use the `style reference` image input, you can use `Ctrl-B` to bypass the marked node group.
4. Write your prompt or keep default
5. Set the image size if you need
6. The EasyCache node is for inference acceleration, but it will also sacrifice some quality and details. You can bypass it (Ctrl+B) if you don't need to use it.
7. Click the `Run` button, or use the shortcut `Ctrl(Cmd) + Enter` to run the workflow

### 4. Additional Notes

1. Style reference only:

We also provide a workflow that only uses style reference in the same workflow we provided

<img alt="Workflow" />

The only different is we replaced the `content reference` node and only use an `Empty Latent Image` node.

2. You can also bypass whole `Style Reference` group and use the workflow as a text to image workflow, which means this workflow has 4 variations

* Only use content (subject) reference
* Only use style reference
* Mixed content and style reference
* As a text to image workflow


# ComfyUI Flux.2 Dev Example
Source: https://docs.comfy.org/tutorials/flux/flux-2-dev

This guide provides a brief introduction to the Flux.2 model and guides you through using the Flux.2 Dev model for text-to-image generation in ComfyUI.

<iframe title="YouTube video player" />

## About FLUX.2

[FLUX.2](https://bfl.ai/blog/flux-2) is a next-generation image model from [Black Forest Labs](https://blackforestlabs.ai/), delivering up to 4MP photorealistic output with far better lighting, skin, fabric, and hand detail. It adds reliable multi-reference consistency (up to 10 images), improved editing precision, better visual understanding, and professional-class text rendering.

**Key Features:**

* **Multi-Reference Consistency:** Reliably maintains identity, product geometry, textures, materials, wardrobe, and composition intent across multiple outputs
* **High-Resolution Photorealism:** Generates images up to 4MP with real-world lighting behavior, spatial reasoning, and physics-aware detail
* **Professional-Grade Control:** Exact pose control, hex-code accurate brand colors, any aspect ratio, and structured prompting for programmatic workflows
* **Usable Text Rendering:** Produces clean, legible text across UI screens, infographics, and multi-language content

**Available Models:**

* **FLUX.2 Dev:** Open-source model (used in this tutorial)
* **FLUX.2 Pro:** API version from Black Forest Labs

<Note>
  We are using quantized weights in this workflow. The original FLUX.2 repository is available [here](https://huggingface.co/black-forest-labs/FLUX.2-dev/).
</Note>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Single image generation workflow

Basic text-to-image workflow for generating single images with FLUX.2 Dev.

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_flux2&utm_source=docs">
  Open this workflow directly in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_flux2.json">
  Download the JSON workflow file for local use
</Card>

## Multi-image reference workflow

A 2-image reference workflow example. You can extend this implementation to support more reference images.

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_flux2_fp8&utm_source=docs">
  Open this workflow directly in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/comfyui-wiki/workflow_templates/refs/heads/main/templates/image_flux2_fp8.json">
  Download the JSON workflow file for local use
</Card>

## Model links

**text\_encoders**

* [mistral\_3\_small\_flux2\_bf16.safetensors](https://huggingface.co/Comfy-Org/flux2-dev/resolve/main/split_files/text_encoders/mistral_3_small_flux2_bf16.safetensors)

**diffusion\_models**

* [flux2\_dev\_fp8mixed.safetensors](https://huggingface.co/Comfy-Org/flux2-dev/resolve/main/split_files/diffusion_models/flux2_dev_fp8mixed.safetensors)

**vae**

* [flux2-vae.safetensors](https://huggingface.co/Comfy-Org/flux2-dev/resolve/main/split_files/vae/flux2-vae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── mistral_3_small_flux2_bf16.safetensors
│   ├── 📂 diffusion_models/
│   │      └── flux2_dev_fp8mixed.safetensors
│   └── 📂 vae/
│          └── flux2-vae.safetensors
```


# ComfyUI Flux.2 Klein 4B Guide
Source: https://docs.comfy.org/tutorials/flux/flux-2-klein

A quick introduction to FLUX.2 [klein] 4B and how to run text-to-image and image editing workflows in ComfyUI.

<iframe title="YouTube video player" />

## About FLUX.2 \[klein]

FLUX.2 \[Klein] is the fastest model in the Flux family, unifying text-to-image and image editing in one compact architecture. It’s designed for interactive workflows, immediate previews, and latency-critical applications, with distilled variants delivering end-to-end inference around one second while keeping strong quality for single- and multi-reference editing.

**Model highlights:**

* Two 4B types: Base (undistilled) for maximum flexibility and fine-tuning; Distilled (4-step) for speed-first deployments
* Performance: distilled \~1.2s (5090) · 8.4GB VRAM; base \~17s (5090) · 9.2GB VRAM
* Editing support: style transforms, semantic edits, object replacement/removal, multi-reference composition, iterative edits

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Flux.2 Klein 4B Workflows

<Card title="4B Text-to-Image Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_flux2_klein_text_to_image.json">
  Download the text-to-image workflow for Flux.2 Klein 4B.
</Card>

<Card title="4B Image Edit Base" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_flux2_klein_image_edit_4b_base.json">
  Download the image editing workflow using the 4B base model.
</Card>

<Card title="4B Image Edit Distilled" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_flux2_klein_image_edit_4b_distilled.json">
  Download the fast distilled 4B image editing workflow.
</Card>

## Flux.2 Klein 4B Model Downloads

<Card title="qwen_3_4b.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/flux2-klein-4B/resolve/main/split_files/text_encoders/qwen_3_4b.safetensors">
  Text encoder for 4B models.
</Card>

<Card title="flux-2-klein-base-4b-fp8.safetensors" icon="download" href="https://huggingface.co/black-forest-labs/FLUX.2-klein-base-4b-fp8/resolve/main/flux-2-klein-base-4b-fp8.safetensors">
  Diffusion model (4B base).
</Card>

<Card title="flux-2-klein-4b-fp8.safetensors" icon="download" href="https://huggingface.co/black-forest-labs/FLUX.2-klein-4b-fp8/resolve/main/flux-2-klein-4b-fp8.safetensors">
  Diffusion model (4B distilled).
</Card>

<Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/flux2-dev/resolve/main/split_files/vae/flux2-vae.safetensors">
  VAE for 4B models.
</Card>

**4B Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_3_4b.safetensors
│   ├── 📂 diffusion_models/
│   │      ├── flux-2-klein-base-4b-fp8.safetensors
│   │      └── flux-2-klein-4b-fp8.safetensors
│   └── 📂 vae/
│          └── flux2-vae.safetensors
```

## Flux.2 Klein 9B Workflows

<Card title="9B Text-to-Image Workflow" icon="download" href="http://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_flux2_text_to_image_9b.json">
  Download the text-to-image workflow for Flux.2 Klein 9B.
</Card>

<Card title="9B Image Edit Base" icon="download" href="http://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_flux2_klein_image_edit_9b_base.json">
  Download the image editing workflow using the 9B base model.
</Card>

<Card title="9B Image Edit Distilled" icon="download" href="http://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_flux2_klein_image_edit_9b_distilled.json">
  Download the fast distilled 9B image editing workflow.
</Card>

## Flux.2 Klein 9B Model Downloads

<Note>
  For diffusion models, please visit BFL's repo, accept the agreement, and then download the models.
</Note>

<Card title="flux-2-klein-base-9b-fp8.safetensors" icon="download" href="https://huggingface.co/black-forest-labs/FLUX.2-klein-base-9b-fp8">
  Diffusion model (9B base).
</Card>

<Card title="flux-2-klein-9b-fp8.safetensors" icon="download" href="https://huggingface.co/black-forest-labs/FLUX.2-klein-9b-fp8">
  Diffusion model (9B distilled).
</Card>

<Card title="qwen_3_8b_fp8mixed.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/flux2-klein-9B/resolve/main/split_files/text_encoders/qwen_3_8b_fp8mixed.safetensors">
  Text encoder for 9B models.
</Card>

<Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/flux2-dev/resolve/main/split_files/vae/flux2-vae.safetensors">
  VAE for 9B models.
</Card>

**9B Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │      ├── flux-2-klein-9b-fp8.safetensors
│   │      └── flux-2-klein-base-9b-fp8.safetensors
│   ├── 📂 text_encoders/
│   │      └── qwen_3_8b_fp8mixed.safetensors
│   └── 📂 vae/
│          └── flux2-vae.safetensors
```


# Flux.1 Krea Dev ComfyUI Workflow Tutorial
Source: https://docs.comfy.org/tutorials/flux/flux1-krea-dev

Best open-source FLUX model developed by Black Forest Labs in collaboration with Krea, focusing on unique aesthetic style and natural details, avoiding AI look, providing exceptional realism and image quality.

<img alt="Flux.1 Krea Dev Poster" />

[Flux.1 Krea Dev](https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev) is an advanced text-to-image generation model developed in collaboration between Black Forest Labs (BFL) and Krea. This is currently the best open-source FLUX model, specifically designed for text-to-image generation.

**Model Features**

* **Unique Aesthetic Style**: Focuses on generating images with unique aesthetics, avoiding common "AI look" appearance
* **Natural Details**: Does not produce blown-out highlights, maintaining natural detail representatio
* **Exceptional Realism**: Provides outstanding realism and image quality
* **Fully Compatible Architecture**: Fully compatible architecture design with FLUX.1 \[dev]

**Model License**
This model is released under the [flux-1-dev-non-commercial-license](https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev/blob/main/LICENSE.md)

## Flux.1 Krea Dev ComfyUI Workflow

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

#### 1. Workflow Files

Download the image or JSON below and drag it into ComfyUI to load the corresponding workflow
![Flux Krea Dev Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/flux/krea/flux1_krea_dev.png)

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/flux1_krea_dev.json">
  <p>Download JSON Workflow</p>
</a>

<a href="https://cloud.comfy.org/?template=flux1_krea_dev&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

#### 2. Manual Model Installation

Please download the following model files:
**Diffusion model**

* [flux1-krea-dev\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/FLUX.1-Krea-dev_ComfyUI/blob/main/split_files/diffusion_models/flux1-krea-dev_fp8_scaled.safetensors)

If you want to pursue higher quality and have enough VRAM, you can try the original model weights

* [flux1-krea-dev.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev/resolve/main/flux1-krea-dev.safetensors)

<Note>
  The `flux1-dev.safetensors` file requires agreeing to the [black-forest-labs/FLUX.1-Krea-dev](https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev/) agreement before downloading via browser.
</Note>

If you have used Flux related workflows before, the following models are the same and don't need to be downloaded again

**Text encoders**

* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors?download=true)
* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors?download=true) Recommended when your VRAM is greater than 32GB.
* [t5xxl\_fp8\_e4m3fn.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp8_e4m3fn.safetensors)  For Low VRAM

**VAE**

* [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/ae.safetensors?download=true)

File save location:

```
ComfyUI/
├── models/
│   ├── diffusion_models/
│   │   └── flux1-krea-dev_fp8_scaled.safetensors or flux1-krea-dev.safetensors
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── t5xxl_fp16.safetensors or t5xxl_fp8_e4m3fn.safetensors
│   ├── vae/
│   │   └── ae.safetensors

```

#### 3. Step-by-step Verification to Ensure Workflow Runs Properly

<Tip>
  For low VRAM users, this model may not run smoothly on your device, you can wait for the community to provide FP8 or GGUF version.
</Tip>

Please refer to the image below to ensure all model files have been loaded correctly

<img alt="ComfyUI Flux Krea Dev Workflow" />

1. Ensure that `flux1-krea-dev_fp8_scaled.safetensors` or `flux1-krea-dev.safetensors` is loaded in the `Load Diffusion Model` node
   * `flux1-krea-dev_fp8_scaled.safetensors` is recommended for low VRAM users
   * `flux1-krea-dev.safetensors` is the original weights, if you have enough VRAM like 24GB you can use it for better quality
2. Ensure the following models are loaded in the `DualCLIPLoader` node:
   * clip\_name1: t5xxl\_fp16.safetensors or t5xxl\_fp8\_e4m3fn.safetensors
   * clip\_name2: clip\_l.safetensors
3. Ensure that `ae.safetensors` is loaded in the `Load VAE` node
4. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow


# Anima Base v1 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/image/anima/anima

Anima is a 2B-parameter text-to-image model by CircleStone Labs / Comfy Org, optimized for anime and non-photorealistic illustration generation.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Anima** is an open text-to-image model by [CircleStone Labs](https://huggingface.co/circlestone-labs/Anima) in partnership with Comfy Org. With **2 billion** parameters, it is designed to generate high-quality **anime and non-photorealistic** images — ideal for characters, scenes, and concept art.

**Model highlights**:

* **Anime and artistic illustration focus** — tuned for non-photorealistic art styles
* **ComfyUI native support** — loaded with standard UNETLoader, CLIPLoader, and VAELoader nodes
* **Qwen-3 0.6B text encoder** — provides strong language understanding and prompt adherence
* **No input image needed** — pure text-to-image generation
* **Compact footprint** — 2B diffusion model, runs comfortably on consumer GPUs

**Related links**:

* [Hugging Face (Anima)](https://huggingface.co/circlestone-labs/Anima)

## Available workflows

Anima provides two workflows — the base version for standard use and a preview version for early access.

Both workflows use a **Subgraph** node to manage the text-to-image generation pipeline. You can open the subgraph to inspect or customize the internal nodes.

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

### Anima Base v1: Text to Image

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_anima_base_v1.json">
  Download JSON or search "Aima Base v1" in Template Library
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_anima_base_v1&utm_source=docs&utm_medium=referral&utm_campaign=anima">
  Open in Comfy Cloud
</Card>

#### Get started

1. Update ComfyUI to the latest version or use [Comfy Cloud](https://cloud.comfy.org/?template=image_anima_base_v1\&utm_source=docs\&utm_medium=referral\&utm_campaign=anima)
2. Go to **Template** and search for **Aima Base v1**
3. Select the **Aima Base v1: Text to Image** workflow
4. Download any missing models (see [model downloads](#anima-model-downloads)), enter your prompt, and click **Queue**

#### Example output

<img alt="Anima Base v1 example output" />

### Anima Preview: Anime Text-to-Image Generation

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_anima_preview.json">
  Download JSON or search "Anima Preview" in Template Library
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_anima_preview&utm_source=docs&utm_medium=referral&utm_campaign=anima">
  Open in Comfy Cloud
</Card>

#### Get started

1. Update ComfyUI to the latest version or use [Comfy Cloud](https://cloud.comfy.org/?template=image_anima_preview\&utm_source=docs\&utm_medium=referral\&utm_campaign=anima)
2. Go to **Template** and search for **Anima Preview**
3. Select the **Anima Anime Text-to-Image Generation** workflow
4. Download any missing models (see [model downloads](#anima-model-downloads)), enter your prompt, and click **Queue**

#### Example output

<img alt="Anima Preview example output" />

## Anima model downloads

You can find all model files at [circlestone-labs/Anima](https://huggingface.co/circlestone-labs/Anima) on Hugging Face.

<Card title="anima-base-v1.0.safetensors" icon="download" href="https://huggingface.co/circlestone-labs/Anima/resolve/main/split_files/diffusion_models/anima-base-v1.0.safetensors">
  Diffusion model (2B) for Anima Base v1.
</Card>

<Card title="qwen_3_06b_base.safetensors" icon="download" href="https://huggingface.co/circlestone-labs/Anima/resolve/main/split_files/text_encoders/qwen_3_06b_base.safetensors">
  Text encoder (Qwen-3 0.6B) shared by both workflows.
</Card>

<Card title="qwen_image_vae.safetensors" icon="download" href="https://huggingface.co/circlestone-labs/Anima/resolve/main/split_files/vae/qwen_image_vae.safetensors">
  VAE shared by both workflows.
</Card>

**Model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── anima-base-v1.0.safetensors
│   ├── 📂 text_encoders/
│   │   └── qwen_3_06b_base.safetensors
│   └── 📂 vae/
│       └── qwen_image_vae.safetensors
```

### Preview model

If you are using the Preview workflow, download the preview diffusion model instead:

<Card title="anima-preview3-base.safetensors" icon="download" href="https://huggingface.co/circlestone-labs/Anima/resolve/main/split_files/diffusion_models/anima-preview3-base.safetensors">
  Diffusion model (2B) for Anima Preview.
</Card>

**Preview model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 diffusion_models/
│       └── anima-preview3-base.safetensors
```

## Limitations

* **No realism** — the model is intentionally designed for anime and illustration styles; realistic renderings are out of scope
* **Weak text rendering** — high-resolution text and complex typography may not render clearly
* **Plain styling** — the base model produces simpler compositions; advanced artistic styles may require refinement or fine-tuning


# Cosmos Predict2 Text-to-Image ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/image/cosmos/cosmos-predict2-t2i

This guide demonstrates how to complete Cosmos-Predict2 text-to-image workflow in ComfyUI

Cosmos-Predict2 is NVIDIA's next-generation physical world foundation model, specifically designed for high-quality visual generation and prediction tasks in physical AI scenarios.
The model features exceptional physical accuracy, environmental interactivity, and detail reproduction capabilities, enabling realistic simulation of complex physical phenomena and dynamic scenes.

Cosmos-Predict2 supports various generation methods including Text-to-Image (Text2Image) and Video-to-World (Video2World), and is widely used in industrial simulation, autonomous driving, urban planning, scientific research, and other fields.

GitHub:[Cosmos-predict2](https://github.com/nvidia-cosmos/cosmos-predict2)
huggingface: [Cosmos-Predict2](https://huggingface.co/collections/nvidia/cosmos-predict2-68028efc052239369a0f2959)

This guide will walk you through completing **text-to-image** workflow in ComfyUI.

For the video generation section, please refer to the following part:

<Card title="Cosmos Predict2 Video Generation" icon="book" href="/tutorials/video/cosmos/cosmos-predict2-video2world">
  Using Cosmos-Predict2  for video generation
</Card>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>


# ERNIE-Image ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/image/ernie-image/ernie-image

ERNIE-Image is Baidu's open 8B Diffusion Transformer text-to-image model with precise text rendering, strong instruction following, and a built-in Prompt Enhancer.

**ERNIE-Image** is an open text-to-image model by Baidu, licensed under Apache-2.0. Built on an **8B** parameter Diffusion Transformer (DiT), it delivers high-quality image generation with precise text rendering, strong instruction following, and structured visual generation.

The model includes a built-in **Prompt Enhancer** (3B) that expands short inputs into richer prompts for better results.

**Model highlights**:

* **Precise text rendering** — dense and layout-sensitive text in English, Chinese, and more
* **Strong instruction following** — handles complex prompts, multi-object relations, and knowledge-intensive descriptions
* **Structured visual generation** — posters, manga/anime storyboards, multi-panel compositions
* **Broad stylistic range** — realistic photography to cinematic film-like aesthetics
* **Compact and deployable** — 8B parameters, runs on 24 GB VRAM
* **Built-in Prompt Enhancer** — 3B model that expands short inputs into richer prompts

**Related links**:

* [Hugging Face (ERNIE-Image)](https://huggingface.co/Baidu/ERNIE-Image)
* [Hugging Face (ComfyUI Support)](https://huggingface.co/Comfy-Org/ERNIE-Image)

## ERNIE-Image text-to-image workflow

<Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_ernie_image.json">
  Download the ERNIE-Image text-to-image workflow JSON file.
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_ernie_image&utm_source=docs">
  Run this workflow directly on Comfy Cloud.
</Card>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Get started

1. Update ComfyUI to the latest version or use [Comfy Cloud](https://cloud.comfy.org/?template=image_ernie_image\&utm_source=docs)
2. Go to **Template** and search for **ERNIE-Image**
3. Select the **ERNIE-Image** workflow
4. Download any missing models, update the prompt, and click **Run**

### ERNIE-Image model downloads

You can find all repackaged model files at [Comfy-Org/ERNIE-Image](https://huggingface.co/Comfy-Org/ERNIE-Image) on Hugging Face.

<Card title="ernie-image.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/resolve/main/diffusion_models/ernie-image.safetensors">
  Diffusion model for ERNIE-Image.
</Card>

<Card title="ministral-3-3b.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/resolve/main/text_encoders/ministral-3-3b.safetensors">
  Text encoder for ERNIE-Image.
</Card>

<Card title="ernie-image-prompt-enhancer.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/resolve/main/text_encoders/ernie-image-prompt-enhancer.safetensors">
  Prompt Enhancer text encoder for ERNIE-Image.
</Card>

<Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/resolve/main/vae/flux2-vae.safetensors">
  VAE for ERNIE-Image.
</Card>

**Model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── ernie-image.safetensors
│   ├── 📂 text_encoders/
│   │   ├── ministral-3-3b.safetensors
│   │   └── ernie-image-prompt-enhancer.safetensors
│   └── 📂 vae/
│       └── flux2-vae.safetensors
```

## ERNIE-Image-Turbo

[ERNIE-Image-Turbo](https://huggingface.co/Baidu/ERNIE-Image-Turbo) is a faster variant optimized with DMD and RL, generating images in just **8 steps** compared to the \~50 steps required by the standard model.

<Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_ernie_image_turbo.json">
  Download the ERNIE-Image-Turbo text-to-image workflow JSON file.
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_ernie_image_turbo&utm_source=docs">
  Run this workflow directly on Comfy Cloud.
</Card>

### ERNIE-Image-Turbo model downloads

<Card title="ernie-image-turbo.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/resolve/main/diffusion_models/ernie-image-turbo.safetensors">
  Diffusion model for ERNIE-Image-Turbo.
</Card>

<Card title="ministral-3-3b.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/resolve/main/text_encoders/ministral-3-3b.safetensors">
  Text encoder for ERNIE-Image-Turbo.
</Card>

<Card title="ernie-image-prompt-enhancer.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/resolve/main/text_encoders/ernie-image-prompt-enhancer.safetensors">
  Prompt Enhancer text encoder for ERNIE-Image-Turbo.
</Card>

<Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ERNIE-Image/resolve/main/vae/flux2-vae.safetensors">
  VAE for ERNIE-Image-Turbo.
</Card>

**Model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── ernie-image-turbo.safetensors
│   ├── 📂 text_encoders/
│   │   ├── ministral-3-3b.safetensors
│   │   └── ernie-image-prompt-enhancer.safetensors
│   └── 📂 vae/
│       └── flux2-vae.safetensors
```

## Available models

| Model             | Description                                                | Inference steps | Link                                                           |
| ----------------- | ---------------------------------------------------------- | --------------- | -------------------------------------------------------------- |
| ERNIE-Image       | Main SFT model — stronger quality and instruction fidelity | \~50            | [Hugging Face](https://huggingface.co/Baidu/ERNIE-Image)       |
| ERNIE-Image-Turbo | Turbo model optimized with DMD and RL — faster generation  | 8               | [Hugging Face](https://huggingface.co/Baidu/ERNIE-Image-Turbo) |

## Examples

### Text rendering and design layouts

![Coffee making process infographic](https://substack-post-media.s3.amazonaws.com/public/images/1cc1c3e6-e556-45b4-b6a9-205e5610d022_1360x768.png)

<Accordion title="Prompt">
  ```text theme={null}
  Educational comic book style infographic showing the coffee making process. The background has a light beige vintage paper texture. At the top center of the image is a bold brown title that reads 'The Coffee Making Process', with a smaller English subtitle 'How Coffee is Made' below. The main part consists of six step blocks connected by brown dotted arrows, arranged in two rows up and down, forming a Z-shaped visual guide.

  The first step in the upper left corner illustrates a coffee tree full of ripe red coffee cherries, with a cut coffee cherry next to it showing the beans inside, labeled 'Step 1: Harvesting Cherries' below the block.
  The second step in the upper middle shows wooden fermentation boxes filled with coffee beans, labeled 'Step 2: Pulping and Fermentation'.
  The third step in the upper right depicts coffee beans being dried under the sun on bamboo mats, labeled 'Step 3: Sun Drying'.
  The fourth step in the lower left shows a vintage metal roasting machine with coffee beans rolling inside and steam rising, labeled 'Step 4: Roasting'.
  The fifth step in the lower middle features a stone grinder pouring out smooth coffee grounds, labeled 'Step 5: Grinding'.
  The sixth step in the lower right shows a production line where coffee liquid is being poured into molds, with finished packaged coffee beside it, labeled 'Step 6: Brewing and Forming'.

  The four corners of the image are decorated with hand-drawn coffee leaves and coffee beans. The overall color palette consists of warm brown, caramel, cream, deep red and olive green, with delicate lines and clear layout.
  ```
</Accordion>

![Japanese Ukiyo-e language flashcard](https://substack-post-media.s3.amazonaws.com/public/images/913c7f5e-f1fe-4f19-b811-ad777ed430b7_768x1360.png)

<Accordion title="Prompt">
  ```text theme={null}
  Vertical rectangular language learning flashcard in traditional Japanese Ukiyo-e woodblock style. Whole card framed by dark blue traditional Seigaiha wave borders, with aged beige rough washi paper texture background.

  Upper two-thirds: Ukiyo-e illustration. A graceful spotted sika deer stands calmly in the center, with delicate black outlines and traditional flat coloring. Background: classic Japanese scenery — snow-capped Mount Fuji in distance, stylized layered clouds, falling pink cherry blossom petals. A red square antique seal with the Chinese character '鹿' in seal script at the lower right. Color scheme: indigo, vermilion, moss green, beige, with woodblock color misalignment and vintage charm.

  Lower one-third: centered text area. Top: small hiragana しか; large Japanese kanji 鹿; below it romaji shika; then English "Deer". Bottom: bilingual example — Japanese: 鹿が桜の花を見ている。English: The deer is looking at the cherry blossoms. All black text with slight brush calligraphy texture, matching Ukiyo-e antique style.
  ```
</Accordion>

![Split-screen conceptual poster](https://substack-post-media.s3.amazonaws.com/public/images/c814eef7-7df4-4f66-8889-e8325fe79dba_768x1360.png)

<Accordion title="Prompt">
  ```text theme={null}
  Split-screen conceptual poster with vertical split composition, left half representing the present and future featuring a solid stone analog clock dial with bright red hands and red scale markings, set against a deeply cracked, dry, parched earth texture in muted cool gray tones, embodying slow, static structural decay and temporal erosion, right half representing the past that is violently disintegrating, dissolving and exploding into chaotic dust, debris, flying stone shards and swirling cosmic nebula energy with a deep blood red and black color palette, the circular clock frame itself is half solid weathered stone and half crumbling into particles merging the two worlds, with the red clock hands fully positioned on the left present/future side of the dial, embodying the concept of time, past vs future, slow decay vs violent collapse, hyper-realistic 3D render with cinematic dramatic lighting, high contrast, sharp details on the left side, motion blur and dynamic particle effects on the right side, photorealistic textures of cracked earth and floating dust, atmospheric haze, futuristic graphic design with minimalist red vertical UI elements and custom technical text overlays in the corners, bold red stylized title text "ETERNAL DAWN" in the top right corner, small red technical metadata text "SPECDARY BOTHUNG" directly below the main title in the top right, dense lines of small red technical data blocks including "TIMESTAMP: 00:00:00", "COLLAPSE RATE: 99.8%", "TEMPORAL ANOMALY DETECTED", "PAST DIMENSION: DECAYING" in the bottom right corner with a red horizontal accent bar and footer text "FOR DECAY OF THE EONS" below, small red header text "TEMPORAL SHIFT PROTOCOL" with vertical red accent line running down the left edge in the top left, vertical red accent line with small red technical text annotations including "PRESENT: STABLE", "FUTURE: UNFOLDING" along it in the bottom left, red text "WARNING: TEMPORAL DISINTEGRATION" curving around the center clock dial perimeter, small red footer text "PAST FADES, FUTURE RISES" spanning the split at the bottom center, shot in the style of a high-end sci-fi movie poster, 8K ultra-high resolution, photorealistic, cinematic composition, dramatic depth, moody and intense atmosphere, detailed particle simulation, photorealistic material rendering.
  ```
</Accordion>

### Cinematic and stylized aesthetics

![Urban night street scene](https://substack-post-media.s3.amazonaws.com/public/images/d4f27467-4d1f-4f6d-8c15-ebc92983c29d_1360x768.png)

<Accordion title="Prompt">
  ```text theme={null}
  First-person vertical real-world urban night photo. Narrow, wet, busy city street with strong depth; towering buildings on both sides with fire escapes, pipes, AC units, warm window lights. Red vertical "HOTEL" neon on left, bright blue "BAR" sign and yellow "OPEN 24 HOURS" box on right. Distant huge digital billboard glowing cyan "NEON CITY". Rough wet asphalt reflects neon lights; vintage yellow taxi with "TAXI" sign drives down center, red taillights on. Two pedestrians in dark coats with black umbrellas walk away on right sidewalk. Giant needle-like steel TV tower peeks through building gaps at end, red aircraft warning light glowing. Cinematic volumetric light, misty air, cool cyan-blue vs warm orange-red contrast, immersive and realistic.
  ```
</Accordion>

![Editorial fashion photograph](https://substack-post-media.s3.amazonaws.com/public/images/3044c459-db9a-453c-88f8-32470fa2ecf9_1360x768.png)

<Accordion title="Prompt">
  ```text theme={null}
  Full-body editorial fashion shot, elegant European woman aged 28-30 with soft natural blonde hair styled in a loose low bun, wearing a tailored soft cream ribbed knit long-sleeve maxi dress with a fitted waist and flowing floor-length skirt, minimalist nude leather mules and delicate gold jewelry, standing leaning against an ornate carved stone balustrade on a gravel terrace in the garden of a grand Lake Como villa, tall iconic Italian cypress trees framing the background, calm still Lake Como water stretching out to hazy misty Alpine mountains in the distance, overcast soft diffused natural light, muted warm earthy color palette, quiet luxury aesthetic, hyper-realistic editorial fashion photography, natural skin texture with subtle pores, soft bokeh foreground foliage, shallow depth of field, shot on a medium format camera with an 85mm f/1.4 lens, sharp focus on the subject, fine film grain, muted contrast, timeless sophisticated mood, shot by Lachlan Bailey in the style of Vogue editorial, 8K ultra-high resolution, photorealistic, cinematic composition following the rule of thirds, golden hour overcast lighting, atmospheric haze, refined Italian villa garden details.
  ```
</Accordion>

![3D illustration of a duck with coffee](https://substack-post-media.s3.amazonaws.com/public/images/01abb65b-6d3e-4b08-a0b2-d0ae539f6516_1024x1024.png)

<Accordion title="Prompt">
  ```text theme={null}
  A charming, whimsical 3D illustration featuring a fluffy, plush-textured white duck sitting comfortably in a fuzzy coral-pink armchair, holding a bright red mug of steaming black coffee against a solid warm coral-red background; defined by its tactile, huggable fabric-like texture across all elements, a bold, minimalist warm color palette of creamy white, vibrant orange, and rich reds, gentle anthropomorphism that blends cuteness with relatable cozy relaxation, soft diffused lighting, and a subtle film grain that adds a nostalgic, handcrafted feel, creating a playful yet serene mood perfect for themes of calm downtime and morning routines.
  ```
</Accordion>

### Multi-panel compositions

![North American native species infographic](https://substack-post-media.s3.amazonaws.com/public/images/4e9a2968-9f7c-4b2f-92e6-b0fa9a91ede2_1360x768.png)

<Accordion title="Prompt">
  ```text theme={null}
  Educational comic book infographic. Five vertical panels side by side, earthy color palette, hand-drawn illustration style. Top title: "NORTH AMERICAN NATIVE SPECIES". Style: comic line art, watercolor fills, white panel backgrounds, bold headers.
  Panel 1: Gray squirrel holding an acorn. Header: "EASTERN GRAY SQUIRREL" Fact: "Buries acorns to help forests grow." Arrow → tail: "Bushy tail"

  Panel 2: Robin with orange-red breast on a branch. Header: "AMERICAN ROBIN" Fact: "A sign of spring returning." Arrow → breast: "Orange-red breast"

  Panel 3: Red maple tree with autumn leaves. Header: "RED MAPLE TREE" Fact: "Shelters wildlife year-round." Arrow → leaves: "Red in autumn"

  Panel 4: Deer with white tail raised. Header: "WHITE-TAILED DEER" Fact: "White tail signals danger." Arrow → tail: "Alarm signal"

  Panel 5: Monarch butterfly on a flower. Header: "MONARCH BUTTERFLY" Fact: "Migrates 3,000 miles each year." Arrow → wings: "Warning colors"
  ```
</Accordion>

![6-panel comic page](https://substack-post-media.s3.amazonaws.com/public/images/adc8fe73-f431-4bdd-8578-1a18d717d4d7_1360x768.png)

<Accordion title="Prompt">
  ```text theme={null}
  A 6-panel comic page, 2 columns × 3 rows, black border between each panel.

  Panel 1 (top-left): wide shot — a young woman in a red coat stands at a rainy train station. Caption box: "She had waited three years for this moment."
  Panel 2 (top-right): close-up on her face — anxious eyes, rain on her cheek. No text.
  Panel 3 (mid-left): medium shot — a train arrives, doors slide open, steam rising. Sound effect text: "WHOOOOSH"
  Panel 4 (mid-right): her point-of-view — a man in a gray jacket steps out, back to camera.
  Panel 5 (bottom-left): extreme close-up — her hand trembling as she reaches forward.
  Panel 6 (bottom-right): wide shot — they face each other under one umbrella. Caption box: "Some arrivals change everything."

  Ink and watercolor style, cool blue-gray palette, expressive line art. Same character design consistent across all 6 panels.
  ```
</Accordion>


# ComfyUI Native HiDream-E1, E1.1 Workflow Example
Source: https://docs.comfy.org/tutorials/image/hidream/hidream-e1

This guide will help you understand and complete the ComfyUI native HiDream-I1 text-to-image workflow example

![HiDream-E1 Demo](https://raw.githubusercontent.com/HiDream-ai/HiDream-E1/refs/heads/main/assets/demo.jpg)

HiDream-E1 is an interactive image editing large model officially open-sourced by HiDream-ai, built based on HiDream-I1.

It allows you to edit images using natural language. The model is released under the [MIT License](https://github.com/HiDream-ai/HiDream-E1?tab=MIT-1-ov-file), supporting use in personal projects, scientific research, and commercial applications.
In combination with the previously released [hidream-i1](/tutorials/image/hidream/hidream-i1), it enables **creative capabilities from image generation to editing**.

| Name            | Update Date | Inference Steps | Resolution            | HuggingFace Repository                                                  |
| --------------- | ----------- | --------------- | --------------------- | ----------------------------------------------------------------------- |
| HiDream-E1-Full | 2025-4-28   | 28              | 768x768               | 🤗 [HiDream-E1-Full](https://huggingface.co/HiDream-ai/HiDream-E1-Full) |
| HiDream-E1.1    | 2025-7-16   | 28              | Dynamic (1 Megapixel) | 🤗 [HiDream-E1.1](https://huggingface.co/HiDream-ai/HiDream-E1-1)       |

[HiDream E1 - Github](https://github.com/HiDream-ai/HiDream-E1)

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## HiDream E1 and E1.1 Workflow Related Models

All the models involved in this guide can be found [here](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/tree/main/split_files). Except for the Diffusion model, E1 and E1.1 use the same models.
The corresponding workflow files also include the relevant model information. You can choose to manually download and save the models, or follow the workflow prompts to download them after loading the workflow. It is recommended to use E1.1.

This model requires a large amount of VRAM to run. Please refer to the relevant sections for specific VRAM requirements.

**Diffusion Model**

You do not need to download both models. Since E1.1 is an iterative version based on E1, our tests show that its quality and performance are significantly improved compared to E1.

* [hidream\_e1\_1\_bf16.safetensors (Recommended)](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/resolve/main/split_files/diffusion_models/hidream_e1_1_bf16.safetensors) 34.2GB
* [hidream\_e1\_full\_bf16.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/resolve/main/split_files/diffusion_models/hidream_e1_full_bf16.safetensors) 34.2GB

**Text Encoder**:

* [clip\_l\_hidream.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/clip_l_hidream.safetensors) 236.12MB
* [clip\_g\_hidream.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/clip_g_hidream.safetensors) 1.29GB
* [t5xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/t5xxl_fp8_e4m3fn_scaled.safetensors) 4.8GB
* [llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/llama_3.1_8b_instruct_fp8_scaled.safetensors) 8.46GB

**VAE**

* [ae.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/vae/ae.safetensors) 319.77MB

> This is the VAE model for Flux. If you have used the Flux workflow before, you may have already downloaded this file.

Model Save Location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │   ├─── clip_l_hidream.safetensors
│   │   ├─── clip_g_hidream.safetensors
│   │   ├─── t5xxl_fp8_e4m3fn_scaled.safetensors
│   │   └─── llama_3.1_8b_instruct_fp8_scaled.safetensors
│   └── 📂 vae/
│   │   └── ae.safetensors
│   └── 📂 diffusion_models/
│       ├── hidream_e1_1_bf16.safetensors
│       └── hidream_e1_full_bf16.safetensors
```

## HiDream E1.1 ComfyUI Native Workflow Example

E1.1 is an updated version released on July 16, 2025. This version supports dynamic 1-megapixel resolution, and the workflow uses the `Scale Image to Total Pixels` node to dynamically adjust the input image to 1 million pixels.

<Tip>
  Here are the VRAM usage references during testing:

  1. A100 40GB (VRAM usage 95%): First generation: 211s, second generation: 73s

  2. 4090D 24GB (VRAM usage 98%)

  * Full version: Out of memory
  * FP8\_e4m3fn\_fast (VRAM 98%) First generation: 120s, second generation: 91s
</Tip>

### 1. HiDream E1.1 Workflow and Related Materials

Download the image below and drag it into ComfyUI with the corresponding workflow and models loaded:
![HiDream E1.1 Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/hidream/e1.1/hidream_e1_1.png)

Download the image below as input:
![HiDream E1.1 Workflow Input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/hidream/e1.1/input.webp)

### 2. Step-by-step Guide to Running the HiDream-e1 Workflow

<img alt="hidream_e1_1_guide" />

Follow these steps to run the workflow:

1. Make sure the `Load Diffusion Model` node loads the `hidream_e1_1_bf16.safetensors` model.
2. Make sure the four corresponding text encoders in `QuadrupleCLIPLoader` are loaded correctly:
   * clip\_l\_hidream.safetensors
   * clip\_g\_hidream.safetensors
   * t5xxl\_fp8\_e4m3fn\_scaled.safetensors
   * llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors
3. Make sure the `Load VAE` node uses the `ae.safetensors` file.
4. In the `Load Image` node, load the provided input or your desired image.
5. In the `Empty Text Encoder(Positive)` node, enter **the modifications you want to make to the image**.
6. In the `Empty Text Encoder(Negative)` node, enter **the content you do not want to appear in the image**.
7. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute image generation.

### 3. Additional Notes on the Workflow

* Since HiDream E1.1 supports dynamic input with a total of 1 million pixels, the workflow uses `Scale Image to Total Pixels` to process and convert all input images, which may cause the aspect ratio to differ from the original input image.
* When using the fp16 version of the model, in actual tests, the full version ran out of memory on both A100 40GB and 4090D 24GB, so the workflow is set by default to use `fp8_e4m3fn_fast` for inference.

## HiDream E1 ComfyUI Native Workflow Example

<a href="https://cloud.comfy.org/?template=hidream_e1_full&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

E1 is a model released on April 28, 2025. This model only supports 768\*768 resolution.

<Tip>
  For reference, this workflow takes about 500s for the first run and 370s for the second run with 28 sampling steps on Google Colab L4 with 22.5GB VRAM.
</Tip>

### 1. HiDream-e1 workflow

Please download the image below and drag it into ComfyUI. The workflow already contains model download information, and after loading, it will prompt you to download the corresponding models.

![ComfyUI Native HiDream-e1 Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hidream_e1/hidream_e1_full.png)

Download this image below as input:
![ComfyUI Native HiDream-e1 Workflow Input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hidream_e1/input.webp)

### 2. Complete the HiDream-e1 Workflow Step by Step

<img alt="hidream_e1_full_step_guide" />

Follow these steps to complete the workflow:

1. Make sure the `Load Diffusion Model` node has loaded the `hidream_e1_full_bf16.safetensors` model
2. Ensure that the four corresponding text encoders are correctly loaded in the `QuadrupleCLIPLoader`
   * clip\_l\_hidream.safetensors
   * clip\_g\_hidream.safetensors
   * t5xxl\_fp8\_e4m3fn\_scaled.safetensors
   * llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors
3. Make sure the `Load VAE` node is using the `ae.safetensors` file
4. Load the input image we downloaded earlier in the `Load Image` node
5. (Important) Enter **the prompt for how you want to modify the image** in the `Empty Text Encoder(Positive)` node
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to generate the image

### Additional Notes on ComfyUI HiDream-e1 Workflow

* You may need to modify the prompt multiple times or generate multiple times to get better results
* This model has difficulty maintaining consistency when changing image styles, so try to make your prompts as complete as possible
* As the model supports a resolution of 768\*768, in actual testing with other dimensions, the image performance is poor or even significantly different at other dimensions


# ComfyUI Native HiDream-I1 Text-to-Image Workflow Example
Source: https://docs.comfy.org/tutorials/image/hidream/hidream-i1

This guide will walk you through completing a ComfyUI native HiDream-I1 text-to-image workflow example

![HiDream-I1 Demo](https://raw.githubusercontent.com/HiDream-ai/HiDream-I1/main/assets/demo.jpg)

HiDream-I1 is a text-to-image model officially open-sourced by HiDream-ai on April 7, 2025. The model has 17B parameters and is released under the [MIT license](https://github.com/HiDream-ai/HiDream-I1/blob/main/LICENSE), supporting personal projects, scientific research, and commercial use.
It currently performs excellently in multiple benchmark tests.

## Model Features

**Hybrid Architecture Design**
A combination of Diffusion Transformer (DiT) and Mixture of Experts (MoE) architecture:

* Based on Diffusion Transformer (DiT), with dual-stream MMDiT modules processing multimodal information and single-stream DiT modules optimizing global consistency.
* Dynamic routing mechanism flexibly allocates computing resources, enhancing complex scene processing capabilities and delivering excellent performance in color restoration, edge processing, and other details.

**Multimodal Text Encoder Integration**
Integrates four text encoders:

* OpenCLIP ViT-bigG, OpenAI CLIP ViT-L (visual semantic alignment)
* T5-XXL (long text parsing)
* Llama-3.1-8B-Instruct (instruction understanding)
  This combination achieves SOTA performance in complex semantic parsing of colors, quantities, spatial relationships, etc., with Chinese prompt support significantly outperforming similar open-source models.

**Original Model Versions**

HiDream-ai provides three versions of the HiDream-I1 model to meet different needs. Below are the links to the original model repositories:

| Model Name      | Description    | Inference Steps | Repository Link                                                         |
| --------------- | -------------- | --------------- | ----------------------------------------------------------------------- |
| HiDream-I1-Full | Full version   | 50              | [🤗 HiDream-I1-Full](https://huggingface.co/HiDream-ai/HiDream-I1-Full) |
| HiDream-I1-Dev  | Distilled dev  | 28              | [🤗 HiDream-I1-Dev](https://huggingface.co/HiDream-ai/HiDream-I1-Dev)   |
| HiDream-I1-Fast | Distilled fast | 16              | [🤗 HiDream-I1-Fast](https://huggingface.co/HiDream-ai/HiDream-I1-Fast) |

## About This Workflow Example

In this example, we will use the repackaged version from ComfyOrg. You can find all the model files we'll use in this example in the [HiDream-I1\_ComfyUI](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/) repository.

<Tip>
  Before starting, please update your ComfyUI version to ensure it's at least after this [commit](https://github.com/Comfy-Org/ComfyUI/commit/9ad792f92706e2179c58b2e5348164acafa69288) to make sure your ComfyUI has native support for HiDream
</Tip>

## HiDream-I1 Workflow

The model requirements for different ComfyUI native HiDream-I1 workflows are basically the same, with only the [diffusion models](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/tree/main/split_files/diffusion_models) files being different.

If you don't know which version to choose, please refer to the following suggestions:

* **HiDream-I1-Full** can generate the highest quality images
* **HiDream-I1-Dev** balances high-quality image generation with speed
* **HiDream-I1-Fast** can generate images in just 16 steps, suitable for scenarios requiring real-time iteration

For the **dev** and **fast** versions, negative prompts are not needed, so please set the `cfg` parameter to `1.0` during sampling. We have noted the corresponding parameter settings in the relevant workflows.

<Tip>
  The full versions of all three versions require a lot of VRAM - you may need more than 27GB of VRAM to run them smoothly. In the corresponding workflow tutorials,
  we will use the **fp8** version as a demonstration example to ensure that most users can run it smoothly.
  However, we will still provide download links for different versions of the model in the corresponding examples, and you can choose the appropriate file based on your VRAM situation.
</Tip>

### Model Installation

The following model files are common files that we will use.
Please click on the corresponding links to download and save them according to the model file save location.
We will guide you to download the corresponding **diffusion models** in the corresponding workflows.

**text\_encoders**：

* [clip\_l\_hidream.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/clip_l_hidream.safetensors)
* [clip\_g\_hidream.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/clip_g_hidream.safetensors)
* [t5xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/t5xxl_fp8_e4m3fn_scaled.safetensors) This model has been used in many workflows, you may have already downloaded this file.
* [llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/text_encoders/llama_3.1_8b_instruct_fp8_scaled.safetensors)

**VAE**

* [ae.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/blob/main/split_files/vae/ae.safetensors) This is Flux's VAE model, if you have used Flux's workflow before, you may have already downloaded this file.

**diffusion models**
We will guide you to download the corresponding model files in the corresponding workflows.

Model file save location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │   ├─── clip_l_hidream.safetensors
│   │   ├─── clip_g_hidream.safetensors
│   │   ├─── t5xxl_fp8_e4m3fn_scaled.safetensors
│   │   └─── llama_3.1_8b_instruct_fp8_scaled.safetensors
│   └── 📂 vae/
│   │   └── ae.safetensors
│   └── 📂 diffusion_models/
│       └── ...               # We will guide you to install in the corresponding version workflow       
```

### HiDream-I1 Full Version Workflow

<a href="https://cloud.comfy.org/?template=hidream_i1_full&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

#### 1. Model File Download

Please select the appropriate version based on your hardware. Click the link and download the corresponding model file to save it to the `ComfyUI/models/diffusion_models/` folder.

* FP8 version: [hidream\_i1\_full\_fp8.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/resolve/main/split_files/diffusion_models/hidream_i1_full_fp8.safetensors?download=true) requires more than 16GB of VRAM
* Full version: [hidream\_i1\_full\_f16.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/resolve/main/split_files/diffusion_models/hidream_i1_full_fp16.safetensors?download=true) requires more than 27GB of VRAM

#### 2. Workflow File Download

Please download the image below and drag it into ComfyUI to load the corresponding workflow
![HiDream-I1 Full Version Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hidream_i1/hidream_i1_full.png)

#### 3. Complete the Workflow Step by Step

<img alt="HiDream-I1 Full Version Flow Diagram" />

Complete the workflow execution step by step

1. Make sure the `Load Diffusion Model` node is using the `hidream_i1_full_fp8.safetensors` file
2. Make sure the four corresponding text encoders in `QuadrupleCLIPLoader` are loaded correctly
   * clip\_l\_hidream.safetensors
   * clip\_g\_hidream.safetensors
   * t5xxl\_fp8\_e4m3fn\_scaled.safetensors
   * llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors
3. Make sure the `Load VAE` node is using the `ae.safetensors` file
4. For the **full** version, you need to set the `shift` parameter in `ModelSamplingSD3` to `3.0`
5. For the `Ksampler` node, you need to make the following settings
   * Set `steps` to `50`
   * Set `cfg` to `5.0`
   * (Optional) Set `sampler` to `lcm`
   * (Optional) Set `scheduler` to `normal`
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

### HiDream-I1 Dev Version Workflow

<a href="https://cloud.comfy.org/?template=hidream_i1_dev&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

#### 1. Model File Download

Please select the appropriate version based on your hardware, click the link and download the corresponding model file to save to the `ComfyUI/models/diffusion_models/` folder.

* FP8 version: [hidream\_i1\_dev\_fp8.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/resolve/main/split_files/diffusion_models/hidream_i1_dev_fp8.safetensors?download=true) requires more than 16GB of VRAM
* Full version: [hidream\_i1\_dev\_bf16.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/resolve/main/split_files/diffusion_models/hidream_i1_dev_bf16.safetensors?download=true) requires more than 27GB of VRAM

#### 2. Workflow File Download

Please download the image below and drag it into ComfyUI to load the corresponding workflow

![HiDream-I1 Dev Version Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hidream_i1/hidream_i1_dev.png)

#### 3. Complete the Workflow Step by Step

<img alt="HiDream-I1 Dev Version Flow Diagram" />

Complete the workflow execution step by step

1. Make sure the `Load Diffusion Model` node is using the `hidream_i1_dev_fp8.safetensors` file
2. Make sure the four corresponding text encoders in `QuadrupleCLIPLoader` are loaded correctly
   * clip\_l\_hidream.safetensors
   * clip\_g\_hidream.safetensors
   * t5xxl\_fp8\_e4m3fn\_scaled.safetensors
   * llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors
3. Make sure the `Load VAE` node is using the `ae.safetensors` file
4. For the **dev** version, you need to set the `shift` parameter in `ModelSamplingSD3` to `6.0`
5. For the `Ksampler` node, you need to make the following settings
   * Set `steps` to `28`
   * (Important) Set `cfg` to `1.0`
   * (Optional) Set `sampler` to `lcm`
   * (Optional) Set `scheduler` to `normal`
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

### HiDream-I1 Fast Version Workflow

<a href="https://cloud.comfy.org/?template=hidream_i1_fast&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

#### 1. Model File Download

Please select the appropriate version based on your hardware, click the link and download the corresponding model file to save to the `ComfyUI/models/diffusion_models/` folder.

* FP8 version: [hidream\_i1\_fast\_fp8.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/resolve/main/split_files/diffusion_models/hidream_i1_fast_fp8.safetensors?download=true) requires more than 16GB of VRAM
* Full version: [hidream\_i1\_fast\_bf16.safetensors](https://huggingface.co/Comfy-Org/HiDream-I1_ComfyUI/resolve/main/split_files/diffusion_models/hidream_i1_fast_bf16.safetensors?download=true) requires more than 27GB of VRAM

#### 2. Workflow File Download

Please download the image below and drag it into ComfyUI to load the corresponding workflow

![HiDream-I1 Fast Version Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hidream_i1/hidream_i1_fast.png)

#### 3. Complete the Workflow Step by Step

<img alt="HiDream-I1 Fast Version Flow Diagram" />

Complete the workflow execution step by step

1. Make sure the `Load Diffusion Model` node is using the `hidream_i1_fast_fp8.safetensors` file
2. Make sure the four corresponding text encoders in `QuadrupleCLIPLoader` are loaded correctly
   * clip\_l\_hidream.safetensors
   * clip\_g\_hidream.safetensors
   * t5xxl\_fp8\_e4m3fn\_scaled.safetensors
   * llama\_3.1\_8b\_instruct\_fp8\_scaled.safetensors
3. Make sure the `Load VAE` node is using the `ae.safetensors` file
4. For the **fast** version, you need to set the `shift` parameter in `ModelSamplingSD3` to `3.0`
5. For the `Ksampler` node, you need to make the following settings
   * Set `steps` to `16`
   * (Important) Set `cfg` to `1.0`
   * (Optional) Set `sampler` to `lcm`
   * (Optional) Set `scheduler` to `normal`
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation

## Other Related Resources

### GGUF Version Models

* [HiDream-I1-Full-gguf](https://huggingface.co/city96/HiDream-I1-Full-gguf)
* [HiDream-I1-Dev-gguf](https://huggingface.co/city96/HiDream-I1-Dev-gguf)

You need to use the “Unet Loader (GGUF)” node in City96's [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) to replace the “Load Diffusion Model” node.

### NF4 Version Models

* [HiDream-I1-nf4](https://github.com/hykilpikonna/HiDream-I1-nf4)
* Use the [ComfyUI-HiDream-Sampler](https://github.com/SanDiegoDude/ComfyUI-HiDream-Sampler) node to use the NF4 version model.


# ComfyUI Native HiDream-O1-Image Workflow Example
Source: https://docs.comfy.org/tutorials/image/hidream/hidream-o1

This guide walks you through the ComfyUI native HiDream-O1-Image text-to-image and image editing workflows

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

![HiDream-O1-Image Demo](https://raw.githubusercontent.com/HiDream-ai/HiDream-O1-Image/main/assets/general.webp)

HiDream-O1-Image is a unified image generative foundation model open-sourced by HiDream-ai on May 8, 2026. Built on a Pixel-level Unified Transformer (UiT), it operates without external VAEs or disjoint text encoders, supporting **text-to-image**, **instruction-based image editing**, **subject-driven personalization**, and **storyboard generation** at up to 2,048 × 2,048 resolution.

HiDream-O1-Image is released under the [MIT License](https://github.com/HiDream-ai/HiDream-O1-Image?tab=MIT-1-ov-file) and natively supported in ComfyUI (PR [#13817](https://github.com/Comfy-Org/ComfyUI/pull/13817)).

[HiDream-O1-Image - GitHub](https://github.com/HiDream-ai/HiDream-O1-Image)

### Model Versions

| Model                   | Inference Steps | Repository                                                                        |
| ----------------------- | --------------- | --------------------------------------------------------------------------------- |
| HiDream-O1-Image (Full) | 50              | [🤗 HiDream-O1-Image](https://huggingface.co/HiDream-ai/HiDream-O1-Image)         |
| HiDream-O1-Image-Dev    | 28              | [🤗 HiDream-O1-Image-Dev](https://huggingface.co/HiDream-ai/HiDream-O1-Image-Dev) |

## HiDream-O1-Image Full Workflow

### 1. Download Workflow

Update your ComfyUI to the latest version, then go to `Workflow` -> `Browse Templates` -> `Image` and find "HiDream O1 Full: Image generation".

![HiDream-O1-Image Full Workflow](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_hidream_o1.png)

<Card title="Download JSON Workflow File" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_hidream_o1.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_hidream_o1&utm_source=docs">
  Open in cloud
</Card>

### 2. Download Models

**Checkpoint** — re-packaged and quantized. All use bf16 for worst outliers, unused deepstack layers removed:

* [hidream\_o1\_image\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/resolve/main/checkpoints/hidream_o1_image_fp8_scaled.safetensors) — FP8, uses fp8/mxfp8 matmuls on safe MLP layers for speedup on supported hardware
* [hidream\_o1\_image\_mxfp8.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/resolve/main/checkpoints/hidream_o1_image_mxfp8.safetensors) — MXFP8 quantized variant
* [hidream\_o1\_image\_bf16.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/resolve/main/checkpoints/hidream_o1_image_bf16.safetensors) — Full bf16 precision (largest)

**Text Encoder** (prompt enhancement) — shared across all versions:

* [gemma4\_e4b\_it\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/gemma-4/resolve/main/text_encoders/gemma4_e4b_it_fp8_scaled.safetensors)

**LoRA (optional)** — the Dev distillation can also be applied to the Full model as a LoRA, allowing you to adjust the distillation strength (by [Kijai](https://huggingface.co/Kijai/hidream-O1-image_comfy)):

* [hidream\_o1\_dev\_lora\_rank\_64\_bf16.safetensors](https://huggingface.co/Kijai/hidream-O1-image_comfy/resolve/main/loras/hidream_o1_dev_lora_rank_64_bf16.safetensors) — Full rank
* [hidream\_o1\_dev\_lora\_rank\_64\_bf16\_pruned\_v1.safetensors](https://huggingface.co/Kijai/hidream-O1-image_comfy/resolve/main/loras/hidream_o1_dev_lora_rank_64_bf16_pruned_v1.safetensors) — Pruned variant
* [hidream\_o1\_image\_dev\_2604\_lora\_avg\_rankg\_224\_bf16.safetensors](https://huggingface.co/Kijai/hidream-O1-image_comfy/resolve/main/loras/hidream_o1_image_dev_2604_lora_avg_rankg_224_bf16.safetensors) — Alternative checkpoint-based distillation

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   ├── hidream_o1_image_fp8_scaled.safetensors
│   │   ├── hidream_o1_image_mxfp8.safetensors
│   │   └── hidream_o1_image_bf16.safetensors
│   ├── 📂 loras/
│   │   └── hidream_o1_dev_lora_rank_64_bf16.safetensors
│   └── 📂 text_encoders/
│       └── gemma4_e4b_it_fp8_scaled.safetensors
```

### 3. Using the Workflow

* Make sure `CheckpointLoaderSimple` loads your chosen checkpoint
* Enter your prompt in the `CLIPTextEncode` node
* **Text-to-Image mode:** set the **"Switch to Image Edit"** toggle to **off** (default). The sampler will use your text prompt directly.
* **Image Edit mode:** set **"Switch to Image Edit"** to **on**, then upload a reference image in the `Load Image` node and connect it to `HiDreamO1ReferenceImages`.

> **Note:** The O1 sampler outputs latent samples that need to be decoded through a `VAEDecode` node using the VAE loaded by `CheckpointLoaderSimple`.

## HiDream-O1-Image Dev Workflow

### 1. Download Workflow

Go to `Workflow` -> `Browse Templates` -> `Image` and find "HiDream O1 Dev".

![HiDream-O1-Image Dev Workflow](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_hidream_o1_dev.png)

<Card title="Download JSON Workflow File" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_hidream_o1_dev.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_hidream_o1_dev&utm_source=docs">
  Open in cloud
</Card>

### 2. Download Models

**Checkpoint (Dev)** — re-packaged and quantized. All use bf16 for worst outliers, unused deepstack layers removed:

* [hidream\_o1\_image\_dev\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/resolve/main/checkpoints/hidream_o1_image_dev_fp8_scaled.safetensors) — FP8, uses fp8/mxfp8 matmuls on safe MLP layers for speedup on supported hardware
* [hidream\_o1\_image\_dev\_mxfp8.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/resolve/main/checkpoints/hidream_o1_image_dev_mxfp8.safetensors) — MXFP8 quantized variant
* [hidream\_o1\_image\_dev\_bf16.safetensors](https://huggingface.co/Comfy-Org/HiDream-O1-Image/resolve/main/checkpoints/hidream_o1_image_dev_bf16.safetensors) — Full bf16 precision (largest)

**Text Encoder** (prompt enhancement) — shared across all versions:

* [gemma4\_e4b\_it\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/gemma-4/resolve/main/text_encoders/gemma4_e4b_it_fp8_scaled.safetensors)

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   ├── hidream_o1_image_dev_fp8_scaled.safetensors
│   │   ├── hidream_o1_image_dev_mxfp8.safetensors
│   │   └── hidream_o1_image_dev_bf16.safetensors
│   └── 📂 text_encoders/
│       └── gemma4_e4b_it_fp8_scaled.safetensors
```

### 3. Using the Workflow

* Make sure `CheckpointLoaderSimple` loads `hidream_o1_image_dev_fp8_scaled.safetensors`
* The Dev version uses 28 steps with CFG=1.0 — no negative prompt needed
* **Text-to-Image mode:** set the **"Switch to Image Edit"** toggle to **off** (default)
* **Image Edit mode:** set **"Switch to Image Edit"** to **on**, upload a reference image in `Load Image`, and connect it to `HiDreamO1ReferenceImages`

## Additional Notes

* **Long Text Rendering:** HiDream-O1-Image excels at rendering text within images. Specify text content, font style, color, and positioning in your prompt for best results.

  ![Long-Text Rendering & Layout Control](https://raw.githubusercontent.com/HiDream-ai/HiDream-O1-Image/main/assets/text-layout.webp)

* **Image Scaling:** If your input reference image is too large, enable the `ImageScaleToTotalPixels` node (Ctrl+B) to scale it to 4MP.

* **Patch Seam Smoothing (Experimental):** The `HiDreamO1PatchSeamSmoothing` node reduces visible seam artifacts during sampling. Enabled by default in the Full workflow.


# ComfyUI Ideogram 4.0 Open-Source Model Tutorial
Source: https://docs.comfy.org/tutorials/image/ideogram/ideogram-v4

Learn how to use the Ideogram 4.0 open-source model in ComfyUI

Ideogram 4.0 is the latest text-to-image model from Ideogram, released as an open-source model that runs entirely on your own hardware. It delivers superior photorealistic quality, accurate text rendering, and precise style control. You can use either plain natural language or **structured JSON prompts** for fine-grained control over layout, colors, and in-image text.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Ideogram 4.0 Text-to-Image Workflow

<Card title="Run in Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_ideogram4_t2i&utm_source=docs&utm_medium=referral&utm_campaign=ideogram-v4">
  Open in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_ideogram4_t2i.json">
  Download JSON or search "Ideogram v4: Text to Image" in Template Library
</Card>

![Ideogram 4.0 Example Output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/image_ideogram4_t2i.png)
*Example output from the Ideogram 4.0 model*

### Prompt Format

The open-source workflow supports two prompt modes:

1. **Natural language** — Quick and easy, best for simple ideas
2. **Structured JSON** — For precise control over layout, colors, and style

The workflow includes a prompt construction template that you can use with any LLM to generate matching JSON prompts.

A note inside the workflow explains:

> The model is trained on structured JSON captions (scene summary, style block, background, and optional per-object descriptions with bounding boxes and hex color palettes). Official inference validates prompts against that schema.

### Ideogram 4.0 model downloads

You can find all repackaged model files at [Comfy-Org/Ideogram-4](https://huggingface.co/Comfy-Org/Ideogram-4) on Hugging Face.

<Card title="ideogram4_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Ideogram-4/resolve/main/diffusion_models/ideogram4_fp8_scaled.safetensors">
  Diffusion model for Ideogram 4.0 (\~13.8 GB). Place in <code>models/diffusion\_models/</code>
</Card>

<Card title="ideogram4_unconditional_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Ideogram-4/resolve/main/diffusion_models/ideogram4_unconditional_fp8_scaled.safetensors">
  Unconditional diffusion model for Ideogram 4.0 (\~13.8 GB). Place in <code>models/diffusion\_models/</code>
</Card>

<Card title="qwen3vl_8b_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3-VL/resolve/main/text_encoders/qwen3vl_8b_fp8_scaled.safetensors">
  Text encoder for Ideogram 4.0 (\~8 GB). Place in <code>models/text\_encoders/</code>
</Card>

<Card title="gemma4_e4b_it_fp8_scaled.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/gemma-4/resolve/main/text_encoders/gemma4_e4b_it_fp8_scaled.safetensors">
  Text encoder for Ideogram 4.0 (\~2 GB). Place in <code>models/text\_encoders/</code>
</Card>

<Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/flux2-dev/resolve/main/split_files/vae/flux2-vae.safetensors">
  VAE for Ideogram 4.0 (\~335 MB). Place in <code>models/vae/</code>
</Card>

**Model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── ideogram4_fp8_scaled.safetensors
│   │   └── ideogram4_unconditional_fp8_scaled.safetensors
│   ├── 📂 text_encoders/
│   │   ├── qwen3vl_8b_fp8_scaled.safetensors
│   │   └── gemma4_e4b_it_fp8_scaled.safetensors
│   └── 📂 vae/
│       └── flux2-vae.safetensors
```

<CardGroup>
  <Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
    This workflow uses Subgraph nodes for modular processing. Check the Subgraph documentation to learn how to customize and extend.
  </Card>
</CardGroup>

### Workflow Steps

1. Download and place the models in the correct directories (see table above)
2. Download and drag the workflow file into ComfyUI
3. Enter your prompt (natural language or structured JSON) in the Ideogram4 subgraph node
4. (Optional) Adjust resolution using the `ResolutionSelector` node
5. Click `Run` or use shortcut `Ctrl(cmd) + Enter` to generate the image
6. View the result in the `Save Image` node — output files are saved to `ComfyUI/output/`

### Note on Safety Filter

If you see "Image blocked by safety filter", this is due to safety training baked into the model itself. ComfyUI does not add any safety filters. Try adjusting your prompt to avoid triggering the built-in safety mechanisms.


# Lens ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/image/lens/lens

Lens is a 3.8B parameter text-to-image model by Microsoft, using dual-stream MMDiT with GPT-OSS-20B text features and FLUX.2 VAE for efficient, high-resolution generation.

**Lens** is an open text-to-image model by **Microsoft**, licensed under MIT. With **3.8 billion** parameters, it uses a **dual-stream MMDiT** architecture with **GPT-OSS-20B** text encoder features and the **FLUX.2 semantic VAE** to deliver competitive image quality with substantially less training compute than larger T2I models.

**Model highlights**:

* **Dual-stream MMDiT architecture** — joint image-text processing for coherent generation
* **GPT-OSS-20B multi-layer text features** — rich text understanding for accurate prompt following
* **FLUX.2 semantic VAE** — high-fidelity latent representation
* **Mixed-resolution training** — supports various aspect ratios without cropping
* **Compact 3.8B footprint** — runs on consumer GPUs with 24 GB VRAM

**Related links**:

* [Paper (arXiv)](https://arxiv.org/abs/2605.21573)
* [GitHub](https://github.com/microsoft/Lens)
* [Hugging Face (Microsoft)](https://huggingface.co/microsoft/Lens)
* [Hugging Face (Comfy-Org)](https://huggingface.co/Comfy-Org/Lens)

## Lens text-to-image workflow

Both the standard and Turbo variants use a **Subgraph** node to manage the text-to-image generation pipeline. You can open the subgraph to inspect or customize the internal nodes.

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

### Lens

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_lens_t2i.json">
    Download JSON or search "Lens" in Template Library
  </Card>
</CardGroup>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

#### Get started

1. Update ComfyUI to the latest version
2. Go to **Template** and search for **Lens**
3. Select the **Lens** workflow
4. Download any missing models (see [model downloads](#lens-model-downloads)), enter your prompt, and click **Queue**

#### Example output

<img alt="Lens text-to-image example output" />

### Lens Turbo

Lens Turbo is a distilled variant that generates images in fewer sampling steps for faster inference.

<CardGroup>
  <Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_lens_turbo_t2i.json">
    Download JSON or search "Lens Turbo" in Template Library
  </Card>
</CardGroup>

#### Get started

1. Update ComfyUI to the latest version
2. Go to **Template** and search for **Lens Turbo**
3. Select the **Lens Turbo** workflow
4. Download any missing models (see [model downloads](#lens-model-downloads)), enter your prompt, and click **Queue**

#### Example output

<img alt="Lens Turbo text-to-image example output" />

## Lens model downloads

You can find all model files at [Comfy-Org/Lens](https://huggingface.co/Comfy-Org/Lens) on Hugging Face.

<CardGroup>
  <Card title="lens_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Lens/resolve/main/diffusion_models/lens_bf16.safetensors">
    Diffusion model for Lens (BF16).
  </Card>

  <Card title="lens_turbo_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Lens/resolve/main/diffusion_models/lens_turbo_bf16.safetensors">
    Diffusion model for Lens Turbo (BF16).
  </Card>
</CardGroup>

<CardGroup>
  <Card title="gpt_oss_20b_nvfp4.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Lens/resolve/main/text_encoders/gpt_oss_20b_nvfp4.safetensors">
    Text encoder (GPT-OSS-20B) shared by both Lens and Lens Turbo.
  </Card>

  <Card title="flux2-vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Lens/resolve/main/vae/flux2-vae.safetensors">
    VAE (FLUX.2) shared by both Lens and Lens Turbo.
  </Card>
</CardGroup>

**Model storage location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── lens_bf16.safetensors (or lens_mxfp8.safetensors)
│   │   └── lens_turbo_bf16.safetensors (or lens_turbo_mxfp8.safetensors)
│   ├── 📂 text_encoders/
│   │   └── gpt_oss_20b_nvfp4.safetensors
│   └── 📂 vae/
│       └── flux2-vae.safetensors
```

## Available models

| Model      | Description                                            | Inference steps | Link                                                  |
| ---------- | ------------------------------------------------------ | --------------- | ----------------------------------------------------- |
| Lens       | Standard 3.8B model — higher quality, more steps       | \~50            | [Hugging Face](https://huggingface.co/microsoft/Lens) |
| Lens Turbo | Distilled variant — faster generation with fewer steps | \~8             | [Hugging Face](https://huggingface.co/microsoft/Lens) |


# ComfyUI NewBie-image-Exp0.1 Workflow Example
Source: https://docs.comfy.org/tutorials/image/newbie-image/newbie-image-exp-0-1

NewBie-image-Exp0.1 is a 3.5B parameter anime-style text-to-image generation model based on Next-DiT architecture, optimized for high-quality anime image generation with XML structured prompts.

**NewBie-image-Exp0.1** is a 3.5B parameter DiT model developed by NewBieAI Lab for anime-style text-to-image generation. Built on the Next-DiT architecture, it delivers remarkably detailed and visually striking anime images.

**Key Features**:

* **3.5B Parameter Model**: Efficient yet powerful model size for high-quality anime generation
* **Next-DiT Architecture**: Based on research from the Lumina architecture with a newly designed NewBie architecture
* **Dual Text Encoders**: Uses Gemma3-4B-it as primary encoder with Jina CLIP v2 for improved prompt understanding
* **FLUX VAE**: Utilizes FLUX.1-dev 16-channel VAE for richer colors and finer texture details
* **XML Structured Prompts**: Supports XML format for better attention binding and attribute disentanglement

**Related Links**:

* [GitHub](https://github.com/NewBieAI-Lab/NewBie-image-Exp0.1)
* [Hugging Face](https://huggingface.co/NewBie-AI/NewBie-image-Exp0.1)
* [Getting Started Guide](https://ai.feishu.cn/wiki/NZl9wm7V1iuNzmkRKCUcb1USnsh)

## NewBie-image text-to-image workflow

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_newbieimage_exp0_1-t2i.json">
  <p>Download JSON Workflow File</p>
</a>

<a href="https://cloud.comfy.org/?template=image_newbieimage_exp0_1-t2i&utm_source=docs">
  <p>Run on ComfyUI Cloud</p>
</a>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model links

**text\_encoders**

* [gemma\_3\_4b\_it\_bf16.safetensors](https://huggingface.co/Comfy-Org/NewBie-image-Exp0.1_repackaged/resolve/main/split_files/text_encoders/gemma_3_4b_it_bf16.safetensors)
* [jina\_clip\_v2\_bf16.safetensors](https://huggingface.co/Comfy-Org/NewBie-image-Exp0.1_repackaged/resolve/main/split_files/text_encoders/jina_clip_v2_bf16.safetensors)

**diffusion\_models**

* [NewBie-Image-Exp0.1-bf16.safetensors](https://huggingface.co/Comfy-Org/NewBie-image-Exp0.1_repackaged/resolve/main/split_files/diffusion_models/NewBie-Image-Exp0.1-bf16.safetensors)

**vae**

* [ae.safetensors](https://huggingface.co/Comfy-Org/z_image_turbo/resolve/main/split_files/vae/ae.safetensors)

**Model Storage Location**

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │      ├── gemma_3_4b_it_bf16.safetensors
│   │      └── jina_clip_v2_bf16.safetensors
│   ├── diffusion_models/
│   │      └── NewBie-Image-Exp0.1-bf16.safetensors
│   └── vae/
│          └── ae.safetensors
```

## Prompt format

NewBie-image is an anime image generation model optimized for character generation. It uses XML structured prompts for training, where each `<>` tag defines a category (like `<appearance>`, `<clothing>`) and `</>` closes it. The tags inside are standard Danbooru tags. This structure enables precise control over multi-character scenes with better attribute binding.

For the complete prompt writing guide, see the [official documentation](https://ai.feishu.cn/wiki/NZl9wm7V1iuNzmkRKCUcb1USnsh).

NewBie-image-Exp0.1 supports three prompt formats:

* **Natural language**: Standard text descriptions
* **Tags**: Danbooru-style tags
* **XML structured format**: Recommended for multi-character scenes

### XML structured prompt

For multi-character scenes, using XML structured prompts typically leads to more accurate image generation results with better attention binding and attribute disentanglement.

```xml theme={null}
<character_1>
<n>$character_1$</n>
<gender>1girl</gender>
<appearance>chibi, red_eyes, blue_hair, long_hair, hair_between_eyes, head_tilt, tareme, closed_mouth</appearance>
<clothing>school_uniform, serafuku, white_sailor_collar, white_shirt, short_sleeves, red_neckerchief, bow, blue_skirt, miniskirt, pleated_skirt, blue_hat, mini_hat, thighhighs, grey_thighhighs, black_shoes, mary_janes</clothing>
<expression>happy, smile</expression>
<action>standing, holding, holding_briefcase</action>
<position>center_left</position>
</character_1>

<character_2>
<n>$character_2$</n>
<gender>1girl</gender>
<appearance>chibi, red_eyes, pink_hair, long_hair, very_long_hair, multi-tied_hair, open_mouth</appearance>
<clothing>school_uniform, serafuku, white_sailor_collar, white_shirt, short_sleeves, red_neckerchief, bow, red_skirt, miniskirt, pleated_skirt, hair_bow, multiple_hair_bows, white_bow, ribbon_trim, ribbon-trimmed_bow, white_thighhighs, black_shoes, mary_janes, bow_legwear, bare_arms</clothing>
<expression>happy, smile</expression>
<action>standing, holding, holding_briefcase, waving</action>
<position>center_right</position>
</character_2>

<general_tags>
<count>2girls, multiple_girls</count>
<style>anime_style, digital_art</style>
<background>white_background, simple_background</background>
<atmosphere>cheerful</atmosphere>
<quality>high_resolution, detailed</quality>
<objects>briefcase</objects>
<other>alternate_costume</other>
</general_tags>
```

### XML tag reference

| Tag            | Description                               |
| -------------- | ----------------------------------------- |
| `<n>`          | Character name/identifier                 |
| `<gender>`     | Character gender (1girl, 1boy, etc.)      |
| `<appearance>` | Physical features (hair, eyes, body type) |
| `<clothing>`   | Outfit and accessories                    |
| `<expression>` | Facial expression                         |
| `<action>`     | Pose and actions                          |
| `<position>`   | Position in the image                     |
| `<count>`      | Number of characters                      |
| `<style>`      | Art style                                 |
| `<background>` | Background description                    |
| `<atmosphere>` | Overall mood                              |
| `<quality>`    | Quality tags                              |
| `<objects>`    | Objects in the scene                      |
| `<other>`      | Additional tags                           |


# ComfyUI OmniGen2 Native Workflow Examples
Source: https://docs.comfy.org/tutorials/image/omnigen/omnigen2

ComfyUI OmniGen2 Native Workflow Examples - Unified text-to-image, image editing, and multi-image composition model.

## About OmniGen2

OmniGen2 is a powerful and efficient unified multimodal generation model with approximately **7B** total parameters (3B text model + 4B image generation model). Unlike OmniGen v1, OmniGen2 adopts an innovative dual-path Transformer architecture with completely independent text autoregressive model and image diffusion model, achieving parameter decoupling and specialized optimization.

### Model Highlights

* **Visual Understanding**: Inherits the powerful image content interpretation and analysis capabilities of the Qwen-VL-2.5 foundation model
* **Text-to-Image Generation**: Creates high-fidelity and aesthetically pleasing images from text prompts
* **Instruction-guided Image Editing**: Performs complex, instruction-based image modifications, achieving state-of-the-art performance among open-source models
* **Contextual Generation**: Versatile capabilities to process and flexibly combine diverse inputs (including people, reference objects, and scenes), producing novel and coherent visual outputs

### Technical Features

* **Dual-path Architecture**: Based on Qwen 2.5 VL (3B) text encoder + independent diffusion Transformer (4B)
* **Omni-RoPE Position Encoding**: Supports multi-image spatial positioning and identity distinction
* **Parameter Decoupling Design**: Avoids negative impact of text generation on image quality
* Support for complex text understanding and image understanding
* Controllable image generation and editing
* Excellent detail preservation capabilities
* Unified architecture supporting multiple image generation tasks
* Text generation capability: Can generate clear text content within images

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## OmniGen2 Model Download

Since this article involves different workflows, the corresponding model files and installation locations are as follows. The download information for model files is also included in the corresponding workflows:

**Diffusion Models**

* [omnigen2\_fp16.safetensors](https://huggingface.co/Comfy-Org/Omnigen2_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/omnigen2_fp16.safetensors)

**VAE**

* [ae.safetensors](https://huggingface.co/Comfy-Org/Lumina_Image_2.0_Repackaged/resolve/main/split_files/vae/ae.safetensors)

**Text Encoders**

* [qwen\_2.5\_vl\_fp16.safetensors](https://huggingface.co/Comfy-Org/Omnigen2_ComfyUI_repackaged/resolve/main/split_files/text_encoders/qwen_2.5_vl_fp16.safetensors)

File save location:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── omnigen2_fp16.safetensors
│   ├── 📂 vae/
│   │   └── ae.safetensors
│   └── 📂 text_encoders/
│       └── qwen_2.5_vl_fp16.safetensors
```

## ComfyUI OmniGen2 Text-to-Image Workflow

### 1. Download Workflow File

<a href="https://cloud.comfy.org/?template=image_omnigen2_t2i&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

![Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/image/omnigen2/image_omnigen2_t2i.png)

### 2. Complete Workflow Step by Step

<img alt="Workflow Step Guide" />

Please follow the numbered steps in the image for step-by-step confirmation to ensure smooth operation of the corresponding workflow:

1. **Load Main Model**: Ensure the `Load Diffusion Model` node loads `omnigen2_fp16.safetensors`
2. **Load Text Encoder**: Ensure the `Load CLIP` node loads `qwen_2.5_vl_fp16.safetensors`
3. **Load VAE**: Ensure the `Load VAE` node loads `ae.safetensors`
4. **Set Image Dimensions**: Set the generated image dimensions in the `EmptySD3LatentImage` node (recommended 1024x1024)
5. **Input Prompts**:
   * Input positive prompts in the first `CLipTextEncode` node (content you want to appear in the image)
   * Input negative prompts in the second `CLipTextEncode` node (content you don't want to appear in the image)
6. **Start Generation**: Click the `Queue Prompt` button, or use the shortcut `Ctrl(cmd) + Enter` to execute text-to-image generation
7. **View Results**: After generation is complete, the corresponding images will be automatically saved to the `ComfyUI/output/` directory, and you can also preview them in the `SaveImage` node

## ComfyUI OmniGen2 Image Editing Workflow

OmniGen2 has rich image editing capabilities and supports adding text to images

### 1. Download Workflow File

<a href="https://cloud.comfy.org/?template=image_omnigen2_image_edit&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

![Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/image/omnigen2/image_omnigen2_image_edit.png)

Download the image below, which we will use as the input image.
![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/image/omnigen2/input_fairy.png)

### 2. Complete Workflow Step by Step

<img alt="Workflow Step Guide" />

1. **Load Main Model**: Ensure the `Load Diffusion Model` node loads `omnigen2_fp16.safetensors`
2. **Load Text Encoder**: Ensure the `Load CLIP` node loads `qwen_2.5_vl_fp16.safetensors`
3. **Load VAE**: Ensure the `Load VAE` node loads `ae.safetensors`
4. **Upload Image**: Upload the provided image in the `Load Image` node
5. **Input Prompts**:
   * Input positive prompts in the first `CLipTextEncode` node (content you want to appear in the image)
   * Input negative prompts in the second `CLipTextEncode` node (content you don't want to appear in the image)
6. **Start Generation**: Click the `Queue Prompt` button, or use the shortcut `Ctrl(cmd) + Enter` to execute text-to-image generation
7. **View Results**: After generation is complete, the corresponding images will be automatically saved to the `ComfyUI/output/` directory, and you can also preview them in the `SaveImage` node

### 3. Additional Workflow Instructions

* If you want to enable the second image input, you can use the shortcut **Ctrl + B** to enable the corresponding node inputs for nodes that are in pink/purple state in the workflow
* If you want to customize dimensions, you can delete the `Get image size` node linked to the `EmptySD3LatentImage` node and input custom dimensions


# Ovis-Image ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/ovis/ovis-image

Ovis-Image is a 7B text-to-image model specifically optimized for high-quality text rendering, designed to operate efficiently under stringent computational constraints.

**Ovis-Image** is a 7B text-to-image model built upon [Ovis-U1](https://github.com/AIDC-AI/Ovis-U1), specifically optimized for high-quality text rendering. It delivers text rendering quality comparable to much larger 20B-class systems while remaining compact enough to run on widely accessible hardware.

**Model Highlights**:

* **Strong Text Rendering at 7B Scale**: Delivers text rendering quality comparable to much larger 20B-class systems like Qwen-Image and competitive with leading closed-source models like GPT4o in text-centric scenarios
* **High Fidelity on Text-Heavy Prompts**: Excels on prompts that demand tight alignment between linguistic content and rendered typography (e.g., posters, banners, logos, UI mockups, infographics)
* **Accurate Bilingual Text Rendering**: Produces legible, correctly spelled, and semantically consistent text in both Chinese and English across diverse fonts, sizes, and aspect ratios
* **Efficiency and Deployability**: Fits on a single high-end GPU with moderate memory, supports low-latency interactive use

**Related Links**:

* [GitHub](https://github.com/AIDC-AI/Ovis-Image)
* [Hugging Face](https://huggingface.co/AIDC-AI/Ovis-Image-7B)

## Ovis-Image text-to-image workflow

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_ovis_text_to_image.json">
  <p>Download JSON Workflow File</p>
</a>

<a href="https://cloud.comfy.org/?template=image_ovis_text_to_image&utm_source=docs">
  <p>Run on ComfyUI Cloud</p>
</a>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model links

**text\_encoders**

* [ovis\_2.5.safetensors](https://huggingface.co/Comfy-Org/Ovis-Image/resolve/main/split_files/text_encoders/ovis_2.5.safetensors)

**diffusion\_models**

* [ovis\_image\_bf16.safetensors](https://huggingface.co/Comfy-Org/Ovis-Image/resolve/main/split_files/diffusion_models/ovis_image_bf16.safetensors)

**vae**

* [ae.safetensors](https://huggingface.co/Comfy-Org/z_image_turbo/resolve/main/split_files/vae/ae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── ovis_2.5.safetensors
│   ├── 📂 diffusion_models/
│   │      └── ovis_image_bf16.safetensors
│   └── 📂 vae/
│          └── ae.safetensors
```


# PixelDiT ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/pixeldit/pixeldit

PixelDiT is NVIDIA's pixel-space diffusion transformer for 1024px text-to-image generation. It operates directly in pixel space — no VAE encode/decode required.

**PixelDiT** is NVIDIA's pixel-space diffusion transformer for 1024px text-to-image generation. Unlike traditional diffusion models that operate in latent space, PixelDiT generates images directly in pixel space using a dual-level DiT architecture — a patch-level DiT combined with a pixel-level DiT — with MM-DiT fusion for joint attention between text and image tokens.

**Model Highlights**:

* **VAE-free** — generates directly in pixel space; no traditional VAE encode/decode
* **Dual-level DiT** — patch-level DiT + pixel-level DiT for high-quality generation
* **Multi aspect ratio** — 1024px base resolution with support for several aspect ratios
* **\~1.3B parameters** — efficient enough for consumer GPUs
* **License**: NSCLv1 (non-commercial research/evaluation only)

**Related Links**:

* [Official model on Hugging Face](https://huggingface.co/nvidia/PixelDiT-1300M-1024px)
* [Comfy-Org/PixelDiT](https://huggingface.co/Comfy-Org/PixelDiT)

## PixelDiT text-to-image workflow

<img alt="PixelDiT text-to-image workflow" />

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_pixeldit_t2i.json">
  Download JSON or search "PixelDiT" in Template Library
</Card>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

The workflow consists of three main nodes:

1. **ResolutionSelector** — choose your desired output resolution
2. **Text to Image (PixelDiT) subgraph** — the core generation node with exposed controls for prompt, seed, model selection and resolution
3. **SaveImage** — saves the generated image

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

### Workflow controls

The exposed controls on the **Text to Image (PixelDiT)** subgraph node include:

| Control             | Description                                               |
| ------------------- | --------------------------------------------------------- |
| **Positive Prompt** | The text prompt describing the image you want to generate |
| **Negative Prompt** | Text describing what to avoid in the generated image      |
| **Seed**            | Random seed for reproducibility                           |
| **UNet Model**      | PixelDiT model checkpoint selection                       |
| **CLIP Model**      | Text encoder model selection                              |

## Model downloads

PixelDiT uses two model files: a text encoder and the diffusion model.

<Card title="Text Encoder" icon="download" href="https://huggingface.co/Comfy-Org/PixelDiT/resolve/main/text_encoders/gemma_2_2b_it_elm_bf16.safetensors">
  gemma\_2\_2b\_it\_elm\_bf16.safetensors — Gemma-2-2B-IT text encoder
</Card>

<Card title="Diffusion Model" icon="download" href="https://huggingface.co/Comfy-Org/PixelDiT/resolve/main/diffusion_models/pixeldit_1300m_1024px_bf16.safetensors">
  pixeldit\_1300m\_1024px\_bf16.safetensors — PixelDiT 1300M 1024px diffusion model
</Card>

### Model storage location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── gemma_2_2b_it_elm_bf16.safetensors
│   └── 📂 diffusion_models/
│          └── pixeldit_1300m_1024px_bf16.safetensors
```


# Qwen-Image ComfyUI Native Workflow Example
Source: https://docs.comfy.org/tutorials/image/qwen/qwen-image

Qwen-Image is a 20B parameter MMDiT (Multimodal Diffusion Transformer) model open-sourced under the Apache 2.0 license.

**Qwen-Image** is the first image generation foundation model released by Alibaba's Qwen team. It's a 20B parameter MMDiT (Multimodal Diffusion Transformer) model open-sourced under the Apache 2.0 license. The model has made significant advances in **complex text rendering** and **precise image editing**, achieving high-fidelity output for multiple languages including English and Chinese.

**Model Highlights**:

* **Excellent Multilingual Text Rendering**: Supports high-precision text generation in multiple languages including English, Chinese, Korean, Japanese, maintaining font details and layout consistency
* **Diverse Artistic Styles**: From photorealistic scenes to impressionist paintings, from anime aesthetics to minimalist design, fluidly adapting to various creative prompts

**Related Links**:

* [GitHub](https://github.com/QwenLM/Qwen-Image)
* [Hugging Face](https://huggingface.co/Qwen/Qwen-Image)
* [ModelScope](https://modelscope.cn/models/qwen/Qwen-Image)

Currently Qwen-Image has multiple ControlNet support options available:

* [Qwen-Image-DiffSynth-ControlNets/model\_patches](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/tree/main/split_files/model_patches): Includes canny, depth, and inpaint models
* [qwen\_image\_union\_diffsynth\_lora.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/blob/main/split_files/loras/qwen_image_union_diffsynth_lora.safetensors): Image structure control LoRA supporting canny, depth, pose, lineart, softedge, normal, openpose
* InstantX ControlNet: To be updated

## ComfyOrg Qwen-Image live stream

**Qwen-Image in ComfyUI - Lightning & LoRAs**

<iframe title="Qwen-Image in ComfyUI - Lightning & LoRAs / August 15th, 2025" />

**Qwen-Image ControlNet in ComfyUI - DiffSynth**

<iframe title="Qwen-Image ControlNet in ComfyUI - DiffSynth / August 26th, 2025" />

## Qwen-Image Native Workflow Example

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<a href="https://cloud.comfy.org/?template=image_qwen_image&utm_source=docs">
  Run on Comfy Cloud
</a>

There are three different models used in the workflow attached to this document:

1. Qwen-Image original model fp8\_e4m3fn
2. 8-step accelerated version: Qwen-Image original model fp8\_e4m3fn with lightx2v 8-step LoRA
3. Distilled version: Qwen-Image distilled model fp8\_e4m3fn

**VRAM Usage Reference**
GPU: RTX4090D 24GB

| Model Used                            | VRAM Usage | First Generation | Second Generation |
| ------------------------------------- | ---------- | ---------------- | ----------------- |
| fp8\_e4m3fn                           | 86%        | ≈ 94s            | ≈ 71s             |
| fp8\_e4m3fn with lightx2v 8-step LoRA | 86%        | ≈ 55s            | ≈ 34s             |
| Distilled fp8\_e4m3fn                 | 86%        | ≈ 69s            | ≈ 36s             |

### 1. Workflow File

After updating ComfyUI, you can find the workflow file in the templates, or drag the workflow below into ComfyUI to load it.
![Qwen-image Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/image/qwen/qwen-image.png)

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_image.json">
  <p>Download Workflow for Qwen-Image Official Model</p>
</a>

Distilled version

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/image/qwen/image_qwen_image_distill.json">
  <p>Download Workflow for Distilled Model</p>
</a>

### 2. Model Download

**Available Models in ComfyUI**

* Qwen-Image\_bf16 (40.9 GB)
* Qwen-Image\_fp8 (20.4 GB)
* Distilled versions (non-official, requires only 15 steps)

All models are available at [Huggingface](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main) and [Modelscope](https://modelscope.cn/models/Comfy-Org/Qwen-Image_ComfyUI/files)

**Diffusion model**

* [qwen\_image\_fp8\_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/diffusion_models/qwen_image_fp8_e4m3fn.safetensors)

Qwen\_image\_distill

* [qwen\_image\_distill\_full\_fp8\_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/non_official/diffusion_models/qwen_image_distill_full_fp8_e4m3fn.safetensors)
* [qwen\_image\_distill\_full\_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/non_official/diffusion_models/qwen_image_distill_full_bf16.safetensors)

<Note>
  - The original author of the distilled version recommends using 15 steps with cfg 1.0.
  - According to tests, this distilled version also performs well at 10 steps with cfg 1.0. You can choose either euler or res\_multistep based on the type of image you want.
</Note>

**LoRA**

* [Qwen-Image-Lightning-8steps-V1.0.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/resolve/main/Qwen-Image-Lightning-8steps-V1.0.safetensors)

**Text encoder**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)

**VAE**

[qwen\_image\_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/vae/qwen_image_vae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   ├── qwen_image_fp8_e4m3fn.safetensors
│   │   └── qwen_image_distill_full_fp8_e4m3fn.safetensors ## 蒸馏版
│   ├── 📂 loras/
│   │   └── Qwen-Image-Lightning-8steps-V1.0.safetensors   ## 8步加速 LoRA 模型
│   ├── 📂 vae/
│   │   └── qwen_image_vae.safetensors
│   └── 📂 text_encoders/
│       └── qwen_2.5_vl_7b_fp8_scaled.safetensors
```

### 3. Workflow Instructions

<img alt="Step Guide" />

1. Make sure the `Load Diffusion Model` node has loaded `qwen_image_fp8_e4m3fn.safetensors`
2. Make sure the `Load CLIP` node has loaded `qwen_2.5_vl_7b_fp8_scaled.safetensors`
3. Make sure the `Load VAE` node has loaded `qwen_image_vae.safetensors`
4. Make sure the `EmptySD3LatentImage` node is set with the correct image dimensions
5. Set your prompt in the `CLIP Text Encoder` node; currently, it supports at least English, Chinese, Korean, Japanese, Italian, etc.
6. If you want to enable the 8-step acceleration LoRA by lightx2v, select the node and use `Ctrl + B` to enable it, and modify the Ksampler settings as described in step 8
7. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow
8. For different model versions and workflows, adjust the KSampler parameters accordingly

<Note>
  The distilled model and the 8-step acceleration LoRA by lightx2v do not seem to be compatible for simultaneous use. You can experiment with different combinations to verify if they can be used together.
</Note>

## Qwen Image InstantX ControlNet Workflow

This is a ControlNet model, so you can use it as normal ControlNet.

<a href="https://cloud.comfy.org/?template=image_qwen_image_instantx_controlnet&utm_source=docs">
  Run on Comfy Cloud
</a>

### 1. Workflow and Input Images

Download the image below and drag it into ComfyUI to load the workflow
![workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/qwen/qwen-image-instantx-controlnet/image_qwen_image_instantx_controlnet.png)

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_image_instantx_controlnet.json">
  <p>Download JSON Format Workflow</p>
</a>

Download the image below as input
![input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/qwen/qwen-image-instantx-controlnet/input.jpg)

### 2. Model Links

1. InstantX Controlnet

Download [Qwen-Image-InstantX-ControlNet-Union.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-InstantX-ControlNets/resolve/main/split_files/controlnet/Qwen-Image-InstantX-ControlNet-Union.safetensors) and save it to the `ComfyUI/models/controlnet/` folder

2. **Lotus Depth model**

We will use this model to generate the depth map of the image. The following two models need to be downloaded:

**Diffusion Model**

* [lotus-depth-d-v1-1.safetensors](https://huggingface.co/Comfy-Org/lotus/resolve/main/lotus-depth-d-v1-1.safetensors)

**VAE Model**

* [vae-ft-mse-840000-ema-pruned.safetensors](https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.safetensors)  or any SD1.5 VAE

```
ComfyUI/
├── models/
│   ├── diffusion_models/
│   │   └─── lotus-depth-d-v1-1.safetensors
│   └── vae/
│       └──  lvae-ft-mse-840000-ema-pruned.safetensors
```

> You can also use custom nodes like [comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) to generate depth map.

### 3. Workflow Instructions

<img alt="Process Instructions" />

1. Ensure that the `Load ControlNet Model` node correctly loads the `Qwen-Image-InstantX-ControlNet-Union.safetensors` model
2. Upload input image
3. This subgraph uses the Lotus Depth model. You can find it in the templates or edit the subgraph to learn more, make sure all the models are loaded correctly
4. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Qwen Image ControlNet DiffSynth-ControlNets Model Patches Workflow

<a href="https://cloud.comfy.org/?template=image_qwen_image_controlnet_patch&utm_source=docs">
  Run on Comfy Cloud
</a>

This model is actually not a ControlNet, but a Model patch that supports three different control modes: canny, depth, and inpaint.

Original model address: [DiffSynth-Studio/Qwen-Image ControlNet](https://www.modelscope.cn/collections/Qwen-Image-ControlNet-6157b44e89d444)
Comfy Org rehost address: [Qwen-Image-DiffSynth-ControlNets/model\_patches](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/tree/main/split_files/model_patches)

### 1. Workflow and Input Images

Download the image below and drag it into ComfyUI to load the corresponding workflow
![workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/qwen/qwen-image-controlnet-model-patch/image_qwen_image_controlnet_patch.png)

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_image_controlnet_patch.json">
  <p>Download JSON Format Workflow</p>
</a>

Download the image below as input:

![input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/qwen/qwen-image-controlnet-model-patch/input.png)

### 2. Model Links

Other models are the same as the Qwen-Image basic workflow. You only need to download the models below and save them to the `ComfyUI/models/model_patches` folder

* [qwen\_image\_canny\_diffsynth\_controlnet.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/resolve/main/split_files/model_patches/qwen_image_canny_diffsynth_controlnet.safetensors)
* [qwen\_image\_depth\_diffsynth\_controlnet.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/resolve/main/split_files/model_patches/qwen_image_depth_diffsynth_controlnet.safetensors)
* [qwen\_image\_inpaint\_diffsynth\_controlnet.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/resolve/main/split_files/model_patches/qwen_image_inpaint_diffsynth_controlnet.safetensors)

### 3. Workflow Usage Instructions

Currently, diffsynth has three patch models: Canny, Depth, and Inpaint.

If you're using ControlNet-related workflows for the first time, you need to understand that control images need to be preprocessed into supported image formats before they can be used and recognized by the model.

<img alt="Input Type Diagram" />

* Canny: Processed canny edge, line art contours
* Depth: Preprocessed depth map showing spatial relationships
* Inpaint: Requires using Mask to mark areas that need to be repainted

Since this patch model is divided into three different models, you need to select the correct preprocessing type when inputting to ensure proper image preprocessing.

**Canny Model ControlNet Usage Instructions**

<img alt="Canny Workflow" />

1. Ensure that `qwen_image_canny_diffsynth_controlnet.safetensors` is loaded
2. Upload input image for subsequent processing
3. The Canny node is a native preprocessing node that will preprocess the input image according to your set parameters to control generation
4. If needed, you can modify the `strength` in the `QwenImageDiffsynthControlnet` node to control the intensity of line art control
5. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

> For using qwen\_image\_depth\_diffsynth\_controlnet.safetensors, you need to preprocess the image into a depth map and replace the `image processing` part. For this usage, please refer to the InstantX processing method in this document. Other parts are similar to using the Canny model.

**Inpaint Model ControlNet Usage Instructions**

<img alt="Inpaint Workflow" />

For the Inpaint model, it requires using the [Mask Editor](/interface/maskeditor) to draw a mask and use it as input control condition.

1. Ensure that `ModelPatchLoader` loads the `qwen_image_inpaint_diffsynth_controlnet.safetensors` model
2. Upload image and use the [Mask Editor](/interface/maskeditor) to draw a mask. You need to connect the `mask` output of the corresponding `Load Image` node to the `mask` input of `QwenImageDiffsynthControlnet` to ensure the corresponding mask is loaded
3. Use the `Ctrl-B` shortcut to set the original Canny in the workflow to bypass mode, making the corresponding Canny node processing ineffective
4. In `CLIP Text Encoder`, input what you want to change the masked area to
5. If needed, you can modify the `strength` in the `QwenImageDiffsynthControlnet` node to control the corresponding control intensity
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Qwen Image Union ControlNet LoRA Workflow

<a href="https://cloud.comfy.org/?template=image_qwen_image_union_control_lora&utm_source=docs">
  Run on Comfy Cloud
</a>

Original model address: [DiffSynth-Studio/Qwen-Image-In-Context-Control-Union](https://www.modelscope.cn/models/DiffSynth-Studio/Qwen-Image-In-Context-Control-Union/)
Comfy Org rehost address: [qwen\_image\_union\_diffsynth\_lora.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/blob/main/split_files/loras/qwen_image_union_diffsynth_lora.safetensors): Image structure control LoRA supporting canny, depth, pose, lineart, softedge, normal, openpose

### 1. Workflow and Input Images

Download the image below and drag it into ComfyUI to load the workflow
![workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/qwen/qwen-image-union-control-lora/image_qwen_image_union_control_lora.png)

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_image_union_control_lora.json">
  <p>Download JSON Format Workflow</p>
</a>

Download the image below as input

![workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/qwen/qwen-image-union-control-lora/input.png)

### 2. Model Links

Download the model below. Since this is a LoRA model, it needs to be saved to the `ComfyUI/models/loras/` folder

* [qwen\_image\_union\_diffsynth\_lora.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets/blob/main/split_files/loras/qwen_image_union_diffsynth_lora.safetensors): Image structure control LoRA supporting canny, depth, pose, lineart, softedge, normal, openpose

### 3. Workflow Instructions

This model is a unified control LoRA that supports canny, depth, pose, lineart, softedge, normal, openpose controls. Since many image preprocessing native nodes are not fully supported, you should use something like [comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) to complete other image preprocessing.

<img alt="Union Control LoRA" />

1. Ensure that `LoraLoaderModelOnly` correctly loads the `qwen_image_union_diffsynth_lora.safetensors` model
2. Upload input image
3. If needed, you can adjust the `Canny` node parameters. Since different input images require different parameter settings to get better image preprocessing results, you can try adjusting the corresponding parameter values to get more/fewer details
4. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

> For other types of control, you also need to replace the image processing part.


# Qwen-Image-2512 ComfyUI Native Workflow Example
Source: https://docs.comfy.org/tutorials/image/qwen/qwen-image-2512

Qwen-Image-2512 is the December update of Qwen-Image's text-to-image foundational model, featuring enhanced human realism, finer natural detail, and improved text rendering.

**Qwen-Image-2512** is the December update of Qwen-Image's text-to-image foundational model. Compared to the base Qwen-Image model released in August, Qwen-Image-2512 features significant improvements in image quality and realism.

**Key Enhancements in Qwen-Image-2512**:

* **Enhanced Human Realism**: Significantly reduces the "AI-generated" look and substantially enhances overall image realism, especially for human subjects
* **Finer Natural Detail**: Delivers notably more detailed rendering of landscapes, animal fur, and other natural elements
* **Improved Text Rendering**: Improves the accuracy and quality of textual elements, achieving better layout and more faithful multimodal (text + image) composition

**Official Links**:

* [GitHub Repository](https://github.com/QwenLM/Qwen-Image)
* [Hugging Face](https://huggingface.co/Qwen/Qwen-Image-2512)
* [ModelScope](https://modelscope.cn/models/Qwen/Qwen-Image-2512)
* [Tech Report](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/Qwen_Image.pdf)
* [Blog](https://qwen.ai/blog?id=qwen-image-2512)

## Supported Aspect Ratios

| Aspect Ratio | Resolution |
| ------------ | ---------- |
| 1:1          | 1328x1328  |
| 16:9         | 1664x928   |
| 9:16         | 928x1664   |
| 4:3          | 1472x1104  |
| 3:4          | 1104x1472  |
| 3:2          | 1584x1056  |
| 2:3          | 1056x1584  |

## Qwen-Image-2512 ComfyUI Native Workflow Example

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<a href="https://cloud.comfy.org/?template=image_qwen_Image_2512&utm_source=docs">
  Run on Comfy Cloud
</a>

### 1. Workflow file

After updating ComfyUI, you can find the workflow file from the templates, or drag the workflow below into ComfyUI to load it.

The workflow includes two subgraphs:

* **Text to Image (Qwen-Image 2512)**: Standard 50-step generation
* **Text to Image (Qwen-Image 2512 4steps)**: Accelerated 4-step generation using Lightning LoRA

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_Image_2512.json">
  <p>Download JSON Workflow</p>
</a>

### 2. Model download

**Text Encoders**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)

**LoRA (Optional - for 4-step Lightning acceleration)**

* [Qwen-Image-Lightning-4steps-V1.0.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/resolve/main/Qwen-Image-Lightning-4steps-V1.0.safetensors)

**Diffusion Models**

* [qwen\_image\_2512\_fp8\_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/diffusion_models/qwen_image_2512_fp8_e4m3fn.safetensors) (Recommended for most users)
* [qwen\_image\_2512\_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/diffusion_models/qwen_image_2512_bf16.safetensors) (If you have enough VRAM and want better quality)

**VAE**

* [qwen\_image\_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/vae/qwen_image_vae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   ├── 📂 loras/
│   │      └── Qwen-Image-Lightning-4steps-V1.0.safetensors
│   ├── 📂 diffusion_models/
│   │      ├── qwen_image_2512_bf16.safetensors
│   │      └── qwen_image_2512_fp8_e4m3fn.safetensors
│   └── 📂 vae/
│          └── qwen_image_vae.safetensors
```


# Qwen-Image-Edit ComfyUI Native Workflow Example
Source: https://docs.comfy.org/tutorials/image/qwen/qwen-image-edit

Qwen-Image-Edit is the image editing version of Qwen-Image, further trained based on the 20B model, supporting precise text editing and dual semantic/appearance editing capabilities.

**Qwen-Image-Edit** is the image editing version of Qwen-Image. It is further trained based on the 20B Qwen-Image model, successfully extending Qwen-Image's unique text rendering capabilities to editing tasks, enabling precise text editing. In addition, Qwen-Image-Edit feeds the input image into both Qwen2.5-VL (for visual semantic control) and the VAE Encoder (for visual appearance control), thus achieving dual semantic and appearance editing capabilities.

**Model Features**

Features include:

* Precise Text Editing: Qwen-Image-Edit supports bilingual (Chinese and English) text editing, allowing direct addition, deletion, and modification of text in images while preserving the original text size, font, and style.
* Dual Semantic/Appearance Editing: Qwen-Image-Edit supports not only low-level visual appearance editing (such as style transfer, addition, deletion, modification, etc.) but also high-level visual semantic editing (such as IP creation, object rotation, etc.).
* Strong Cross-Benchmark Performance: Evaluations on multiple public benchmarks show that Qwen-Image-Edit achieves SOTA in editing tasks, making it a powerful foundational model for image generation.

**Official Links**:

* [GitHub Repository](https://github.com/QwenLM/Qwen-Image)
* [Hugging Face](https://huggingface.co/Qwen/Qwen-Image-Edit)
* [ModelScope](https://modelscope.cn/models/qwen/Qwen-Image-Edit)

## ComfyOrg Qwen-Image-Edit Live Stream

<iframe title="Qwen-Image Edit in ComfyUI - Image Editing Model / August 19th, 2025" />

## Qwen-Image-Edit ComfyUI Native Workflow Example

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### 1. Workflow File

After updating ComfyUI, you can find the workflow file from the templates, or drag the workflow below into ComfyUI to load it.
![Qwen-image Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/qwen/qwen-image-edit/qwen_image_edit.png)

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_image_edit.json">
  <p>Download JSON Workflow</p>
</a>

<a href="https://cloud.comfy.org/?template=image_qwen_image_edit&utm_source=docs">
  <p>Run on ComfyUI Cloud</p>
</a>

Download the image below as input
![Qwen-image Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/image/qwen/qwen-image-edit/input.png)

### 2. Model Download

All models can be found at [Comfy-Org/Qwen-Image\_ComfyUI](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main) or [Comfy-Org/Qwen-Image-Edit\_ComfyUI](https://huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI)

**Diffusion model**

* [qwen\_image\_edit\_fp8\_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI/resolve/main/split_files/diffusion_models/qwen_image_edit_fp8_e4m3fn.safetensors)

**LoRA**

* [Qwen-Image-Lightning-4steps-V1.0.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Lightning/resolve/main/Qwen-Image-Lightning-4steps-V1.0.safetensors)

**Text encoder**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)

**VAE**

* [qwen\_image\_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/vae/qwen_image_vae.safetensors)

Model Storage Location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── qwen_image_edit_fp8_e4m3fn.safetensors
│   ├── 📂 loras/
│   │   └── Qwen-Image-Lightning-4steps-V1.0.safetensors
│   ├── 📂 vae/
│   │   └── qwen_image_vae.safetensors
│   └── 📂 text_encoders/
│       └── qwen_2.5_vl_7b_fp8_scaled.safetensors
```

### 3. Follow the Steps to Complete the Workflow

<img alt="Steps Diagram" />

1. Model Loading
   * Ensure the `Load Diffusion Model` node loads `qwen_image_edit_fp8_e4m3fn.safetensors`
   * Ensure the `Load CLIP` node loads `qwen_2.5_vl_7b_fp8_scaled.safetensors`
   * Ensure the `Load VAE` node loads `qwen_image_vae.safetensors`
2. Image Loading
   * Ensure the `Load Image` node uploads the image to be edited
3. Prompt Setting
   * Set the prompt in the `CLIP Text Encoder` node
4. The Scale Image to Total Pixels node will scale your input image to a total of one million pixels,
   * Mainly to avoid quality loss in output images caused by oversized input images such as 2048x2048
   * If you are familiar with your input image size, you can bypass this node using `Ctrl+B`
5. If you want to use the 4-step Lighting LoRA to speed up image generation, you can select the `LoraLoaderModelOnly` node and press `Ctrl+B` to enable it
6. For the `steps` and `cfg` settings of the Ksampler node, we've added a note below the node where you can test the optimal parameter settings
7. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow


# Qwen-Image-Edit-2511 ComfyUI Native Workflow Example
Source: https://docs.comfy.org/tutorials/image/qwen/qwen-image-edit-2511

Qwen-Image-Edit-2511 is an enhanced version of Qwen-Image-Edit, featuring improved character consistency, multi-person editing, integrated LoRA capabilities, and enhanced geometric reasoning.

**Qwen-Image-Edit-2511** is an enhanced version of Qwen-Image-Edit-2509, featuring multiple improvements including notably better consistency. This model extends Qwen-Image's unique text rendering capabilities to editing tasks, enabling precise text editing with dual semantic and appearance editing capabilities.

**Key Enhancements in Qwen-Image-Edit-2511**:

* **Mitigate Image Drift**: Improved stability during editing operations
* **Improved Character Consistency**: Better preservation of identity and visual characteristics during imaginative edits
* **Multi-Person Consistency**: High-fidelity fusion of multiple person images into coherent group shots
* **Integrated LoRA Capabilities**: Popular community LoRAs built directly into the base model
* **Enhanced Industrial Design Generation**: Better support for batch industrial product design and material replacement
* **Strengthened Geometric Reasoning**: Direct generation of auxiliary construction lines for design or annotation

**Official Links**:

* [GitHub Repository](https://github.com/QwenLM/Qwen-Image)
* [Hugging Face](https://huggingface.co/Qwen/Qwen-Image-Edit-2511)
* [ModelScope](https://modelscope.cn/models/Qwen/Qwen-Image-Edit-2511)
* [Tech Report](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/Qwen_Image.pdf)
* [Blog](https://qwenlm.github.io/blog/qwen-image-edit-2511/)

## Qwen-Image-Edit-2511 ComfyUI Native Workflow Example

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### 1. Workflow file

After updating ComfyUI, you can find the workflow file from the templates, or drag the workflow below into ComfyUI to load it.

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_image_edit_2511.json">
  <p>Download JSON Workflow</p>
</a>

<a href="https://cloud.comfy.org/?template=image_qwen_image_edit_2511&utm_source=docs">
  <p>Run on ComfyUI Cloud</p>
</a>

### 2. Model download

**Text Encoders**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)

**LoRA (Optional - for 4-step Lightning acceleration)**

* [Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors](https://huggingface.co/lightx2v/Qwen-Image-Edit-2511-Lightning/resolve/main/Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors)

**Diffusion Models**

* [qwen\_image\_edit\_2511\_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-Edit_ComfyUI/resolve/main/split_files/diffusion_models/qwen_image_edit_2511_bf16.safetensors)

**VAE**

* [qwen\_image\_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/vae/qwen_image_vae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   ├── 📂 loras/
│   │      └── Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors
│   ├── 📂 diffusion_models/
│   │      └── qwen_image_edit_2511_bf16.safetensors
│   └── 📂 vae/
│          └── qwen_image_vae.safetensors
```


# Qwen-Image-Layered ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/qwen/qwen-image-layered

Qwen-Image-Layered is a model capable of decomposing an image into multiple RGBA layers, enabling inherent editability through layer decomposition.

**Qwen-Image-Layered** is a model developed by Alibaba's Qwen team that can decompose an image into multiple RGBA layers. This layered representation unlocks inherent editability: each layer can be independently manipulated without affecting other content.

**Key Features**:

* **Inherent Editability**: Each layer can be independently manipulated without affecting other content
* **High-Fidelity Elementary Operations**: Supports resizing, repositioning, and recoloring with physical isolation of semantic components
* **Variable-Layer Decomposition**: Not limited to a fixed number of layers - decompose into 3, 4, 8, or more layers as needed
* **Recursive Decomposition**: Any layer can be further decomposed, enabling infinite decomposition depth

**Related Links**:

* [Hugging Face](https://huggingface.co/Qwen/Qwen-Image-Layered)
* [Research Paper](https://arxiv.org/abs/2512.15603)
* [Blog](https://qwenlm.github.io/blog/qwen-image-layered/)

## Qwen-Image-Layered workflow

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_image_layered.json">
  <p>Download JSON Workflow File</p>
</a>

<a href="https://cloud.comfy.org/?template=image_qwen_image_layered&utm_source=docs">
  <p>Run on ComfyUI Cloud</p>
</a>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model links

**text\_encoders**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)

**diffusion\_models**

* [qwen\_image\_layered\_bf16.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-Layered_ComfyUI/resolve/main/split_files/diffusion_models/qwen_image_layered_bf16.safetensors)

**vae**

* [qwen\_image\_layered\_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-Layered_ComfyUI/resolve/main/split_files/vae/qwen_image_layered_vae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   ├── 📂 diffusion_models/
│   │      └── qwen_image_layered_bf16.safetensors
│   └── 📂 vae/
│          └── qwen_image_layered_vae.safetensors
```

## FP8 version

By default we are using bf16, which requires high VRAM. For lower VRAM usage, you can use the fp8 version:

* [qwen\_image\_layered\_fp8mixed.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image-Layered_ComfyUI/blob/main/split_files/diffusion_models/qwen_image_layered_fp8mixed.safetensors)

Then update the **Load Diffusion model** node inside the [Subgraph](/interface/features/subgraph) to use it.

## Workflow settings

### Sampler settings

This model is slow. The original sampling settings are steps: 50 and CFG: 4.0, which will at least double the generation time.

### Input size

For input size, 640px is recommended. Use 1024px for high-resolution output.

### Prompt (optional)

The text prompt is intended to describe the overall content of the input image—including elements that may be partially occluded (e.g., you may specify the text hidden behind a foreground object). It is not designed to control the semantic content of individual layers explicitly.


# Z-Image ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/z-image/z-image

Z-Image is a 6B parameter efficient image generation foundation model with single-stream diffusion transformer for community-driven fine-tuning and custom development.

**Z-Image (造相)** is a powerful and highly efficient image generation model with **6B** parameters, developed by Alibaba's Tongyi Lab. It uses a **Scalable Single-Stream DiT** (S3-DiT) architecture where text, visual semantic tokens, and image VAE tokens are concatenated at the sequence level to serve as a unified input stream, maximizing parameter efficiency.

Z-Image (Base) is the non-distilled foundation model designed for community-driven fine-tuning and custom development.

**Model Highlights**:

* **Photorealistic Quality**: Delivers strong photorealistic image generation while maintaining excellent aesthetic quality
* **Accurate Bilingual Text Rendering**: Excels at accurately rendering complex Chinese and English text
* **Prompt Enhancing & Reasoning**: Prompt Enhancer empowers the model with reasoning capabilities
* **Fine-tuning Ready**: Ideal base model for custom training and adaptation

**Related Links**:

* [GitHub](https://github.com/Tongyi-MAI/Z-Image)
* [Hugging Face](https://huggingface.co/Tongyi-MAI/Z-Image)
* [ModelScope](https://modelscope.cn/models/Tongyi-MAI/Z-Image)

## Z-Image text-to-image workflow

<Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_z_image.json">
  Download the Z-Image text-to-image workflow JSON file.
</Card>

<Card title="Run on ComfyUI Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_z_image&utm_source=docs&utm_medium=inhouse_social&utm_campaign=z_image_launch">
  Run this workflow directly on ComfyUI Cloud.
</Card>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Z-Image model downloads

<Card title="qwen_3_4b.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image_turbo/resolve/main/split_files/text_encoders/qwen_3_4b.safetensors">
  Text encoder for Z-Image.
</Card>

<Card title="z_image_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image/resolve/main/split_files/diffusion_models/z_image_bf16.safetensors">
  Diffusion model for Z-Image.
</Card>

<Card title="ae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image_turbo/resolve/main/split_files/vae/ae.safetensors">
  VAE for Z-Image.
</Card>

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_3_4b.safetensors
│   ├── 📂 diffusion_models/
│   │      └── z_image_bf16.safetensors
│   └── 📂 vae/
│          └── ae.safetensors
```


# Z-Image-Turbo ComfyUI Workflow Example
Source: https://docs.comfy.org/tutorials/image/z-image/z-image-turbo

Z-Image-Turbo is a distilled 6B parameter efficient image generation model with sub-second inference latency.

<iframe title="YouTube video player" />

**Z-Image (造相)** is a powerful and highly efficient image generation model with **6B** parameters, developed by Alibaba's Tongyi Lab. It uses a **Scalable Single-Stream DiT** (S3-DiT) architecture where text, visual semantic tokens, and image VAE tokens are concatenated at the sequence level to serve as a unified input stream, maximizing parameter efficiency.

**Model Variants**:

* 🚀 **Z-Image-Turbo** – A distilled version that matches or exceeds leading competitors with only **8 NFEs** (Number of Function Evaluations). It offers **sub-second inference latency** on enterprise-grade H800 GPUs and fits within **16GB VRAM consumer devices**.
* 🧱 **Z-Image-Base** – The non-distilled foundation model for community-driven fine-tuning and custom development.
* ✍️ **Z-Image-Edit** – A variant fine-tuned for image editing tasks with impressive instruction-following capabilities.

**Model Highlights**:

* **Photorealistic Quality**: Delivers strong photorealistic image generation while maintaining excellent aesthetic quality
* **Accurate Bilingual Text Rendering**: Excels at accurately rendering complex Chinese and English text
* **Prompt Enhancing & Reasoning**: Prompt Enhancer empowers the model with reasoning capabilities
* **Sub-second Inference**: Achieves fast generation speed on supported hardware

**Related Links**:

* [GitHub](https://github.com/Tongyi-MAI/Z-Image)
* [Hugging Face](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo)

## Z-Image-Turbo text-to-image workflow

<Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_z_image_turbo.json">
  Download the Z-Image-Turbo text-to-image workflow JSON file.
</Card>

<Card title="Run on ComfyUI Cloud" icon="cloud" href="https://cloud.comfy.org/?template=image_z_image_turbo&utm_source=docs&utm_medium=inhouse_social&utm_campaign=z_image_launch">
  Run this workflow directly on ComfyUI Cloud.
</Card>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### Z-Image-Turbo model downloads

<Card title="qwen_3_4b.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image_turbo/resolve/main/split_files/text_encoders/qwen_3_4b.safetensors">
  Text encoder for Z-Image-Turbo.
</Card>

<Card title="z_image_turbo_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image_turbo/resolve/main/split_files/diffusion_models/z_image_turbo_bf16.safetensors">
  Diffusion model for Z-Image-Turbo.
</Card>

<Card title="ae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/z_image_turbo/resolve/main/split_files/vae/ae.safetensors">
  VAE for Z-Image-Turbo.
</Card>

**Z-Image-Turbo Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_3_4b.safetensors
│   ├── 📂 diffusion_models/
│   │      └── z_image_turbo_bf16.safetensors
│   └── 📂 vae/
│          └── ae.safetensors
```

## Z-Image-Turbo Fun Union ControlNet workflow

This workflow uses the Z-Image-Turbo Fun Union ControlNet model to generate images with ControlNet guidance. It applies Canny edge detection to a reference image and uses the ControlNet to guide the generation process.

<Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_z_image_turbo_fun_union_controlnet.json">
  Download the Z-Image-Turbo Fun Union ControlNet workflow JSON file.
</Card>

### Additional model for ControlNet

<Card title="Z-Image-Turbo-Fun-Controlnet-Union.safetensors" icon="download" href="https://huggingface.co/alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union/resolve/main/Z-Image-Turbo-Fun-Controlnet-Union.safetensors">
  ControlNet model patch for Z-Image-Turbo.
</Card>

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── qwen_3_4b.safetensors
│   ├── 📂 diffusion_models/
│   │      └── z_image_turbo_bf16.safetensors
│   ├── 📂 vae/
│   │      └── ae.safetensors
│   └── 📂 model_patches/
│          └── Z-Image-Turbo-Fun-Controlnet-Union.safetensors
```


# Gemma 4 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/llm/gemma4/gemma4

Gemma 4 is Google's multimodal LLM family supporting text generation, image understanding, video analysis, and audio transcription with up to 256K context. Available in 2B, 4B, and 31B sizes.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Gemma 4** is the latest generation of lightweight open LLMs from Google DeepMind, built for text generation, image understanding, video analysis, audio transcription, and structured tool use. It is natively supported in ComfyUI as the default **Text Generation** model.

**Model highlights**:

* **Multimodal by design** — accepts text, image, video, and audio inputs simultaneously
* **Three sizes available**:
  * **E2B (2B)** — Fast and lightweight, ideal for consumer GPUs
  * **E4B (4B)** — Balanced performance, recommended default
  * **31B** — Best quality, requires higher VRAM
* **Thinking mode** — Built-in step-by-step reasoning before generating answers
* **Long context** — Up to 128K tokens (E2B/E4B) and 256K tokens (31B)
* **Multilingual** — 35+ languages out of the box, pre-trained on 140+
* **Function calling** — Native support for structured tool use and agentic workflows
* **ComfyUI native** — loaded and run through the built-in `TextGenerate` and `CLIPLoader` nodes

**Related links**:

* [Hugging Face (Comfy-Org/gemma-4)](https://huggingface.co/Comfy-Org/gemma-4)
* [Google AI for Developers](https://ai.google.dev/gemma)
* [ComfyUI Source Code (nodes\_textgen.py)](https://github.com/Comfy-Org/ComfyUI/blob/master/comfy_extras/nodes_textgen.py)

## Available workflow

### Gemma 4: Text Generation

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/llm_gemma4_text_gen.json">
  Download JSON or search "Gemma 4 Text Generation" in Template Library
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=llm_gemma4_text_gen&utm_source=docs&utm_medium=referral&utm_campaign=gemma4">
  Open in Comfy Cloud
</Card>

![Gemma 4 Text Generation Workflow](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/llm_gemma4_text_gen-1.webp)

This workflow demonstrates the core **text generation** capabilities of Gemma 4. It accepts an optional image, audio file, or video as additional context alongside your text prompt, and generates natural language output — with support for reasoning, coding, and multilingual prompts.

**Inputs**:

* **Text prompt** — your question or instruction
* **Image** (optional) — for visual understanding tasks (OCR, object detection, chart reading, etc.)
* **Audio** (optional) — for speech recognition or transcription
* **Video** (optional) — for video understanding across frames (subsampled to 1 FPS internally)

**Key controls**:

* **Max length** — maximum number of tokens to generate (default 256)
* **Sampling mode** — toggle sampling on/off and adjust temperature, top-k, top-p, repetition penalty, and seed
* **Thinking mode** — enable step-by-step reasoning before the final answer
* **Use default template** — apply the built-in system prompt for the model

**Output**:

* **Generated text** — the model's response as a plain text string

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Model Download

Gemma 4 models are loaded as text encoders in ComfyUI. Download the relevant model file and place it in the correct directory:

<Card title="Gemma 4 2B (E2B IT FP8)" icon="download" href="https://huggingface.co/Comfy-Org/gemma-4/resolve/main/text_encoders/gemma4_e2b_it_fp8_scaled.safetensors">
  Fast, lightweight. Recommended for consumer GPUs.
</Card>

<Card title="Gemma 4 4B (E4B IT FP8)" icon="download" href="https://huggingface.co/Comfy-Org/gemma-4/resolve/main/text_encoders/gemma4_e4b_it_fp8_scaled.safetensors">
  Balanced performance. The default model in the workflow.
</Card>

<Card title="View All Variants" icon="external-link" href="https://huggingface.co/Comfy-Org/gemma-4/tree/main/text_encoders">
  Browse all Gemma 4 model weights.
</Card>

Place the downloaded `.safetensors` file in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 text_encoders/
│       └── gemma4_e4b_it_fp8_scaled.safetensors
```


# Qwen 3.0 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/llm/qwen/qwen3

Qwen 3.0 is Alibaba Cloud's powerful open-source LLM with strong reasoning capabilities, available in 4B size for text generation and structured reasoning tasks.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Qwen 3.0** (also known as Qwen3) is a powerful open-source LLM from Alibaba Cloud built for text generation, reasoning, and structured analysis. It is natively supported in ComfyUI through the built-in `TextGenerate` node.

**Model highlights**:

* **Strong reasoning** — Qwen3-4B-Thinking supports step-by-step chain-of-thought reasoning
* **Text generation focused** — optimized for structured text output, analysis, and coding tasks
* **ComfyUI native** — works with the built-in `TextGenerate` node, no custom nodes needed
* **Lightweight** — shares the same text encoder format as Qwen3.5, available in 2B, 4B, and 9B variants to fit different hardware

## Use Cases

Qwen 3.0 is well-suited for tasks that require structured text generation and intelligent reasoning within a ComfyUI workflow:

* **Prompt optimization** — feed existing prompts to Qwen 3.0 and ask it to rewrite, expand, or refine them for better image generation results. For example, convert a short keyword prompt into detailed, structured descriptions with style, lighting, and composition details.
* **Workflow logic reasoning** — use the model to analyze workflow parameters, suggest processing steps, or generate structured instructions that feed into other nodes.
* **Text-based analysis** — extract information, classify content, or generate structured reports from text inputs.
* **Chain-of-thought reasoning** — enable thinking mode for complex multi-step tasks that benefit from intermediate reasoning before producing the final output.

## Available workflow

### Qwen 3.0: Text Generation

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/llm_qwen3_text_gen.json">
  Download JSON or search "Qwen 3.0 Text Generation" in Template Library
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=llm_qwen3_text_gen&utm_source=docs&utm_medium=referral&utm_campaign=qwen3">
  Open in Comfy Cloud
</Card>

![Qwen 3.0 Text Generation Workflow](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/llm_qwen3_text_gen-1.webp)

This workflow demonstrates the core **text generation** capabilities of Qwen 3.0. It accepts a text prompt and generates detailed, structured responses using the model's built-in reasoning capabilities.

**Inputs**:

* **Text prompt** — your question, instruction, or task description

**Key controls**:

* **Max length** — maximum number of tokens to generate (default 256)
* **Sampling mode** — toggle sampling on/off and adjust temperature, top-k, top-p, repetition penalty, and seed
* **Thinking mode** — enable step-by-step reasoning before the final answer
* **Use default template** — apply the built-in system prompt for the model

**Output**:

* **Generated text** — the model's response as a plain text string

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Model Download

Qwen 3.0 models are loaded as text encoders in ComfyUI. The model files are shared with Qwen3.5 — download the variant that best fits your hardware:

<Card title="Qwen3.5 2B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/resolve/main/text_encoders/qwen3.5_2b_bf16.safetensors">
  Lightweight, \~4.5 GB. Best for low VRAM setups and fast downloads.
</Card>

<Card title="Qwen3.5 4B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/resolve/main/text_encoders/qwen3.5_4b_bf16.safetensors">
  Balanced size and quality. Recommended for most consumer GPUs.
</Card>

<Card title="Qwen3.5 9B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/resolve/main/text_encoders/qwen3.5_9b_bf16.safetensors">
  Largest variant, \~19 GB. Higher quality output, requires more VRAM.
</Card>

Place the downloaded `.safetensors` file in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 text_encoders/
│       └── qwen3.5_4b_bf16.safetensors   # or 2b / 9b variant
```


# Qwen3.5 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/llm/qwen/qwen3_5

Qwen3.5 is Alibaba Cloud's open-source multimodal LLM with image understanding and text generation capabilities, available in 4B size for image captioning and reverse prompt engineering.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Qwen3.5** is an open-source multimodal LLM from Alibaba Cloud, building on the Qwen 3.0 series with added image understanding capabilities. It supports both text generation and image-based tasks such as image captioning and reverse prompt engineering.

**Model highlights**:

* **Multimodal** — accepts text and image inputs for visual understanding tasks
* **Image captioning** — can describe images and generate detailed captions
* **Reverse prompt engineering** — extract prompts and generation parameters from reference images
* **ComfyUI native** — works with the built-in `TextGenerate` node, no custom nodes needed
* **Lightweight** — 4B parameter model, suitable for consumer GPUs

## Use Cases

Qwen3.5 excels in scenarios where combining visual understanding with text generation adds value to a ComfyUI workflow:

* **Image reverse prompt engineering** — feed a reference image to Qwen3.5 and ask it to generate a detailed text prompt that could reproduce the image. This is especially useful when you encounter a great image but don't know how it was prompted.
* **Prompt optimization** — load an existing prompt and an image concept, then ask Qwen3.5 to generate, refine, or expand prompts with richer detail for better generation results.
* **Image captioning** — automatically generate captions, descriptions, or metadata tags for generated images, useful for cataloging or training data preparation.
* **Visual question answering** — ask questions about image content ("What objects are in this scene?", "What color is the background?") and get structured text answers.
* **Text reading** — with a suitable prompt, the model may attempt to read visible text or labels in images, though reliability depends on the quality and clarity of the rendered text.

## Available workflow

### Qwen3.5: Text Generation

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/llm_qwen3_5_text_gen.json">
  Download JSON or search "Qwen3.5 Text Generation" in Template Library
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=llm_qwen3_5_text_gen&utm_source=docs&utm_medium=referral&utm_campaign=qwen3_5">
  Open in Comfy Cloud
</Card>

![Qwen3.5 Text Generation Workflow](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/llm_qwen3_5_text_gen-1.webp)

This workflow demonstrates the **text generation and image understanding** capabilities of Qwen3.5. It accepts a text prompt and an optional image, and generates descriptive text or structured analysis based on the input.

**Inputs**:

* **Text prompt** — your question, instruction, or task description
* **Image** (optional) — for visual understanding tasks (image captioning, reverse prompt engineering, prompt optimization, etc.)

**Key controls**:

* **Max length** — maximum number of tokens to generate (default 256)
* **Sampling mode** — toggle sampling on/off and adjust temperature, top-k, top-p, repetition penalty, and seed
* **Use default template** — apply the built-in system prompt for the model

**Output**:

* **Generated text** — the model's response as a plain text string

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Model Download

Qwen3.5 models are loaded as text encoders in ComfyUI. Choose the variant that best suits your hardware:

<Card title="Qwen3.5 2B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/resolve/main/text_encoders/qwen3.5_2b_bf16.safetensors">
  Lightweight, \~4.5 GB. Best for low VRAM setups and fast downloads.
</Card>

<Card title="Qwen3.5 4B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/resolve/main/text_encoders/qwen3.5_4b_bf16.safetensors">
  Balanced size and quality. Recommended for most consumer GPUs.
</Card>

<Card title="Qwen3.5 9B (bf16)" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/resolve/main/text_encoders/qwen3.5_9b_bf16.safetensors">
  Largest variant, \~19 GB. Higher quality output, requires more VRAM.
</Card>

Place the downloaded `.safetensors` file in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 text_encoders/
│       └── qwen3.5_4b_bf16.safetensors   # or 2b / 9b variant
```


# LTX-2.0 ComfyUI Workflow Examples
Source: https://docs.comfy.org/tutorials/video/ltx/ltx-2

Learn how to use LTX-2 in ComfyUI for synchronized audio-video generation

<iframe title="YouTube video player" />

[LTX-2](https://huggingface.co/Lightricks/LTX-2) is a 19B parameter DiT-based audio-video foundation model by Lightricks. It generates synchronized video and audio in a single pass, creating cohesive experiences where motion, dialogue, background noise, and music are produced together.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Key features

* **Synchronized audio-video generation**: Generates motion, dialogue, SFX, and music together in one pass
* **Multiple generation modes**: Text-to-video, image-to-video, and video-to-video
* **Control options**: Canny, Depth, and Pose video-to-video control via IC-LoRAs
* **Keyframe-driven generation**: Interpolate between keyframe images
* **Native upscaling**: Spatial (2x) and temporal (2x) upscalers for higher resolution and FPS
* **Prompt enhancement**: Automatic prompt enhancement support

## Model checkpoints

| Name                           | Description                                |
| ------------------------------ | ------------------------------------------ |
| ltx-2-19b-dev                  | Full model in bf16, flexible and trainable |
| ltx-2-19b-dev-fp8              | Full model in fp8 quantization             |
| ltx-2-19b-distilled            | Distilled version, 8 steps, CFG=1          |
| ltx-2-spatial-upscaler-x2-1.0  | 2x spatial upscaler for higher resolution  |
| ltx-2-temporal-upscaler-x2-1.0 | 2x temporal upscaler for higher FPS        |

## Getting started

LTX-2 is natively supported in ComfyUI. To get started:

1. Update ComfyUI to the latest version
2. Go to **Template Library** > **Video** > choose any LTX-2 workflow
3. Follow the pop-up to download models and run the workflow

## Workflows

### Text-to-video

Generate videos from text prompts.

<Card title="Text-to-Video" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_ltx2_t2v.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_t2v&utm_source=docs&utm_campaign=ltx_2">
  Open in cloud
</Card>

**Distilled version** (faster, 8 steps):

<Card title="Text-to-Video Distilled" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_ltx2_t2v_distilled.json">
  Download workflow
</Card>

### Image-to-video

Generate videos from an input image.

<Card title="Image-to-Video" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_ltx2_i2v.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_i2v&utm_source=docs&utm_campaign=ltx_2">
  Open in cloud
</Card>

**Distilled version** (faster, 8 steps):

<Card title="Image-to-Video Distilled" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_ltx2_i2v_distilled.json">
  Download workflow
</Card>

### Control-to-video

Generate videos with structural control using IC-LoRAs.

**Depth control:**

<Card title="Depth-to-Video" icon="download" href="https://github.com/Comfy-Org/workflow_templates/raw/refs/heads/main/templates/video_ltx2_depth_to_video.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_depth_to_video&utm_source=docs&utm_campaign=ltx_2">
  Open in cloud
</Card>

**Canny control:**

<Card title="Canny-to-Video" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_ltx2_canny_to_video.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_canny_to_video&utm_source=docs&utm_campaign=ltx_2">
  Open in cloud
</Card>

**Pose control:**

<Card title="Pose-to-Video" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_ltx2_pose_to_video.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=video_ltx2_pose_to_video&utm_source=docs&utm_campaign=ltx_2">
  Open in cloud
</Card>

## Prompting tips

When writing prompts for LTX-2, focus on detailed, chronological descriptions of actions and scenes. Include specific movements, appearances, camera angles, and environmental details in a single flowing paragraph. Start directly with the action and keep descriptions literal and precise.

Structure your prompts with:

* Main action in a single sentence
* Specific details about movements and gestures
* Character/object appearances
* Background and environment details
* Camera angles and movements
* Lighting and colors
* Any changes or sudden events

Keep prompts within 200 words for best results.

## Resources

* [GitHub Repository](https://github.com/Lightricks/LTX-2)
* [Hugging Face Model](https://huggingface.co/Lightricks/LTX-2)
* [LTX-2 Prompting Guide](https://ltx.video/blog/how-to-prompt-for-ltx-2)
* [ComfyUI-LTXVideo](https://github.com/Lightricks/ComfyUI-LTXVideo/)


# LTX-2.3 ComfyUI Workflow Examples
Source: https://docs.comfy.org/tutorials/video/ltx/ltx-2-3

Learn how to use LTX-2.3 in ComfyUI for enhanced audio-video generation with improved details and portrait support

[LTX-2.3](https://huggingface.co/Lightricks/LTX-2.3) is the latest evolution of Lightricks' open-source audio-video generation model, now natively supported in ComfyUI. Building on LTX-2, this release delivers major quality improvements across fine details, portrait video, audio, image-to-video, prompt understanding, and text rendering.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Key features

* **Finer details**: New latent space & updated VAE for sharper textures, cleaner edges, and more precise visuals
* **9:16 Portrait support**: Greatly improved quality for vertical portrait videos, perfect for social media & mobile
* **Better audio**: Cleaner sound with reduced noise, enhanced dialogue, music, and ambient audio
* **Improved image-to-video**: More consistent motion and fewer glitches, such as frozen frames, for smoother, more natural animations
* **Smarter prompt understanding**: Improved text encoder for more accurate interpretation of complex prompts
* **Clearer text rendering**: More accurate text and letter rendering in videos

## Getting started

LTX-2.3 is natively supported in ComfyUI. To get started:

1. Update ComfyUI to the latest version
2. Go to **Template Library** > **Video** > choose any LTX-2.3 workflow
3. Follow the pop-up to download models and run the workflow

## Workflows

### Image-to-video

Generate videos from an input image with more consistent motion and smoother animations.

<Card title="Image-to-Video" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_ltx2_3_i2v.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://links.comfy.org/4skdlDQ">
  Open in cloud
</Card>

### Text-to-video

Generate videos from text prompts with improved prompt understanding and text rendering.

<Card title="Text-to-Video" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_ltx2_3_t2v.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://links.comfy.org/4rZ1DyY">
  Open in cloud
</Card>

## Model downloads

### Checkpoints

| Name                | Description         | Download                                                                                               |
| ------------------- | ------------------- | ------------------------------------------------------------------------------------------------------ |
| ltx-2.3-22b-dev     | BF16 full model     | [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-22b-dev.safetensors)         |
| ltx-2.3-22b-dev-fp8 | FP8 quantized model | [Download](https://huggingface.co/Lightricks/LTX-2.3-fp8/resolve/main/ltx-2.3-22b-dev-fp8.safetensors) |

### LoRAs

| Name                           | Download                                                                                                      |
| ------------------------------ | ------------------------------------------------------------------------------------------------------------- |
| ltx-2.3-22b-distilled-lora-384 | [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-22b-distilled-lora-384.safetensors) |

### Latent upscale models

| Name                            | Download                                                                                                       |
| ------------------------------- | -------------------------------------------------------------------------------------------------------------- |
| ltx-2.3-spatial-upscaler-x2-1.0 | [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-spatial-upscaler-x2-1.0.safetensors) |

### Text encoders

| Name                          | Download                                                                                                                       |
| ----------------------------- | ------------------------------------------------------------------------------------------------------------------------------ |
| gemma\_3\_12B\_it\_fp4\_mixed | [Download](https://huggingface.co/Comfy-Org/ltx-2/resolve/main/split_files/text_encoders/gemma_3_12B_it_fp4_mixed.safetensors) |

## Model storage location

```
ComfyUI/
├── models/
│   ├── latent_upscale_models/
│   │   └── ltx-2.3-spatial-upscaler-x2-1.0.safetensors
│   ├── checkpoints/
│   │   ├── ltx-2.3-22b-dev-fp8.safetensors
│   │   └── ltx-2.3-22b-dev.safetensors
│   ├── loras/
│   │   └── ltx-2.3-22b-distilled-lora-384.safetensors
│   └── text_encoders/
│       └── gemma_3_12B_it_fp4_mixed.safetensors
```

## Resources

* [Hugging Face Model](https://huggingface.co/Lightricks/LTX-2.3)
* [GitHub Repository](https://github.com/Lightricks/LTX-2)
* [ComfyUI-LTXVideo](https://github.com/Lightricks/ComfyUI-LTXVideo/)


# LTX-0.9.5 ComfyUI Workflow Examples
Source: https://docs.comfy.org/tutorials/video/ltxv

Learn how to use LTX-Video 0.9.5 in ComfyUI for efficient video generation

[LTX-Video](https://huggingface.co/Lightricks/LTX-Video) is a very efficient video model by lightricks. The important thing with this model is to give it long descriptive prompts.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Multi Frame Control

Allows you to control the video with a series of images. You can download the input images: [starting frame](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/ltxv/multi-frame/house1.png) and [ending frame](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/ltxv/multi-frame/house2.png).

<img alt="LTX-Video Multi Frame Control" />

<Tip>
  Drag the video directly into ComfyUI to run the workflow.
</Tip>

## Image to Video

Allows you to control the video with a first [frame image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/ltxv/i2v/girl1.png).

<a href="https://cloud.comfy.org/?template=ltxv_image_to_video&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

<img alt="LTX-Video Image to Video" />

<Tip>
  Drag the video directly into ComfyUI to run the workflow.
</Tip>

## Text to Video

<img alt="LTX-Video Text to Video" />

<Tip>
  Drag the video directly into ComfyUI to run the workflow.
</Tip>

## Requirements

Download the following models and place them in the locations specified below:

* [ltx-video-2b-v0.9.5.safetensors](https://huggingface.co/Lightricks/LTX-Video/resolve/main/ltx-video-2b-v0.9.5.safetensors?download=true)
* [t5xxl\_fp16.safetensors](https://huggingface.co/Comfy-Org/mochi_preview_repackaged/resolve/main/split_files/text_encoders/t5xxl_fp16.safetensors?download=true)

```
├── checkpoints/
│   └── ltx-video-2b-v0.9.5.safetensors
└── text_encoders/
    └── t5xxl_fp16.safetensors
```


# Wan2.2 Animate ComfyUI native workflow
Source: https://docs.comfy.org/tutorials/video/wan/wan2-2-animate

Unified character animation and replacement framework with precise motion and expression replication.

Wan-Animate is a unified framework for character animation and replacement developed by the WAN Team.

The model can animate any character based on a performer’s video, precisely replicating the performer’s facial expressions and movements to generate highly realistic character videos.

It can also replace characters in a video with animated characters, preserving their expressions and movements while replicating the original lighting and color tone for seamless environmental integration.

## Model Highlights

* Dual Mode Functionality: A single architecture supports both animation and replacement functions, enabling easy operation switching.
* Advanced Body Motion Control: Uses spatially-aligned skeleton signals for accurate body movement replication
* Precise Motion and Expression: Accurately reproduces the movements and facial expressions from the reference video.
* Natural Environment Integration: Seamlessly blends the replaced character with the original video environment.
* Smooth Long Video Generation: Iterative generation ensures consistent motion and visual flow in extended videos

## ComfyOrg Wan2.2 Animate stream replay

<iframe title="Wan 2.2 Animate in ComfyUI with Flipping Sigmas / September 19th, 2025" />

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## About Wan2.2 Animate workflow

In this docs, we will provide two workflow:

1. Workflow that only uses core nodes (It is incomplete; you need to preprocess the image by yourself first)
2. Workflow that includes some custom nodes (It is complete; you can use it directly, but some new user might not know how to install the custom nodes)

## Wan2.2 Anmate ComfyUI native workflow(without custom nodes)

### 1. Download Workflow File

Download the following workflow file and drag it into ComfyUI to load the workflow.

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_wan2_2_14B_animate.json">
  <p>Download JSON Workflow</p>
</a>

<a href="https://cloud.comfy.org/?template=video_wan2_2_14B_animate&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

Download materials below as input:

**Reference Image:**
![Reference\_Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/wan2.2_animate/ref_image.png)

**Input Video**

<video />

### 2. Model links

**diffusion\_models**

* [Wan2\_2-Animate-14B\_fp8\_e4m3fn\_scaled\_KJ.safetensors](https://huggingface.co/Kijai/WanVideo_comfy_fp8_scaled/resolve/main/Wan22Animate/Wan2_2-Animate-14B_fp8_e4m3fn_scaled_KJ.safetensors) This is the model that from Kijai's repo
* [wan2.2\_animate\_14B\_bf16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_animate_14B_bf16.safetensors) original model weight

**clip\_visions**

* [clip\_vision\_h.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors)

**loras**

* [lightx2v\_I2V\_14B\_480p\_cfg\_step\_distill\_rank64\_bf16.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/resolve/main/Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors) 这是一个 4 步的加速 lora

**vae**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors)

**text\_encoders**

* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── Wan2_2-Animate-14B_fp8_e4m3fn_scaled_KJ.safetensors
│   │   └─── wan2.2_animate_14B_bf16.safetensors
│   ├───📂 loras/
│   │   └─── lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   ├───📂 clip_visions/ 
│   │   └─── clip_vision_h.safetensors
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Install custom nodes

Download the following workflow file and drag it into ComfyUI to load the workflow, if you have [ComfyUI-Manager](https://github.com/Comfy-Org/ComfyUI-Manager) installed, you can just click the `Install missing nodes` button to install the missing nodes.

We need to install the following custom nodes:

* [ComfyUI-KJNodes](https://github.com/kijai/ComfyUI-KJNodes)
* [ComfyUI-comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux)

If you don't know how to install custom nodes please refer to [How to install custom nodes](/installation/install_custom_node)

### 4. Workflow Instructions

The Wan2.2 animate has two modes: Mix and move

* Mix: use the reference image to replace the character in the video
* Move: Use the character movement from the input video to animate the character in the reference image (like Wan2.2 Fun Control)

#### 4.1 Mix mode

<img alt="Workflow Instructions" />

0. If you are running this workflow for the first time, please use a small size for video generation, in case you don't have enough VRAM to run the workflow, and due to the `WanAnimateToVideo` limited, the video width or height should be multiples of 16.
1. Make sure all the models are loaded correctly
2. Update the prompt if you want
3. Upload the reference image, the character is this image will be the target character
4. You can use the videos we provided as input videos for the first time， the **DWPose Estimator** node  in [comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) will preprocess the input video to pose and face control videos
5. The `Points Editor` is from [KJNodes](https://github.com/kijai/ComfyUI-KJNodes/), by default this node will not load the first frame from the input video, you need to run the workflow once or manually upload the first frame
   * Below the `Points Editor` node, we have added a note about how this node works, and how to edit it. Please refer to it
6. For the "Video Extend" group, it's in order to extend to the output video length
   * Each `Video Extend` will extend another 77 frames(Around 4.8125 seconds)
   * If your input video is less than 5s, you might not need it
   * If you want to extend longer, you need to copy and paste multiple times, you need to link the `batch_images` from last Video Extend to next one, and also the `video_frame_offset` from last Video Extend to next one
7. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation

#### 4.2 Move mode

We used [subgraph](/interface/features/subgraph) in the Wan2.2 animate workflow, here is how to switching to move mode:

<img alt="Subgraph" />

If you want to switch to Move mode, you can disconnect `background_video` and `character_mask` inputs from the `Video Sampling and output(Subgraph)` node.


# Wan2.2-S2V Audio-Driven Video Generation ComfyUI Native Workflow Example
Source: https://docs.comfy.org/tutorials/video/wan/wan2-2-s2v

This is a native workflow example for Wan2.2-S2V audio-driven video generation in ComfyUI.

We're excited to announce that Wan2.2-S2V, the advanced audio-driven video generation model, is now natively supported in ComfyUI! This powerful AI model can transform static images and audio inputs into dynamic video content, supporting dialogue, singing, performance, and various creative content needs.

**Model Highlights**

* **Audio-Driven Video Generation**: Transforms static images and audio into synchronized videos
* **Cinematic-Grade Quality**: Generates film-quality videos with natural expressions and movements
* **Minute-Level Generation**: Supports long-form video creation
* **Multi-Format Support**: Works with full-body and half-body characters
* **Enhanced Motion Control**: Generates actions and environments from text instructions

Wan2.2 S2V Code: [GitHub](https://github.com/aigc-apps/VideoX-Fun)
Wan2.2 S2V Model: [Hugging Face](https://huggingface.co/Wan-AI/Wan2.2-S2V-14B)

## Wan2.2 S2V ComfyUI Native Workflow

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### 1. Download Workflow File

Download the following workflow file and drag it into ComfyUI to load the workflow.

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_wan2_2_14B_s2v.json">
  <p>Download JSON Workflow</p>
</a>

<a href="https://cloud.comfy.org/?template=video_wan2_2_14B_s2v&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

Download the following image and audio as input:
![input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/wan2.2_s2v/input.jpg)

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/wan2.2_s2v/input_audio.MP3">
  <p>Download Input  Audio</p>
</a>

### 2. Model Links

You can find the models in [our repo](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged)

**diffusion\_models**

* [wan2.2\_s2v\_14B\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_s2v_14B_fp8_scaled.safetensors)
* [wan2.2\_s2v\_14B\_bf16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_s2v_14B_bf16.safetensors)

**audio\_encoders**

* [wav2vec2\_large\_english\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/audio_encoders/wav2vec2_large_english_fp16.safetensors)

**vae**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors)

**text\_encoders**

* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_s2v_14B_fp8_scaled.safetensors
│   │   └─── wan2.2_s2v_14B_bf16.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   ├───📂 audio_encoders/ # Create one if you can't find this folder
│   │   └─── wav2vec2_large_english_fp16.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Workflow Instructions

<img alt="Workflow Instructions" />

#### 3.1 About Lightning LoRA

#### 3.2 About fp8\_scaled and bf16 Models

You can find both models [here](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/main/split_files/diffusion_models):

* [wan2.2\_s2v\_14B\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_s2v_14B_fp8_scaled.safetensors)
* [wan2.2\_s2v\_14B\_bf16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_s2v_14B_bf16.safetensors)

This template uses `wan2.2_s2v_14B_fp8_scaled.safetensors`, which requires less VRAM. But you can try `wan2.2_s2v_14B_bf16.safetensors` to reduce quality degradation.

#### 3.3 Step-by-Step Operation Instructions

**Step 1: Load Models**

1. **Load Diffusion Model**: Load `wan2.2_s2v_14B_fp8_scaled.safetensors` or `wan2.2_s2v_14B_bf16.safetensors`
   * The provided workflow uses `wan2.2_s2v_14B_fp8_scaled.safetensors`, which requires less VRAM
   * But you can try `wan2.2_s2v_14B_bf16.safetensors` to reduce quality degradation

2. **Load CLIP**: Load `umt5_xxl_fp8_e4m3fn_scaled.safetensors`

3. **Load VAE**: Load `wan_2.1_vae.safetensors`

4. **AudioEncoderLoader**: Load `wav2vec2_large_english_fp16.safetensors`

5. **LoraLoaderModelOnly**: Load `wan2.2_t2v_lightx2v_4steps_lora_v1.1_high_noise.safetensors` (Lightning LoRA)
   * We tested all wan2.2 lightning LoRAs. Since this is not a LoRA specifically trained for Wan2.2 S2V, many key values don't match, but we added it because it significantly reduces generation time. We will continue to optimize this template
   * Using it will cause significant dynamic and quality loss
   * If you find the output quality too poor, you can try the original 20-step workflow

6. **LoadAudio**: Upload our provided audio file or your own audio

7. **Load Image**: Upload reference image

8. **Batch sizes**: Set according to the number of Video S2V Extend subgraph nodes you add
   * Each Video S2V Extend subgraph adds 77 frames to the final output
   * For example: If you added 2 Video S2V Extend subgraphs, the batch size should be 3, which means the total number of sampling iterations
   * **Chunk Length**: Keep the default value of 77

9. **Sampler Settings**: Choose different settings based on whether you use Lightning LoRA
   * With 4-step Lightning LoRA: steps: 4, cfg: 1.0
   * Without 4-step Lightning LoRA: steps: 20, cfg: 6.0

10. **Size Settings**: Set the output video dimensions

11. **Video S2V Extend**: Video extension subgraph nodes. Since our default frames per sampling is 77, and this is a 16fps model, each extension will generate 77 / 16 = 4.8125 seconds of video
    * You need some calculation to match the number of video extension subgraph nodes with the input audio length. For example: If input audio is 14s, the total frames needed are 14x16=224, each video extension is 77 frames, so you need 224/77 = 2.9, rounded up to 3 video extension subgraph nodes

12. Use Ctrl-Enter or click the Run button to execute the workflow


# Wan2.2 Video Generation ComfyUI Official Native Workflow Example
Source: https://docs.comfy.org/tutorials/video/wan/wan2_2

Official usage guide for Alibaba Cloud Tongyi Wanxiang 2.2 video generation model in ComfyUI

<iframe title="ComfyUI Selection Toolbox New Features" />

Wan 2.2 is a new generation multimodal generative model launched by WAN AI. This model adopts an innovative MoE (Mixture of Experts) architecture, consisting of high-noise and low-noise expert models. It can divide expert models according to denoising timesteps, thus generating higher quality video content.

Wan 2.2 has three core features: cinematic-level aesthetic control, deeply integrating professional film industry aesthetic standards, supporting multi-dimensional visual control such as lighting, color, and composition; large-scale complex motion, easily restoring various complex motions and enhancing the smoothness and controllability of motion; precise semantic compliance, excelling in complex scenes and multi-object generation, better restoring users' creative intentions.
The model supports multiple generation modes such as text-to-video and image-to-video, suitable for content creation, artistic creation, education and training, and other application scenarios.

[Wan2.2 Prompt Guide](https://alidocs.dingtalk.com/i/nodes/EpGBa2Lm8aZxe5myC99MelA2WgN7R35y)

## Model Highlights

* **Cinematic-level Aesthetic Control**: Professional camera language, supports multi-dimensional visual control such as lighting, color, and composition
* **Large-scale Complex Motion**: Smoothly restores various complex motions, enhances motion controllability and naturalness
* **Precise Semantic Compliance**: Complex scene understanding, multi-object generation, better restoring creative intentions
* **Efficient Compression Technology**: 5B version with high compression ratio VAE, memory optimization, supports mixed training

## Wan2.2 Open Source Model Versions

The Wan2.2 series models are based on the Apache 2.0 open source license and support commercial use. The Apache 2.0 license allows you to freely use, modify, and distribute these models, including for commercial purposes, as long as you retain the original copyright notice and license text.

| Model Type     | Model Name      | Parameters | Main Function                                                                                                                | Model Repository                                                    |
| -------------- | --------------- | ---------- | ---------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------- |
| Hybrid Model   | Wan2.2-TI2V-5B  | 5B         | Hybrid version supporting both text-to-video and image-to-video, a single model meets two core task requirements             | 🤗 [Wan2.2-TI2V-5B](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B)   |
| Image-to-Video | Wan2.2-I2V-A14B | 14B        | Converts static images into dynamic videos, maintaining content consistency and smooth dynamic process                       | 🤗 [Wan2.2-I2V-A14B](https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B) |
| Text-to-Video  | Wan2.2-T2V-A14B | 14B        | Generates high-quality videos from text descriptions, with cinematic-level aesthetic control and precise semantic compliance | 🤗 [Wan2.2-T2V-A14B](https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B) |

## ComfyOrg Wan2.2 Live Streams

For ComfyUI Wan2.2 usage, we have conducted live streams, which you can view to learn how to use them.

<iframe title="ComfyUI Wan2.2 Live Streams" />

<iframe title="ComfyUI Wan2.2 Deep Dive" />

<iframe title="ComfyUI Wan2.2 Deep Dive #2" />

This tutorial will use the [🤗 Comfy-Org/Wan\_2.2\_ComfyUI\_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged) version.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<img alt="Wan2.2 template" />

## Wan2.2 TI2V 5B Hybrid Version Workflow Example

<Tip>
  The Wan2.2 5B version should fit well on 8GB vram with the ComfyUI native offloading.
</Tip>

### 1. Download Workflow File

Please update your ComfyUI to the latest version, and through the menu `Workflow` -> `Browse Templates` -> `Video`, find "Wan2.2 5B video generation" to load the workflow.

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_wan2_2_5B_ti2v.json">
  <p>Download JSON Workflow File</p>
</a>

<a href="https://cloud.comfy.org/?template=video_wan2_2_5B_ti2v&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 2. Manually Download Models

**Diffusion Model**

* [wan2.2\_ti2v\_5B\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_ti2v_5B_fp16.safetensors)

**VAE**

* [wan2.2\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/vae/wan2.2_vae.safetensors)

**Text Encoder**

* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   └───wan2.2_ti2v_5B_fp16.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   └───📂 vae/
│       └── wan2.2_vae.safetensors
```

### 3. Follow the Steps

<img alt="Step Diagram" />

1. Ensure the `Load Diffusion Model` node loads the `wan2.2_ti2v_5B_fp16.safetensors` model.
2. Ensure the `Load CLIP` node loads the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model.
3. Ensure the `Load VAE` node loads the `wan2.2_vae.safetensors` model.
4. (Optional) If you need to perform image-to-video generation, you can use the shortcut Ctrl+B to enable the `Load image` node to upload an image.
5. (Optional) In the `Wan22ImageToVideoLatent` node, you can adjust the size settings and the total number of video frames (`length`).
6. (Optional) If you need to modify the prompts (positive and negative), please do so in the `CLIP Text Encoder` node at step 5.
7. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.

## Wan2.2 14B T2V Text-to-Video Workflow Example

### 1. Workflow File

Please update your ComfyUI to the latest version, and through the menu `Workflow` -> `Browse Templates` -> `Video`, find "Wan2.2 14B T2V" to load the workflow.

Or update your ComfyUI to the latest version, then download the following video and drag it into ComfyUI to load the workflow.

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_wan2_2_14B_t2v.json">
  <p>Download JSON Workflow File</p>
</a>

<a href="https://cloud.comfy.org/?template=video_wan2_2_14B_t2v&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 2. Manually Download Models

**Diffusion Model**

* [wan2.2\_t2v\_high\_noise\_14B\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors)
* [wan2.2\_t2v\_low\_noise\_14B\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors)

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors)

**Text Encoder**

* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors
│   │   └─── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Follow the Steps

<img alt="Step Diagram" />

1. Ensure the first `Load Diffusion Model` node loads the `wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors` model.
2. Ensure the second `Load Diffusion Model` node loads the `wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors` model.
3. Ensure the `Load CLIP` node loads the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model.
4. Ensure the `Load VAE` node loads the `wan_2.1_vae.safetensors` model.
5. (Optional) In the `EmptyHunyuanLatentVideo` node, you can adjust the size settings and the total number of video frames (`length`).
6. (Optional) If you need to modify the prompts (positive and negative), please do so in the `CLIP Text Encoder` node at step 5.
7. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.

## Wan2.2 14B I2V Image-to-Video Workflow Example

### 1. Workflow File

Please update your ComfyUI to the latest version, and through the menu `Workflow` -> `Browse Templates` -> `Video`, find "Wan2.2 14B I2V" to load the workflow.

Or update your ComfyUI to the latest version, then download the following video and drag it into ComfyUI to load the workflow.

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_wan2_2_14B_i2v.json">
  <p>Download JSON Workflow File</p>
</a>

<a href="https://cloud.comfy.org/?template=video_wan2_2_14B_i2v&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

You can use the following image as input:
![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/2.2/input.jpg)

### 2. Manually Download Models

**Diffusion Model**

* [wan2.2\_i2v\_high\_noise\_14B\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_i2v_high_noise_14B_fp16.safetensors)
* [wan2.2\_i2v\_low\_noise\_14B\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_i2v_low_noise_14B_fp16.safetensors)

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors)

**Text Encoder**

* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_i2v_low_noise_14B_fp16.safetensors
│   │   └─── wan2.2_i2v_high_noise_14B_fp16.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Follow the Steps

<img alt="Step Diagram" />

1. Make sure the first `Load Diffusion Model` node loads the `wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors` model.
2. Make sure the second `Load Diffusion Model` node loads the `wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors` model.
3. Make sure the `Load CLIP` node loads the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model.
4. Make sure the `Load VAE` node loads the `wan_2.1_vae.safetensors` model.
5. In the `Load Image` node, upload the image to be used as the initial frame.
6. If you need to modify the prompts (positive and negative), do so in the `CLIP Text Encoder` node at step 6.
7. (Optional) In `EmptyHunyuanLatentVideo`, you can adjust the size settings and the total number of video frames (`length`).
8. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.

## Wan2.2 14B FLF2V Workflow Example

The first and last frame workflow uses the same model locations as the I2V section.

### 1. Workflow and Input Material Preparation

Download the video or the JSON workflow below and open it in ComfyUI.

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_wan2_2_14B_flf2v.json">
  <p>Download JSON Workflow</p>
</a>

<a href="https://cloud.comfy.org/?template=video_wan2_2_14B_flf2v&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

Download the following images as input materials:

![Input Material](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/2.2/wan22_14B_flf2v_start_image.png)
![Input Material](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/2.2/wan22_14B_flf2v_end_image.png)

### 2. Follow the Steps

<img alt="Step Diagram" />

1. Upload the image to be used as the starting frame in the first `Load Image` node.
2. Upload the image to be used as the ending frame in the second `Load Image` node.
3. Adjust the size settings in the `WanFirstLastFrameToVideo` node.
   * By default, a relatively small size is set to prevent low VRAM users from consuming too many resources.
   * If you have enough VRAM, you can try a resolution around 720P.
4. Write appropriate prompts according to your first and last frames.
5. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.

## Community Resources

### GGUF Versions

* [bullerwins/Wan2.2-I2V-A14B-GGUF/](https://huggingface.co/bullerwins/Wan2.2-I2V-A14B-GGUF/)
* [bullerwins/Wan2.2-T2V-A14B-GGUF](https://huggingface.co/bullerwins/Wan2.2-T2V-A14B-GGUF)
* [QuantStack/Wan2.2 GGUFs](https://huggingface.co/collections/QuantStack/wan22-ggufs-6887ec891bdea453a35b95f3)

**Custom Node**
[City96/ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF)

### WanVideoWrapper

[Kijai/ComfyUI-WanVideoWrapper](https://github.com/kijai/ComfyUI-WanVideoWrapper)

**Wan2.2 models**
[Kijai/WanVideo\_comfy\_fp8\_scaled](https://hf-mirror.com/Kijai/WanVideo_comfy_fp8_scaled)

**Wan2.1 models**
[Kijai/WanVideo\_comfy/Lightx2v](https://huggingface.co/Kijai/WanVideo_comfy/tree/main/Lightx2v)

**Lightx2v 4steps LoRA**

* [Wan2.2-T2V-A14B-4steps-lora-rank64-V1](https://huggingface.co/lightx2v/Wan2.2-Lightning/tree/main/Wan2.2-T2V-A14B-4steps-lora-rank64-V1)


# MeshyAnimateModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyAnimateModelNode

Complete documentation for the MeshyAnimateModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyAnimateModelNode/en.md)

This node applies a specific animation to a 3D character model that has already been rigged using the Meshy service. It takes a task ID from a previous rigging operation and an action ID to select the desired animation from the library. The node then processes the request and returns the animated model in both GLB and FBX file formats.

## Inputs

| Parameter     | Data Type | Required | Range    | Description                                                                                                                                                                                         |
| ------------- | --------- | -------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `rig_task_id` | STRING    | Yes      | N/A      | The unique task ID from a previously completed Meshy character rigging operation.                                                                                                                   |
| `action_id`   | INT       | Yes      | 0 to 696 | The ID number of the animation action to apply. Visit [https://docs.meshy.ai/en/api/animation-library](https://docs.meshy.ai/en/api/animation-library) for a list of available values. (default: 0) |

## Outputs

| Output Name  | Data Type | Description                                                                                          |
| ------------ | --------- | ---------------------------------------------------------------------------------------------------- |
| `model_file` | STRING    | A string identifier for the animated model. This output is provided for backward compatibility only. |
| `GLB`        | FILE3DGLB | The animated 3D model file in GLB format.                                                            |
| `FBX`        | FILE3DFBX | The animated 3D model file in FBX format.                                                            |

***

**Source fingerprint (SHA-256):** `0af4e96d031025fdb5e11d6dd35e408b61dcdd4ca64f88464a6510426485dac2`


# MeshyImageToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyImageToModelNode

Complete documentation for the MeshyImageToModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyImageToModelNode/en.md)

The Meshy: Image to Model node uses the Meshy API to generate a 3D model from a single input image. It uploads your image, submits a processing task, and returns the generated 3D model files (GLB and FBX) along with the task ID for reference.

## Inputs

| Parameter          | Data Type     | Required | Range                                        | Description                                                                                                                                                                                   |
| ------------------ | ------------- | -------- | -------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`            | COMBO         | Yes      | `"latest"`                                   | Specifies the AI model version to use for generation.                                                                                                                                         |
| `image`            | IMAGE         | Yes      | -                                            | The input image to convert into a 3D model.                                                                                                                                                   |
| `should_remesh`    | DYNAMIC COMBO | Yes      | `"true"`<br />`"false"`                      | Determines if the generated mesh should be processed. When set to `"false"`, the node returns an unprocessed triangular mesh.                                                                 |
| `topology`         | COMBO         | No\*     | `"triangle"`<br />`"quad"`                   | The target polygon topology for the remeshed model. This input is only available when `should_remesh` is set to `"true"`.                                                                     |
| `target_polycount` | INT           | No\*     | 100 - 300000                                 | The target number of polygons for the remeshed model. This input is only available when `should_remesh` is set to `"true"`. The default value is 300000.                                      |
| `symmetry_mode`    | COMBO         | Yes      | `"auto"`<br />`"on"`<br />`"off"`            | Controls the symmetry applied to the generated 3D model.                                                                                                                                      |
| `should_texture`   | DYNAMIC COMBO | Yes      | `"true"`<br />`"false"`                      | Determines whether textures are generated for the model. Setting it to `"false"` skips the texture phase and returns a mesh without textures.                                                 |
| `enable_pbr`       | BOOLEAN       | No\*     | -                                            | When `should_texture` is `"true"`, this option generates PBR maps (metallic, roughness, normal) in addition to the base color. The default value is `False`.                                  |
| `texture_prompt`   | STRING        | No\*     | -                                            | A text prompt to guide the texturing process (maximum 600 characters). This input is only available when `should_texture` is `"true"`. It cannot be used at the same time as `texture_image`. |
| `texture_image`    | IMAGE         | No\*     | -                                            | An image to guide the texturing process. This input is only available when `should_texture` is `"true"`. It cannot be used at the same time as `texture_prompt`.                              |
| `pose_mode`        | COMBO         | Yes      | `""` (empty)<br />`"A-pose"`<br />`"T-pose"` | Specifies the pose mode for the generated model. This is an advanced parameter.                                                                                                               |
| `seed`             | INT           | Yes      | 0 - 2147483647                               | A seed value for the generation process. The results are non-deterministic regardless of the seed value. The default value is 0.                                                              |

**Note on Parameter Constraints:**

* The `topology` and `target_polycount` inputs are only available when `should_remesh` is set to `"true"`.
* The `enable_pbr`, `texture_prompt`, and `texture_image` inputs are only available when `should_texture` is set to `"true"`.
* You cannot use `texture_prompt` and `texture_image` at the same time. If both are provided when `should_texture` is `"true"`, the node will raise an error.

## Outputs

| Output Name     | Data Type       | Description                                                                                       |
| --------------- | --------------- | ------------------------------------------------------------------------------------------------- |
| `model_file`    | STRING          | The filename of the generated GLB model. (Maintained for backward compatibility).                 |
| `meshy_task_id` | MESHY\_TASK\_ID | The unique identifier for the Meshy API task, which can be used for reference or troubleshooting. |
| `GLB`           | FILE3DGLB       | The generated 3D model in the GLB file format.                                                    |
| `FBX`           | FILE3DFBX       | The generated 3D model in the FBX file format.                                                    |

***

**Source fingerprint (SHA-256):** `87825d9d78ccfb1efdf07da0e9c8cfca39a8446dd99d346c732e4d1470194205`


# MeshyMultiImageToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyMultiImageToModelNode

Complete documentation for the MeshyMultiImageToModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyMultiImageToModelNode/en.md)

This node uses the Meshy API to generate a 3D model from multiple input images. It uploads the provided images, submits a processing task, and returns the resulting 3D model files (GLB and FBX) along with the task ID for reference.

## Inputs

| Parameter          | Data Type | Required | Range                                        | Description                                                                                                                                                                                           |
| :----------------- | :-------- | :------- | :------------------------------------------- | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`            | COMBO     | Yes      | `"latest"`                                   | Specifies the AI model version to use.                                                                                                                                                                |
| `images`           | IMAGE     | Yes      | 2 to 4 images                                | A set of images used to generate the 3D model. You must provide between 2 and 4 images.                                                                                                               |
| `should_remesh`    | COMBO     | Yes      | `"true"`<br />`"false"`                      | Determines if the generated mesh should be processed. When set to `"false"`, the node returns an unprocessed triangular mesh.                                                                         |
| `topology`         | COMBO     | No       | `"triangle"`<br />`"quad"`                   | The target polygon type for the remeshed output. This parameter is only available and required when `should_remesh` is set to `"true"`.                                                               |
| `target_polycount` | INT       | No       | 100 to 300000                                | The target number of polygons for the remeshed model (default: 300000). This parameter is only available when `should_remesh` is set to `"true"`.                                                     |
| `symmetry_mode`    | COMBO     | Yes      | `"auto"`<br />`"on"`<br />`"off"`            | Controls whether symmetry is applied to the generated model.                                                                                                                                          |
| `should_texture`   | COMBO     | Yes      | `"true"`<br />`"false"`                      | Determines whether textures are generated. Setting it to `"false"` skips the texture phase and returns a mesh without textures.                                                                       |
| `enable_pbr`       | BOOLEAN   | No       | True / False                                 | When `should_texture` is `"true"`, this option generates PBR Maps (metallic, roughness, normal) in addition to the base color (default: False).                                                       |
| `texture_prompt`   | STRING    | No       | -                                            | A text prompt to guide the texturing process (maximum 600 characters). Cannot be used at the same time as `texture_image`. This parameter is only available when `should_texture` is set to `"true"`. |
| `texture_image`    | IMAGE     | No       | -                                            | An image to guide the texturing process. Only one of `texture_image` or `texture_prompt` may be used at the same time. This parameter is only available when `should_texture` is set to `"true"`.     |
| `pose_mode`        | COMBO     | Yes      | `""` (empty)<br />`"A-pose"`<br />`"T-pose"` | Specifies the pose mode for the generated model.                                                                                                                                                      |
| `seed`             | INT       | Yes      | 0 to 2147483647                              | A seed value for the generation process (default: 0). Results are non-deterministic regardless of the seed, but changing the seed can trigger the node to re-run.                                     |

**Parameter Constraints:**

* You must provide between 2 and 4 images for the `images` input.
* The `topology` and `target_polycount` parameters are only active when `should_remesh` is set to `"true"`.
* The `enable_pbr`, `texture_prompt`, and `texture_image` parameters are only active when `should_texture` is set to `"true"`.
* You cannot use `texture_prompt` and `texture_image` at the same time; they are mutually exclusive.

## Outputs

| Output Name     | Data Type       | Description                                                                                  |
| :-------------- | :-------------- | :------------------------------------------------------------------------------------------- |
| `model_file`    | STRING          | The filename of the generated GLB model. This output is provided for backward compatibility. |
| `meshy_task_id` | MESHY\_TASK\_ID | The unique identifier for the Meshy API task.                                                |
| `GLB`           | FILE3DGLB       | The generated 3D model in GLB format.                                                        |
| `FBX`           | FILE3DFBX       | The generated 3D model in FBX format.                                                        |

***

**Source fingerprint (SHA-256):** `7118368e2d9c1a7df9866d19a033c6e2efd632381624a9ee537552502185d444`


# MeshyRefineNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyRefineNode

Complete documentation for the MeshyRefineNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyRefineNode/en.md)

The Meshy: Refine Draft Model node takes a previously generated 3D draft model and improves its quality, optionally adding textures. It submits a refinement task to the Meshy API and returns the final 3D model files once processing is complete.

## Inputs

| Parameter        | Data Type       | Required | Range      | Description                                                                                                                                                                                                           |
| ---------------- | --------------- | -------- | ---------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`          | COMBO           | Yes      | `"latest"` | Specifies the AI model to use for refinement. Currently, only the "latest" model is available.                                                                                                                        |
| `meshy_task_id`  | MESHY\_TASK\_ID | Yes      | -          | The unique task ID of the draft model you want to refine.                                                                                                                                                             |
| `enable_pbr`     | BOOLEAN         | No       | -          | Generate PBR Maps (metallic, roughness, normal) in addition to the base color. Note: this should be set to false when using Sculpture style, as Sculpture style generates its own set of PBR maps. (default: `False`) |
| `texture_prompt` | STRING          | No       | -          | Provide a text prompt to guide the texturing process. Maximum 600 characters. Cannot be used at the same time as `texture_image`. (default: empty string)                                                             |
| `texture_image`  | IMAGE           | No       | -          | Only one of `texture_image` or `texture_prompt` may be used at the same time.                                                                                                                                         |

**Note:** The `texture_prompt` and `texture_image` inputs are mutually exclusive. You cannot provide both a text prompt and an image for texturing in the same operation.

## Outputs

| Output Name     | Data Type       | Description                                                                |
| --------------- | --------------- | -------------------------------------------------------------------------- |
| `model_file`    | STRING          | The filename of the generated GLB model. (For backward compatibility only) |
| `meshy_task_id` | MESHY\_TASK\_ID | The unique task ID for the submitted refinement job.                       |
| `GLB`           | FILE3DGLB       | The final refined 3D model in GLB format.                                  |
| `FBX`           | FILE3DFBX       | The final refined 3D model in FBX format.                                  |

***

**Source fingerprint (SHA-256):** `b1cfdeb12d1f79c4c18f96b4f8a92de227210e369b22356fe7232e025956696e`


# MeshyRigModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyRigModelNode

Complete documentation for the MeshyRigModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyRigModelNode/en.md)

The Meshy: Rig Model node takes a 3D model from a previous Meshy task and automatically creates a skeleton for it, producing a rigged character that can be posed and animated. The node outputs the rigged model in both GLB and FBX file formats.

## Inputs

| Parameter       | Data Type | Required | Range       | Description                                                                                                                 |
| --------------- | --------- | -------- | ----------- | --------------------------------------------------------------------------------------------------------------------------- |
| `meshy_task_id` | STRING    | Yes      | N/A         | The unique task ID from a previous Meshy operation (e.g., text-to-3D or image-to-3D) that generated the model to be rigged. |
| `height_meters` | FLOAT     | Yes      | 0.1 to 15.0 | The approximate height of the character model in meters. This aids in scaling and rigging accuracy (default: 1.7).          |
| `texture_image` | IMAGE     | No       | N/A         | The model's UV-unwrapped base color texture image.                                                                          |

**Note:** The auto-rigging process is currently not suitable for untextured meshes, non-humanoid assets, or humanoid assets with unclear limb and body structure.

## Outputs

| Output Name   | Data Type | Description                                                                               |
| ------------- | --------- | ----------------------------------------------------------------------------------------- |
| `model_file`  | STRING    | A legacy output for backward compatibility, containing the filename of the GLB model.     |
| `rig_task_id` | STRING    | The unique task ID for this rigging operation, which can be used to reference the result. |
| `GLB`         | FILE3DGLB | The rigged 3D character model saved in the GLB file format.                               |
| `FBX`         | FILE3DFBX | The rigged 3D character model saved in the FBX file format.                               |

***

**Source fingerprint (SHA-256):** `de47454600293b647fd6e244ad7e53de66169bb0d2b65df517a85bc6bc3ee6e0`


# MeshyTextToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyTextToModelNode

Complete documentation for the MeshyTextToModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyTextToModelNode/en.md)

The Meshy: Text to Model node uses the Meshy API to generate a 3D model from a text description. It sends a request to the API with your prompt and settings, then waits for the generation to complete and downloads the resulting model files.

## Inputs

| Parameter          | Data Type     | Required | Range                                | Description                                                                                                                                                                                        |
| ------------------ | ------------- | -------- | ------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`            | COMBO         | Yes      | `"latest"`                           | Specifies the AI model version to use. Currently, only the "latest" version is available.                                                                                                          |
| `prompt`           | STRING        | Yes      | -                                    | The text description of the 3D model you want to generate. Must be between 1 and 600 characters long.                                                                                              |
| `style`            | COMBO         | Yes      | `"realistic"`<br />`"sculpture"`     | The artistic style for the generated 3D model.                                                                                                                                                     |
| `should_remesh`    | DYNAMIC COMBO | Yes      | `"true"`<br />`"false"`              | Controls whether the generated mesh is processed. When set to "false", the node returns an unprocessed triangular mesh. Selecting "true" reveals additional parameters for topology and polycount. |
| `topology`         | COMBO         | No\*     | `"triangle"`<br />`"quad"`           | The target polygon type for the remeshed model. This parameter is only available and required when `should_remesh` is set to "true".                                                               |
| `target_polycount` | INT           | No\*     | 100 - 300000                         | The target number of polygons for the remeshed model. Default is 300000. This parameter is only available and required when `should_remesh` is set to "true".                                      |
| `symmetry_mode`    | COMBO         | Yes      | `"auto"`<br />`"on"`<br />`"off"`    | Controls symmetry in the generated model.                                                                                                                                                          |
| `pose_mode`        | COMBO         | Yes      | `""`<br />`"A-pose"`<br />`"T-pose"` | Specifies the pose mode for the generated model. An empty string means no specific pose is requested.                                                                                              |
| `seed`             | INT           | Yes      | 0 - 2147483647                       | A seed value for generation. Setting this controls whether the node should re-run, but results are non-deterministic regardless of the seed value. Default is 0.                                   |

\*Note: The `topology` and `target_polycount` parameters are conditionally required. They only appear and must be set when the `should_remesh` parameter is set to "true".

## Outputs

| Output Name     | Data Type       | Description                                                                                  |
| --------------- | --------------- | -------------------------------------------------------------------------------------------- |
| `model_file`    | STRING          | The filename of the generated GLB model. This output is provided for backward compatibility. |
| `meshy_task_id` | MESHY\_TASK\_ID | The unique identifier for the Meshy API task.                                                |
| `GLB`           | FILE3DGLB       | The generated 3D model file in GLB format.                                                   |
| `FBX`           | FILE3DFBX       | The generated 3D model file in FBX format.                                                   |

***

**Source fingerprint (SHA-256):** `4b02709a29d3df85e0ab1741b46d3ac74b0fe04135afa435f882b5a02114cc97`


# MeshyTextureNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MeshyTextureNode

Complete documentation for the MeshyTextureNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MeshyTextureNode/en.md)

The Meshy: Texture Node applies AI-generated textures to a 3D model. It takes a task ID from a previous Meshy 3D generation or conversion node and uses either a text description or a reference image to create new textures for the model. The node outputs the textured model in GLB and FBX file formats.

## Inputs

| Parameter            | Data Type       | Required | Range      | Description                                                                                                                                                                                                                                 |
| -------------------- | --------------- | -------- | ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`              | COMBO           | Yes      | `"latest"` | The AI model version to use for texturing. Currently, only the "latest" version is available.                                                                                                                                               |
| `meshy_task_id`      | MESHY\_TASK\_ID | Yes      | -          | The unique identifier (task ID) from a previous Meshy 3D generation or conversion task. This provides the base 3D model to be textured.                                                                                                     |
| `enable_original_uv` | BOOLEAN         | No       | -          | Use the original UV of the model instead of generating new UVs. When enabled (default: `True`), Meshy preserves existing textures from the uploaded model. If the model has no original UV, the quality of the output might not be as good. |
| `pbr`                | BOOLEAN         | No       | -          | Enables Physically Based Rendering (PBR) material output for the textured model (default: `False`).                                                                                                                                         |
| `text_style_prompt`  | STRING          | No       | -          | Describe your desired texture style of the object using text. Maximum 600 characters. Cannot be used at the same time as `image_style`.                                                                                                     |
| `image_style`        | IMAGE           | No       | -          | A 2D image to guide the texturing process. Cannot be used at the same time with `text_style_prompt`.                                                                                                                                        |

**Parameter Constraints:**

* You must provide either a `text_style_prompt` or an `image_style`, but you cannot provide both at the same time.
* The `text_style_prompt` is limited to a maximum of 600 characters.

## Outputs

| Output Name     | Data Type       | Description                                                                                   |
| --------------- | --------------- | --------------------------------------------------------------------------------------------- |
| `model_file`    | STRING          | The filename of the generated GLB model. This output is provided for backward compatibility.  |
| `meshy_task_id` | MODEL\_TASK\_ID | The unique task identifier for this texturing job, which can be used to reference the result. |
| `GLB`           | FILE3DGLB       | The textured 3D model saved in the GLB file format.                                           |
| `FBX`           | FILE3DFBX       | The textured 3D model saved in the FBX file format.                                           |

***

**Source fingerprint (SHA-256):** `ac14eadd89c884abb8cb4800093fca93c8da5d8c86beec94bbdd40d34368ca09`


# Rodin3D_Detail - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Detail

Complete documentation for the Rodin3D_Detail node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Detail/en.md)

The Rodin 3D Detail node generates detailed 3D assets using the Rodin API. It takes input images and processes them through the Rodin service to create high-quality 3D models with detailed geometry and materials. The node handles the entire workflow from task creation to downloading the final 3D model file.

## Inputs

| Parameter       | Data Type | Required | Range                                                                                   | Description                                                                                                             |
| --------------- | --------- | -------- | --------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------- |
| `Images`        | IMAGE     | Yes      | -                                                                                       | Input images used for 3D model generation. A minimum of 1 image is required, and a maximum of 5 images can be provided. |
| `Seed`          | INT       | No       | 0 to 65535                                                                              | Random seed value for reproducible results (default: 0)                                                                 |
| `Material_Type` | STRING    | No       | `"PBR"`<br />`"Shaded"`                                                                 | Type of material to apply to the 3D model (default: "PBR")                                                              |
| `Polygon_count` | STRING    | No       | `"4K-Quad"`<br />`"8K-Quad"`<br />`"18K-Quad"`<br />`"50K-Quad"`<br />`"200K-Triangle"` | Target polygon count for the generated 3D model. Determines the mesh quality level (default: "18K-Quad")                |

## Outputs

| Output Name     | Data Type | Description                                                           |
| --------------- | --------- | --------------------------------------------------------------------- |
| `3D Model Path` | STRING    | File path to the generated 3D model (for backward compatibility only) |
| `GLB`           | FILE3DGLB | The generated 3D model in GLB format                                  |

***

**Source fingerprint (SHA-256):** `ccdee80eb972c13a8849488080c08ba7276cec0b77a2089c7a9ad5b8adc5937b`


# Rodin3D_Gen2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Gen2

Complete documentation for the Rodin3D_Gen2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Gen2/en.md)

The Rodin3D\_Gen2 node generates 3D assets using the Rodin API. It takes input images and converts them into 3D models with various material types and polygon counts. The node handles the entire generation process including task creation, status polling, and file downloading automatically.

## Inputs

| Parameter       | Data Type | Required | Range                                                                                                                                     | Description                                                                                                                                                                  |
| --------------- | --------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `Images`        | IMAGE     | Yes      | -                                                                                                                                         | Input images to use for 3D model generation. Accepts 1 to 5 images.                                                                                                          |
| `Seed`          | INT       | No       | 0-65535                                                                                                                                   | Random seed value for generation (default: 0)                                                                                                                                |
| `Material_Type` | COMBO     | No       | "PBR"<br />"Shaded"                                                                                                                       | Type of material to apply to the 3D model (default: "PBR")                                                                                                                   |
| `Polygon_count` | COMBO     | No       | "4K-Quad"<br />"8K-Quad"<br />"18K-Quad"<br />"50K-Quad"<br />"2K-Triangle"<br />"20K-Triangle"<br />"150K-Triangle"<br />"500K-Triangle" | Target polygon count and mesh type for the generated 3D model. "Quad" options use quad-based meshes, "Triangle" options use triangle-based meshes (default: "500K-Triangle") |
| `TAPose`        | BOOLEAN   | No       | -                                                                                                                                         | Whether to apply TAPose processing (default: False). This is an advanced parameter.                                                                                          |

## Outputs

| Output Name     | Data Type | Description                                                      |
| --------------- | --------- | ---------------------------------------------------------------- |
| `3D Model Path` | STRING    | File path to the generated 3D model (for backward compatibility) |
| `GLB`           | FILE3DGLB | The generated 3D model in GLB format                             |

***

**Source fingerprint (SHA-256):** `98e183ba480d2ef8dc1930132ea4edf83481cf6bf7ee18a22972b71dd532c7ea`


# Rodin3D_Gen25_Image - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Gen25_Image

Complete documentation for the Rodin3D_Gen25_Image node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Gen25_Image/en.md)

## Overview

This node generates a 3D model from one to five reference images using the Rodin Gen-2.5 API. You can choose between Fast, Regular, or Extreme-High quality modes to balance generation speed and cost.

## Inputs

| Parameter              | Data Type | Required | Range                                           | Description                                                                                                                     |
| ---------------------- | --------- | -------- | ----------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| `images`               | IMAGE     | Yes      | 1 to 5 images                                   | One to five input images. The first image is used for materials when multiple images are provided.                              |
| `mode`                 | COMBO     | Yes      | `"Fast"`<br />`"Regular"`<br />`"Extreme-High"` | The generation quality mode. Higher quality modes produce better results but cost more.                                         |
| `material`             | COMBO     | Yes      | `"PBR"`<br />`"Matte"`                          | The material type for the generated 3D model.                                                                                   |
| `geometry_file_format` | COMBO     | Yes      | `"glb"`<br />`"obj"`<br />`"stl"`<br />`"usdz"` | The output file format for the 3D model geometry.                                                                               |
| `texture_mode`         | COMBO     | Yes      | `"Original"`<br />`"Clean"`<br />`"Style"`      | The texture generation mode. "Original" preserves input textures, "Clean" removes them, and "Style" applies a stylized texture. |
| `seed`                 | INT       | Yes      | 0 to 2147483647                                 | A random seed for reproducible results. Use the same seed to get the same output.                                               |
| `TAPose`               | BOOLEAN   | Yes      | True / False                                    | Whether to apply T-pose to the generated model.                                                                                 |
| `hd_texture`           | BOOLEAN   | Yes      | True / False                                    | Whether to generate a high-definition texture map.                                                                              |
| `texture_delight`      | BOOLEAN   | Yes      | True / False                                    | Whether to remove lighting from the input images before texture generation.                                                     |
| `use_original_alpha`   | BOOLEAN   | Yes      | True / False                                    | Whether to use the original alpha channel from the input images.                                                                |
| `addon_highpack`       | BOOLEAN   | Yes      | True / False                                    | Whether to generate a high-polygon version of the model in addition to the standard one.                                        |
| `bbox_width`           | INT       | Yes      | 1 to 1000                                       | The width of the bounding box for the generated model in centimeters.                                                           |
| `bbox_height`          | INT       | Yes      | 1 to 1000                                       | The height of the bounding box for the generated model in centimeters.                                                          |
| `bbox_length`          | INT       | Yes      | 1 to 1000                                       | The length of the bounding box for the generated model in centimeters.                                                          |
| `height_cm`            | INT       | Yes      | 1 to 300                                        | The height of the generated model in centimeters.                                                                               |

**Note on Image Count:** The node accepts between 1 and 5 images. If you provide a batch of images (e.g., a 4-image batch), each image in the batch is treated as a separate input image. Providing more than 5 images will result in an error.

## Outputs

| Output Name  | Data Type | Description                                                  |
| ------------ | --------- | ------------------------------------------------------------ |
| `model_file` | FILE3D    | The generated 3D model file in the selected geometry format. |

***

**Source fingerprint (SHA-256):** `65f755a2c3bd2317eb61c4681a406b51b06f960e36864d3602c3d03a44aa4878`


# Rodin3D_Gen25_Text - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Gen25_Text

Complete documentation for the Rodin3D_Gen25_Text node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Gen25_Text/en.md)

## Overview

Generate a 3D model from a text prompt using the Rodin Gen-2.5 API. You can choose between different quality modes (Fast, Regular, or Extreme-High) to balance generation speed and output quality.

## Inputs

| Parameter              | Data Type | Required | Range                                             | Description                                                                                                                                   |
| ---------------------- | --------- | -------- | ------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`               | STRING    | Yes      | Max 2500 characters                               | Text prompt describing the 3D model you want to generate.                                                                                     |
| `mode`                 | COMBO     | Yes      | `"Fast"`<br />`"Regular"`<br />`"Extreme-High"`   | The generation quality and speed mode. "Fast" is quickest, "Extreme-High" produces the highest quality but takes longer.                      |
| `material`             | COMBO     | Yes      | `"PBR"`<br />`"Matte"`<br />`"Shiny"`             | The material style for the generated 3D model.                                                                                                |
| `geometry_file_format` | COMBO     | Yes      | `"glb"`<br />`"obj"`<br />`"stl"`<br />`"usdz"`   | The file format for the output 3D model.                                                                                                      |
| `texture_mode`         | COMBO     | Yes      | `"None"`<br />`"Generated"`<br />`"Generated+HD"` | Texture generation mode. "None" produces no textures, "Generated" creates standard textures, "Generated+HD" creates high-definition textures. |
| `seed`                 | INT       | Yes      | 0 to 2147483647                                   | Random seed for reproducible results. Using the same seed with the same inputs will produce the same output.                                  |
| `TAPose`               | BOOLEAN   | Yes      | True / False                                      | Whether to apply T-pose (arms outstretched) to the generated model.                                                                           |
| `hd_texture`           | BOOLEAN   | Yes      | True / False                                      | Whether to generate high-definition textures for the model.                                                                                   |
| `texture_delight`      | BOOLEAN   | Yes      | True / False                                      | Whether to apply texture delight (enhanced texture quality) to the model.                                                                     |
| `addon_highpack`       | BOOLEAN   | Yes      | True / False                                      | Whether to generate a high-polygon version of the model in addition to the standard one.                                                      |
| `bbox_width`           | INT       | Yes      | 1 to 1000                                         | The width of the bounding box in world units.                                                                                                 |
| `bbox_height`          | INT       | Yes      | 1 to 1000                                         | The height of the bounding box in world units.                                                                                                |
| `bbox_length`          | INT       | Yes      | 1 to 1000                                         | The length of the bounding box in world units.                                                                                                |
| `height_cm`            | INT       | Yes      | 1 to 300                                          | The height of the generated model in centimeters.                                                                                             |

**Note:** The `prompt` parameter must be between 1 and 2500 characters long. The `seed` parameter defaults to 0 (random) if not specified.

## Outputs

| Output Name  | Data Type | Description                                          |
| ------------ | --------- | ---------------------------------------------------- |
| `model_file` | FILE3DANY | The generated 3D model file in the specified format. |

***

**Source fingerprint (SHA-256):** `79fbaf466e9af88cdfdac0f9136a2df17ba4bc2e5bb65a35b9ad2b1181da94db`


# Rodin3D_Regular - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Regular

Complete documentation for the Rodin3D_Regular node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Regular/en.md)

The Rodin 3D Regular node generates 3D assets using the Rodin API. It takes input images and processes them through the Rodin service to create 3D models. The node handles the entire workflow from task creation to downloading the final 3D model files.

## Inputs

| Parameter       | Data Type | Required | Range                                                                                   | Description                                                                          |
| --------------- | --------- | -------- | --------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------ |
| `Images`        | IMAGE     | Yes      | -                                                                                       | Input images used for 3D model generation. Up to 5 images can be provided.           |
| `Seed`          | INT       | No       | 0 to 65535                                                                              | Random seed value for reproducible results (default: 0).                             |
| `Material_Type` | STRING    | No       | `"PBR"`<br />`"Shaded"`                                                                 | Type of material to apply to the 3D model (default: "PBR").                          |
| `Polygon_count` | STRING    | No       | `"4K-Quad"`<br />`"8K-Quad"`<br />`"18K-Quad"`<br />`"50K-Quad"`<br />`"200K-Triangle"` | Target polygon count and mesh type for the generated 3D model (default: "18K-Quad"). |

**Note:** At least 1 image is required for 3D model generation. A maximum of 5 images can be provided.

## Outputs

| Output Name     | Data Type | Description                                                                  |
| --------------- | --------- | ---------------------------------------------------------------------------- |
| `3D Model Path` | STRING    | File path to the generated 3D model (maintained for backward compatibility). |
| `GLB`           | FILE3DGLB | The generated 3D model in GLB format.                                        |

***

**Source fingerprint (SHA-256):** `5d65be9cb92da615690df5665ca02c98e98e95510e002502a33fd869c31e7419`


# Rodin3D_Sketch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Sketch

Complete documentation for the Rodin3D_Sketch node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Sketch/en.md)

This node generates 3D assets using the Rodin API. It takes input images and converts them into 3D models through an external service. The node handles the entire process from task creation to downloading the final 3D model files.

## Inputs

| Parameter | Data Type | Required | Range         | Description                                                                          |
| --------- | --------- | -------- | ------------- | ------------------------------------------------------------------------------------ |
| `Images`  | IMAGE     | Yes      | 1 to 5 images | Input images to be converted into 3D models. You can provide between 1 and 5 images. |
| `Seed`    | INT       | No       | 0 to 65535    | Random seed value for generation (default: 0). Set to 0 for a random seed.           |

**Note:** The node requires at least 1 image and supports a maximum of 5 images. If no images are provided, the node will raise an error.

## Outputs

| Output Name     | Data Type | Description                                                           |
| --------------- | --------- | --------------------------------------------------------------------- |
| `3D Model Path` | STRING    | File path to the generated 3D model (for backward compatibility only) |
| `GLB`           | FILE3DGLB | The generated 3D model in GLB format                                  |

***

**Source fingerprint (SHA-256):** `7030e6966a13b62055a17fc1eb39f34aa228fa37bbdcf7c2d5dbbbc1ca96c819`


# Rodin3D_Smooth - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Rodin3D_Smooth

Complete documentation for the Rodin3D_Smooth node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Rodin3D_Smooth/en.md)

The Rodin 3D Smooth node generates 3D assets using the Rodin API by processing input images and converting them into smooth 3D models. It takes multiple images as input and produces a downloadable 3D model file. The node handles the entire generation process including task creation, status polling, and file downloading automatically.

## Inputs

| Parameter       | Data Type | Required | Range                                                                         | Description                                                                                                          |
| --------------- | --------- | -------- | ----------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------- |
| `Images`        | IMAGE     | Yes      | -                                                                             | Input images to use for 3D model generation. Multiple images can be provided (up to 5).                              |
| `Seed`          | INT       | No       | 0 to 65535                                                                    | Random seed value for generation consistency (default: 0).                                                           |
| `Material_Type` | STRING    | No       | "PBR"<br />"Shaded"                                                           | Type of material to apply to the 3D model (default: "PBR").                                                          |
| `Polygon_count` | STRING    | No       | "4K-Quad"<br />"8K-Quad"<br />"18K-Quad"<br />"50K-Quad"<br />"200K-Triangle" | Target polygon count for the generated 3D model. Determines the mesh quality and detail level (default: "18K-Quad"). |

**Note:** The node accepts up to 5 input images. If no images are provided, an error will be raised.

## Outputs

| Output Name     | Data Type | Description                                                             |
| --------------- | --------- | ----------------------------------------------------------------------- |
| `3D Model Path` | STRING    | File path to the downloaded 3D model (for backward compatibility only). |
| `GLB`           | FILE3DGLB | The generated 3D model in GLB format.                                   |

***

**Source fingerprint (SHA-256):** `60a5d70fa095b46f221ce452e290739852b1ebeba34ab7ec21b0b4e3c8e6d164`


# Tencent3DPartNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Tencent3DPartNode

Complete documentation for the Tencent3DPartNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Tencent3DPartNode/en.md)

This node uses the Tencent Hunyuan3D API to automatically analyze a 3D model and generate or identify its components based on its structure. It processes the model and returns a new FBX file.

## Inputs

| Parameter  | Data Type | Required | Range           | Description                                                                                                                          |
| ---------- | --------- | -------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------ |
| `model_3d` | FILE3D    | Yes      | FBX, Any        | The 3D model to process. The model should be in FBX format and have less than 30000 faces.                                           |
| `seed`     | INT       | No       | 0 to 2147483647 | A seed value to control whether the node should re-run. The results are non-deterministic regardless of the seed value. (default: 0) |

**Note:** The `model_3d` input only supports files in the FBX format. If a different 3D file format is provided, the node will raise an error.

## Outputs

| Output Name | Data Type | Description                                      |
| ----------- | --------- | ------------------------------------------------ |
| `FBX`       | FILE3DFBX | The processed 3D model, returned as an FBX file. |

***

**Source fingerprint (SHA-256):** `094ed587f2989312c0eea86105e8c2bdf48a2c626e424eaa07ba528c2e8b4f89`


# Tencent3DTextureEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Tencent3DTextureEditNode

Complete documentation for the Tencent3DTextureEditNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Tencent3DTextureEditNode/en.md)

This node uses the Tencent Hunyuan3D API to edit the textures of a 3D model. You provide a 3D model and a text description of the desired changes, and the node returns a new version of the model with its textures redrawn according to your prompt.

## Inputs

| Parameter  | Data Type | Required | Range           | Description                                                                                                  |
| ---------- | --------- | -------- | --------------- | ------------------------------------------------------------------------------------------------------------ |
| `model_3d` | FILE3D    | Yes      | FBX, Any        | 3D model in FBX format. Model should have less than 100000 faces.                                            |
| `prompt`   | STRING    | Yes      |                 | Describes texture editing. Supports up to 1024 UTF-8 characters.                                             |
| `seed`     | INT       | No       | 0 to 2147483647 | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) |

**Note:** The `model_3d` input must be a file in the FBX format. Other 3D file formats are not supported by this node.

## Outputs

| Output Name     | Data Type | Description                                         |
| --------------- | --------- | --------------------------------------------------- |
| `GLB`           | FILE3D    | The processed 3D model in GLB format.               |
| `OBJ`           | FILE3D    | The processed 3D model in OBJ format.               |
| `texture_image` | IMAGE     | The newly generated texture image for the 3D model. |

***

**Source fingerprint (SHA-256):** `e8d3f9fbd49b0e641ed4bb415d6ee6a34018623eb717ac54c0588383f9caed44`


# TencentImageToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TencentImageToModelNode

Complete documentation for the TencentImageToModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TencentImageToModelNode/en.md)

This node uses Tencent's Hunyuan3D Pro API to generate a 3D model from one or more input images. It processes the images, sends them to the API, and returns the generated 3D model files in GLB and OBJ formats, along with optional texture maps.

## Inputs

| Parameter                    | Data Type    | Required | Range                                         | Description                                                                                                                                                         |
| ---------------------------- | ------------ | -------- | --------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`                      | COMBO        | Yes      | `"3.0"`<br />`"3.1"`                          | The version of the Hunyuan3D model to use. The LowPoly option is unavailable for the `3.1` model.                                                                   |
| `image`                      | IMAGE        | Yes      | -                                             | The primary input image used to generate the 3D model. Must be at least 128x128 pixels.                                                                             |
| `image_left`                 | IMAGE        | No       | -                                             | An optional image of the object's left side for multi-view generation. Must be at least 128x128 pixels.                                                             |
| `image_right`                | IMAGE        | No       | -                                             | An optional image of the object's right side for multi-view generation. Must be at least 128x128 pixels.                                                            |
| `image_back`                 | IMAGE        | No       | -                                             | An optional image of the object's back side for multi-view generation. Must be at least 128x128 pixels.                                                             |
| `face_count`                 | INT          | Yes      | 3000 - 1500000                                | The target number of faces for the generated 3D model (default: 500000).                                                                                            |
| `generate_type`              | DYNAMICCOMBO | Yes      | `"Normal"`<br />`"LowPoly"`<br />`"Geometry"` | The type of 3D model to generate. Selecting an option reveals additional related parameters.                                                                        |
| `generate_type.pbr`          | BOOLEAN      | No       | -                                             | Enables Physically Based Rendering (PBR) material generation. This parameter is only visible when `generate_type` is set to "Normal" or "LowPoly" (default: False). |
| `generate_type.polygon_type` | COMBO        | No       | `"triangle"`<br />`"quadrilateral"`           | The type of polygon to use for the mesh. This parameter is only visible when `generate_type` is set to "LowPoly".                                                   |
| `seed`                       | INT          | Yes      | 0 - 2147483647                                | A seed value for the generation process. Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0).               |

**Note:** All input images must have a minimum width and height of 128 pixels. Images are automatically downscaled if they exceed 4900 pixels on their longest side.

## Outputs

| Output Name          | Data Type | Description                                                                    |
| -------------------- | --------- | ------------------------------------------------------------------------------ |
| `model_file`         | STRING    | A legacy output for backward compatibility.                                    |
| `GLB`                | FILE3DGLB | The generated 3D model in the GLB (Binary GL Transmission Format) file format. |
| `OBJ`                | FILE3DOBJ | The generated 3D model in the OBJ (Wavefront) file format.                     |
| `texture_image`      | IMAGE     | The texture image for the generated 3D model.                                  |
| `optional_metallic`  | IMAGE     | The metallic map for PBR materials. Returns a black image if not available.    |
| `optional_normal`    | IMAGE     | The normal map for PBR materials. Returns a black image if not available.      |
| `optional_roughness` | IMAGE     | The roughness map for PBR materials. Returns a black image if not available.   |

***

**Source fingerprint (SHA-256):** `b4cb268fe3b2f5890e5460d5e69897ccc47e205b05546aea18a85ad15717f12a`


# TencentModelTo3DUVNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TencentModelTo3DUVNode

Complete documentation for the TencentModelTo3DUVNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TencentModelTo3DUVNode/en.md)

This node uses the Tencent Hunyuan3D API to perform UV unfolding on a 3D model. It takes a 3D model file as input, sends it to the API for processing, and returns the processed model in OBJ and FBX formats along with a generated UV texture image. The input model must have fewer than 30,000 faces.

## Inputs

| Parameter  | Data Type | Required | Range                 | Description                                                                                                                              |
| ---------- | --------- | -------- | --------------------- | ---------------------------------------------------------------------------------------------------------------------------------------- |
| `model_3d` | FILE3D    | Yes      | GLB<br />OBJ<br />FBX | Input 3D model (GLB, OBJ, or FBX). The model must have less than 30000 faces.                                                            |
| `seed`     | INT       | No       | 0 to 2147483647       | A seed value (default: 1). This controls whether the node should re-run, but results are non-deterministic regardless of the seed value. |

## Outputs

| Output Name | Data Type | Description                                |
| ----------- | --------- | ------------------------------------------ |
| `OBJ`       | FILE3D    | The processed 3D model file in OBJ format. |
| `FBX`       | FILE3D    | The processed 3D model file in FBX format. |
| `uv_image`  | IMAGE     | The generated UV texture image.            |

***

**Source fingerprint (SHA-256):** `f09167ca1aacf299ff278817a50b6c311b6211fe447cfbe7c3a0ccc481058cf6`


# TencentSmartTopologyNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TencentSmartTopologyNode

Complete documentation for the TencentSmartTopologyNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TencentSmartTopologyNode/en.md)

This node performs smart retopology on a 3D model, automatically creating a new, cleaner mesh with optimized polygon count. It connects to a Tencent Hunyuan 3D API to process the model, supporting GLB and OBJ file formats up to 200MB. The node returns the processed model as an OBJ file.

## Inputs

| Parameter      | Data Type | Required | Range                                 | Description                                                                                                  |
| -------------- | --------- | -------- | ------------------------------------- | ------------------------------------------------------------------------------------------------------------ |
| `model_3d`     | FILE3D    | Yes      | -                                     | Input 3D model (GLB or OBJ). The file must be in GLB or OBJ format and cannot exceed 200MB.                  |
| `polygon_type` | STRING    | Yes      | `"triangle"`<br />`"quadrilateral"`   | Surface composition type.                                                                                    |
| `face_level`   | STRING    | Yes      | `"medium"`<br />`"high"`<br />`"low"` | Polygon reduction level.                                                                                     |
| `seed`         | INT       | No       | 0 to 2147483647                       | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) |

**Note:** The `seed` parameter is used to trigger a re-run of the node, but the final output is not guaranteed to be the same for the same seed value.

## Outputs

| Output Name | Data Type | Description                                                             |
| ----------- | --------- | ----------------------------------------------------------------------- |
| `OBJ`       | FILE3D    | The processed 3D model with optimized topology, returned in OBJ format. |

***

**Source fingerprint (SHA-256):** `41f52d3553c2c0773d539d029f21fe405ffac739a5a43d89da1c55c5a4d75e5b`


# TencentTextToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TencentTextToModelNode

Complete documentation for the TencentTextToModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TencentTextToModelNode/en.md)

This node uses Tencent's Hunyuan3D Pro API to generate a 3D model from a text description. It sends a request to create a generation task, polls for the result, and downloads the final model files in GLB and OBJ formats.

## Inputs

| Parameter       | Data Type    | Required | Range                                         | Description                                                                                                                                                                                                                                                                                                                                                                                              |
| --------------- | ------------ | -------- | --------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`         | COMBO        | Yes      | `"3.0"`<br />`"3.1"`                          | The version of the Hunyuan3D model to use. The LowPoly option is unavailable for the `3.1` model.                                                                                                                                                                                                                                                                                                        |
| `prompt`        | STRING       | Yes      | -                                             | The text description of the 3D model to generate. Supports up to 1024 characters.                                                                                                                                                                                                                                                                                                                        |
| `face_count`    | INT          | Yes      | 3000 - 1500000                                | The target number of faces for the generated 3D model. Default: 500000.                                                                                                                                                                                                                                                                                                                                  |
| `generate_type` | DYNAMICCOMBO | Yes      | `"Normal"`<br />`"LowPoly"`<br />`"Geometry"` | The type of 3D model to generate. The available options and their associated parameters are:<br />- **Normal**: Generates a standard model. Includes a `pbr` parameter (default: `False`).<br />- **LowPoly**: Generates a low-polygon model. Includes `polygon_type` (`"triangle"` or `"quadrilateral"`) and `pbr` (default: `False`) parameters.<br />- **Geometry**: Generates a geometry-only model. |
| `seed`          | INT          | No       | 0 - 2147483647                                | A seed value for the generation. Results are non-deterministic regardless of seed. Setting a new seed controls whether the node should re-run. Default: 0.                                                                                                                                                                                                                                               |

**Note:** The `generate_type` parameter is dynamic. Selecting `"LowPoly"` will reveal additional inputs for `polygon_type` and `pbr`. Selecting `"Normal"` will reveal an input for `pbr`. Selecting `"Geometry"` will not reveal any additional inputs.

**Constraint:** The `"LowPoly"` generate type cannot be used with the `"3.1"` model.

## Outputs

| Output Name     | Data Type | Description                                                            |
| --------------- | --------- | ---------------------------------------------------------------------- |
| `model_file`    | STRING    | A legacy output for backward compatibility.                            |
| `GLB`           | FILE3DGLB | The generated 3D model in the GLB file format.                         |
| `OBJ`           | FILE3DOBJ | The generated 3D model in the OBJ file format.                         |
| `texture_image` | IMAGE     | The texture image extracted from the generated OBJ file, if available. |

***

**Source fingerprint (SHA-256):** `2e8799d6863a0a7113d22f1637251735a217797679d7a97268910b88d9864e4a`


# TripoConversionNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoConversionNode

Complete documentation for the TripoConversionNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoConversionNode/en.md)

The TripoConversionNode converts 3D models between different file formats using the Tripo API. It takes a task ID from a previous Tripo operation (model generation, rigging, or retargeting) and converts the resulting model to your desired format with various export options.

## Inputs

| Parameter                  | Data Type                                        | Required | Range                                                                                  | Description                                                                             |
| -------------------------- | ------------------------------------------------ | -------- | -------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------- |
| `original_model_task_id`   | MODEL\_TASK\_ID,RIG\_TASK\_ID,RETARGET\_TASK\_ID | Yes      | MODEL\_TASK\_ID<br />RIG\_TASK\_ID<br />RETARGET\_TASK\_ID                             | The task ID from a previous Tripo operation (model generation, rigging, or retargeting) |
| `format`                   | COMBO                                            | Yes      | GLTF<br />USDZ<br />FBX<br />OBJ<br />STL<br />3MF                                     | The target file format for the converted 3D model                                       |
| `quad`                     | BOOLEAN                                          | No       | True/False                                                                             | Whether to convert triangles to quads (default: False)                                  |
| `face_limit`               | INT                                              | No       | -1 to 2000000                                                                          | Maximum number of faces in the output model, use -1 for no limit (default: -1)          |
| `texture_size`             | INT                                              | No       | 128 to 4096                                                                            | Size of output textures in pixels (default: 4096)                                       |
| `texture_format`           | COMBO                                            | No       | BMP<br />DPX<br />HDR<br />JPEG<br />OPEN\_EXR<br />PNG<br />TARGA<br />TIFF<br />WEBP | Format for exported textures (default: JPEG)                                            |
| `force_symmetry`           | BOOLEAN                                          | No       | True/False                                                                             | Whether to force symmetry on the model (default: False)                                 |
| `flatten_bottom`           | BOOLEAN                                          | No       | True/False                                                                             | Whether to flatten the bottom of the model (default: False)                             |
| `flatten_bottom_threshold` | FLOAT                                            | No       | 0.0 to 1.0                                                                             | Threshold for bottom flattening (default: 0.0)                                          |
| `pivot_to_center_bottom`   | BOOLEAN                                          | No       | True/False                                                                             | Whether to move the pivot point to the center bottom of the model (default: False)      |
| `scale_factor`             | FLOAT                                            | No       | 0.0 and above                                                                          | Scale factor to apply to the model (default: 1.0)                                       |
| `with_animation`           | BOOLEAN                                          | No       | True/False                                                                             | Whether to include animation data in the export (default: False)                        |
| `pack_uv`                  | BOOLEAN                                          | No       | True/False                                                                             | Whether to pack UV coordinates (default: False)                                         |
| `bake`                     | BOOLEAN                                          | No       | True/False                                                                             | Whether to bake textures (default: False)                                               |
| `part_names`               | STRING                                           | No       | Comma-separated list                                                                   | Comma-separated list of part names to include in the export (default: "")               |
| `fbx_preset`               | COMBO                                            | No       | blender<br />mixamo<br />3dsmax                                                        | FBX export preset to use (default: blender)                                             |
| `export_vertex_colors`     | BOOLEAN                                          | No       | True/False                                                                             | Whether to export vertex colors (default: False)                                        |
| `export_orientation`       | COMBO                                            | No       | align\_image<br />default                                                              | Export orientation mode (default: default)                                              |
| `animate_in_place`         | BOOLEAN                                          | No       | True/False                                                                             | Whether to animate the model in place (default: False)                                  |

**Note:** The `original_model_task_id` must be a valid task ID from a previous Tripo operation (model generation, rigging, or retargeting). Parameters marked as "advanced" are optional and only need to be configured for specific export requirements.

## Outputs

| Output Name        | Data Type | Description                                                                                           |
| ------------------ | --------- | ----------------------------------------------------------------------------------------------------- |
| *No named outputs* | -         | This node processes the conversion asynchronously and returns the result through the Tripo API system |

***

**Source fingerprint (SHA-256):** `7542fd7ee2307b06e5caa78ce427140fbcb56e8ea383ce327828040330ea1b01`


# ComfyUI Built-in Nodes
Source: https://docs.comfy.org/built-in-nodes/overview

Introduction to ComfyUI Built-in Nodes

Built-in nodes are ComfyUI's default nodes. They are core functionalities of ComfyUI that you can use without installing any third-party custom node packages.

## About built-in node document

We have now added built-in node help documentation, so the content of this section is periodically synced from [this repo](https://github.com/Comfy-Org/embedded-docs). We will update the content manually once a week.

## Contribute

If you find any errors in the content, or want to contribute missing content, please submit an issue or PR in [this repo](https://github.com/Comfy-Org/embedded-docs) to help us improve.


# Changelog
Source: https://docs.comfy.org/changelog/index

Track ComfyUI's latest features, improvements, and bug fixes. For detailed release notes, see the [Github releases](https://github.com/Comfy-Org/ComfyUI/releases) page.

<Update label="v0.22.0" description="May 20, 2026">
  **Open-Source Model Support**

  * [**Stable Audio 3.0**](https://blog.comfy.org/p/stable-audio-3-day-0-support): Support for the latest Stable Audio 3 model with improved audio generation capabilities
  * **MoGe:** Added support for MoGe models for enhanced geometry processing
  * **HiDream-O1:** Added area conditioning support for more precise image generation control
  * **LTXV Enhancements:** Added downscaled IC-LoRA support and optional attention\_mask input for improved video control
  * **Temporal Processing:** Implemented downscale\_ratio\_temporal functionality for better temporal control in video workflows
  * **LTX2.3 Optimization:** Reduced peak VRAM usage when guide\_mask is in use for more efficient video generation

  **Partner Node**

  * **Seed2.0:** New node added for enhanced language model capabilities from ByteDance
  * **Opus 4.7:** Fixed deprecated temperature parameter for better model compatibility

  **Node Enhancements**

  * **StringFormat Node:** New node added for advanced string manipulation in workflows
  * **Audio Processing:** Improved audio latent nodes with temporal downscale support for better reusability
  * **Batch Nodes:** Reduced minimum batch size from 2 to 1 for Image/Mask/Latent batch nodes, providing more flexibility
  * **Negative Values Support:** Allow negative values on specific node parameters for expanded creative control

  **Others**

  * **Model Sampling:** Preserved noise\_scale/shift across chained model\_sampling patches for consistent results
  * **Text Generation:** Fixed Qwen3.5 multi-image prompt handling for improved text generation workflows
  * **Dynamic CLIP:** Implemented proper dynamic CLIP saving functionality
  * **BiRefNet:** Resolved compatibility issues for better background removal performance
  * **Hunyuan3D 2.1:** Fixed batch size crashes in attention and forward pass operations
  * Various node display names, descriptions, and categories updated for better user experience
  * Improved frontend version warning system for better compatibility checking
  * Enhanced README with application and cloud links for easier access to resources
  * Added security documentation and careers information to project resources
  * Fixed FeatherMask negative zero indexing for proper right/bottom feathering
  * Corrected OOM memory summary format for clearer error reporting
  * Fixed Batch processing issues and improved model loading stability
  * Resolved various workflow compatibility issues and deprecated parameter handling
</Update>

<Update label="v0.21.1" description="May 13, 2026">
  **New Partner Nodes**

  * **Flux2ImageNode and GrokImageEditNodeV2:** Added new nodes for enhanced image generation and editing workflows
  * **ByteDanceSeedreamNodeV2:** New version with DynamicCombo and Autogrow features for improved parameter handling
  * **OpenAI Image node:** New integration with DynamicCombo and Autogrow capabilities
  * **Claude LLM node:** Added Claude language model support for text generation workflows

  **Model Support Enhancements**

  * **Anima TE LoRA:** Added support for Anima TE LoRA in Kohya format
  * **HiDream-O1-Image:** Full support for HiDream-O1-Image model with dtype fixes and improved memory usage for non-dynamic VRAM configurations

  **Technical Improvements**

  * Fixed safetensors saving of fp8 format in model patcher
  * Corrected LTXV mid-video multi-frame guide alignment for better video processing
  * Improved VOID model compatibility by fixing RuntimeError issues
  * Enhanced Save3D node to support vertex colors and textures for comprehensive 3D workflow support

  **UI and Documentation Updates**

  * Added "Create Video" to the essentials tab for easier access to video generation workflows
  * Updated embedded documentation to v0.5.0 and workflow templates to v0.9.75
  * Fixed input directory creation in LoadAudio define\_schema for better audio workflow handling

  **Bug Fixes**

  * Reverted breaking changes to maintain workflow compatibility
  * Fixed Quiver nodes functionality
  * Corrected deprecated cloud-runtime endpoints marking in API specification
</Update>

<Update label="v0.21.0" description="May 11, 2026">
  **Open-source model support**

  * [**BiRefNet**](https://github.com/Comfy-Org/ComfyUI/pull/12747): Background removal
  * [**Gemma4**](https://github.com/Comfy-Org/ComfyUI/pull/13376): LLM text generation
  * [**Void**](https://github.com/Comfy-Org/ComfyUI/pull/13403): Pass 1 & 2 model support

  **Partner model support**

  * [**Tripo 3.1**](https://github.com/Comfy-Org/ComfyUI/pull/13788): Production-ready 3D generation
  * **NanoBanana2** node v2: DynamicCombo and Autogrow UX refresh

  **Node improvements**

  * **Math Expression:** Added Boolean support for more complex calculations
  * **Flux2 latent previews:** High-quality preview support for Flux2 model latents
  * **Core Blueprints:** New built-in blueprint templates

  **Bug fixes & stability**

  * Corrected VAEDecodeAudio compatibility with LTX-2.x generated audio latents
  * Resolved SolidMask and MaskComposite device mismatch issues
  * Other fixes and improvements (CPU TE meta-tensor handling, port-in-use errors, save filenames without trailing underscores, and more)

  **Additional model & media updates**

  * **CogVideoX:** Video generation models
  * **Wan-Dancer:** Model support
  * **Major media loading:** Unified audio/video in the video loader; PyAV replaces Pillow for images (JPEG memory, tRNS PNG); automatic metadata rotation

  **Performance & video generation**

  * Block prefetch and LoRA async loading (notably faster for LTX)
  * Dynamic VRAM tuning with `--cache-ram 2` and lower peak usage for video
  * Triton ComfyUI kitchen CLI option for advanced optimizations
  * Auto-regressive video; image-to-video for causal models; `causal_window_fix` for long sequences; improved frame interpolation memory and overhead

  **More partner integrations**

  * **Luma UNI-1**, **Topaz Astra 2**, **GPT-5.5** / **GPT-5.5-pro**

  **Further node fixes**

  * Image blending fixes with `--gpu-only`; batch broadcasting on JoinImageWithAlpha; tile stride fixes on SplitImageToTileList and ImageMergeTileList

  **Developer & API**

  * `--feature-flag` registry; OpenAPI cloud-runtime and experiment endpoints; blueprint subgraph descriptions; deterministic ControlNet load order
</Update>

<Update label="v0.20.1" description="April 27, 2026">
  **New Model Support**

  * **SUPIR:** Added support for SUPIR image super-resolution models
  * **SAM 3.1:** Introduced segment anything model 3.1 support for advanced image segmentation
  * **RIFE and FILM:** New frame interpolation models for smooth video frame generation
  * **LTXV Audio VAE:** Support for standalone LTXV audio VAE models with improved native integration

  **Partner Node Enhancements**

  * **Video Generation:** Added 4K resolution support for ByteDance 2, Veo models, and Kling nodes
  * **Veo 3 Lite:** New lightweight version of Veo model for faster video generation
  * **SD2 Real Human:** Added support for Stable Diffusion 2 real human generation
  * **GPT-Image 2:** New version option with additional resolution support and fixed price badges
  * **HappyHorse:** New model integration for enhanced image generation capabilities

  **Performance Optimizations**

  * Faster Ernie model inference through targeted optimizations
  * Improved LTXV audio VAE processing with more native implementation
  * Enhanced ModelPatcherDynamic with better weight handling for ComfyUI layers
  * Anti-cycle validation added to execution system for improved workflow stability

  **Video Processing Improvements**

  * Support for loading higher bit depth videos with proper color accuracy
  * Alpha channel support for video loading, enabling transparency workflows
  * Auto-downscaling functionality for ByteDance 2 nodes to optimize processing

  **Technical Updates**

  * Fixed SQLAlchemy version pinning (>=2.0) for improved database compatibility
  * Enhanced logging capabilities in ComfyUI app files for better debugging
  * Added OpenAPI 3.1 specification for comprehensive API documentation
  * Improved shader handling for blur/sharpen operations using textureSize

  **UI & Frontend**

  * Updated ComfyUI frontend to version 1.42.15 with various improvements
  * Enhanced Preview Any node to display more tensor values for better debugging
  * Added range type support for improved node parameter handling
</Update>

<Update label="v0.20.0" description="April 27, 2026">
  **New Model Support**

  * **SUPIR model support:** Added enhanced super-resolution capabilities for high-quality upscaling workflows
  * **RIFE and FILM frame interpolation:** Introduced advanced frame interpolation models for smooth video transitions
  * **SAM 3.1 support:** Updated Segment Anything Model with improved segmentation accuracy
  * **LTX audio VAE improvements:** Enhanced native audio processing with support for standalone LTXV audio VAEs

  **Performance Optimizations**

  * Optimized Ernie inference for faster generation times
  * Added anti-cycle validation to prevent workflow execution loops
  * Improved ModelPatcherDynamic weight handling for better model compatibility

  **Video Processing Enhancements**

  * Support for loading higher bit depth videos with improved quality preservation
  * Added alpha channel support for video loading workflows
  * Auto-downscaling capabilities for ByteDance 2 nodes to handle large video files

  **Partner Node Updates**

  * **Veo models:** Added 4K resolution support and Veo 3 Lite model
  * **Kling nodes:** Enhanced with 4K resolution capabilities
  * **GPTImage:** Added gpt-image-2 version option and new resolution support
  * **HappyHorse model:** New partner model integration
  * **SD2 real human support:** Enhanced realistic human generation capabilities

  **UI and API Improvements**

  * Added OpenAPI 3.1 specification for better API documentation
  * Fixed texture size handling in blur/sharpen shaders for more accurate effects
  * Enhanced Preview Any node to display more tensor values for debugging

  **Bug Fixes**

  * Fixed SQLAlchemy compatibility by pinning version ≥2.0
  * Resolved Parameter assignment for Stable\_Zero123 cc\_projection weights
  * Corrected LTXV Reference Audio node functionality
  * Fixed 4K resolution restriction for veo-3.0 models
</Update>

<Update label="v0.19.3" description="April 17, 2026">
  **LTX text generation**

  * Implemented `use_default_template` for LTX models in text generation nodes

  **Partner node updates**

  * Added Quiver **arrow-1.1** and **arrow-1.1-max** SVG models for enhanced vector graphics capabilities
  * Made "obj" output optional in Hunyuan3D Text and Image to 3D nodes for improved workflow flexibility
  * Corrected StabilityAI price badges for accurate API node pricing information
</Update>

<Update label="v0.19.2" description="April 17, 2026">
  **Performance & memory**

  * Fixed OOM regression in quantized models during inference, improving memory usage for \_apply() operations

  **Text generation**

  * **LTX:** Added option to disable the default template in text generation nodes for more flexible prompt handling
  * Introduced JsonExtractString node for JSON data manipulation in workflows

  **Bug fixes**

  * **Ernie Image:** Fixed incorrect class name — use `ErnieTEModel_` instead of `ErnieTEModel`

  **Partner nodes**

  * Added 1080p resolution support for SeeDance 2.0 model, enabling higher quality video generation
</Update>

<Update label="v0.19.1" description="April 16, 2026">
  **New Model Support**

  * [Erine Image  Text to Image](https://blog.comfy.org/p/ernie-image-day-0-support)
  * LLM: Ministral model

  **Partner Node**

  * [Sonilo: Create music for your video](https://blog.comfy.org/p/comfyui-now-supports-sonilo-via-partner)

  **Capability**

  * Preview as Text node update: Support any value to string conversion
</Update>

<Update label="v0.19.0" description="April 13, 2026">
  **Model & Generation Support**

  * Added support for LTX2 reference audio (ID-LoRA) functionality
  * Implemented Qwen3.5 text generation models with enhanced 8B model compatibility for TextGenerate node
  * Added RT-DETRv4 detection model support for improved object detection capabilities
  * Introduced Ace Step 1.5 XL model support with intermediate dtype compatibility
  * Added support for small flux.2 decoder and enabled Flux conditioning without pooled output
  * Implemented Ernie Image model for expanded generation options

  **New Nodes & Features**

  * Added CURVE node for advanced curve manipulation in workflows
  * Introduced Number Convert node with improved precision handling for large numbers
  * Added Image Histogram node for image analysis capabilities
  * Implemented Color Adjustment node with zero default values
  * Enhanced GLSL shader node with curve inputs and raised uniform limits
  * Added has\_intermediate\_output flag for nodes with interactive UI elements

  **Memory & Performance**

  * Integrated RAM cache with model RAM management for improved efficiency
  * Enhanced pinned memory accounting and model memory handling
  * Fixed blur and sharpen nodes compatibility with FP16 intermediates
  * Improved memory management for intermediate device operations in ImageUpscaleWithModel

  **API & Partner Nodes**

  * Updated xAI Grok nodes with enhanced functionality
  * Added new Topaz model integration
  * Introduced WAN2.7 nodes for expanded workflow capabilities
  * Added SeeDance 2.0 nodes for enhanced video generation
  * Updated Tencent3D nodes with improved features

  **Bug Fixes & Stability**

  * Fixed Train LoRA crash with training\_dtype "none" and bfloat16 LoRA weights
  * Resolved text generation regression with LTXAV model
  * Fixed FP8 scaled checkpoints compatibility issues
  * Improved browser security handling for insecure browsers
  * Fixed SVG file MIME type registration for proper file handling

  **Infrastructure Updates**

  * Bumped manager version to 4.1 with improved functionality
  * Updated frontend to version 1.42.10 with enhanced stability
  * Added Intel XPU portable release support
  * Updated workflow templates to version 0.9.47
  * Enhanced asset registration system for output files
</Update>

<Update label="v0.18.2" description="March 25, 2026">
  **Partner Node(API)**

  * Grok Reference to Video
  * Grok Video Extend
  * [Blog](https://blog.comfy.org/p/grok-imagine-model-feature-updates)
</Update>

<Update label="v0.18.1" description="March 23, 2026">
  **FP16 Support Fixes**

  * Fixed Canny node compatibility with FP16 precision, resolving workflow issues when using 16-bit floating point operations
  * Resolved sampling problems with FP16 intermediates that were causing inconsistent generation results
  * Fixed FP16 intermediates producing different results than expected, ensuring consistent output across runs

  **VAE Improvements**

  * Fixed light and color issues in WAN VAE processing, improving output quality and color accuracy
</Update>

<Update label="v0.18.0" description="March 21, 2026">
  **Memory & Performance Optimizations**

  * Added `--fp16-intermediates` flag to use FP16 for intermediate values between operations, reducing VRAM usage
  * Major VRAM reductions for LTX and WAN VAE models with inplace output processing and chunked encoder implementation
  * Improved tiled decode peak memory usage and fixed VRAM leaks in video VAE tiler fallback
  * Enhanced RAM pressure release strategies for Windows with comfy-aimdo updates (0.2.11-0.2.12)
  * Added `--enable-dynamic-vram` option to force enable dynamic VRAM management

  **Model & Hardware Support**

  * Added support for mxfp8 precision format for enhanced model compatibility
  * Enabled PyTorch Attention for AMD gfx1150 (Strix Point) GPUs
  * Enhanced training capabilities with FP4, 8, 16 native dtype support and quantized linear autograd functions
  * Fixed text encoder compatibility issues and disabled SageAttention for Hunyuan3D v2.1 DiT models

  **Node & API Enhancements**

  * Fixed Tencent TextToModel and ImageToModel API nodes
  * Added Nano Banana 2 "thought\_image" support and Quiver SVG nodes
  * Marked seedream-3-0-t2i and seedance-1-0-lite models as deprecated
  * Added slice\_cond and per-model context window conditioning resizing capabilities
  * Enhanced EmptyLatentImage and EmptyImage nodes to follow intermediate dtype settings

  **Frontend & Infrastructure**

  * Updated frontend package to version 1.41.21 with improved caching headers to prevent stale chunks
  * Added CacheProvider API for external distributed caching support
  * Implemented atomic writes for userdata to prevent data loss on crashes
  * Enhanced essentials category support for nodes and blueprints
  * Updated workflow templates to version 0.9.26

  **Bug Fixes & Stability**

  * Fixed pixel space VAE compatibility issues and model finalizer execution at exit
  * Improved weight dtype handling in Load Diffusion Model node (marked as advanced input)
  * Enhanced deferred weight initialization for subclassed models
  * Fixed various memory leaks and corruption issues in rare edge cases
</Update>

<Update label="v0.17.2" description="March 15, 2026">
  This release focuses on stability and bug fixes. For complete technical details, see the [full changelog](https://github.com/Comfy-Org/ComfyUI/compare/v0.17.1...v0.17.2) on GitHub.
</Update>

<Update label="v0.17.1" description="March 13, 2026">
  This is a patch release that includes various bug fixes and stability improvements. For full details on changes included in this release, see the complete changelog comparison between v0.17.0 and v0.17.1.
</Update>

<Update label="v0.17.0" description="March 13, 2026">
  **Architecture & Performance Improvements**

  * Implemented modular asset architecture with asynchronous two-phase scanner and background seeder for improved loading performance
  * Added Python fault handler for better debugging and stability
  * Enhanced memory usage optimization for KV cache models
  * Improved dynamic VRAM handling with better error management for AcceleratorError compatibility

  **Model Support & Enhancements**

  * Added support for Flux 2 Klein KV cache model through the FluxKVCache node
  * Enhanced model patching system with cleanup functions and pre-attention patches for Flux models
  * Added pre-attention and post-input patches to Qwen image model
  * Fixed text encoder LoRA loading for wrapped models
  * Improved batch processing with fixes for batch\_size > 1 on various models

  **New Nodes & Features**

  * Added Painter node for enhanced image editing capabilities
  * Introduced Reve Image API nodes for expanded functionality
  * Updated workflow templates to version 0.9.21
  * Enhanced gradient stops formatting for better frontend compatibility

  **Bug Fixes & Stability**

  * Fixed audio extraction and truncation issues
  * Resolved model detection problems with deep clone pre-edited weights
  * Improved ComfyUI Manager installation guidance and updated to version 4.1b2
  * Enhanced package version reporting for better troubleshooting

  **Frontend Updates**

  * Updated frontend package to version 1.41.18 with various improvements and bug fixes
  * Updated comfy-kitchen to version 0.2.8 and comfy-aimdo to version 0.2.10
</Update>

<Update label="v0.16.4" description="March 7, 2026">
  **New Nodes & Features**

  * Added Math Expression node with simpleeval evaluation for mathematical operations in workflows
  * Introduced TencentSmartTopology API node for enhanced topology processing capabilities
  * Added Gemini 3.1 Flash-Lite model support to LLM node, expanding AI language model options

  **Bug Fixes & Performance**

  * Fixed fp16 audio encoder models compatibility issues
  * Resolved Text Encoder CPU execution when dynamic VRAM is enabled
  * Fixed requirements version conflicts
  * Enhanced memory management with compute stream synchronization before buffer freeing

  **Workflow Templates**

  * Updated workflow templates to version 0.9.11 with latest improvements
</Update>

<Update label="v0.16.3" description="March 5, 2026">
  **LTX Audio Model Improvements**

  * Fixed LTX2 vocoder conv\_transpose1d with manual casting for improved audio processing stability
  * Resolved LTX audio VAE novram compatibility issues for better memory management during audio generation
  * Added causal\_fix parameter to add\_keyframe\_index and append\_keyframe functions, enhancing keyframe handling precision in video workflows
</Update>

<Update label="v0.16.2" description="March 5, 2026">
  **Core Updates**

  * Updated comfy-aimdo to version 0.2.7 for improved AI model operations
  * Enhanced CPU weight handling in VBAR caster for better performance across different hardware configurations

  **Workflow Templates**

  * Updated workflow templates to version 0.9.10 with latest improvements and optimizations
  * Code refactoring improvements for enhanced stability
</Update>

<Update label="v0.16.1" description="March 5, 2026">
  **API Nodes Updates**

  * Updated xAI models and pricing for improved cost management and model selection
  * Enabled Kling 3.0 Motion Control for enhanced video generation capabilities

  **Workflow Templates**

  * Updated workflow templates to version 0.9.8 with latest improvements and optimizations
</Update>

<Update label="v0.16.0" description="March 5, 2026">
  **New Nodes & Features**

  * Added ResolutionSelector node with aspect ratio presets for easier image dimension setup
  * Introduced CURVE type support for advanced parameter control
  * Added text preview support to jobs API for better workflow monitoring
  * Native LongCat-Image implementation for enhanced image processing capabilities

  **Model & Format Support**

  * Added ACE-Step 1.5 lycoris key alias mapping for LoKR compatibility
  * Support for SDPose-OOD models
  * Added SCAIL WanVideo model support
  * Support for zeta chroma weights loading
  * Added LTXAV 2.3 model support
  * Z-image pixel space support implementation

  **Memory & Performance**

  * Dynamic VRAM mode is now the default, improving memory efficiency
  * Implemented LoRA requantization for non-QuantizedTensor fp8
  * Enhanced dynamic offload heuristics for better performance
  * Updated comfy-aimdo to version 0.2.6 with improved allocator handling
  * Fixed dynamic VRAM conflicts with weight hooks and WSL compatibility

  **API & UI Improvements**

  * Added "IMAGE+TEXT" support in NanoBanana2 API node
  * Renamed Mahiro CFG to Similarity-Adaptive Guidance for clarity
  * Fixed GLSL node input dimension requirements
  * Enhanced VAEDecodeAudioTiled to properly use tile\_size input

  **Bug Fixes**

  * Fixed WanVAE encoder/decoder confusion in feat\_map processing
  * Resolved ACE-1.5 memory estimation issues with missing lm\_metadata
  * Fixed context window step handling for substep sigmas
  * Prevented VideoFromComponents crashes when writing to BytesIO
  * Limited image tile overlap to prevent processing issues

  **Workflow Templates**

  * Updated workflow templates to version 0.9.7
</Update>

<Update label="v0.15.1" description="February 26, 2026">
  **Bug Fixes & Stability**

  * Fixed KeyError when prompt entries lack class\_type key, preventing workflow crashes
  * Resolved GLSL node compatibility issues with pyopengl accelerate numpy textures
  * Fixed LTXAV text encoder minimum length and memory estimation problems
  * Disabled dynamic VRAM when using torch compiler to prevent conflicts

  **Model & API Updates**

  * Updated comfy aimdo to version 0.2.2 with improved fallback handling
  * Added WanVideo-based segmentation model FlowRVS support for advanced video processing
  * Added NanoBanana2 API node for expanded functionality
  * Fixed Aimdo fallback to prevent zero-copy sft issues

  **UI & Frontend**

  * Patched frontend to version 1.39.19, fixing progress text serialization in API nodes
  * Moved essentials\_category to correct replacement nodes for better organization

  **New Features**

  * Added per-guide attention strength control in self-attention for fine-tuned workflow control
  * Updated workflow templates to version 0.9.4
</Update>

<Update label="v0.15.0" description="February 24, 2026">
  **New Nodes & Features**

  * Added BBox widget for precise bounding box selection in image workflows
  * Introduced 3-band equalizer node for audio processing workflows
  * Added basic text generation support with native models, initially supporting Gemma3 and Qwen 3
  * New GLSL shader node using PyOpenGL for advanced visual effects
  * Added ElevenLabs API nodes for text-to-speech functionality
  * New gradient-slider display mode for FLOAT inputs with improved UI
  * Added SplitImageToTileList and ImageMergeTileList nodes for tiled processing workflows

  **API Nodes**

  * Added price badge for Rodin Gen-2 node
  * Added KlingAvatar node for avatar generation
  * Added ByteDance Seedream-5 model support
  * Fixed Gemini image MIME type handling with glob matching
  * Forced Gemini to return uncompressed images for better quality

  **Performance & Bug Fixes**

  * Fixed FP8 dynamic VRAM workflow performance issues by limiting return of requants
  * Resolved non-contiguous audio waveform crashes in video save operations
  * Fixed LTXAV model loading issues including fp8 checkpoint support and embedding connector dtype problems
  * Improved PyOpenGL compatibility for versions \< 3.1.4

  **UI Improvements**

  * Marked 429 widgets as advanced for collapsible UI
  * Added essentials\_category for better node organization
  * Enhanced essential subgraph blueprints with improved categorization
  * Updated frontend to version 1.39.16

  **Model Support**

  * Enhanced text generation with tokenization improvements and minimum length enforcement
  * Updated LTXAV av embedding connectors integration
  * Temporary compatibility fixes for LTX 2.0 workflows during migration period
</Update>

<Update label="v0.14.2" description="February 18, 2026">
  **Bug Fixes**

  * Fixed issue with Gemini/Nano banana API nodes that sometimes returned blank images, improving reliability for AI-powered image generation workflows.
</Update>

<Update label="v0.14.1" description="February 17, 2026">
  **Bug Fixes**

  * Fixed anima LLM adapter forward when manual cast

  **New Model Support**

  * Added "viduq3-turbo" model support in API nodes
  * Added Recraft V4 nodes for enhanced creative workflows

  **Updates**

  * Updated workflow templates to v0.8.43
</Update>

<Update label="v0.8.1" description="January 8, 2026">
  **Model Support**

  * Added Gemma 12B support with quantized weights
  * Enhanced LTXAV text encoder with device selection support and reduced VRAM usage
  * Improved memory estimation for LTXAV text encoder

  **Performance Improvements**

  * Fixed FP8MM offloading performance issues
  * Added warning for outdated PyTorch versions with recommendation to upgrade to cu130 for performance boost
  * Updated comfy kitchen version requirements

  **Bug Fixes**

  * Fixed stable release workflow to properly pull latest comfy kitchen updates
  * Removed confusing load statistics from model patcher
  * Updated workflow templates to v0.7.69
</Update>

<Update label="v0.8.0" description="January 7, 2026">
  **New Models Support**

  * Added LTXV 2 model support
  * Added NVFP4 checkpoint support (fp4 matrix multiplication)
  * Added Sage Attention 3 support via CLI argument

  **API Improvements**

  * V3 API: Exposed DynamicCombo and Autogrow functionality
  * API nodes: Kling Omni 720p resolution support, WAN2.6 ReferenceToVideo
  * Tripo3D: Optimized face\_limit parameter handling
  * Fixed URL encoding preservation for Vidu API signed URLs

  **Fixes**

  * Fixed upscale model CPU offloading
  * Fixed LTXV2 text encoder lowvram compatibility
  * Fixed fp8 processing issues
  * Fixed MPO format images to use first frame only
  * Conditional comfy-kitchen CUDA support based on PyTorch version

  **Other**

  * Added OOM memory summary for debugging
  * Mahiro CFG display name update
  * Workflow templates updated to v0.7.67
  * Code refactoring and cleanup (CLIP preprocessing, comfy-kitchen integration)
</Update>

<Update label="v0.7.0" description="December 31, 2025">
  **System Requirements**

  * PyTorch 2.4+ minimum version requirement

  **Fixes & Improvements**

  * Enabled async memory offload by default for AMD GPUs
  * Fixed ancestral sampler noise on CPU inference
  * Improved memory management error handling (pin/unpin operations)
  * Added VACE context handling in context windows

  **Updates**

  * ComfyUI Frontend updated to v1.35.9
  * ComfyUI Manager updated to v4.0.4
  * Workflow templates updated to v0.7.64

  **New Nodes**

  * Added ManualSigmas node for sampling control
  * Added Kling Motion Control node
  * ResizeByLongerSide now supports video processing

  **API Nodes**

  * Gemini API: Force enable prompt enhancement
  * Billing changed from dollars to credits
  * Deprecated "seededit", updated Seedream node display names

  **Technical**

  * Converted image processing nodes to V3 schema
  * Optimized Lumina/Z image model (removed unused components)
</Update>

<Update label="v0.6.0" description="December 24, 2025">
  **New Model Support**

  * Qwen Image Layered
  * NewBie Image Exp0.1

  **New Features**

  * Unified jobs API with /api/jobs endpoints for workflow monitoring

  **Improvements**

  * Disabled watermark generation by default in API nodes
  * Refactored trainer with resolution bucketing for better training efficiency
  * Enhanced AMD GPU support
  * Extended Kling O1 StartEndFrame node duration range
  * Updated Topaz 4k video upscaling functionality

  **Bug Fixes**

  * Fixed mask concatenation issues in ZImageFunControlNet in --gpu-only mode
</Update>

<Update label="v0.5.1" description="December 18, 2025">
  * Added GPT-Image-1.5 API nodes
  * Fixed V3 nodes processing regression
  * Improved SA-Solver accuracy
</Update>

<Update label="v0.5.0" description="December 17, 2025">
  **New Models & Features**

  * WanMove model for advanced motion processing
  * Qwen Edit 2511 with automatic detection
  * Z-Image Fun Control Union 2.0 with inpainting

  **API Nodes**

  * Kling Omni Image, TextToVideoWithAudio, ImageToVideoWithAudio
  * Wan2.6 model integration
  * Tripo3.0 for 3D model generation

  **Performance**

  * Improved memory estimation for Z-Image and SD3 models
  * Better GPU memory management for Qwen-Image VAE
  * Frontend updated to v1.34.9
</Update>

<Update label="v0.4.0" description="December 10, 2025">
  **Model Support**

  * Ovis Image
  * Kandinsky 5.0 (T2V/I2V/T2I variants)
  * Z-Image Alibaba PAI-Fun ControlNet support
  * Improved Z-Image FP16 compatibility
  * Added PATCH method to CORS headers and chroma-radiance-x0 mode

  **Workflow &  Enhancements**

  * Context windows fixes and enhanced temporal processing
  * Kling API @image reference format
  * ComfyUI-Manager pip installation support

  **Frontend Improvements**

  * Improve frontend load/startup time significantly
  * Restored settings button in sidebar
  * GPU accelerated maskeditor rendering
  * Improve asset cards and queue progress panel designs
  * Add missing nodes warning UI to queue button and breadcrumb
  * Mobile fixes
  * various bug fixes

  **Major VRAM Optimizations**

  * Temporal rolling VAE delivering massive VRAM reductions for video models (Hunyuan/Kandinsky)
  * Reduced LoRA memory reservations, especially beneficial for Flux2 workflows
  * Fixed Flux2 OOM errors with improved dequantization offload accounting
  * Enhanced LoRA computation speed with FP16 processing
  * Optimized text encoder GPU usage to prevent unnecessary CPU fallbacks

  **V3 Schema Migration**

  * Converted 3D, audio, freelunch, and mask nodes to V3 schema
  * Added MatchType, DynamicCombo, and Autogrow support for improved workflow flexibility

  **Bug Fixes & Compatibility**

  * Fixed text encoder regression when loaded directly on GPU
  * Resolved transformer\_options clearing issue in Lumina models
  * Fixed Qwen Image LoRA training, HunyuanVideo 1.5 meanflow distil issues
  * Corrected EmptyAudio node input types for proper audio workflow integration
  * Enhanced VRAM calculation accuracy to prevent unwanted full offloading
  * Support for "transformer." LoRA prefix in Z-Image workflows
  * Improved scaled FP8 format compatibility with mixed quantization operations

  **Note: for Desktop users**

  * If you have not turned off the auto-update, please wait for the latest Desktop release, it will auto-update to the latest version.
  * If you are using the Desktop and **if you also turn off the auto-update**, the Desktop might not be able to auto-update for the latest version this time.
  * Please download the latest Desktop version from [here](https://www.comfy.org/download) to get the latest features.
</Update>

<Update label="v0.3.76" description="December 2, 2025">
  **Frontend UI/UX**

  * New UI: **Nodes 2.0** public beta
  * Linear mode beta version (You can enable it by setting a hot-key in keybinding.)
  * Subgraphs improvement and bug fixes
  * Improve missing node UX
  * New workflow progress panel
  * New Assets sidebar

  **3D feature**

  * Support panoramic image in the 3D node
  * Merge 3D animation node into 3D node

  **Lora Trainer**

  * Support multi-resolution for ComfyUI native LoRA trainer
  * Support Z-Image LoRA training

  **Performance & model support**

  * Support video tiny VAEs
  * Support z-image LoRA formats
  * Enable async offloading by default on Nvidia

  **Partner Nodes**

  * Veo3 First-Last-Frame Node
  * Add Kling v2.5 turbo to Kling FirstLastFrame node
  * Kling O1 model support
</Update>

<Update label="v0.3.75" description="November 26, 2025">
  **New Model Support**

  * Added Z Image model with optimized performance for image processing workflows

  **Bug Fixes**

  * Fixed LoRA functionality with mixed FP8 precision models
  * Enhanced Flux2 reference image memory estimation to reduce VRAM errors
</Update>

<Update label="v0.3.73" description="November 26, 2025">
  **Bug Fixes**

  * Fixed critical system crashes that could interrupt workflow execution
  * Optimized Flux 2 text encoder VRAM usage for better performance
</Update>

<Update label="v0.3.72" description="November 25, 2025">
  **New Model Support**

  * Added comprehensive Flux 2 model support including Flux 2 Pro API nodes
  * Enhanced HunyuanVideo workflows with new variants and improved display names

  **API & Security Improvements**

  * Improved API security with Content Security Policy headers
  * Fixed public API access issues and Gemini model support

  **Video Processing**

  * Added `get_frame_count` and `get_frame_rate` methods for better video workflow control

  **Performance Optimizations**

  * Optimized text encoder quantization with hardware-aware detection
  * Enhanced quantization support with better memory management

  **Developer Tools**

  * Added BlockInfo support for Chroma, Qwen-Image, and HunyuanVideo models

  **Frontend & Dependencies**

  * Updated frontend to v1.30.6
  * Bumped Transformers version
</Update>

<Update label="v0.3.71" description="November 21, 2025">
  **Model Compatibility & Enhancements**

  * **HunyuanVideo 1.5 Support**: Added compatibility for the latest version of HunyuanVideo models, expanding video generation capabilities
  * **LLAMA Text Encoder Improvements**: Added ability to disable final normalization in LLAMA-based text encoder models for better workflow customization
  * **HunyuanV3D Schema Migration**: Updated Hunyuan3D nodes to V3 schema for improved performance and compatibility

  **API Node Expansions**

  * **New Topaz API Nodes**: Added support for Topaz video enhancement workflows directly within ComfyUI
  * **Nano Banana Pro Integration**: Expanded API node collection with Nano Banana Pro for enhanced processing capabilities
  * **Kling Lip Sync Improvements**: Fixed audio format conversion issues in KlingLipSyncAudioToVideoNode, ensuring proper MP3 format handling

  **Image Processing & Workflow Improvements**

  * **Enhanced Image Batching**: Fixed ImageBatch node to handle images with different channel counts and automatically add alpha channels when needed
  * **Preview Node Refinement**: Renamed PreviewAny node to "Preview as Text" for clearer workflow organization
  * **Workflow Template Updates**: Enhanced server template handler to support multi-package distribution for better workflow management

  **Performance & System Optimizations**

  * **CUDA Optimization**: Disabled unnecessary workarounds on newer CUDNN versions for improved GPU performance
  * Fixed workflow naming issues and improved overall stability for complex processing pipelines
</Update>

<Update label="v0.3.70" description="November 19, 2025">
  **CUDA 12.6 Support & Distribution**

  * Added official CUDA 12.6 release workflow and portable download support for enhanced GPU compatibility
  * Updated README with corrected portable download links for streamlined installation

  **Model Compatibility & Fixes**

  * **HunYuan 3D 2.0 Support**: Fixed compatibility issues for improved 3D model generation workflows
  * **EasyCache Improvements**: Resolved input/output channel mismatches that affected certain model configurations
  * Enhanced block swap functionality by removing potentially harmful native custom node implementations

  **API Node Enhancements**

  * **New Gemini Models Added**: Expanded AI model options for text and multimodal generation workflows
  * Improved API node development infrastructure with updated PR templates and Python 3.10 minimum version requirements

  **Development & Infrastructure**

  * Enhanced pylint configuration for better code quality in custom node development
  * Improved release automation and distribution processes for more reliable updates
</Update>

<Update label="v0.3.69" description="November 18, 2025">
  **Memory & Performance Optimizations**

  * **Pinned Memory Enabled by Default** for NVIDIA and AMD GPUs
  * **Reduced VRAM Usage** for Flux, Qwen, and LTX-Video models
  * Smart model unloading that automatically frees memory when VRAM usage increases
  * Improved weight casting performance on offload streams

  **New Features**

  * **ScaleROPE Node Now Works with Flux Models**
  * Added left padding support to tokenizers
  * Added `create_time` field to `/history` and `/queue` endpoints

  **Bug Fixes**

  * Fixed custom node import errors for SingleStreamBlock/DoubleStreamBlock (temporary fix)
  * Fixed Qwen ControlNet regression
  * Enhanced quantized operations with offload support and stability improvements
  * Unified RoPE function implementation across models
</Update>

<Update label="v0.3.68" description="November 5, 2025">
  **Performance & Memory Optimizations**

  * Introduced **Mixed Precision Quantization System** for optimized model loading
  * Added **RAM Pressure Cache Mode** for intelligent memory management under resource constraints
  * Accelerated model offloading using pinned memory with automatic low-RAM hardware detection
  * Enhanced FP8 operations: reduced memory usage and fixed torch.compile performance regressions
  * Improved async offload speeds and resolved race conditions

  **New Nodes & Execution Features**

  * **ScaleROPE Node**: Rope scaling support for WAN and Lumina models
  * Enhanced subgraph execution allowing multiple runs within single workflows
  * Improved caching system with proper handling of bytes data and None outputs

  **API Node Enhancements**

  * Migrated API nodes to V3 client architecture: Luma, Minimax, Pixverse, Ideogram, StabilityAI, Pika, Recraft, Hypernetwork, OpenAI
  * Extended LTXV API nodes with 12s-20s duration options
  * Fixed img2img operations in DALL-E 2 node
  * Enhanced Rodin3D nodes to return proper relative paths

  **Updates**

  * Embedded documentation updated to v0.3.1
  * Workflow templates updated to v0.2.11
  * Fixed Windows pinned memory allocation issues
</Update>

<Update label="v0.3.67" description="October 28, 2025">
  **API Nodes**

  * **LTXV API Integration**: Added new LTXV API nodes for Lightricks LTX video generation
  * Network Client V2 upgrade with async operations and cancellation support
  * Converted Tripo and Gemini API nodes to V3 schema

  **Performance & Compatibility**

  * Improved AMD GPU support by only disabling cudnn on newer AMD GPUs
  * Fixed Windows-specific network issues in API nodes for better retry handling

  **Core Improvements**

  * Enhanced dependency-aware caching system that fixes --cache-none behavior with loops
  * Added support for multi-dimensional latents
  * Added custom node published subgraphs endpoint

  **Updates**

  * Frontend bumped to version 1.28.8
  * Template updates to version 0.2.4
</Update>

<Update label="v0.3.66" description="October 21, 2025">
  **Frontend Updates**

  * **Subgraph Widget Editing**: Edit subgraph parameters directly from new Parameters panel without entering the subgraph
  * **Template Modal Redesign**: New template browser with advanced filtering by model tags and categories

  **Performance Optimizations**

  * Iimproved workflow cancellation speed
  * Fixed VAE memory issue consuming 3x more on PyTorch 2.9 with NVIDIA GPUs
  * Enhanced chroma radiance processing speed and fixed batch size issues above 1

  **API Nodes**

  * Added Veo 3.1 model support
  * Added TemporalScoreRescaling node for advanced temporal control in video workflows

  **Hardware & Compatibility**

  * Disabled FP8 operations for AMD gfx942 GPUs
  * Improved CUDA memory management in --fast autotune mode

  **Execution & Schema**

  * Converted ControlNet nodes to V3 schema
  * Enhanced EasyCache with proper batch\_slice handling
  * Improved merge\_nested\_dicts functionality with proper input ordering
  * Added deprecation warnings for unused files
</Update>

<Update label="v0.3.65" description="October 14, 2025">
  **Node Schema Migration (V3)**

  * Migrated core node categories to V3 schema including model downscale, LoRA extraction, compositing, latent ops, SD3/SLG, Flux, upscale models, and HunyuanVideo nodes

  **Audio & Model Improvements**

  * Added MMaudio 16K VAE support for high-fidelity audio workflows
  * Fixed mono audio incorrectly saving as stereo
  * Refactored model sampling sigmas code and fixed FP8 scaled LoRA issues
  * Fixed loading of older Stable Diffusion checkpoints on newer NumPy versions

  **AMD GPU Optimizations**

  * Better memory estimation for SD/Flux VAE operations
  * Enabled RDNA4 PyTorch attention on ROCm 7.0+

  **API Node Updates**

  * Added price extractor and improvements to Kling/Pika API nodes
  * Enhanced Gemini Image API with aspect\_ratio support

  **Updates**

  * Template v0.1.95, node docs v0.3.0
  * Fixed WAN2.2 cache VRAM leak
</Update>

<Update label="v0.3.64" description="October 8, 2025">
  **API Nodes**

  * Added Sora2 API node for OpenAI's video generation API
</Update>

<Update label="v0.3.63" description="October 6, 2025">
  **Model Compatibility Enhancements**

  * **HunyuanVAE Support**: Added support for the new HunyuanVAE, expanding model compatibility for advanced image generation workflows
  * **Epsilon Scaling Node**: Introduced new Epsilon Scaling node that reduces exposure bias in diffusion models by scaling predicted noise, improving generation quality (based on the paper [Elucidating the Exposure Bias in Diffusion Models](https://arxiv.org/abs/2308.15321))

  **Memory and Performance Optimizations**

  * **VAE Memory Leak Fix**: Fixed VRAM leak caused by Python call stack holding tensor references during VAE OOM exception handling, significantly improving tiled fallback reliability on low VRAM devices
  * **AMD Support**: Enabled TORCH\_ROCM\_AOTRITON\_ENABLE\_EXPERIMENTAL by default

  **API Node Updates**

  * **Kling 2.5 Turbo**: Added support for kling-2-5-turbo in both txt2video and img2video nodes, with proper mode configuration fixes
  * **API Node Fixes**: Improved Gemini node base64 handling and fixed indentation issues in Recraft API node functions

  **Node Schema Migration (V3)**

  * **Extensive V3 Conversion**: Migrated numerous node categories to V3 schema including audio encoder, GITS, differential diffusion, optimal steps, PAG, LT, IP2P, morphology, torch compile, EPS, Pixverse, TomeSD, edit model, Rodin, and Stable3D nodes for improved workflow compatibility

  **Developer Experience Improvements**

  * **Code Quality**: Added pylint support for comfy\_api\_nodes folder and updated example\_node.py to use V3 schema, making custom node development more consistent
  * **Documentation Updates**: Enhanced AMD installation instructions with nightly PyTorch commands for Windows users

  **Frontend Updates**

  * **Subgraph Publish**: Allows publishing subgraphs to the node library
  * **Node Selection Toolbox Redesign**: Redesigned the node selection toolbox
</Update>

<Update label="v0.3.62" description="September 30, 2025">
  **API Node**

  * **Rodin3D-Gen2 Parameter Fix**
  * **Seedance Pro Model Support**
</Update>

<Update label="v0.3.61" description="September 30, 2025">
  **API Node**

  * **Rodin3D Gen-2**: Rodin's most powerful image-to-3D tool, is now live in ComfyUI!
  * **WAN Image-to-Image**: Wan2.5 Image-to-Image API node, support image editing.

  **Enhanced Audio Capabilities**

  * **New Audio Nodes**: Added new audio nodes for enhanced audio-driven workflows and multimodal content creation

  **Model Compatibility Fixes**

  * **Qwen2.5VL Template Handling**: Improved template management for Qwen2.5VL models when templates are already present in prompts
  * **HuMo View Operation**: Fixed .view() operation issues in HuMo models for more stable video generation

  **Memory and Performance Optimizations**

  * **Memory Leak Fix**: Resolved memory leaks by explicitly detaching model finalizers, improving long-running workflow stability
  * **Sampler CFG Enhancement**: Added 'input\_cond' and 'input\_uncond' parameters to sampler CFG function arguments for more flexible conditioning control
</Update>

<Update label="v0.3.60" description="September 23, 2025">
  **New Model Support**

  * **Wan2.2 Animate**: Support for Wan2.2 Animate video generation model with character replacement and motion transfer capabilities
  * **Qwen Image Edit 2509 Support**: Support for the updated Qwen Image Edit 2509 with multi-image editing, higher consistency, and native ControlNet support
  * **HuMo Models**: Added support for both 1.7B and 17B HuMo models that use audio to drive video generation while maintaining lip sync
  * **Chroma Radiance**: A model that performs image generation in pixel space, reducing losses during the image generation process
  * **Omnigen2 UMO LoRA**: Added support for Omnigen2 UMO LoRA models

  **API Node Additions**

  * **Kling v2.1 Support**: Added kling-v2-1 model to KlingStartEndFrame node
  * **Seedream4 Fixes**: Fixed the flag that ignores errors on partial success, making workflows more robust

  **Node Schema Migration (V3)**

  * **Core Node Updates**: Migrated multiple node categories to V3 schema including Minimax API, Cosmos, conditioning, CFG, and Canny nodes

  **Performance & Technical Improvements**

  * **FP8 Operations**: Enabled FP8 operations by default on gfx1200 hardware for faster processing
  * **LoRA Trainer Fixes**: Resolved bugs with FP8 model compatibility in LoRA training workflows

  **Frontend Updates**

  * **Frontend Version Update**: Updated to version 1.26.13
</Update>

<Update label="v0.3.59" description="September 10, 2025">
  **ByteDance Seedream 4.0 Integration**

  * **New Seedream Node**: Added ByteDanceSeedream (4.0) node.
</Update>

<Update label="v0.3.58" description="September 6, 2025">
  **New Model Support**

  * Hunyuan Image 2.1 regular model
  * Hunyuan 3D 2.1

  **New API Nodes**

  * Stable Audio 2.5 API
  * Seedance Video API
</Update>

<Update label="v0.3.57" description="September 4, 2025">
  **ByteDance USO Model Support**

  * **UXO Subject Identity LoRA Support**: It's a subject identity LoRA model based on FLUX architecture
  * **Related Workflow**: Please find the workflow in the template `Flux` -> `Flux.1 Dev USO Reference Image Generation`

  **Workflow Utilities**

  * **ImageScaleToMaxDimension Node**: New utility for intelligent image scaling
  * **SEEDS Noise System**: Updated noise decomposition with improved algorithms
  * **Enhanced Prompt Control**: Interrupt handler now accepts prompt\_id parameters

  **Performance & Architecture**

  * **V3 Schema Migration**: Converted some core nodes to V3 schema
  * **Convolution AutoTuning**: Enabled automatic convolution optimization

  **New API Integration**

  * **ByteDance Image Nodes**: Added support for ByteDance image generation services
  * **Ideogram Character Reference**: Ideogram v3 API now supports character reference
</Update>

<Update label="v0.3.56" description="August 30, 2025">
  **Performance Enhancement**

  * **Reduced RAM Usage on Windows**
</Update>

<Update label="v0.3.55" description="August 29, 2025">
  **Wan2.2 S2V Workflow Enhancements & Model Support Expansion**

  This release focuses on Wan2.2 S2V related video workflow capabilities and model support expansion:

  **Wan2.2 S2V Workflow Control**

  * **WanSoundImageToVideoExtend Node**: New manual video extension node for audio-driven video workflows, giving creators precise control over generated video length and timing. This enables fine-tuned control over how audio content translates to video sequences.
  * **Audio-Video Synchronization**: Fixed critical issue where extending video past audio length caused workflow failures, ensuring reliable sound-to-video generation regardless of audio duration.
  * **Automatic Audio Trimming**: Video saves now automatically trim audio to match video length, eliminating audio-video sync issues in final output files.

  **Advanced Latent Processing**

  * **LatentCut Node**: New node for cutting latents at precise points, enabling more granular control over latent space manipulation in complex generation workflows. This is particularly useful for batch processing and temporal video workflows, such as removing specific frames from videos.

  **Wan2.2 5B Model Integration**

  * **Fun Control Model Support**: Added support for Wan2.2 5B fun control model.
  * **Fun Inpaint Model Support**: Integrated Wan2.2 5B fun inpaint model.
</Update>

<Update label="v0.3.54" description="August 28, 2025">
  **Node Model Patch Improvements**

  This focused update improves the core node model patching system that underpins ComfyUI's flexible architecture:

  **Core Infrastructure Enhancement**

  * **Node Model Patch Updates**: Enhanced nodes\_model\_patch.py with improvements to the underlying model patching mechanism, making ComfyUI extensions for Qwen-Image ControlNet easier

  **Workflow Benefits**

  * **Enhanced Stability**: Core model patching improvements contribute to more reliable node execution and model handling across different workflow configurations
</Update>

<Update label="v0.3.53" description="August 28, 2025">
  **Audio Workflow Integration & Enhanced Performance Optimizations**

  This release adds ComfyUI audio processing capabilities and includes performance improvements and model compatibility updates:

  **Audio Processing Updates**

  * **Wav2vec2 Audio Encoder**: Added native wav2vec2 implementation as an audio encoder model, enabling audio-to-embedding workflows for multimodal applications
  * **Audio Encoders Directory**: Added models/audio\_encoders directory, which is the audio encoder directory for Wan2.2 S2V
  * **AudioEncoderOutput V3 Support**: Made AudioEncoderOutput compatible with V3 node schema, ensuring seamless integration with modern workflow architectures

  **Google Gemini API Integration**

  * **Gemini Image API Node**: Added new Google Gemini Image API node, the "nano-Nano-banana" image editing model API with high consistency

  **Video Generation Performance & Memory Optimizations**

  * **WAN 2.2 S2V Model Support**: Work-in-progress implementation of WAN 2.2 Sound-to-Video model with optimized memory usage and performance
  * **Enhanced S2V Performance**: Performance improvements for video generation longer than 120 frames, improving extended video workflows
  * **Better Memory Estimation**: Improved memory usage estimation for S2V workflows prevents out-of-memory errors during long video generation
  * **Negative Audio Handling**: Fixed negative audio input handling in S2V workflows to use proper zero values

  **Sampling & Node Enhancements**

  * **DPM++ 2M SDE Heun (RES) Sampler**: New advanced sampler by @Balladie provides additional sampling options for fine-tuned generation control
  * **LatentConcat Node**: New node for concatenating latent tensors, enabling advanced latent space manipulation workflows
  * **EasyCache/LazyCache Stability**: Fixed critical crashes when tensor properties (shape/dtype/device) change during sampling, ensuring workflow reliability

  **Model Compatibility Improvements**

  * **ControlNet Type Models**: Enhanced compatibility fixes for ControlNet-type models working with Qwen Edit and Kontext workflows
  * **Flux Memory Optimization**: Adjusted Flux model memory usage factors for better resource utilization

  **Infrastructure & Reliability**

  * **Template Updates**: Updated to versions 0.1.66 and 0.1.68
  * **Documentation Cleanup**: Removed incompletely implemented models from readme to avoid user confusion
</Update>

<Update label="v0.3.52" description="August 23, 2025">
  **Enhanced Model Support & Qwen Image ControlNet Integration**

  This release significantly expands ControlNet capabilities and improves model compatibility, making ComfyUI workflows more versatile and reliable:

  **Qwen ControlNet Ecosystem**

  * **Diffsynth ControlNet Support**: Added support for Qwen Diffsynth ControlNets with Canny and depth conditioning, enabling precise edge and depth-based image control
  * **InstantX Qwen ControlNet**: Integrated InstantX Qwen ControlNet for expanded creative control options
  * **Inpaint ControlNet/Model Patches**: Enhanced inpainting capabilities with dedicated Diffsynth inpaint ControlNet support

  **Node Architecture & API Evolution**

  * **V3 Architecture Migration**: String nodes, Google Veo API, and Ideogram API nodes upgraded to V3 architecture for better performance and consistency
  * **Enhanced API Nodes**: OpenAI Chat node renamed to "OpenAI ChatGPT" for clarity, Gemini Chat node now includes copy button functionality
  * **Improved Usability**: API nodes now provide better user experience with clearer labeling and enhanced interaction features

  **Workflow Reliability & Performance**

  * **LTXV Noise Mask Fix**: Resolved key frame noise mask dimension issues when real noise masks exist, ensuring stable video workflow execution
  * **3D Latent Conditioning Control**: Fixed conditioning masks on 3D latents, enabling proper depth-aware conditioning control in advanced workflows
  * **Invalid Filename Handling**: Improved workflow save functionality with proper handling of invalid filenames, preventing save failures
  * **EasyCache & LazyCache**: Implemented advanced caching systems for improved workflow execution performance

  **Platform & Development Improvements**

  * **Python 3.13 Support**: Full compatibility with Python 3.13, keeping ComfyUI current with latest Python developments
  * **Frontend Update**: Updated to v1.25.10 with improved navigation and user interface enhancements
  * **Elementwise Fusions**: Added performance optimizations through elementwise operations fusion
  * **Navigation Mode Rollback**: Rolled back navigation default to traditional legacy mode, avoiding user experience issues caused by default enabled standard navigation mode. Users can still enable standard navigation mode in settings
</Update>

<Update label="v0.3.51" description="August 20, 2025">
  **Model Support**

  * **Qwen-Image-Edit Model**: Native support for Qwen-Image-Edit
  * **FluxKontextMultiReferenceLatentMethod Node**: Multi-reference input node for Flux workflows
  * **WAN 2.2 Fun Camera Model Support**: Support for video generation through camera control
  * **Template Updates**: Upgraded to version 0.1.62, added Wan2.2 Fun Camera and Qwen Image Edit templates

  **Core Function Improvements**

  * **Context Windows Support**: Enhanced sampling code to support longer sequence generation tasks
  * **SDPA Backend Optimization**: Improved Scaled Dot Product Attention backend settings for better performance

  **Multimedia Node Support**

  * **Audio Recording Node**: New native audio recording node, now you can record audio directly in ComfyUI
  * **Audio Video Integration**: Complete audio-video dependency integration

  **API Node Support Updates**

  * **GPT-5 Series Models**: Support for the latest GPT-5 models
  * **Kling V2-1 and V2-1-Master**: Updated video generation model functionality
  * **Minimax Hailuo Video Node**: New video generation node
  * **Vidu Video Node**: Vidu API node support
  * **Google Model Updates**: Added new Google Gemini models
  * **OpenAI API Fix**: Fixed MIME type errors in OpenAI API node input images

  **Performance Optimization**

  * **Intel GPU Compatibility**: Fixed Intel integrated GPU compatibility issues
  * **PyTorch Compatibility**: Enhanced compatibility with older PyTorch versions
  * **Torch Compile Optimization**: Improved torch compile behavior
  * **Memory Management**: Optimized installation size and memory efficiency

  **Frontend Changes**

  * **Subgraph Support**: Subgraph functionality support
  * **Shortcut Panel**: Added bottom shortcut panel
  * **UI Layout Modifications**: Modified terminal entry layout, added template, log panel and other entries
  * **Standard Canvas Mode**: Added standard canvas mode, can be switched in `Lite Graph` > `Canvas` > `Canvas Navigation Mode`
  * **Mini Map**: Added workflow mini map
  * **Tab Preview**: Added workflow tab preview
  * **Top Tab Menu Layout Adjustments**
</Update>

<Update label="v0.3.50" description="August 13, 2025">
  **Model Integration & Performance Enhancements**

  This release expands ComfyUI's model ecosystem with enhanced Qwen support, async API capabilities, and stability improvements for complex workflows:

  **Qwen Model Ecosystem**

  * **Qwen Image Model Support**: Improved integration including proper LoRA loading and model merging capabilities for sophisticated vision workflows
  * **Qwen Model Merging Node**: New dedicated node for merging Qwen image models, allowing creators to combine different model strengths
  * **SimpleTuner Lycoris LoRA Support**: Extended compatibility with SimpleTuner-trained Lycoris LoRAs for Qwen-Image models

  **API & Performance Infrastructure**

  * **Async API Nodes**: Introduction of asynchronous API nodes, enabling non-blocking workflow execution for better performance
  * **Memory Handling**: Enhanced RepeatLatentBatch node now properly handles multi-dimensional latents, fixing workflow interruptions
  * **WAN 2.2 Fun Control Support**: Added support for WAN 2.2 fun control features, expanding creative control for video workflows

  **Hardware Optimization & Compatibility**

  * **AMD GPU Improvements**: Enhanced AMD Radeon support with improved FP16 accuracy handling and performance optimization
  * **RDNA3 Architecture Fixes**: Resolved issues with gfx1201 GPUs when using Flux models with PyTorch attention
  * **Updated PyTorch Support**: Bumped CUDA and ROCM PyTorch versions with testing on Python 3.13 and CUDA 12.9

  **Developer Experience Enhancements**

  * **Cleaner Logging**: Feature flags now only display in verbose mode, reducing console noise
  * **Audio Processing Safety**: Enhanced torchaudio import safety checks prevent crashes when audio dependencies are unavailable
  * **Kling API Improvements**: Fixed image type parameter handling in Kling Image API nodes

  **Workflow Benefits**

  * **Async Workflow Execution**: New async API capabilities enable more responsive workflows when integrating external services
  * **Model Flexibility**: Expanded Qwen support allows for more diverse vision-language workflows with improved LoRA compatibility
  * **Hardware Utilization**: AMD GPU optimizations and updated PyTorch support improve performance across hardware configurations
  * **Batch Processing**: Fixed RepeatLatentBatch ensures reliable operation with complex multi-dimensional data structures
  * **Video Control**: WAN 2.2 fun control features provide advanced creative control for video generation workflows
</Update>

<Update label="v0.3.49" description="August 5, 2025">
  **UI Experience & Model Support**

  This release brings user experience improvements and model support that enhance workflow creation and performance:

  **User Interface Enhancements**

  * **Recently Used Items API**: New API for tracking recently used items in the interface, streamlining workflow creation
  * **Workflow Navigation**: Enhanced user experience with better organization of commonly accessed elements

  **Model Integration**

  * **Qwen Vision Model Support**: Initial support for Qwen image models with configuration options
  * **Image Processing**: Enhanced Qwen model integration allows for more versatile image analysis and generation workflows

  **Video Generation**

  * **Veo3 Video Generation**: Added Veo3 video generation node with integrated audio support
  * **Audio-Visual Synthesis**: Capability combining video and audio generation in a single node

  **Performance & Stability Improvements**

  * **Memory Management**: Optimized conditional VRAM usage through improved casting and device transfer operations
  * **Device Consistency**: Fixes ensuring all conditioning data and context remain on correct devices
  * **ControlNet Stability**: Resolved ControlNet compatibility issues, restoring functionality for image control workflows

  **Developer & System Enhancements**

  * **Error Handling**: Added warnings and crash prevention when conditioning devices don't match
  * **Template Updates**: Multiple template version updates (0.1.47, 0.1.48, 0.1.51) maintaining compatibility

  **Workflow Benefits**

  * **Faster Iteration**: Recently used items API enables quicker workflow assembly and modification
  * **Enhanced Creativity**: Qwen vision models open new possibilities for image understanding and manipulation workflows
  * **Video Production**: Veo3 integration transforms ComfyUI into a comprehensive multimedia creation platform
  * **Reliability**: Memory optimizations and device management fixes ensure stable operation with complex workflows
  * **Performance**: Optimized VRAM usage allows for more ambitious projects on systems with limited resources
</Update>

<Update label="v0.3.48" description="August 2, 2025">
  **API Enhancement & Performance Optimizations**

  This release introduces backend improvements and performance optimizations that enhance workflow execution and node development:

  **ComfyAPI Core Framework**

  * **ComfyAPI Core v0.0.2**: Update to the core API framework, providing improved stability and extensibility
  * **Partial Execution Support**: New backend support for partial workflow execution, enabling efficient processing of multi-stage workflows

  **Video Processing Improvements**

  * **WAN Camera Memory Optimization**: Enhanced memory management for WAN-based camera workflows, reducing VRAM usage
  * **WanFirstLastFrameToVideo Fix**: Resolved issue preventing proper video generation when clip vision components are not available

  **Performance & Model Optimizations**

  * **VAE Nonlinearity Enhancement**: Replaced manual activation functions with optimized torch.silu in VAE operations
  * **WAN VAE Optimizations**: Fine-tuning optimizations for WAN VAE operations, improving processing speed and memory efficiency

  **Node Schema Evolution**

  * **V3 Node Schema Definition**: Implementation of next-generation node schema system
  * **Template Updates**: Multiple template version updates (0.1.44, 0.1.45) ensuring compatibility

  **Workflow Development Benefits**

  * **Video Workflows**: Improved stability and performance for video generation pipelines
  * **Memory Management**: Optimized memory usage patterns enable more complex workflows on systems with limited VRAM
  * **API Reliability**: Core API enhancements provide more stable foundation for custom node development
  * **Execution Flexibility**: New partial execution capabilities allow for more efficient debugging and development
</Update>

<Update label="v0.3.47" description="July 30, 2025">
  **Memory Optimization & Large Model Performance**

  This release focuses on memory optimizations for large model workflows, improving performance with WAN 2.2 models and VRAM management:

  **WAN 2.2 Model Optimizations**

  * **Reduced Memory Footprint**: Eliminated unnecessary memory clones in WAN 2.2 VAE operations, reducing memory usage
  * **5B I2V Model Support**: Memory optimization for WAN 2.2 5B image-to-video models, making these models more accessible

  **Enhanced VRAM Management**

  * **Windows Large Card Support**: Added reserved VRAM allocation for high-end graphics cards on Windows
  * **Memory Allocation**: Improved memory management for users working with multiple large models simultaneously

  **Workflow Performance Benefits**

  * **VAE Processing**: WAN 2.2 VAE operations now run more efficiently with reduced memory overhead
  * **Large Model Inference**: Enhanced stability when working with billion-parameter models
  * **Batch Processing**: Memory optimizations enable better handling of batch operations with large models
</Update>

<Update label="v0.3.46" description="July 28, 2025">
  **Hardware Acceleration & Audio Processing**

  This release expands hardware support and enhances audio processing capabilities:

  **Audio Processing Enhancements**

  * **PyAV Audio Backend**: Replaced torchaudio.load with PyAV for more reliable audio processing in video workflows
  * **Audio Integration**: Enhanced audio handling for multimedia generation workflows

  **Hardware Support**

  * **Iluvatar CoreX Support**: Added native support for Iluvatar CoreX accelerators
  * **Intel XPU Optimization**: XPU support improvements including async offload capabilities
  * **AMD ROCm Enhancements**: Enabled PyTorch attention by default for gfx1201 on Torch 2.8
  * **CUDA Memory Management**: Fixed CUDA malloc to only activate on CUDA-enabled PyTorch installations

  **Sampling Algorithm Improvements**

  * **Euler CFG++ Enhancement**: Separated denoised and noise estimation processes in Euler CFG++ sampler
  * **WAN Model Support**: Added support for WAN (Wavelet-based Attention Network) models

  **Training Features**

  * **Training Nodes**: Added algorithm support, gradient accumulation, and optional gradient checkpointing
  * **Training Flexibility**: Better memory management and performance optimization for custom model training

  **Node & Workflow Enhancements**

  * **Moonvalley V2V Node**: Added Moonvalley Marey V2V node with enhanced input validation
  * **Negative Prompt Updates**: Improved negative prompt handling for Moonvalley nodes
  * **History API Enhancement**: Added map\_function parameter to get\_history API

  **API & System Improvements**

  * **Frontend Version Tracking**: Added required\_frontend\_version parameter in /system\_stats API response
  * **Device Information**: Enhanced XPU device name printing for better hardware identification
  * **Template Updates**: Multiple template updates (0.1.40, 0.1.41) ensuring compatibility

  **Developer Experience**

  * **Documentation Updates**: Enhanced README with examples and updated model integration guides
  * **Line Ending Fixes**: Improved cross-platform compatibility by standardizing line endings
  * **Code Cleanup**: Removed deprecated code and optimized components
</Update>

<Update label="v0.3.45" description="July 21, 2025">
  **Sampling & Training Improvements**

  This release introduces enhancements to sampling algorithms, training capabilities, and node functionality:

  **Sampling & Generation Features**

  * **SA-Solver Sampler**: New reconstructed SA-Solver sampling algorithm providing enhanced numerical stability
  * **Experimental CFGNorm Node**: Classifier-free guidance normalization for improved control over generation quality
  * **Nested Dual CFG Support**: Added nested style configuration to DualCFGGuider node
  * **SamplingPercentToSigma Node**: New utility node for precise sigma calculation from sampling percentages

  **Training Capabilities**

  * **Multi Image-Caption Dataset Support**: LoRA training node now handles multiple image-caption datasets simultaneously
  * **Training Loop Implementation**: Optimized training algorithms for improved convergence and stability
  * **Error Detection**: Added model detection error hints for LoRA operations

  **Platform & Performance Improvements**

  * **Async Node Support**: Full support for asynchronous node functions with earlier execution optimization
  * **Chroma Flexibility**: Un-hardcoded patch\_size parameter in Chroma
  * **LTXV VAE Decoder**: Switched to improved default padding mode for better image quality
  * **Safetensors Memory Management**: Added workaround for mmap issues

  **API & Integration Enhancements**

  * **Custom Prompt IDs**: API now allows specifying prompt IDs for better workflow tracking
  * **Kling API Optimization**: Increased polling timeout to prevent user timeouts
  * **History Token Cleanup**: Removed sensitive tokens from history items
  * **Python 3.9 Compatibility**: Fixed compatibility issues ensuring broader platform support

  **Bug Fixes & Stability**

  * **MaskComposite Fixes**: Resolved errors when destination masks have 2 dimensions
  * **Fresca Input/Output**: Corrected input and output handling for Fresca model workflows
  * **Reference Bug Fixes**: Resolved incorrect reference bugs in Gemini node implementations
  * **Line Ending Standardization**: Automated detection and removal of Windows line endings

  **Developer Experience**

  * **Warning Systems**: Added torch import mistake warnings to catch common configuration issues
  * **Template Updates**: Multiple template version updates (0.1.36, 0.1.37, 0.1.39) for improved custom node development
  * **Documentation**: Enhanced fast\_fp16\_accumulation documentation
</Update>

<Update label="v0.3.44" description="July 8, 2025">
  **Sampling & Model Control Enhancements**

  This release delivers improvements to sampling algorithms and model control systems:

  **Sampling Capabilities**

  * **TCFG Node**: Enhanced classifier-free guidance control for more nuanced generation control
  * **ER-SDE Sampler**: Migrated from VE to VP algorithm with new sampler node
  * **Skip Layer Guidance (SLG)**: Implementation for precise layer-level control during inference

  **Development Tools**

  * **Custom Node Management**: New `--whitelist-custom-nodes` argument pairs with `--disable-all-custom-nodes`
  * **Performance Optimizations**: Dual CFG node now optimizes automatically when CFG is 1.0
  * **GitHub Actions Integration**: Automated release webhook notifications

  **Image Processing Improvements**

  * **Transform Nodes**: Added ImageRotate and ImageFlip nodes for enhanced image manipulation
  * **ImageColorToMask Fix**: Corrected mask value returns for more accurate color-based masking
  * **3D Model Support**: Upload 3D models to custom subfolders for better organization

  **Guidance & Conditioning Enhancements**

  * **PerpNeg Guider**: Updated with improved pre and post-CFG handling
  * **Latent Conditioning Fix**: Resolved issues with conditioning at index > 0 for multi-step workflows
  * **Denoising Steps**: Added denoising step support to several samplers

  **Platform Stability**

  * **PyTorch Compatibility**: Fixed contiguous memory issues with PyTorch nightly builds
  * **FP8 Fallback**: Automatic fallback to regular operations when FP8 operations encounter exceptions
  * **Audio Processing**: Removed deprecated torchaudio.save function dependencies

  **Model Integration**

  * **Moonvalley Nodes**: Added native support for Moonvalley model workflows
  * **Scheduler Reordering**: Simple scheduler now defaults first
  * **Template Updates**: Multiple template version updates (0.1.31-0.1.35)

  **Security & Safety**

  * **Safe Loading**: Added warnings when loading files unsafely
  * **File Validation**: Enhanced checkpoint loading safety measures
</Update>

<Update label="v0.3.43" description="June 30, 2025">
  **Model Support & Workflow Reliability**

  This release brings improvements to model compatibility and workflow stability:

  **Expanded Model Documentation**: Added support documentation for Flux Kontext and Omnigen 2 models
  **VAE Encoding Improvements**: Removed unnecessary random noise injection during VAE encoding
  **Memory Management Fix**: Resolved a memory estimation bug affecting Kontext model usage
</Update>

<Update label="v0.3.41" description="June 17, 2025">
  **Model Support Additions**

  * **Cosmos Predict2 Support**: Implementation for text-to-image (2B and 14B models) and image-to-video generation workflows
  * **Flux Compatibility**: Chroma Text Encoder now works with regular Flux models
  * **LoRA Training Integration**: New native LoRA training node using weight adapter scheme

  **Performance & Hardware Optimizations**

  * **AMD GPU Enhancements**: Enabled FP8 operations and PyTorch attention on AMD GPUs
  * **Apple Silicon Fixes**: Addressed FP16 attention issues on Apple devices
  * **Flux Model Stability**: Resolved black image generation issues with certain Flux models

  **Sampling Improvements**

  * **Rectified Flow Samplers**: Added SEEDS and multistep DPM++ SDE samplers with RF support
  * **ModelSamplingContinuousEDM**: New cosmos\_rflow option for enhanced sampling control
  * **Memory Optimization**: Improved memory estimation for Cosmos models

  **Developer & Integration Features**

  * **SQLite Database Support**: Enhanced data management capabilities for custom nodes
  * **PyProject.toml Integration**: Automatic web folder registration from pyproject files
  * **Frontend Flexibility**: Support for semver suffixes and prerelease frontend versions
  * **Tokenizer Enhancements**: Configurable min\_length settings with tokenizer\_data

  **Quality of Life Improvements**

  * **Kontext Aspect Ratio Fix**: Resolved widget-only limitation
  * **SaveLora Consistency**: Standardized filename format across all save nodes
  * **Python Version Warnings**: Added alerts for outdated Python installations
  * **WebcamCapture Fixes**: Corrected IS\_CHANGED signature
</Update>

<Update label="v0.3.40" description="June 5, 2025">
  **Workflow Tools & Performance Optimizations**

  This release brings new workflow utilities and performance optimizations:

  **Workflow Tools**

  * **ImageStitch Node**: Concatenate multiple images seamlessly in your workflows
  * **GetImageSize Node**: Extract image dimensions with batch processing support
  * **Regex Replace Node**: Advanced text manipulation capabilities for workflows

  **Model Compatibility**

  * **Tensor Handling**: Streamlined list processing makes multi-model workflows more reliable
  * **BFL API Optimization**: Refined support for Kontext models with cleaner node interfaces
  * **Performance Boost**: Fused multiply-add operations in chroma processing for faster generation

  **Developer Experience**

  * **Custom Node Support**: Added pyproject.toml support for better dependency management
  * **Help Menu Integration**: New help system in the Node Library sidebar
  * **API Documentation**: Enhanced API nodes documentation

  **Frontend & UI Enhancements**

  * **Frontend Updated to v1.21.7**: Stability fixes and performance improvements
  * **Custom API Base Support**: Better subpath handling for custom deployment configurations
  * **Security Hardening**: XSS vulnerability fixes

  **Bug Fixes & Stability**

  * **Pillow Compatibility**: Updated deprecated API calls
  * **ROCm Support**: Improved version detection for AMD GPU users
  * **Template Updates**: Enhanced project templates for custom node development
</Update>


# ComfyUI ACE-Step Native Example
Source: https://docs.comfy.org/tutorials/audio/ace-step/ace-step-v1

This guide will help you create dynamic music using the ACE-Step model in ComfyUI

ACE-Step is an open-source foundational music generation model jointly developed by Chinese team StepFun and ACE Studio, aimed at providing music creators with efficient, flexible and high-quality music generation and editing tools.

The model is released under the [Apache-2.0](https://github.com/ace-step/ACE-Step?tab=readme-ov-file#-license) license and is free for commercial use.

As a powerful music generation foundation, ACE-Step provides rich extensibility. Through fine-tuning techniques like LoRA and ControlNet, developers can customize the model according to their actual needs.
Whether it's audio editing, vocal synthesis, accompaniment production, voice cloning or style transfer applications, ACE-Step provides stable and reliable technical support.
This flexible architecture greatly simplifies the development process of music AI applications, allowing more creators to quickly apply AI technology to music creation.

Currently, ACE-Step has released related training code, including LoRA model training, and the corresponding ControlNet training code will be released in the future.
You can visit their [Github](https://github.com/ace-step/ACE-Step?tab=readme-ov-file#-roadmap) to learn more details.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## ACE-Step ComfyUI Text-to-Audio Generation Workflow Example

### 1. Download Workflow and Related Models

Click the button below to download the corresponding workflow file. Drag it into ComfyUI to load the workflow information. The workflow includes model download information.

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/audio/ace-step/ace_step_1_t2m.json">
  <p>Download Json Format Workflow File</p>
</a>

You can also manually download [ace\_step\_v1\_3.5b.safetensors](https://huggingface.co/Comfy-Org/ACE-Step_ComfyUI_repackaged/blob/main/all_in_one/ace_step_v1_3.5b.safetensors) and save it to the `ComfyUI/models/checkpoints` folder

### 2. Complete the Workflow Step by Step

<img alt="Step Guide" />

1. Ensure the `Load Checkpoints` node has loaded the `ace_step_v1_3.5b.safetensors` model
2. (Optional) In the `EmptyAceStepLatentAudio` node, you can set the duration of the music to be generated
3. (Optional) In the `LatentOperationTonemapReinhard` node, you can adjust the `multiplier` to control the volume of the vocals (higher numbers result in more prominent vocals)
4. (Optional) Input corresponding music styles etc. in the `tags` field of `TextEncodeAceStepAudio`
5. (Optional) Input corresponding lyrics in the `lyrics` field of `TextEncodeAceStepAudio`
6. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the audio generation
7. After the workflow completes,, you can preview the generated audio in the `Save Audio` node. You can click to play and listen to it, and the audio will also be saved to `ComfyUI/output/audio` (subdirectory determined by the `Save Audio` node).

## ACE-Step ComfyUI Audio-to-Audio Workflow

Similar to image-to-image workflows, you can input a piece of music and use the workflow below to resample and generate music. You can also adjust the difference from the original audio by controlling the `denoise` parameter in the `Ksampler`.

### 1. Download Workflow File

Click the button below to download the corresponding workflow file. Drag it into ComfyUI to load the workflow information.

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/audio/ace-step/ace_step_1_m2m_editing.json">
  <p>Download Json Format Workflow File</p>
</a>

Download the following audio file as the input audio:

<a href="https://github.com/Comfy-Org/example_workflows/raw/refs/heads/main/audio/ace-step/input.mp3">
  <p>Download Example Audio File for Input</p>
</a>

### 2. Complete the Workflow Step by Step

<img alt="ACE-Step Step Guide" />

1. Ensure the `Load Checkpoints` node has loaded the `ace_step_v1_3.5b.safetensors` model
2. Upload the provided audio file in the `LoadAudio` node
3. (Optional) Input corresponding music styles and lyrics in the `tags` and `lyrics` fields of `TextEncodeAceStepAudio`. Providing lyrics is very important for audio editing
4. (Optional) Modify the `denoise` parameter in the `Ksampler` node to adjust the noise added during sampling to control similarity with the original audio (smaller values result in more similarity to the original audio; setting it to `1.00` is approximately equivalent to having no audio input)
5. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the audio generation
6. After the workflow completes, you can preview the generated audio in the `Save Audio` node. You can click to play and listen to it, and the audio will also be saved to `ComfyUI/output/audio` (subdirectory determined by the `Save Audio` node).

You can also implement the lyrics modification and editing functionality from the ACE-Step project page, modifying the original lyrics to change the audio effect.

### 3. Additional Workflow Notes

1. In the example workflow, you can change the `tags` in `TextEncodeAceStepAudio` from `male voice` to `female voice` to generate female vocals.
2. You can also modify the `lyrics` in `TextEncodeAceStepAudio` to change the lyrics and thus the generated audio. Refer to the examples on the ACE-Step project page for more details.

## ACE-Step Prompt Guide

ACE currently uses two types of prompts: `tags` and `lyrics`.

* `tags`: Mainly used to describe music styles, scenes, etc. Similar to prompts we use for other generations, they primarily describe the overall style and requirements of the audio, separated by English commas
* `lyrics`: Mainly used to describe lyrics, supporting lyric structure tags such as \[verse], \[chorus], and \[bridge] to distinguish different parts of the lyrics. You can also input instrument names for purely instrumental music

You can find rich examples of `tags` and `lyrics` on the [ACE-Step model homepage](https://ace-step.github.io/). You can refer to these examples to try corresponding prompts. This document's prompt guide is organized based on the project to help you quickly try combinations to achieve your desired effect.

### Tags (prompt)

#### Mainstream Music Styles

Use short tag combinations to generate specific music styles

* electronic
* rock
* pop
* funk
* soul
* cyberpunk
* Acid jazz
* electro
* em (electronic music)
* soft electric drums
* melodic

#### Scene Types

Combine specific usage scenarios and atmospheres to generate music that matches the corresponding mood

* background music for parties
* radio broadcasts
* workout playlists

#### Instrumental Elements

* saxophone
* jazz
* piano, violin

#### Vocal Types

* female voice
* male voice
* clean vocals

#### Professional Terms

Use some professional terms commonly used in music to precisely control music effects

* 110 bpm (beats per minute is 110)

* fast tempo

* slow tempo

* loops

* fills

* acoustic guitar

* electric bass

### Lyrics

#### Lyric Structure Tags

* \[outro]
* \[verse]
* \[chorus]
* \[bridge]

#### Multilingual Support

* ACE-Step V1 supports multiple languages. When used, ACE-Step converts different languages into English letters and then generates music.
* In ComfyUI, we haven't fully implemented the conversion of all languages to English letters. Currently, only [Japanese hiragana and katakana characters](https://github.com/Comfy-Org/ComfyUI/commit/5d3cc85e13833aeb6ef9242cdae243083e30c6fc) are implemented.
  So if you need to use multiple languages for music generation, you need to first convert the corresponding language to English letters, and then input the language code abbreviation at the beginning of the `lyrics`, such as Chinese `[zh]`, Korean `[ko]`, etc.

For example:

```
[verse]

[zh]wo3zou3guo4shen1ye4de5jie1dao4
[zh]leng3feng1chui1luan4si1nian4de5piao4liang4wai4tao4
[zh]ni3de5wei1xiao4xiang4xing1guang1hen3xuan4yao4
[zh]zhao4liang4le5wo3gu1du2de5mei3fen1mei3miao3

[chorus]

[verse]​
[ko]hamkke si-kkeuleo-un sesang-ui sodong-eul pihae​
[ko]honja ogsang-eseo dalbich-ui eolyeompus-ileul balaboda​
[ko]niga salang-eun lideum-i ganghan eum-ag gatdago malhaess-eo​
[ko]han ta han tamada ma-eum-ui ondoga eolmana heojeonhanji ijge hae

[bridge]
[es]cantar mi anhelo por ti sin ocultar
[es]como poesía y pintura, lleno de anhelo indescifrable
[es]tu sombra es tan terca como el viento, inborrable
[es]persiguiéndote en vuelo, brilla como cruzar una mar de nubes

[chorus]
[fr]que tu sois le vent qui souffle sur ma main
[fr]un contact chaud comme la douce pluie printanière
[fr]que tu sois le vent qui s'entoure de mon corps
[fr]un amour profond qui ne s'éloignera jamais
```

Currently, ACE-Step supports 19 languages, but the following ten languages have better support:

* English
* Chinese: \[zh]
* Russian: \[ru]
* Spanish: \[es]
* Japanese: \[ja]
* German: \[de]
* French: \[fr]
* Portuguese: \[pt]
* Italian: \[it]
* Korean: \[ko]

<Note>
  The language tags above have not been fully tested at the time of writing this documentation. If any language tag is incorrect, please [submit an issue to our documentation repository](https://github.com/Comfy-Org/docs/issues) and we will make timely corrections.
</Note>

## ACE-Step Related Resources

* [Project Page](https://ace-step.github.io/)
* [Hugging Face](https://huggingface.co/ACE-Step/ACE-Step-v1-3.5B)
* [GitHub](https://github.com/ace-step/ACE-Step)
* [Training Scripts](https://github.com/ace-step/ACE-Step?tab=readme-ov-file#-train)


# ComfyUI ACE-Step 1.5 Music Generation Guide
Source: https://docs.comfy.org/tutorials/audio/ace-step/ace-step-v1-5

Learn how to use ACE-Step 1.5 for AI music generation in ComfyUI. Complete guide with workflows, model downloads, and setup instructions for ComfyUI.

## About ACE-Step 1.5 in ComfyUI

ACE-Step 1.5 is a major update to the open-source music generation model, now natively supported in ComfyUI. It brings commercial-grade quality to your local machine with a novel hybrid architecture where a Language Model acts as an omni-capable planner, transforming simple user queries into comprehensive song blueprints.

**ACE-Step 1.5 Model highlights:**

* **Commercial-grade quality**: Achieves quality beyond most commercial music models, scoring 4.72 on musical coherence
* **Blazing fast generation**: Generate a full 4-minute song in \~1 second on RTX 5090, or under 10 seconds on RTX 3090 with ComfyUI
* **50+ language support**: Strong support for English, Chinese, Japanese, Korean, Spanish, German, French, Portuguese, Italian, and Russian
* **LoRA fine-tuning**: Supports lightweight personalization through LoRA training in ComfyUI

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Option 1: All-in-One Checkpoint (Recommended)

The AIO version packages all models into a single checkpoint file, making it easier to download and manage.

### AIO Workflow

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=audio_ace_step_1_5_checkpoint&utm_source=docs">
  Run the AIO workflow directly on Comfy Cloud.
</Card>

<Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/audio_ace_step_1_5_checkpoint.json">
  Download the all-in-one checkpoint workflow for local use.
</Card>

### AIO Model Download

<Card title="ace_step_1.5_turbo_aio.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files/resolve/main/checkpoints/ace_step_1.5_turbo_aio.safetensors">
  All-in-one checkpoint file (recommended for most users).
</Card>

**AIO Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 checkpoints/
│       └── ace_step_1.5_turbo_aio.safetensors
```

## Option 2: Split Model Files

The split version allows you to download individual model components separately.

### Split Workflow

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=audio_ace_step_1_5_split&utm_source=docs">
  Run the split models workflow directly on Comfy Cloud.
</Card>

<Card title="Download Workflow" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/audio_ace_step_1_5_split.json">
  Download the split models workflow for local use.
</Card>

### Split Model Downloads

<Card title="acestep_v1.5_turbo.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files/resolve/main/split_files/diffusion_models/acestep_v1.5_turbo.safetensors">
  Diffusion model.
</Card>

<Card title="qwen_0.6b_ace15.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files/resolve/main/split_files/text_encoders/qwen_0.6b_ace15.safetensors">
  Text encoder (0.6B).
</Card>

<Card title="qwen_1.7b_ace15.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files/resolve/main/split_files/text_encoders/qwen_1.7b_ace15.safetensors">
  Text encoder (1.7B).
</Card>

<Card title="ace_1.5_vae.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files/resolve/main/split_files/vae/ace_1.5_vae.safetensors">
  VAE model.
</Card>

**Split Models Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── acestep_v1.5_turbo.safetensors
│   ├── 📂 text_encoders/
│   │   ├── qwen_0.6b_ace15.safetensors
│   │   └── qwen_1.7b_ace15.safetensors
│   └── 📂 vae/
│       └── ace_1.5_vae.safetensors
```

## ACE-Step 1.5 Key Features in ComfyUI

### Chain-of-Thought Planning

The ACE-Step 1.5 model synthesizes metadata, lyrics, and captions via Chain-of-Thought reasoning to guide the diffusion process, resulting in more coherent long-form compositions.

### Hybrid LM + DiT Architecture

ACE-Step 1.5 combines a Language Model that plans the song structure with a Diffusion Transformer (DiT) that handles audio synthesis, all running natively in ComfyUI.

## Coming Soon to ComfyUI

These features are available in ACE-Step 1.5 but not yet supported in ComfyUI:

* **Cover**: Give the model any song as input along with a new prompt and lyrics, and it will reimagine the track in a completely different style
* **Repaint**: Select a segment, regenerate just that section, and the model stitches it back in while keeping everything else untouched

## ACE-Step 1.5 ComfyUI Related Resources

* [Project Page](https://ace-step.github.io/)
* [Hugging Face](https://huggingface.co/Comfy-Org/ace_step_1.5_ComfyUI_files)
* [GitHub](https://github.com/ace-step/ACE-Step)
* [Blog Post](https://blog.comfy.org/p/ace-step-15-is-now-available-in-comfyui)


# Stable Audio 1.0 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/audio/stable-audio/stable-audio-1

Guide to using Stability AI's open-source Stable Audio 1.0 model in ComfyUI for text-to-audio generation.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Stable Audio 1.0** is Stability AI's first open-source audio generation model. It takes a text prompt and generates an audio clip. In ComfyUI, it works like a standard text-to-audio pipeline: CLIP encodes the prompt, a KSampler denoises the latent, and the VAE decodes it to audio.

**Related links**:

* [GitHub: Stability-AI/stable-audio-open-1.0](https://github.com/Stability-AI/stable-audio-open-1.0)

## Workflow

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/audio_stable_audio_example.json">
  Download JSON or search "Stable Audio 1.0" in Template Library
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=audio_stable_audio_example&utm_source=docs&utm_medium=referral&utm_campaign=stable-audio-1">
  Open in Comfy Cloud
</Card>

![Stable Audio 1.0 workflow](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/audio_stable_audio_example-1.webp)

The workflow uses **standard ComfyUI nodes** — no custom nodes required. It loads the Stable Audio 1.0 checkpoint, encodes your prompt via a CLIP text encoder (t5-base), denoises the latent audio with a KSampler, and decodes it to audio through the model's VAE.

**How to use**:

1. **Load the checkpoint** — The `CheckpointLoaderSimple` node uses `stable-audio-open-1.0.safetensors`
2. **Write a prompt** — Enter your description in the `CLIPTextEncode` node (e.g. "heaven church electronic dance music")
3. **Set duration** — Adjust the `EmptyLatentAudio` node's length value (default 47.6 seconds)
4. Click **Run** (`Ctrl/Cmd + Enter`) to generate. The audio will be saved to `ComfyUI/output/audio/`

## Model download

When loading the workflow, ComfyUI will prompt you with download links for any missing models. To set up manually, download the files below and place them in the correct folders.

### Checkpoint

<Card title="stable-audio-open-1.0.safetensors" icon="download" href="https://huggingface.co/StabilityAI/stable-audio-open-1.0/resolve/main/stable-audio-open-1.0.safetensors">
  2.3GB. Place in models/checkpoints/
</Card>

Place the checkpoint in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 checkpoints/
│       └── stable-audio-open-1.0.safetensors
```

### Text encoder

<Card title="t5-base.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/t5-base/resolve/main/t5-base.safetensors">
  Text encoder for prompt conditioning. Place in models/text\_encoders/
</Card>

Place the text encoder in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 text_encoders/
│       └── t5-base.safetensors
```

After placing the files, press **R** in ComfyUI to refresh nodes and load the latest models.


# Stable Audio 3 ComfyUI workflow example
Source: https://docs.comfy.org/tutorials/audio/stable-audio/stable-audio-3

Guide to using Stability AI's open-source Stable Audio 3 model in ComfyUI for text-to-audio generation with Qwen prompt expansion and category-aware reprompting.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

**Stable Audio 3** ([GitHub](https://github.com/Stability-AI/stable-audio-3)) is Stability AI's latest open-source audio generation model, trained on fully licensed music data and licensed for commercial use. It uses a dedicated subgraph node to produce high-quality stereo audio — including music, sound effects, and instruments — from text descriptions, with optional Qwen-powered category-aware reprompting.

Stable Audio 3 comes in three variants:

* **Small-SFX** — Sound effects and short ambiance, up to 2:00. Small enough to run on CPU.
* **Small-Music** — Short music loops, on-device-friendly, up to 2:00.
* **Medium** — Longer tracks with stronger structure and musicality, up to \~6:20. Requires a GPU.

**Related links**:

* [GitHub: Stability-AI/stable-audio-3](https://github.com/Stability-AI/stable-audio-3)
* [Hugging Face (Comfy-Org/stable-audio-3)](https://huggingface.co/Comfy-Org/stable-audio-3)
* [Blog: Announcement](https://blog.comfy.org/p/stable-audio-3-day-0-support)

## Available workflows

### Stable Audio 3 Medium

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/audio_stable_audio_3_medium.json">
  Download JSON or search "Stable Audio 3 Medium" in Template Library
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=audio_stable_audio_3_medium&utm_source=docs&utm_medium=referral&utm_campaign=stable-audio-3">
  Open in Comfy Cloud
</Card>

![Stable Audio 3 Medium workflow](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/audio_stable_audio_3_medium-1.webp)

The **Stable Audio 3 Medium** workflow is a full-featured text-to-audio generation pipeline. You provide a short text idea, optional duration, seed, and category — the workflow expands your prompt using Qwen with a **category-aware reprompt template**, then generates stereo audio via the Stable Audio 3 checkpoint.

**How to use**:

1. **Text idea** — Enter a short description of the sound, music, or effect you want (e.g. "upbeat electronic dance track with heavy bass")
2. **Duration** — Set the desired clip length in seconds (default varies)
3. **Seed** — Control reproducibility by adjusting the seed value
4. **Category** — Choose a reprompt preset: **Music**, **Instrument**, **SFX**, or **One-shot**
5. **Enable reprompt** — Toggle `use_reprompt` on to let Qwen expand your short idea into a detailed prompt before generation
6. Click **Run** (`Ctrl/Cmd + Enter`) to generate. The audio will be saved to `ComfyUI/output/audio/`

### Stable Audio 3 Medium Base

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/audio_stable_audio_3_medium_base.json">
  Download JSON or search "Stable Audio 3 Medium Base" in Template Library
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=audio_stable_audio_3_medium_base&utm_source=docs&utm_medium=referral&utm_campaign=stable-audio-3">
  Open in Comfy Cloud
</Card>

![Stable Audio 3 Medium Base workflow](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/audio_stable_audio_3_medium_base-1.webp)

A simplified version of Stable Audio 3 without Qwen reprompt expansion. It expects a complete text prompt and passes it directly to the model. Use this when you already have a detailed prompt and want faster generation.

**How to use**:

1. **Text prompt** — Enter a detailed description of the audio you want
2. **Duration** — Set the clip length in seconds
3. **Seed** — Control reproducibility
4. Click **Run** (`Ctrl/Cmd + Enter`) to generate

## Model download

When loading the workflow, ComfyUI will prompt you with download links for any missing models. To set up manually, download the files below and place them in the correct folders.

### Checkpoints

<Card title="stable_audio_3_medium.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/stable-audio-3/resolve/main/checkpoints/stable_audio_3_medium.safetensors">
  For the Medium workflow. Place in models/checkpoints/
</Card>

<Card title="stable_audio_3_medium_base.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/stable-audio-3/resolve/main/checkpoints/stable_audio_3_medium_base.safetensors">
  For the Medium Base workflow. Place in models/checkpoints/
</Card>

Place checkpoints in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 checkpoints/
│       ├── stable_audio_3_medium.safetensors
│       └── stable_audio_3_medium_base.safetensors
```

### Text encoders

<Card title="t5gemma_b_b_ul2.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/stable-audio-3/resolve/main/text_encoders/t5gemma_b_b_ul2.safetensors">
  Required for all Stable Audio 3 workflows. Place in models/text\_encoders/
</Card>

<Card title="qwen3.5_2b_bf16.safetensors" icon="download" href="https://huggingface.co/Comfy-Org/Qwen3.5/resolve/main/text_encoders/qwen3.5_2b_bf16.safetensors">
  Required for the Medium workflow (Qwen reprompt). Place in models/text\_encoders/
</Card>

Place text encoders in:

```
📂 ComfyUI/
├── 📂 models/
│   └── 📂 text_encoders/
│       ├── t5gemma_b_b_ul2.safetensors
│       └── qwen3.5_2b_bf16.safetensors
```

After placing the files, press **R** in ComfyUI to refresh nodes and load the latest models.


# Anthropic Claude Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/anthropic/claude

This article will introduce how to use Anthropic Claude Partner nodes in ComfyUI to complete conversational functions

Anthropic Claude is a family of powerful AI models known for strong reasoning, safety, and long-context capabilities. ComfyUI has integrated the Anthropic Claude API through Partner Nodes, allowing you to use Claude directly in your workflows for conversational and image analysis tasks.

In this guide, we will walk you through using the Anthropic Claude node in ComfyUI.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Supported Models

| Model          | Strengths                                                                                                                                                          |
| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **Opus 4.7**   | Anthropic's most capable model. Step-change improvement in agentic coding, complex reasoning, and nuanced analysis. 1M context window. Knowledge cutoff: Jan 2026. |
| **Opus 4.6**   | Previous generation flagship with strong all-around performance. 1M context window.                                                                                |
| **Sonnet 4.6** | Best balance of speed and intelligence for most workloads. 1M context window. Fast latency.                                                                        |
| **Sonnet 4.5** | Fast and capable, good for everyday tasks. 200k context window.                                                                                                    |
| **Haiku 4.5**  | Fastest and most cost-effective option for simple queries and high-throughput use cases. 200k context window.                                                      |

All models support both text-only and multimodal (text + image) inputs with up to 20 images per request.

## Anthropic Claude Chat Workflow

<Card title="Run in Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_anthropic_claude&utm_source=docs&utm_medium=referral&utm_campaign=claude">
  Open in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_anthropic_claude.json">
  Download JSON or search "Anthropic Claude" in Template Library
</Card>

<Note>
  In the corresponding template, we have built a prompt for analyzing and generating role prompts, used to interpret your images into corresponding drawing prompts.
</Note>

Refer to the numbered steps in the workflow image to complete the basic workflow execution:

1. In the `Load Image` node, load the image you need AI to interpret (optional — skip for text-only queries)
2. In the `Anthropic Claude` node, modify `prompt` to set your conversation prompt, or change `model` to select a different Claude model
3. (Optional) Set the `system_prompt` to define the model's behavioral instructions
4. Click `Run` or press `Ctrl(cmd) + Enter` to execute the conversation
5. After the API returns results, view the AI response in the `Preview Any` node

### Additional Notes

* Adjust `max_tokens` (up to 32000) and `temperature` (0.0 to 1.0) in the node's advanced options
* The `seed` parameter controls whether the node re-runs — results are non-deterministic regardless of seed value


# Beeble SwitchX Partner Nodes ComfyUI Official Examples
Source: https://docs.comfy.org/tutorials/partner-nodes/beeble/beeble-switchx

This guide explains how to use Beeble SwitchX Partner Nodes in ComfyUI for AI-powered image and video relighting and environment editing

The [Beeble SwitchX](/built-in-nodes/BeebleSwitchXImageEdit) Partner Nodes allow you to transform the environment, lighting, and style of existing images and videos while preserving the original subject. Upload a character or subject image along with a reference environment, and SwitchX composites your subject into the new scene with realistic lighting and shadows.

In this guide, we'll show you how to use the Image Edit and Video Edit workflows.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Beeble SwitchX: Image Edit

Replace the background environment and relight your subject with a reference image.

<img alt="Beeble SwitchX Image Edit Workflow" />

<Card title="Run in Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_beeble_switchx_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=beeble_switchx_img">
  Open in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_beeble_switchx_image_edit.json">
  Download JSON or search "Beeble SwitchX: Image Edit" in Template Library
</Card>

### How It Works

This workflow takes two input images:

* **Subject image** — your character or main subject (with background)
* **Reference environment** — the new scene, lighting, or style you want to apply

The node generates an output where the subject is naturally composited into the new environment with proper lighting, shadows, and perspective.

### Steps to Run

1. **Upload subject image** — use the first **LoadImage** node to load your subject image (e.g., a person wearing headphones)
2. **Upload reference image** — use the second **LoadImage** node to load the target environment or style
3. **Enter your prompt** — describe the scene in the **BeebleSwitchXImageEdit** node
4. **Set resolution** — choose output resolution
5. **Adjust seed** — modify the seed for different results
6. **Click Queue** — press `Ctrl+Enter` to generate
7. **View results** — the edited image appears in **SaveImage**, and a masked cutout is saved separately

### Node Parameters

| Parameter    | Description                              |
| ------------ | ---------------------------------------- |
| `prompt`     | Description of the scene and environment |
| `resolution` | Output resolution (e.g., 720p)           |
| `seed`       | Random seed for reproducible results     |

## Beeble SwitchX: Video Edit

Apply environment relighting to a video while preserving the original motion and unmasked regions.

<img alt="Beeble SwitchX Video Edit Workflow" />

<Card title="Run in Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_beeble_switchx_video_edit&utm_source=docs&utm_medium=referral&utm_campaign=beeble_switchx_vid">
  Open in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_beeble_switchx_video_edit.json">
  Download JSON or search "Beeble SwitchX: Video Edit" in Template Library
</Card>

### How It Works

This workflow takes a source video and a reference image, then applies the reference lighting and environment to the masked subject regions in the video. Unmasked areas preserve the original pixels and motion. The workflow also generates an alpha matte for easy compositing.

### Steps to Run

1. **Upload source video** — use the **LoadVideo** node to load your input video
2. **Upload reference image** — use the **LoadImage** node to load the target environment/style
3. **Set video range** — the **Video Slice** node controls which frames to process (start, end, inclusive)
4. **Enter your prompt** — describe the desired environment and lighting in the **BeebleSwitchXVideoEdit** node
5. **Set resolution** — choose output resolution
6. **Adjust seed** — modify the seed for different results
7. **Click Queue** — press `Ctrl+Enter`
8. **View results** — the edited video is saved, and a separate alpha matte video is generated for compositing

### Outputs

| Output                         | Description                                                             |
| ------------------------------ | ----------------------------------------------------------------------- |
| **Edited video** (`SaveVideo`) | The final video with new environment/lighting applied to masked regions |
| **Alpha matte** (`SaveVideo`)  | A separate alpha video for compositing the edited regions               |


# Flux 1.1 Pro Ultra Image Partner Nodes ComfyUI Official Workflow Examples
Source: https://docs.comfy.org/tutorials/partner-nodes/black-forest-labs/flux-1-1-pro-ultra-image

This guide covers how to use the Flux 1.1 Pro Ultra Image Partner node in ComfyUI

FLUX 1.1 Pro Ultra is a high-performance AI image generation tool by BlackForestLabs, featuring ultra-high resolution and efficient generation capabilities. It supports up to 4MP resolution (4x the standard version) while keeping single image generation time under 10 seconds - 2.5x faster than similar high-resolution models.

The tool offers two core modes:

* **Ultra Mode**: Designed for high-resolution needs, perfect for advertising and e-commerce where detail magnification is important. It accurately reflects prompts while maintaining generation speed.
* **Raw Mode**: Focuses on natural realism, optimizing skin tones, lighting, and landscape details. Reduces the "AI look" and is ideal for photography and realistic style creation.

We now support the Flux 1.1 Pro Ultra Image node in ComfyUI. This guide will cover:

* Flux 1.1 Pro Text-to-Image
* Flux 1.1 Pro Image-to-Image (Remix)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Flux 1.1 Pro Ultra Image Node Documentation

Check the following documentation for detailed node parameter settings:

* [Flux 1.1 Pro Ultra Image](/images/built-in-nodes/api_nodes/bfl/flux-1-1-pro-ultra-image.jpg)

## Flux 1.1 \[pro] Text-to-Image Tutorial

### 1. Download Workflow File

Download and drag the following file into ComfyUI to load the workflow:

![Flux 1.1 pro Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_1_pro_t2i.png)

### 2. Complete the Workflow Steps

<img alt="Workflow Steps" />

Follow the numbered steps to complete the basic workflow:

1. (Optional) Modify the prompt in the `Flux 1.1 [pro] Ultra Image` node
2. (Optional) Set `raw` parameter to `false` for more realistic output
3. Click `Run` or use shortcut `Ctrl(cmd) + Enter` to generate the image
4. After the API returns results, view the generated image in the `Save Image` node. Images are saved to the `ComfyUI/output/` directory

## Flux 1.1\[pro] Image-to-Image Tutorial

When adding an `image_prompt` to the node input, the output will blend features from the input image (Remix). The `image_prompt_strength` value affects the blend ratio: higher values make the output more similar to the input image.

### 1. Download Workflow File

Download and drag the following file into ComfyUI, or right-click the purple node in the Text-to-Image workflow and set `mode` to `always` to enable `image_prompt` input:

![Flux 1.1 pro Image-to-Image Remix](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_1_pro_i2i.png)

We'll use this image as input:
![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai-dall-e-3/text2image.png)

### 2. Complete the Workflow Steps

<img alt="Workflow Steps" />

Follow these numbered steps:

1. Click **Upload** on the `Load Image` node to upload your input image
2. (Optional) Adjust `image_prompt_strength` in `Flux 1.1 [pro] Ultra Image` to change the blend ratio
3. Click `Run` or use shortcut `Ctrl(cmd) + Enter` to generate the image
4. After the API returns results, view the generated image in the `Save Image` node. Images are saved to the `ComfyUI/output/` directory

Here's a comparison of outputs with different `image_prompt_strength` values:

<img alt="Comparison" />


# ComfyUI Flux.1 Kontext Pro Image Partner Nodes Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/black-forest-labs/flux-1-kontext

This guide will show you how to use the Flux.1 Kontext Pro Image Partner node in ComfyUI to perform image editing

FLUX.1 Kontext is a professional image-to-image editing model developed by Black Forest Labs, focusing on intelligent understanding of image context and precise editing.
It can perform various editing tasks without complex descriptions, including object modification, style transfer, background replacement, character consistency editing, and text editing.
The core advantage of Kontext lies in its excellent context understanding ability and character consistency maintenance, ensuring that key elements such as character features and composition layout remain stable even after multiple iterations of editing.

Currently, ComfyUI has supported two models of Flux.1 Kontext:

* **Kontext Pro** is ideal for editing, composing, and remixing.
* **Kontext Max** pushes the limits on typography, prompt precision, and speed.

In this guide, we will briefly introduce how to use the Flux.1 Kontext Partner nodes to perform image editing through corresponding workflows.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Flux.1 Kontext Multiple Image Input Workflow

We have recently updated to support multiple image input workflows. Using the new `Image Stitch` node, you can stitch multiple images into a single image and edit it using Flux.1 Kontext.

### 1. Workflow File Download

The `metadata` of the images below contains the workflow information. Please download and drag them into ComfyUI to load the corresponding workflow.

![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/multiple_image_input/multiple_image_input.png)

Download the following images for input or use your own images:

![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/multiple_image_input/girl.jpg)
![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/multiple_image_input/dog.jpg)
![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/multiple_image_input/sofa.jpg)

### 2. Complete the Workflow Step by Step

<img alt="ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow Steps" />

You can follow the numbered steps in the image to complete the workflow:

1. Upload the provided images in the `Load image` node
2. Modify the necessary parameters in `Flux.1 Kontext Pro Image`:
   * `prompt` Enter the prompt for the image you want to edit
   * `aspect_ratio` Set the aspect ratio of the original image, which must be between 1:4 and 4:1
   * `prompt_upsampling` Set whether to use prompt upsampling. If enabled, it will automatically modify the prompt to get richer results, but the results are not reproducible
3. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image editing
4. After waiting for the API to return results, you can view the edited image in the `Save Image` node, and the corresponding image will also be saved to the `ComfyUI/output/` directory

<Tip>
  The subsequent two workflows only differ in the Partner nodes used. In fact, you only need to modify based on the multiple image input workflow, with no significant differences
</Tip>

## Flux.1 Kontext Pro Image Partner Nodes Workflow

### 1. Workflow File Download

The `metadata` of the image below contains the workflow information. Please download and drag it into ComfyUI to load the corresponding workflow.

![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_kontext_pro_image.png)

Download the image below for input or use your own image:

![ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_kontext_pro_image_input.png)

### 2. Complete the Workflow Step by Step

<img alt="ComfyUI Flux.1 Kontext Pro Image Partner Nodes Workflow Steps" />

You can follow the numbered steps in the image to complete the workflow:

1. Load the image you want to edit in the `Load Image` node
2. (Optional) Modify the necessary parameters in `Flux.1 Kontext Pro Image`
3. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image editing
4. After waiting for the API to return results, you can view the edited image in the `Save Image` node, and the corresponding image will also be saved to the `ComfyUI/output/` directory

## Flux.1 Kontext Max Image Partner Nodes Workflow

### 1. Workflow File Download

The `metadata` of the image below contains the workflow information. Please download and drag it into ComfyUI to load the corresponding workflow.

![ComfyUI Flux.1 Kontext Max Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_kontext_max_image.png)

Download the image below for input or use your own image for demonstration:

![ComfyUI Flux.1 Kontext Max Image Partner Nodes Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/bfl/flux_1_kontext_max_image_input.png)

### 2. Complete the Workflow Step by Step

<img alt="ComfyUI Flux.1 Kontext Max Image Partner Nodes Workflow Steps" />

You can follow the numbered steps in the image to complete the workflow:

1. Load the image you want to edit in the `Load Image` node
2. (Optional) Modify the necessary parameters in `Flux.1 Kontext Max Image`
3. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image editing
4. After waiting for the API to return results, you can view the edited image in the `Save Image` node, and the corresponding image will also be saved to the `ComfyUI/output/` directory

## Flux Kontext Prompt Techniques

### 1. Basic Modifications

* Simple and direct: `"Change the car color to red"`
* Maintain style: `"Change to daytime while maintaining the same style of the painting"`

### 2. Style Transfer

**Principles:**

* Clearly name style: `"Transform to Bauhaus art style"`
* Describe characteristics: `"Transform to oil painting with visible brushstrokes, thick paint texture"`
* Preserve composition: `"Change to Bauhaus style while maintaining the original composition"`

### 3. Character Consistency

**Framework:**

* Specific description: `"The woman with short black hair"` instead of "she"
* Preserve features: `"while maintaining the same facial features, hairstyle, and expression"`
* Step-by-step modifications: Change background first, then actions

### 4. Text Editing

* Use quotes: `"Replace 'joy' with 'BFL'"`
* Maintain format: `"Replace text while maintaining the same font style"`

## Common Problem Solutions

### Character Changes Too Much

❌ Wrong: `"Transform the person into a Viking"`
✅ Correct: `"Change the clothes to be a viking warrior while preserving facial features"`

### Composition Position Changes

❌ Wrong: `"Put him on a beach"`
✅ Correct: `"Change the background to a beach while keeping the person in the exact same position, scale, and pose"`

### Style Application Inaccuracy

❌ Wrong: `"Make it a sketch"`
✅ Correct: `"Convert to pencil sketch with natural graphite lines, cross-hatching, and visible paper texture"`

## Core Principles

1. **Be Specific and Clear** - Use precise descriptions, avoid vague terms
2. **Step-by-step Editing** - Break complex modifications into multiple simple steps
3. **Explicit Preservation** - State what should remain unchanged
4. **Verb Selection** - Use "change", "replace" rather than "transform"

## Best Practice Templates

**Object Modification:**
`"Change [object] to [new state], keep [content to preserve] unchanged"`

**Style Transfer:**
`"Transform to [specific style], while maintaining [composition/character/other] unchanged"`

**Background Replacement:**
`"Change the background to [new background], keep the subject in the exact same position and pose"`

**Text Editing:**
`"Replace '[original text]' with '[new text]', maintain the same font style"`

> **Remember:** The more specific, the better. Kontext excels at understanding detailed instructions and maintaining consistency.


# Bria FIBO Edit Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/bria/fibo

Learn how to use the Bria FIBO Edit Partner node for precision image editing in ComfyUI

FIBO Edit is Bria AI's JSON-native image editing model, now available in ComfyUI through Partner Nodes. It lets you combine images with structured JSON prompts to make precise, targeted edits—no prompt guessing, no unwanted changes to the rest of your image.

## About FIBO Edit

**Key features:**

* **Surgical edits**: Change specific attributes (lighting, color, texture, materials) without breaking the rest of the scene
* **Background swaps and object modifications**: Precise control over targeted areas
* **Reproducible, auditable edits**: Structured JSON inputs for consistent results
* **100% licensed data**: Full governance and legal clarity for commercial use
* **Strong prompt adherence**: Validated on PRISM-style evaluations

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## FIBO Edit Workflows

<Card title="Image Edit Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bria_image_edit.json">
  Download the Bria FIBO Image Edit workflow.
</Card>

<Card title="Image Outpainting Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bria_image_outpainting.json">
  Download the Bria FIBO Image Outpainting workflow.
</Card>

<Card title="Run Image Edit on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bria_image_edit&utm_source=docs">
  Try the Image Edit workflow instantly on Comfy Cloud.
</Card>

<Card title="Run Outpainting on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bria_image_outpainting&utm_source=docs">
  Try the Image Outpainting workflow instantly on Comfy Cloud.
</Card>

## Example outputs

FIBO Edit excels at various editing tasks:

* **Time of day changes**: Relight your scene or change the time of day
* **Material and texture swaps**: Try different colors, materials, fabrics, and clothing
* **Object material replacement**: Swap out the material on specific objects
* **Masked area editing**: Mask out a specific area to edit with precision
* **Text adjustment**: Adjust the text in an image
* **Art style transformation**: Re-imagine your image in a different art style


# Seedance 2.0 - AI video generation
Source: https://docs.comfy.org/tutorials/partner-nodes/bytedance/seedance-2-0

Generate high-quality video from text, images, video, and audio with synced audio, consistent characters, and cinematic camera control using Seedance 2.0 in ComfyUI

Seedance 2.0 is ByteDance's next-generation multimodal video generation model, now available inside ComfyUI. It accepts text, images, video, and audio as unified inputs and produces high-quality video with synced audio, consistent characters, and cinematic camera motion in a single pass.

## Key capabilities

* **Multimodal in** — Prompt with text plus images, video, and audio
* **Audio-video sync** — Generate video and audio together
* **Directing control** — Camera moves and shot pacing stay controllable
* **Consistency** — Keep characters and scenes stable across a clip
* **Editing + extend** — Edit footage or extend clips without starting over

With these capabilities, Seedance 2.0 fits a wide range of use cases including advertising, short-form drama, film previsualization, product showcases, virtual character content, and assets for games and animation.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Available workflows

### Text to video (T2V)

Generate a video from a text prompt, with Seedance 2.0 handling scene, motion, and pacing.

<Card title="Run Text-to-Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_0_t2v&utm_source=docs">
  Try the Text-to-Video workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Text-to-Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_t2v.json">
  Download the workflow JSON.
</Card>

### Reference to video (R2V)

Use reference images, video, or audio to guide look, motion, and rhythm while keeping results coherent.

<Card title="Run Reference-to-Video on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_0_r2v&utm_source=docs">
  Try the Reference-to-Video workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Reference-to-Video workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_r2v.json">
  Download the workflow JSON.
</Card>

### First-last-frame to video (FLF2V)

Provide a starting frame and ending frame, and Seedance 2.0 generates the motion and transitions between them.

<Card title="Run FLF2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_seedance2_0_flf2v&utm_source=docs">
  Try the First-Last-Frame-to-Video workflow instantly on Comfy Cloud.
</Card>

<Card title="Download FLF2V workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_flf2v.json">
  Download the workflow JSON.
</Card>

## Using real-person and AI-generated portraits in ComfyUI for Seedance 2.0

Seedance 2.0 **supports both** **real-person portraits** (imagery of actual people you use as likeness or on-camera reference) and **AI-generated portraits** (fictional on-screen subjects produced by AI, not depicting a specific real individual). Which path you use determines whether you need ByteDance **liveness** and identity checks.

|                           | **AI-generated portrait**                                                                                    | **Real-person portrait**                                                              |
| ------------------------- | ------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------- |
| **What it refers to**     | The subject looks like an AI-synthesized character; it must not correspond to an identifiable natural person | You use portrait or appearance footage of a real person                               |
| **Identity verification** | No extra check                                                                                               | One-time ByteDance liveness (through **ByteDance Create Image/Video Asset**)          |
| **Workflow**              | Any standard Seedance 2.0 workflow (T2V, R2V, FLF2V)                                                         | Seedance 2.0 Real Human workflow with the **ByteDance Create Image/Video Asset** node |

### AI-generated portrait

<img alt="AI-generated portrait reference in a Seedance 2.0 workflow" />

Use the Seedance 2.0 node like any other generator: upload your **AI-generated character image** (or an equivalent reference), wire it up, and run.

After submission the service classifies the asset. **If it is flagged as protected real-person-related content**, the node returns an error — switch to the **real-person portrait** workflow below instead. Once the backend treats it as an AI portrait and the check clears, use it directly as reference with no extra verification steps.

### Real-person portrait

Use the **Real Human** workflow (requires **ByteDance Create Image/Video Asset**): real likeness needs **one** liveness verification to deter impersonation and unauthorized use of someone's likeness, and to comply with evolving AI transparency requirements.

**First use (verification required)**

1. Upload portrait imagery via **ByteDance Create Image/Video Asset**.
2. Run the workflow — a verification link is generated.
3. Open the link on your phone or browser and finish liveness (typically under \~30 seconds).
4. After verification succeeds you receive two IDs:
   * **Group ID** — the verified individual; retain it when uploading the same person again.
   * **Asset ID** — bound to this portrait; connect it for video generation and reuse across runs.

**New photo or video of the same person (no repeat liveness)**

1. Upload a new photo or video of that person.
2. Enter the saved **Group ID** on **ByteDance Create Image/Video Asset**.
3. The system compares the new face data with the original verification record; when it matches, the new asset activates automatically.

<CardGroup>
  <Card title="Seedance 2.0 Real Human" icon="book" href="/tutorials/partner-nodes/bytedance/seedance-2-0-real-human">
    Full walkthrough, verification flow, and Real Human workflow templates.
  </Card>
</CardGroup>


# Seedance 2.0 Real Human - Verified real person video generation
Source: https://docs.comfy.org/tutorials/partner-nodes/bytedance/seedance-2-0-real-human

Generate videos featuring real people in Seedance 2.0 with identity consistency, native audio-video sync, and a one-time ByteDance liveness verification in ComfyUI

<img alt="Seedance 2.0 Real Human Cover" />

**Seedance 2.0 Real Human** is available directly inside ComfyUI. You can upload a portrait through a ComfyUI workflow, complete a one-time verification, and then generate videos featuring that real person with a consistent identity and authentic facial expressions — without leaving ComfyUI.

With Real Human support in ComfyUI, you are no longer limited to virtual characters. Seedance 2.0's controllability and native audio-video sync now extend to real people, with identity and performance held together across a full clip, using the same node-based workflows you already use for other Seedance 2.0 generations.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Video guide

Watch the full walkthrough covering verification and both Seedance 2.0 Real Human workflows end to end in ComfyUI.

<video />

## What's different

* **Real people, cinematic control** — Direct camera moves, lighting, and scene changes while keeping the subject believable
* **Identity consistency** — Facial features and overall appearance remain stable across motion, camera moves, and transitions
* **Native audio-video sync** — Video and audio (dialogue, ambient, music) are generated together with more reliable lip-sync and expressions
* **Multi-reference directing** — Mix text with up to **9 images**, **3 videos**, and **3 audio clips** to lock in look, motion, and rhythm

## How verification works in ComfyUI

Verification is required before any real person can appear in a Seedance 2.0 generation. It prevents impersonation and unauthorized use of someone's likeness and is handled by ByteDance, which complies with emerging AI transparency regulations. The entire flow is driven from ComfyUI through the **ByteDance Create Image/Video Asset** node — you only need to leave ComfyUI briefly to complete the liveness check on your phone or browser.

<img alt="ByteDance Create Image/Video Asset nodes used to generate Group ID and Asset ID" />

### First run (verification required)

1. In ComfyUI, add the **ByteDance Create Image/Video Asset** node to your workflow and upload a portrait image
2. Run the workflow — ComfyUI returns a verification link from ByteDance
3. Open the link on your phone or browser and complete the liveness check (less than 1 minute)
4. Once verification passes, return to ComfyUI — the node output now contains the verified asset

#### Verification flow screenshots

**Step 1 — Upload and run to start verification**

<img alt="Upload your portrait and run to start liveness verification" />

**Step 2 — Get the verification link**

<img alt="Workflow run returns a verification link to open in browser" />

**Step 3 — Complete liveness check in the H5 page**

<img alt="Complete identity authentication in the H5 verification page" />

**Step 4 — Return to ComfyUI and save IDs (no extra credits)**

<img alt="After verification, ComfyUI outputs Asset ID and Group ID to save for reuse" />

After real human verification passes, the node exposes two IDs you can use in downstream Seedance 2.0 video nodes:

* **Group ID** — represents the verified person. Save this so you can reuse the same identity later without re-verifying
* **Asset ID** — represents this specific image. Wire it into a Seedance 2.0 video generation node to produce a video of the verified person; it can be reused across multiple workflows

### Future uploads (no verification)

1. In ComfyUI, upload a new photo or video of the same person with the **ByteDance Create Image/Video Asset** node
2. Enter the saved **Group ID** in the node
3. On run, ByteDance compares facial features against the original verification
4. If it matches, the new asset is activated automatically and returned to ComfyUI, ready to feed into Seedance 2.0 video generation

#### Skipping verification with an existing Group ID

If you've already completed verification once, you can often skip the liveness step for new uploads of the same person by providing the existing **Group ID**. If ByteDance recognizes the new image as the same person, verification is bypassed.

<img alt="Reuse an existing Group ID to skip liveness verification when the person matches" />

## Available workflows

Two prebuilt Seedance 2.0 Real Human templates are available in ComfyUI. Both wire the **ByteDance Create Image/Video Asset** node into a Seedance 2.0 video generation node so verification and generation happen in a single run.

### Seedance 2.0 Real Human reference-to-video

Use a verified portrait (plus optional additional reference images, videos, or audio) to drive a Seedance 2.0 video with a consistent real-person identity.

<Card title="Seedance 2.0 Real Human R2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_r2v_real_human.json">
  Get the Seedance 2.0 Real Human Reference-to-Video workflow file.
</Card>

### Seedance 2.0 Real Human first-last-frame to video

Provide a verified starting frame and ending frame to generate the video between them while preserving the real person's identity.

<Card title="Seedance 2.0 Real Human FLF2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_seedance2_0_flf2v_real_human.json">
  Get the Seedance 2.0 Real Human First-Last-Frame-to-Video workflow file.
</Card>


# ByteDance Seedream 5.0 Lite - Smart AI Image Creation
Source: https://docs.comfy.org/tutorials/partner-nodes/bytedance/seedream-5-lite

Generate images with web-connected retrieval and enhanced instruction following using Seedream 5.0 lite in ComfyUI

Seedream 5.0 lite is the latest image generation model from BytePlus. It is the first in the Seedream family to bring in web-connected retrieval, which means the model can draw on live online information when generating images.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## What's new in Seedream 5.0 lite

* **Web-connected retrieval** — The model pulls from live web data during generation, allowing creations to be tied to real-world trends, current events, and up-to-date knowledge
* **Smarter instruction following** — Handles complex, multi-step instructional prompts far more reliably. Multi-image inputs, local editing instructions, and batch style requests all land closer to the intended output
* **Stronger consistency** — Character identity, product appearance, style, and lighting all hold up much better across a set of generated images
* **Deeper world knowledge** — Expanded knowledge base makes the model useful for technical illustration, educational diagrams, and knowledge-heavy creative work

## Seedream 5.0 lite image edit workflow

<Card title="Run in Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bytedance_seedream_5_0_lite_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=seedream_5_lite">
  Open in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bytedance_seedream_5_0_lite_image_edit.json">
  Download JSON or search "Seedream 5.0 lite" in Template Library
</Card>

### Image edit showcase

![Instruction following example 1](https://substack-post-media.s3.amazonaws.com/public/images/9a770e2a-c0ed-4253-bd60-14c5beff150d_2048x2048.png)
*Change the glasses in the green box to circular lenses, the orange purse in the blue box to a purple oval purse, and her shoes in the red box are patterned with leopard print.*

![Instruction following example 2](https://substack-post-media.s3.amazonaws.com/public/images/6ec0976b-1cb0-45e0-a657-ab97efd4d915_2048x2048.png)
*While maintaining the original composition, change the overall color tone to navy and white colors. Change "RTX PRO 6000" to "SEEDREAM 5.0 LITE" in the image, and change "2025" to "NOW LIVE".*

![Style transfer example](https://substack-post-media.s3.amazonaws.com/public/images/dc08a07e-edf1-4864-b6a6-5a7b17b78cfa_1920x1080.png)
*Refer to the second image and change the style of the first picture to match that of the second image.*

### Consistency showcase

![Design consistency](https://substack-post-media.s3.amazonaws.com/public/images/cc7b80ef-418c-4376-95e2-38c9110c6456_1920x1080.png)
*Refer to the design and layout style of Figure 2 and adapt the style of Figure 1 accordingly.*

![Character merge](https://substack-post-media.s3.amazonaws.com/public/images/22d1fa08-17f3-4113-86ee-ca0a324cbb3b_1920x1080.png)
*Merge Figure 1 and Figure 2 into a high-angle top-down selfie of two people, compact composition with them close together.*

![Multi-reference composition](https://substack-post-media.s3.amazonaws.com/public/images/2d690f6d-fa30-4152-9dc4-c09341c4e887_1920x1080.png)
*Use the flowers shown in Figure 1‑4 for flower arrangement. Arrange all the flowers in the vase shown in Figure 5, then place the vase on the table shown in Figure 6.*

![Product consistency](https://substack-post-media.s3.amazonaws.com/public/images/585cf84d-afe0-4277-b08a-7a0cddbd6a54_1620x1080.png)
*Using the bottle from the reference image, generate six product photos in different seasonal settings. Consistent bottle design across all six.*

## Seedream 5.0 lite text to image workflow

<Card title="Run in Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_bytedance_seedream_5_0_lite_t2i&utm_source=docs&utm_medium=referral&utm_campaign=seedream_5_lite">
  Open in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_bytedance_seedream_5_0_lite_t2i.json">
  Download JSON or search "Seedream 5.0 lite" in Template Library
</Card>

### World knowledge showcase

![Gravity infographic](https://substack-post-media.s3.amazonaws.com/public/images/fac37b40-faaa-4360-b449-08da38322186_2562x1440.png)
*Pixel art infographic for explaining gravity, rendered in crisp 16-bit style with a dark navy/charcoal background and bold cinematic palette tones.*

![Big Bang infographic](https://substack-post-media.s3.amazonaws.com/public/images/39e35082-3b26-41df-8e09-5cc1841d94c6_2562x1440.png)
*Comic book style infographic for explaining the Big Bang and the age of dinosaurs, with a deep crimson and ink-black background and bold comic palette tones.*

## Get started

1. Update ComfyUI to the latest (0.15.0+)
2. Go to Template Library, search for `Seedream 5.0 lite`


# Concurrency Limits
Source: https://docs.comfy.org/tutorials/partner-nodes/concurrency-limits

Understand how concurrency limits control simultaneous Partner Node requests on your account.

Concurrency limits control how many requests your account can process at the same time. Requests beyond your limit are rejected with a `429` error code. Your concurrency limit is determined by your credit purchase history, and applies at the platform level across all endpoints you call.

## How it works

When you submit a request, the platform tracks it against your concurrency limit. If you exceed the limit, additional requests are rejected with a `429` error until in-flight requests complete.

## Default limits

Every new account starts with a concurrency limit of **5 concurrent requests**. As you purchase credits, the platform automatically increases your limit based on the total amount of paid invoices from the last four weeks. Self-serve limits scale up to **40 concurrent requests**.

## Increasing your limit

For concurrency above 40, contact our support team.

<Card title="Support" icon="life-ring" href="https://support.comfy.org/">
  Get help raising your concurrency limit
</Card>


# FAQs about Partner Nodes
Source: https://docs.comfy.org/tutorials/partner-nodes/faq

Some FAQs you may encounter when using Partner Nodes.

This article addresses common questions regarding the use of Partner nodes.

<AccordionGroup>
  <Accordion title="Why can't I find the Partner Nodes?">
    Please update your ComfyUI to the latest version (the latest commit or the latest [desktop version](https://www.comfy.org/download)).
    We may add more API support in the future, and the corresponding nodes will be updated, so please keep your ComfyUI up to date.

    <Tip>
      Please note that you need to distinguish between the nightly version and the release version.
      In some cases, the latest `release` version may not be updated in time compared to the `nightly` version.
      Since we are still iterating quickly, please ensure you are using the latest version when you cannot find the corresponding node.
    </Tip>
  </Accordion>

  <Accordion title="Why can't I use / log in to the Partner Nodes?">
    API access requires that your current request is based on a secure network environment. The current requirements for API access are as follows:

    * The local network only allows access from `127.0.0.1` or `localhost`, which may mean that you cannot use the Partner Nodes in a ComfyUI service started with the `--listen` parameter in a LAN environment.
    * Able to access our API service normally (a proxy service may be required in some regions).
    * Your account does not have enough [credits](/interface/credits).
  </Accordion>

  <Accordion title="Why can't I use Partner Node even after logging in, or why does it keep asking me to log in while using?">
    * Currently, only `127.0.0.1` or `localhost` access is supported.
    * Ensure your account has enough credits.
  </Accordion>

  <Accordion title="Can Partner Nodes be used for free?">
    Partner Nodes require credits for API calls to closed-source models, so they do not support free usage.
  </Accordion>

  <Accordion title="How to purchase credits?">
    Please refer to the following documentation:

    1. [Comfy Account](/interface/user): Find the `User` section in the settings menu to log in.
    2. [Credits](/interface/credits): After logging in, the settings interface will show the credits menu. You can purchase credits in `Settings` → `Credits`. We use a prepaid system, so there will be no unexpected charges.
    3. Complete the payment through Stripe.
    4. Check if the credits have been updated. If not, try restarting or refreshing the page.
  </Accordion>

  <Accordion title="Are unused credits refundable?">
    Currently, we do not support refunds for credits.
    If you believe there is an error resulting in unused balance due to technical issues, please [contact support](mailto:support@comfy.org).
  </Accordion>

  <Accordion title="Can credits go negative?">
    Credits are not intended to be used as a negative balance or credit line. However, due to race conditions where partner nodes don't always report costs before execution, a single execution may consume more credits than your remaining balance and temporarily result in a negative balance after completion. When your balance is negative, you will not be able to run Partner Nodes until you top up and restore a positive balance. Please ensure you have enough credits before making API calls.
  </Accordion>

  <Accordion title="Where can I check usage and expenses?">
    Please visit the [Credits](/interface/credits) menu after logging in to check the corresponding credits.
  </Accordion>

  <Accordion title="Is it possible to use my own API Key?">
    Currently, the Partner Nodes are still in the testing phase and do not support this feature yet, but we have considered adding it.
  </Accordion>

  <Accordion title="Do credits expire?">
    Yes, the expiration depends on the type of credits:

    * **Monthly credits**: Expire at the end of your billing period
    * **Top-up credits**: Expire 1 year from the date of purchase
  </Accordion>

  <Accordion title="Can credits be transferred or shared?">
    No, your credits cannot be transferred to other users and are limited to the currently logged-in account, but we do not restrict the number of devices that can log in.
  </Accordion>

  <Accordion title="Can I use the same account on different devices?">
    We do not limit the number of devices that can log in; you can use your account anywhere you want.
  </Accordion>

  <Accordion title="How can I request for my account or information to be deleted??">
    Email a request to [support@comfy.org](mailto:support@comfy.org) and we will delete your information
  </Accordion>
</AccordionGroup>


# Google Gemini Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/google/gemini

This article will introduce how to use Google Gemini Partner nodes in ComfyUI to complete conversational functions

Google Gemini is a powerful AI model developed by Google, supporting conversational and text generation functions. Currently, ComfyUI has integrated the Google Gemini API, allowing you to directly use the related nodes in ComfyUI to complete conversational functions.

In this guide, we will walk you through completing the corresponding conversational functionality.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Google Gemini Chat Workflow

### 1. Workflow File Download

Please download the Json file below and drag it into ComfyUI to load the corresponding workflow.

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/google/api_google_gemini.json">
  <p>Download Json Format Workflow File</p>
</a>

### 2. Complete the Workflow Execution Step by Step

<img alt="OpenAI Chat Step Guide" />

<Note>
  In the corresponding template, we have built a prompt for analyzing and generating role prompts, used to interpret your images into corresponding drawing prompts
</Note>

You can refer to the numbers in the image to complete the basic text-to-image workflow execution:

1. In the `Load Image` node, load the image you need AI to interpret
2. (Optional) If needed, you can modify the prompt in `Google Gemini` to have AI execute specific tasks
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the conversation.
4. After waiting for the API to return results, you can view the corresponding AI returned content in the `Preview Any` node.

### 3. Additional Notes

* Currently, the file input node `Gemini Input Files` requires files to be uploaded to the `ComfyUI/input/` directory first. This node is being improved, and we will modify the template after updates
* The workflow provides an example using `Batch Images` for input. If you have multiple images that need AI interpretation, you can refer to the step diagram and use right-click to set the corresponding node mode to `Always` to enable it


# Nano Banana 2 - Fast AI Image Generation
Source: https://docs.comfy.org/tutorials/partner-nodes/google/nano-banana-2

Generate high-quality images with Pro-level quality at Flash speed using Nano Banana 2 in ComfyUI

Nano Banana 2 is now available in ComfyUI through Partner Nodes. This release fundamentally changes the default choice for most creators, delivering Pro-level quality at Flash speed.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## What's new in Nano Banana 2

* **Pro-level quality at Flash speed** — Richer textures, sharper detail, stronger lighting, and better prompt adherence without the latency tradeoff
* **Search-grounded world knowledge** — Intelligently triggers Google Image Search grounding to improve factual accuracy for lesser-known landmarks, niche objects, or real-world details
* **Subject consistency** — Maintain character resemblance of up to 5 characters and fidelity of up to 14 objects in a single workflow
* **Configurable thinking levels** — Control how much the model "thinks" before generating (Minimal for fast exploration, High/Dynamic for complex layouts)
* **Precision text rendering and translation** — Generate accurate, legible text for marketing mockups, greeting cards, and localized assets

## Nano Banana 2 image edit workflow

<Card title="Run in Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_google_nano_banana2_image_edit&utm_source=docs&utm_medium=referral&utm_campaign=nano_banana_2">
  Open in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_google_nano_banana2_image_edit.json">
  Download JSON or search "Nano Banana 2" in Template Library
</Card>

### Pro-level quality showcase

![Quality comparison](https://substack-post-media.s3.amazonaws.com/public/images/1f92ae2e-14d8-4a3b-9ed7-e57dacd2584f_1825x1696.png)
*Replace the text from the input image with: Nano Banana 2 Available on ComfyUI Cheaper and Faster*

### Search-grounded world knowledge showcase

![Educational infographic](https://substack-post-media.s3.amazonaws.com/public/images/edfe3b6b-8942-472e-8772-a3700946fc23_1024x559.png)
*Educational comic book style infographic explaining five lesser-known North American native species, with search-grounding to ensure accurate depictions of rare habitats and ecological roles.*

![Skateboard culture infographic](https://substack-post-media.s3.amazonaws.com/public/images/536b845b-b278-4924-b8e4-114e5e5defa9_2752x1536.png)
*Comic book style infographic for American skateboard culture evolution from the 1970s to the 2020s.*

### Subject consistency showcase

![Subject consistency](https://substack-post-media.s3.amazonaws.com/public/images/e38f7afb-9752-49a1-9e6c-1ea99dba42ff_4908x2626.png)
*Maintain character resemblance and object fidelity across storyboard sequences.*

### Configurable thinking levels showcase

![Thinking levels comparison](https://substack-post-media.s3.amazonaws.com/public/images/6d0d4773-3ff5-4319-bc00-8afb62c2a1ad_4608x1332.png)
*Cinematic portrait with different thinking levels: Minimal for quick iterations, High for detailed outputs.*

![Art Nouveau portrait](https://substack-post-media.s3.amazonaws.com/public/images/49e5f98a-b375-4fda-b280-7b695f535807_4608x1332.png)
*Art Nouveau inspired portrait with configurable reasoning depth.*

### Text rendering and translation showcase

![Text rendering](https://substack-post-media.s3.amazonaws.com/public/images/808ca8d0-acac-470d-a666-23e411254276_1376x768.png)
*Amateur cellphone photograph with stylized graffiti text rendering.*

![Spanish translation](https://substack-post-media.s3.amazonaws.com/public/images/6af9b091-7bbe-49da-b70f-e766394039ef_2784x1536.png)
*Translate text to Spanish.*

![Hindi translation](https://substack-post-media.s3.amazonaws.com/public/images/548d44f6-d43e-484f-a8d8-37638f9ff482_2784x1536.png)
*Translate text to Hindi.*

![Mandarin translation](https://substack-post-media.s3.amazonaws.com/public/images/5f4a52f9-1995-440f-8394-245e43f3a9a2_2784x1536.png)
*Translate text to Mandarin.*

## Which model should you pick?

| Model               | Best for                                                                                |
| ------------------- | --------------------------------------------------------------------------------------- |
| **Nano Banana 2**   | Most creators — fast enough to explore, smart enough to refine, polished enough to ship |
| **Nano Banana Pro** | Maximum factual precision and high-stakes edge cases                                    |

## Get started

1. Update ComfyUI to the latest version
2. Double-click the canvas and search for the "Nano Banana 2" node
3. Or go to the Template Library to use the ready-to-go workflow
4. Choose your resolution, set your aspect ratio, and decide whether the prompt needs deeper reasoning

<Note>
  The new model version has also been added to the previous "Nano Banana Pro" node. If you have old workflows with this node, you don't need to rebuild them — just reselect the model version.
</Note>


# Nano Banana Pro and ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/google/nano-banana-pro

This article will introduce how to use Google's Nano Banana Pro (Gemini 3 Pro Image) in ComfyUI for high-fidelity image generation and editing

Nano Banana Pro is Google DeepMind's new flagship model for high-fidelity image generation and editing. It pushes beyond casual creation into production-ready visuals with advanced capabilities including 4K generation, text rendering, and character consistency.

In this guide, we will walk you through using Nano Banana Pro in ComfyUI.

## Highlights of Nano Banana Pro

* **World knowledge:** Generates accurate, real-world images by tapping into Search's knowledge base.
* **Text & translation:** Renders clean text and supports detection/translation across **10 languages**.
* **High resolutions and studio controls:** Blend up to **14 images**, adjust angles and focus, apply color grading, and create in native **4K**.
* **Consistency:** Turns sketches into dresses or blueprints into 3D visuals with high-fidelity consistency.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Get started

### For new users

The easiest way to use Nano Banana Pro is to go to Comfy Cloud through the link below. No extra setup needed.

<a href="https://cloud.comfy.org/?template=api_nano_banana_pro&utm_source=blog">
  <p>Try Nano Banana Pro on Comfy Cloud</p>
</a>

### For local users

Please update ComfyUI and go to Template → Nano Banana Pro to access the workflow.


# HappyHorse 1.0 Video Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/happyhorse/happyhorse1-0

Learn how to use HappyHorse 1.0 via Partner Nodes in ComfyUI for image-to-video, text-to-video, reference-to-video, and video editing with cinematic aesthetics and multi-shot consistency

HappyHorse 1.0 is a cinematic video generation model from Alibaba, now available in ComfyUI via Partner Nodes. It is designed for high-quality storytelling video and production-ready creative workflows.

HappyHorse 1.0 focuses on strong aesthetics, multi-shot sequencing, and powerful edit-style workflows (generation + editing). It's a great fit for creators building ads, e-commerce visuals, short-form content, and social marketing videos.

## Highlights

* **Multi-modal creation paths**: Text-to-Video (T2V), Image-to-Video (I2V), and Subject-to-Video (S2V)
* **Cinematic aesthetics**: Wide-aperture framing, shallow depth of field, refined texture, and atmospheric mood
* **Multi-shot output**: Up to **15s** at **1080p**, with an emphasis on multi-shot consistency across cut transitions
* **Editing workflows**: V2V and SV2V for transforming footage or replacing/inserting subjects while preserving motion and composition

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## HappyHorse 1.0 image-to-video

Generate cinematic video from a single image with strong aesthetic control and multi-shot consistency.

<Columns>
  <video />

  <video />
</Columns>

<Card title="HappyHorse 1.0 I2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_happyhorse1_0_i2v.json">
  Get the HappyHorse 1.0 Image-to-Video workflow file.
</Card>

<Card title="Run HappyHorse 1.0 I2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_happyhorse1_0_i2v&utm_source=docs">
  Try the Image-to-Video workflow instantly on Comfy Cloud.
</Card>

## HappyHorse 1.0 text-to-video

Generate cinematic video from pure text prompts, with multi-shot sequencing and refined visual atmosphere.

<video />

<Card title="HappyHorse 1.0 T2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_happyhorse1_0_t2v.json">
  Get the HappyHorse 1.0 Text-to-Video workflow file.
</Card>

<Card title="Run HappyHorse 1.0 T2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_happyhorse1_0_t2v&utm_source=docs">
  Try the Text-to-Video workflow instantly on Comfy Cloud.
</Card>

## HappyHorse 1.0 reference-to-video

Use a reference subject to drive video generation, preserving identity across cinematic multi-shot sequences.

<Card title="HappyHorse 1.0 R2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_happyhorse1_0_r2v.json">
  Get the HappyHorse 1.0 Reference-to-Video workflow file.
</Card>

<Card title="Run HappyHorse 1.0 R2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_happyhorse1_0_r2v&utm_source=docs">
  Try the Reference-to-Video workflow instantly on Comfy Cloud.
</Card>

## HappyHorse 1.0 video edit

Transform existing footage or replace/insert subjects while preserving motion and composition with V2V and SV2V editing workflows.

<Card title="HappyHorse 1.0 Video Edit Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_happyhorse1_0_video_edit.json">
  Get the HappyHorse 1.0 Video Edit workflow file.
</Card>

<Card title="Run HappyHorse 1.0 Video Edit on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_happyhorse1_0_video_edit&utm_source=docs">
  Try the Video Edit workflow instantly on Comfy Cloud.
</Card>


# Hunyuan 3D Partner Nodes Model Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/hunyuan3d/hunyuan3d-3-0

This article will introduce how to use Hunyuan 3D node's API in ComfyUI for 3D model generation

Hunyuan 3D 3.0 is Tencent's state-of-the-art 3D generation model that enables minutes-level 3D content creation. It can generate production-ready 3D assets from text prompts, images, or sketches with far lower barriers to entry than traditional 3D modeling pipelines.

ComfyUI has now natively integrated the corresponding Hunyuan 3D API, allowing you to conveniently use the related nodes in ComfyUI for model generation.

Currently, ComfyUI's Partner nodes support the following Hunyuan 3D model generation capabilities:

* Text-to-3D generation
* Image-to-3D generation
* Multi-view-to-3D generation

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Use cases

* **Game development ideation**: Fast generation of characters, props, and environments with optimized topology for rigging and real-time rendering
* **Product & e-commerce**: Turn product photos into interactive 3D models for online display
* **Industrial design**: Sketch-to-3D prototyping and 3D-print-ready part decomposition
* **VFX & animation**: High-resolution assets with professional UVs and PBR materials

## Getting started

### 1. Access workflow templates

1. Open the Template Library in the sidebar
2. Navigate to **3D** → **Hunyuan 3D**
3. Select a workflow template for Hunyuan 3D

### 2. Run the workflow

1. Input your text prompt, images, or sketches depending on the workflow type
2. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation
3. After the workflow completes, preview and export your 3D model

## Text-to-3D workflow

Enter a text description to generate a 3D model in one click. The model accurately follows style, shape, and material details for consistent results.

**Example prompt**: "Mechanical dolphin with gears, steampunk"

<Card title="Hunyuan 3D Text-to-3D Workflow" icon="cloud" href="https://cloud.comfy.org/?template=api_hunyuan3d_text_to_model&utm_source=docs&utm_medium=inhouse_social&utm_campaign=inhouse_feature_launches&utm_content=post&utm_niche=workflow_engineering&utm_creator=purz">
  Run on Comfy Cloud
</Card>

## Image-to-3D workflow

Upload one or more images to generate high-quality 3D models. Support for 2–4 multi-view images improves geometry and material fidelity.

<Card title="Hunyuan 3D Image-to-3D Workflow" icon="cloud" href="https://cloud.comfy.org/?template=api_hunyuan3d_image_to_model&utm_source=docs&utm_medium=inhouse_social&utm_campaign=inhouse_feature_launches&utm_content=post&utm_niche=workflow_engineering&utm_creator=purz">
  Run on Comfy Cloud
</Card>

## Multi-view-to-3D workflow

Provide multiple view images (front, back, side) to generate 3D models with improved accuracy and detail. This uses the same workflow as Image-to-3D—simply upload 2–4 images from different angles.

<Card title="Hunyuan 3D Image-to-3D Workflow" icon="cloud" href="https://cloud.comfy.org/?template=api_hunyuan3d_image_to_model&utm_source=docs&utm_medium=inhouse_social&utm_campaign=inhouse_feature_launches&utm_content=post&utm_niche=workflow_engineering&utm_creator=purz">
  Run on Comfy Cloud
</Card>

## Advanced features

Following the [initial HY 3D 3.0 integration](https://blog.comfy.org/p/hunyuan-3d-30-in-comfyui-state-of), Hunyuan 3D's advanced processing features are now available via Partner Nodes. These workflows help close the gap between generation and production by bringing key post-processing steps into ComfyUI.

### 3D parts decomposition

Split a complete 3D model into meaningful structural parts, such as armor pieces, accessories, wheels, or other distinct components. This makes it easier to edit specific regions of an asset, swap parts for variations, and prepare models for modular workflows, animation, or downstream assembly.

<Card title="Try on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_hunyuan3d_part&utm_source=docs">
  Run the workflow
</Card>

<Card title="Download Workflow" icon="github" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_hunyuan3d_part.json">
  Get the JSON file
</Card>

### UV unwrapping

Automatically generate UV layouts for supported 3D models, turning raw geometry into assets that are much easier to texture. Instead of manually cutting seams and organizing UV islands, creators can move more quickly into painting, baking, and material work with a cleaner starting point.

<Card title="Try on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_hunyuan3d_model2uv&utm_source=docs">
  Run the workflow
</Card>

<Card title="Download Workflow" icon="github" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_hunyuan3d_model2uv.json">
  Get the JSON file
</Card>

### Smart topology

Convert dense geometry into cleaner meshes with more organized edge flow, helping generated models become easier to optimize and reuse in real production pipelines. This is especially useful when preparing assets for game engines, real-time rendering, or any workflow that benefits from lower-density, better-structured geometry.

<Card title="Try on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_hunyuan3d_smart_topology&utm_source=docs">
  Run the workflow
</Card>

<Card title="Download Workflow" icon="github" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_hunyuan3d_smart_topology.json">
  Get the JSON file
</Card>


# ComfyUI Ideogram 3.0 Partner Nodes Official Examples
Source: https://docs.comfy.org/tutorials/partner-nodes/ideogram/ideogram-v3

This guide covers how to use the Ideogram 3.0 Partner node in ComfyUI

Ideogram 3.0 is a powerful text-to-image model by Ideogram, known for its photorealistic quality, accurate text rendering, and consistent style control.

The [Ideogram V3](/built-in-nodes/partner-node/image/ideogram/ideogram-v3) node currently supports two modes:

* Text-to-Image mode
* Image Editing mode (when both image and mask inputs are provided)

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Ideogram 3.0 Node Documentation

Check the following documentation for detailed node parameter settings:

* [Ideogram V3](/built-in-nodes/partner-node/image/ideogram/ideogram-v3)

## Ideogram 3.0 Partner Nodes Text-to-Image Mode

When using [Ideogram V3](/built-in-nodes/partner-node/image/ideogram/ideogram-v3) without image and mask inputs, the node operates in Text-to-Image mode.

### 1. Download Workflow File

Download and drag the following file into ComfyUI to load the workflow:

![Ideogram 3.0 ComfyUI Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/ideogram/v3/ideogram_v3_t2i.png)

### 2. Complete the Workflow Steps

<img alt="Ideogram 3.0 Workflow Steps" />

Follow the numbered steps to complete the basic workflow:

1. Enter your image description in the `prompt` field of the `Ideogram V3` node
2. Click `Run` or use shortcut `Ctrl(cmd) + Enter` to generate the image
3. After the API returns results, view the generated image in the `Save Image` node. Images are saved to the `ComfyUI/output/` directory

## Ideogram 3.0 Partner Nodes Image Editing Mode

\[To be updated]


# ComfyUI Ideogram 4.0 Partner Node Tutorial
Source: https://docs.comfy.org/tutorials/partner-nodes/ideogram/ideogram-v4

Learn how to use the Ideogram 4.0 API Partner node in ComfyUI

Ideogram 4.0 is the latest text-to-image model from Ideogram, offering superior photorealistic quality, accurate text rendering, and precise style control. You can use either plain natural language or **structured JSON prompts** for fine-grained control over layout, colors, and in-image text.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Ideogram 4.0 Partner Node Text-to-Image Workflow

<Card title="Run in Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_ideogram_v4_t2i&utm_source=docs&utm_medium=referral&utm_campaign=ideogram-v4">
  Open in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_ideogram_v4_t2i.json">
  Download JSON or search "Ideogram v4: Text to Image (API)" in Template Library
</Card>

![Ideogram 4.0 Example Output](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/output/api_ideogram_v4_t2i.png)
*Example output from the Ideogram 4.0 API*

### Prompt Format

The Ideogram V4 node supports two prompt formats:

1. **Natural Language** — Simple and intuitive, best for quick ideas.
2. **Structured JSON** — Offers fine-grained control over style palette, element placement (`bbox`), and literal text rendering in the image. Recommended for poster-like compositions.

The default workflow example uses a structured JSON prompt that includes:

* `high_level_description` — Overall scene description
* `style_description` — Aesthetic, lighting, medium, color palette
* `compositional_deconstruction` — Per-element bounding boxes, descriptions, and color palettes

### Workflow Steps

1. Download and drag the workflow file into ComfyUI
2. The `Ideogram V4` node already contains a default structured JSON prompt — you can modify it or write plain natural language
3. Click `Run` or use shortcut `Ctrl(cmd) + Enter` to generate the image
4. After the API returns results, view the generated image in the `Save Image` node. Images are saved to the `ComfyUI/output/` directory

### Using the JSON Prompt Builder (Optional)

The workflow includes a built-in **Gemini** node (Gemini 3.1 Pro) to help you build structured JSON prompts:

1. Describe your idea in the Gemini node's user prompt field
2. The model will generate a schema-matching JSON prompt
3. Connect the `STRING` output to the `Ideogram V4` node's `prompt` input
4. Run the workflow

## Additional Notes

* **Negative prompts are not needed** — The Ideogram 4.0 model uses asymmetric classifier-free guidance, where the unconditional pass drops text tokens, rather than requiring a separate negative prompt string.
* **Model-assisted prompt building** — Consider using the **Ideogram 4 Prompt Builder** (KJNodes) for visual control over prompt construction on ComfyUI.


# Kling 3.0 Video and Image Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/kling/kling-3-0

Learn how to use Kling 3.0 models in ComfyUI for multi-shot video generation, subject consistency, multilingual audio, and native text rendering

Kling 3.0 is one of the most advanced multi-modal generation systems, now available in ComfyUI via Partner Nodes. This release includes **Kling Video 3.0**, **Kling Video 3.0 Omni**, **Kling Image 3.0**, and **Kling Image 3.0 Omni**, bringing video, image, audio-visual, and narrative generation capabilities directly into your node-based workflows.

## About Kling 3.0

**Key features:**

* **Multi-shot generation**: Generate multiple shots with duration control in a single generation
* **Locked subject consistency**: Maintain character and object identity across camera motion and scene evolution
* **Native audio with character awareness**: Multilingual dialogue with precise lip sync and facial expression alignment
* **Native text rendering**: Clear, structured on-screen text for ads, UI scenes, and branded content

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Kling 3.0 workflows

<Card title="I2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_kling_v3_i2v.json">
  Download the Kling 3.0 Image-to-Video workflow.
</Card>

<Card title="Omni Video Edit Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_kling_v3_omni_video_edit.json">
  Download the Kling 3.0 Omni Video Edit workflow.
</Card>

<Card title="Run I2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_kling_v3_i2v&utm_source=docs">
  Try the Image-to-Video workflow instantly on Comfy Cloud.
</Card>

<Card title="Run Omni Edit on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_kling_v3_omni_video_edit&utm_source=docs">
  Try the Omni Video Edit workflow instantly on Comfy Cloud.
</Card>

## Learn more

For detailed examples, prompts, and video demonstrations of Kling 3.0's capabilities, check out our blog post:

<Card title="Kling 3.0 Models Are Now Available" icon="newspaper" href="https://blog.comfy.org/p/kling-30-models-are-now-available">
  Read the full announcement with video examples, prompt tips, and feature deep-dives.
</Card>

## Available models

| Model                    | Type  | Description                                              |
| ------------------------ | ----- | -------------------------------------------------------- |
| **Kling Video 3.0**      | Video | Standard video generation with multi-shot support        |
| **Kling Video 3.0 Omni** | Video | Advanced video generation with audio-visual capabilities |
| **Kling Image 3.0**      | Image | High-quality image generation                            |
| **Kling Image 3.0 Omni** | Image | Multi-modal image generation with enhanced features      |


# Kling 2.6 Motion Control Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/kling/kling-motion-control

Learn how to use the Kling 2.6 Motion Control Partner node in ComfyUI for precise motion transfer from reference videos to character images

Kling 2.6 Motion Control is a specialized multimodal model developed by Kuaishou that enables precise motion transfer from reference videos to character images. By combining a **Reference Image** (your character) and a **Motion Reference Video** (the action), the AI applies the movement, expression, and pacing of the video to your static character while maintaining their identity.

Unlike standard image-to-video generation that guesses motion from text prompts, Motion Control uses a reference video as the movement blueprint. The model acts as a digital puppeteer, extracting choreography from your reference video and applying it to your character with cinema-grade fidelity.

## Product highlights

* **Complex motion handling**: Execute complicated sequences like dance routines, martial arts, or athletic movements without losing character coherence. The model understands weight transfer and momentum for realistic physical impact.
* **Precision hand and finger performance**: Hands have traditionally been a weak point for AI video. This feature specifically improves finger articulation and hand movements by mimicking real footage, making it ideal for presentations and demonstrations.
* **Scene and environment flexibility**: Use text prompts to change the environment while the character continues their referenced motion. You're not limited to the reference video's background.
* **Advanced camera and perspective modes**: Granular control over how the camera interprets your reference with distinct orientation modes.
* **30-second one-shot support**: Generate continuous actions up to 30 seconds in a single generation, enabling uninterrupted character motion for narrative scenes.

## Character orientation modes

The `character_orientation` parameter determines how the model interprets spatial information and constrains output duration:

| Mode    | Description                                                                                                                                        | Max Duration |
| ------- | -------------------------------------------------------------------------------------------------------------------------------------------------- | ------------ |
| `video` | Output character orientation matches the reference video. Best for complex full-body performances like dance sequences and elaborate choreography. | 30 seconds   |
| `image` | Output character orientation matches the reference image. Best for portrait animations with camera movement like pans, tilts, and tracking shots.  | 10 seconds   |

## Model tiers

| Tier         | Resolution | Best For                                                                                                      |
| ------------ | ---------- | ------------------------------------------------------------------------------------------------------------- |
| **Standard** | 720p       | Simple animations, social media content, memes, and quick tests. Faster and more credit-efficient.            |
| **Pro**      | 1080p      | Complex choreography, intricate hand movements, professional marketing assets, and broadcast-quality content. |

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Kling 2.6 Motion Control workflow

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/api_kling_motion_control.json">
  <p>Download the workflow file in JSON format</p>
</a>

## Input requirements

* **Image formats**: JPG, PNG, WEBP, GIF, AVIF (max 10MB)
* **Video formats**: MP4, MOV, WEBM, M4V, GIF (max 100MB)
* **Video duration**: 3-30 seconds depending on orientation mode
* **Minimum resolution**: 720px width and height
* **Subject visibility**: Character must clearly show head, shoulders, and torso

## Tips for better results

* **Match aspect ratios**: Ensure your character image and reference video have similar aspect ratios (e.g., both 16:9 or both 9:16) to prevent awkward stretching or cropping.
* **Clean backgrounds**: Use reference videos with simple or static backgrounds for best motion extraction. High-contrast videos where the actor's silhouette is distinct work best.
* **Clear character angles**: If your reference video shows rotation, use 3D-style characters or realistic photos that handle rotation better. Flat 2D cartoons may struggle with back views.
* **Visible limbs**: Ensure the character's limbs are visible in the source image. If a character has hands in pockets but the motion requires waving, the AI will hallucinate hands, often leading to artifacts.
* **Leave breathing room**: Leave negative space around the subject. If the character will dance or move arms wide, they need space within the frame to avoid clipping.
* **Framing alignment**: Match the framing between your image and reference video. Use a close-up reference for face animations, or a full-body reference for walking/dancing sequences.


# Luma Image to Image Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/luma/luma-image-to-image

This guide covers how to use the Luma Image to Image Partner node in ComfyUI

The [Luma Image to Image](/built-in-nodes/partner-node/image/luma/luma-image-to-image) node allows you to modify existing images based on text prompts using Luma AI technology, while preserving certain features and structures from the original image.

In this guide, we'll show you how to set up an image-to-image workflow using this node.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Luma Image to Image Node Documentation

Check the following documentation for detailed node parameter settings:

<Card title="Luma Image to Image Node Documentation" icon="book" href="/built-in-nodes/partner-node/image/luma/luma-image-to-image">
  Luma Image to Image Partner Nodes Documentation
</Card>

## Luma Image to Image Partner Nodes Workflow

<Tip>
  This feature works well for changing objects and shapes. However, it may not be ideal for color changes. We recommend using lower weight values, around 0.0 to 0.1.
</Tip>

### 1. Download Workflow File

Download and drag the following image into ComfyUI to load the workflow (workflow information is included in the image metadata):

![Luma Image to Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/i2i/luma_i2i.png)

Download this image to use as input:

![Luma Image to Image Workflow Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/i2i/input.png)

### 2. Complete the Workflow Steps

<img alt="Luma Image to Image Workflow Steps" />

Follow these numbered steps:

1. Click **Upload** on the `Load Image` node to upload your input image
2. (Optional) Modify the workflow prompts
3. (Optional) Adjust `image_weight` to change input image influence (lower values stay closer to original)
4. Click `Run` or use shortcut `Ctrl(cmd) + Enter` to generate the image
5. After API returns results, view the generated image in the `Save Image` node. Images are saved to the `ComfyUI/output/` directory

### 3. Results with Different `image_weight` Values

<img alt="Weight Comparison" />


# Luma Image to Video Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/luma/luma-image-to-video

Learn how to use the Luma Image to Video Partner node in ComfyUI

The [Luma Image to Video](/built-in-nodes/partner-node/video/luma/luma-image-to-video) node allows you to convert static images into smooth, dynamic videos using Luma AI's advanced technology, bringing life and motion to your images.

In this guide, we'll show you how to set up a workflow for image-to-video conversion using this node.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Luma Image to Video Node Documentation

Check out the following documentation to learn more about the node's parameters:

<Card title="Luma Image to Video Node Docs" icon="book" href="/built-in-nodes/partner-node/video/luma/luma-image-to-video">
  Luma Image to Video Partner node documentation
</Card>

<Card title="Luma Concepts Node Docs" icon="book" href="/built-in-nodes/partner-node/video/luma/luma-concepts">
  Luma Concepts Partner node documentation
</Card>

## Image to Video Workflow with Luma Partner Nodes

The Luma Image to Video node requires at least one image input (`first_image` or `last_image`) along with text prompts to determine the video's motion effects. In this guide, we've created an example using `first_image` and `luma_concepts` to showcase Luma AI's video generation capabilities.

### 1. Download the Workflow

The workflow information is included in the metadata of the video below. Download and drag it into ComfyUI to load the workflow.

![Luma Image to Video Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/i2v/luma_i2v.mp4)

Download the following image to use as input:

![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/i2v/input.png)

### 2. Follow the Workflow Steps

<img alt="Luma Image to Video Workflow Steps" />

Follow these basic steps to run the workflow:

1. Upload your input image in the `first_image` node
2. (Optional) Write prompts in the Luma Image to Video node to describe how you want the image animated
3. (Optional) Modify the `Luma Concepts` node to control camera movement for professional cinematography
4. Click `Run` or use `Ctrl(cmd) + Enter` to generate the video
5. Once the API returns results, view the generated video in the `Save Video` node. The video will also be saved to the `ComfyUI/output/` directory

### 3. Additional Notes

* **Image Input Requirements**: At least one of `first_image` or `last_image` is required, with a maximum of 1 image per input
* **Luma Concepts**: Controls camera movement for professional video effects
* **Seed Parameter**: Only determines if the node should rerun, doesn't affect generation results
* **Enable Input Nodes**: Right-click on purple "Bypass" mode nodes and set "mode" to "always" to enable inputs
* **Model Selection**: Different video generation models have unique characteristics, adjustable via the model parameter
* **Resolution and Duration**: Adjust output video resolution and length using resolution and duration parameters


# Luma Text to Image Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/luma/luma-text-to-image

This guide explains how to use the Luma Text to Image Partner node in ComfyUI

The [Luma Text to Image](/built-in-nodes/partner-node/image/luma/luma-text-to-image) node allows you to generate high-quality images from text prompts using Luma AI's advanced technology, capable of creating photorealistic content and artistic style images.

In this guide, we'll show you how to set up workflows using this node for text-to-image generation.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Luma Text to Image Node Documentation

You can refer to the following documentation for detailed parameter settings:

<Card title="Luma Text to Image Node Documentation" icon="book" href="/built-in-nodes/partner-node/image/luma/luma-text-to-image">
  Luma Text to Image Partner Nodes Documentation
</Card>

<Card title="Luma Reference Node Documentation" icon="book" href="/built-in-nodes/partner-node/image/luma/luma-reference">
  Luma Reference Partner Nodes Documentation
</Card>

## Luma Text to Image Partner Nodes Workflow

When the `Luma Text to Image` node is used without any image inputs, it functions as a text-to-image workflow. In this guide, we've created examples using `style_image` and `image_luma_ref` to showcase Luma AI's excellent image processing capabilities.

### 1. Download Workflow Files

The workflow information is included in the metadata of the image below. Download and drag it into ComfyUI to load the workflow.

![Luma Text to Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/t2i/luma_t2i.png)

Please download these images for input:

![Input Image - Reference](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/t2i/input_ref.png)
![Input Image - Style](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/t2i/input_style.png)

### 2. Follow Steps to Run the Workflow

<img alt="Luma Text to Image Workflow Steps" />

Follow the numbered steps in the image to complete the basic workflow:

1. Upload the reference image in the `Load image` node
2. Upload the style reference image in the `Load image (renamed to styleref)` node
3. (Optional) Modify the prompts in the `Luma Text to Image` node
4. (Optional) Adjust the `style_image_weight` to control the style reference image's influence
5. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to generate the image
6. After the API returns results, view the generated image in the `Save Image` node. Images are saved to the `ComfyUI/output/` directory

<img alt="Style Image Weight Comparison" />

### 3. Additional Notes

* The [node](/built-in-nodes/partner-node/image/luma/luma-text-to-image) allows up to 4 reference images and character references simultaneously.
* To enable multiple image inputs, right-click on the purple "Bypassed" nodes and set their `mode` to `always`


# Luma Text to Video Partner Nodes ComfyUI Official Guide
Source: https://docs.comfy.org/tutorials/partner-nodes/luma/luma-text-to-video

Learn how to use the Luma Text to Video Partner node in ComfyUI

The [Luma Text to Video](/built-in-nodes/partner-node/video/luma/luma-text-to-video) node allows you to create high-quality, smooth videos from text descriptions using Luma AI's innovative video generation technology.

In this guide, we'll show you how to set up a text-to-video workflow using this node.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Luma Text to Video Node Documentation

Check out the following documentation to learn more about the node parameters:

<Card title="Luma Text to Video Node Docs" icon="book" href="/built-in-nodes/partner-node/video/luma/luma-text-to-video">
  Documentation for the Luma Text to Video Partner node
</Card>

<Card title="Luma Concepts Node Docs" icon="book" href="/built-in-nodes/partner-node/video/luma/luma-concepts">
  Documentation for the Luma Concepts Partner node
</Card>

## Text to Video Workflow with Luma Partner Nodes

The Luma Text to Video node requires text prompts to describe the video content. In this guide, we've created examples using `prompt` and `luma_concepts` to showcase Luma AI's excellent video generation capabilities.

### 1. Download the Workflow

The workflow information is included in the metadata of the video below. Download and drag it into ComfyUI to load the workflow.

![Luma Text to Video Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/luma/t2v/luma_t2v.mp4)

### 2. Follow the Steps

<img alt="Luma Text to Video Workflow Steps" />

Follow these basic steps to run the workflow:

1. Write your prompt in the `Luma Text to Video` node to describe the video content you want
2. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to generate the video
3. After the API returns results, you can view the generated video in the `Save Video` node. The video will also be saved to the `ComfyUI/output/` directory

> (Optional) Modify the `Luma Concepts` node to control camera movements and add professional cinematography

### 3. Additional Notes

* **Writing Prompts**: Describe scenes, subjects, actions, and mood in detail for best results
* **Luma Concepts**: Mainly used for camera control to create professional video shots
* **Seed Parameter**: Only determines if the node should rerun, doesn't affect generation results
* **Model Selection**: Different video models have different features, adjustable via the model parameter
* **Resolution and Duration**: Adjust output video resolution and length using these parameters
* **Ray 1.6 Model Note**: Duration and resolution parameters don't work when using the Ray 1.6 model


# Luma Uni-1 Guide
Source: https://docs.comfy.org/tutorials/partner-nodes/luma/luma-uni-1

Use Luma Uni-1 partner nodes in ComfyUI for Create and Modify image workflows.

In **ComfyUI**, Luma **Uni-1** shows up as **partner Partner Nodes** for unified image work: **Create** graphs generate new images from prompts (with optional references); **Modify** graphs take an existing image as input and edit it in place. You drive both through the usual workflow—wire **Load Image** / **Save Image**, set prompts, seeds, aspect ratio, and reference slots on the Luma node, then queue the graph locally or open a template on **Comfy Cloud**.

Luma describes Uni-1 as a non-diffusion, decoder-only autoregressive model that reasons over your prompt before drawing. On the canvas, what matters most is choosing **Create vs Modify**, labeling references clearly, and iterating with seeds.

This page focuses on how to use Uni-1 **inside ComfyUI**, from simple graphs to multi-reference setups.

## What makes Uni-1 different

* **Two clear modes**: Create Image (generate something new) and Modify Image (edit something existing)
* **Up to 9 reference images**, each with a defined role
* **Strong control over niche and specific visual styles**
* **Seed support** for reproducibility and controlled iteration
* **Nine aspect ratios**, from ultra-tall to ultra-wide
* **Text rendering** that's actually readable
* **Web search grounding** for real-world context
* **Multilingual prompts**
* **Multi-panel output** with temporal consistency

If you understand the modes and how to control references, you understand Uni-1.

## Strengths

Uni-1 excels across a wide range of tasks:

* **Photorealism** with material accuracy
* **Illustration & stylized art** with strong aesthetic control
* **Old photo restoration** and vintage reproduction
* **Surreal and conceptual** compositions
* **Text rendering** — readable text inside images, great for infographics and posters
* **Image editing** and multi-turn refinement
* **Reference-guided generation** with identity preservation
* **Multi-panel output** — consistent characters/scenes across multiple frames

## The core distinction: Create vs Modify

Everything in Uni-1 starts with one question: **Am I creating something new, or changing something that already exists?**

| Mode             | What it does                                                                             | When to use                                     |
| ---------------- | ---------------------------------------------------------------------------------------- | ----------------------------------------------- |
| **Create Image** | Produces a brand-new composition. Can be inspired by references.                         | "Create a new scene in the style of this photo" |
| **Modify Image** | Edits a specific input image. Preserves composition and structure unless told otherwise. | "Make this photo look like nighttime"           |

When in doubt:

* If the output should look like a **version of your input**, use Modify
* If it should feel **inspired but new**, use Create

## Available workflows

### Image Create workflow

<Card title="Run Image Create on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_luma_uni_1_image_create&utm_source=docs">
  Try the Image Create workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Image Create Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_luma_uni_1_image_create.json">
  Download JSON or search "Luma UNI-1 Image Create" in Template Library
</Card>

### Image Edit workflow

<Card title="Run Image Edit on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_luma_uni_1_image_edit&utm_source=docs">
  Try the Image Edit workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Image Edit Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_luma_uni_1_image_edit.json">
  Download JSON or search "Luma UNI-1 Image Edit" in Template Library
</Card>

The workflow is simple: **prompt → evaluate → refine**. Leave the seed blank while exploring. Once you find something strong, lock the seed and iterate from there.

## Core parameters

| Parameter                     | Description                                                                                                      |
| ----------------------------- | ---------------------------------------------------------------------------------------------------------------- |
| **Prompt**                    | Your primary control. Up to 6,000 characters. Be precise.                                                        |
| **Aspect ratio**              | Controls framing, not quality. Choose based on use case.                                                         |
| **Seed**                      | Same seed + same prompt → same result. Same seed + changed prompt → controlled variation. No seed → exploration. |
| **Reference images** (Create) | Up to 9 images to guide different aspects.                                                                       |
| **Source image** (Modify)     | The image you are editing. Dimensions are preserved automatically.                                               |

## Working with reference images

References only work if you tell the model what they are for. Use this structure:

```text theme={null}
Use IMAGE1 ([description]) as a [ROLE] reference.
```

Possible roles: **Style**, **Character**, **Composition**, **Color palette**, **Lighting**, **Texture**, **Mood**.

Without roles, the model guesses, and guesses are unreliable.

### Create mode examples

**Style reference**

```text theme={null}
Use IMAGE1 (impressionist oil painting with loose brushwork and warm
sunset tones) as a STYLE reference. Create a portrait of a woman in her
30s applying IMAGE1's color palette and painterly texture. The subject
should be new.
```

**Character reference**

```text theme={null}
Use IMAGE1 (woman with short copper-red hair, freckles) as a CHARACTER
reference. Preserve her features. Generate a new scene: she's sitting
in a softly lit café.
```

**Multi-reference**

```text theme={null}
Use IMAGE1 as a COLOR PALETTE reference, IMAGE2 as LIGHTING, IMAGE3 as
COMPOSITION. Create a lone figure walking through a rain-slicked street
at night.
```

### Modify mode examples

In Modify mode, clarity is everything. Always specify **what to change** and **what must stay untouched**.

```text theme={null}
Change the time of day to golden hour. Update sky, light direction,
shadows, and color temperature. Keep all subjects and composition
unchanged.
```

```text theme={null}
Make the rain heavier and add reflections on the ground. Keep all other
elements unchanged.
```

## Prompting guidelines

Recommended lengths:

* **Text-to-image** → 80–250 words
* **Reference-guided** → 100–300 words
* **Modify** → 30–100 words

Avoid vague terms ("beautiful", "amazing"), redundant phrasing, and conflicting instructions. Instead, use specific, named aesthetics:

* `Golden hour, 85mm lens, shallow depth of field`
* `1970s Italian giallo film poster, high-contrast color blocking`

Precision beats generality.

## Aspect ratios

Choose based on where the image will live:

| Ratio     | Use case              |
| --------- | --------------------- |
| 1:1       | Social posts          |
| 9:16      | Vertical video        |
| 16:9      | Widescreen            |
| 3:2 / 2:3 | Photography           |
| 2:1 / 3:1 | Cinematic / panoramic |
| 1:2 / 1:3 | Ultra-tall            |

In Modify mode, aspect ratio is locked to the source image.

## Seeds: control and reproducibility

Seeds turn experimentation into systems.

* **Fixed seed** → consistency
* **No seed** → exploration

Workflow:

1. Explore with no seed
2. Find a strong result
3. Lock the seed
4. Change one variable at a time

Save your prompt and seed together. That's your reusable recipe.

## Advanced techniques

### Character consistency

1. Generate a clean, front-facing reference image
2. Reuse it as `IMAGE1 (CHARACTER)` in every scene
3. Keep the label identical across prompts

### Multi-reference architecture

Assign one role per image:

* IMAGE1 → character
* IMAGE2 → style
* IMAGE3 → lighting
* IMAGE4 → environment

End the prompt with:

```text theme={null}
Treat each reference as having authority over its assigned layer only.
```

### Create → Modify chain

Use Create to explore compositions, then Modify to refine details. This is one of the most powerful workflows.

### Iterative refinement

1. Explore (no seed)
2. Lock seed
3. Change one variable per generation
4. Document results

It feels slower, but it's actually faster, because you always know what changed.

## Troubleshooting

| Problem                               | Fix                                       |
| ------------------------------------- | ----------------------------------------- |
| References ignored                    | Label each one clearly                    |
| Modify changes too much               | Explicitly state what must stay unchanged |
| Inconsistent outputs                  | Lock the seed                             |
| Prompt partially ignored              | Remove conflicts or split into steps      |
| Output looks like the reference image | You may be in Modify mode                 |
| Character inconsistency               | Reuse a canonical reference image         |

## Quick reference

**Create Image**

* New compositions
* Text + up to 9 references
* Descriptive prompts

**Modify Image**

* Edits existing images
* Source image + references
* Direct, surgical prompts

## The golden rules

1. Label every reference
2. In Modify mode, always state what should **not** change
3. Change one variable at a time when refining
4. Save prompt + seed for reproducibility
5. Create = new scenes, Modify = edits

## Key takeaway

Mastering Uni-1 comes down to three things: **choose the right mode → control your references → iterate with intention**. Once those are in place, you're no longer guessing, you're directing.


# Meshy 6 Partner Nodes Model Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/meshy/meshy-6

This article will introduce how to use Meshy 6 node's API in ComfyUI for 3D model generation

Meshy is a leading AI-powered 3D generation platform that enables users to create high-quality 3D models from text prompts, images, or multi-view inputs. ComfyUI has now natively integrated the Meshy API, allowing you to conveniently use the related nodes for 3D model generation.

## About Meshy 6

Meshy 6 is the latest generation of Meshy's 3D model generation technology, featuring significant improvements in geometry quality, texture fidelity, and workflow efficiency.

**Model highlights:**

* **Smarter geometry**: Improved mesh topology with cleaner edges and more coherent structures
* **Higher texture fidelity**: Enhanced texture generation with better detail preservation and color accuracy
* **Faster workflows**: Optimized generation pipeline for quicker turnaround times
* **Multiple input modes**: Supports text-to-3D, image-to-3D, and multi-view to 3D generation
* **PBR support**: Generate physically-based rendering maps including metallic, roughness, and normal maps

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Text-to-Model Workflow

Generate 3D models directly from text descriptions using Meshy 6.

<Card title="Try on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_meshy_text_to_model&utm_source=docs">
  Run the text-to-model workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_meshy_text_to_model.json">
  Download the workflow JSON file for local use.
</Card>

## Image-to-Model Workflow

Convert 2D images into detailed 3D models with Meshy 6's image-to-3D capabilities.

<Card title="Try on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_meshy_image_to_model&utm_source=docs">
  Run the image-to-model workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_meshy_image_to_model.json">
  Download the workflow JSON file for local use.
</Card>

## Multi-view to Model Workflow

Generate 3D models from multiple view images for more accurate geometry and texture reconstruction.

<Card title="Try on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_meshy_multi_image_to_model&utm_source=docs">
  Run the multi-view workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_meshy_multi_image_to_model.json">
  Download the workflow JSON file for local use.
</Card>


# Moonvalley Partner Nodes Official ComfyUI Example
Source: https://docs.comfy.org/tutorials/partner-nodes/moonvalley/moonvalley-video-generation

This article introduces how to use Moonvalley Partner nodes for text-to-video, image-to-video, and video-to-video capabilities in ComfyUI.

<Warning>
  **Service unavailable**: The Moonvalley API service is no longer available. These nodes have been deprecated and may not function as expected.
</Warning>

<iframe title="ComfyUI Selection Toolbox New Features" />

Moonvalley Marey Realism v1.5 is an AI video generation model designed for cinematic-level creation. The model is **trained entirely with commercially licensed content**, ensuring **copyright compliance and commercial safety**.

## Product Highlights

* Exceptional prompt comprehension: Accurately interprets complex prompt instructions.
* Native 1080p HD quality: The training dataset is based on **1080P** videos, resulting in fine and detailed output.
* Realistic physics and dynamic performance: Precisely simulates physical motion models and natural dynamics, delivering professional-grade realism.
* Complex scene layering and advanced lighting effects: Supports foreground, midground, and background layering in complex scenes, with intelligent spatial relationship understanding.
* Production-level control features such as motion and pose transfer: Automatically generates realistic lighting for composite scenes.

Currently, Moonvalley-related Partner nodes are natively supported in ComfyUI. You can use the corresponding text-to-video, image-to-video, and video-to-video capabilities directly in ComfyUI.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Moonvalley Text-to-Video Workflow

### 1. Download the Workflow File

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/moonvalley/api_moonvalley_text_to_video.json">
  <p>Download the workflow file in JSON format</p>
</a>

### 2. Follow the Steps to Run the Workflow

<img alt="Text-to-Video Workflow" />

1. Enter the positive prompt (content you want to appear in the video)
2. Enter the negative prompt (content you do not want to appear in the video)
3. Modify the video output resolution
4. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to start video generation
5. After the API returns the result, you can view the generated video in the `Save Video` node. The video will also be saved in the `ComfyUI/output/` directory

## Moonvalley Image-to-Video Workflow

### 1. Download the Workflow File

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/moonvalley/api_moonvalley_image_to_video.json">
  <p>Download the workflow file in JSON format</p>
</a>

Download the image below as the input image

![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/moonvalley/api_moonvalley_image_to_video_input.webp)

### 2. Follow the Steps to Run the Workflow

<img alt="Image-to-Video Workflow" />

1. Load the input image in the `Load Image` node
2. Enter the positive prompt (content you want to appear in the video)
3. Enter the negative prompt (content you do not want to appear in the video)
4. Modify the video output resolution
5. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to start video generation
6. After the API returns the result, you can view the generated video in the `Save Video` node. The video will also be saved in the `ComfyUI/output/` directory

## Moonvalley Video-to-Video Workflow

The `Moonvalley Marey Video to Video` node allows you to input a reference video for video re-drawing. You can use the reference video's motion or character poses for video generation.

### 1. Download the Workflow File

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/moonvalley/api_moonvalley_video_to_video.json">
  <p>Download the workflow file in JSON format</p>
</a>

Download the video below as the input video:

<video />

### 2. Follow the Steps to Run the Workflow

<img alt="Video-to-Video Workflow" />

1. Load the reference video (or your own material) in the `Load Video` node
   * If the final video duration is 5s, the input video must be longer than 5s
   * If the final video duration is 10s, the input video must be longer than 10s
2. Enter the positive prompt (content you want to appear in the video)
3. Enter the negative prompt (content you do not want to appear in the video)
4. Set the `control_type` parameter to choose the reference type for video re-drawing
   * `Motion Transfer`: Generate based on the motion in the reference video
   * `Pose Transfer`: Generate based on the character poses in the reference video
5. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to start video generation
6. After the API returns the result, you can view the generated video in the `Save Video` node. The video will also be saved in the `ComfyUI/output/` directory


# OpenAI Chat Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/openai/chat

This article will introduce how to use OpenAI Chat Partner nodes in ComfyUI to complete conversational functions

OpenAI is a company focused on generative AI, providing powerful conversational capabilities. Currently, ComfyUI has integrated the OpenAI API, allowing you to directly use the related nodes in ComfyUI to complete conversational functions.

In this guide, we will walk you through completing the corresponding conversational functionality.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## OpenAI Chat Workflow

### 1. Workflow File Download

Please download the Json file below and drag it into ComfyUI to load the corresponding workflow.

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/openai/api_openai_chat.json">
  <p>Download Json Format Workflow File</p>
</a>

### 2. Complete the Workflow Execution Step by Step

<img alt="OpenAI Chat Step Guide" />

<Note>
  In the corresponding template, we have built a role setting for analyzing prompt generation.
</Note>

You can refer to the numbers in the image to complete the basic text-to-image workflow execution:

1. In the `Load Image` node, load the image you need AI to interpret
2. (Optional) If needed, you can modify the settings in `OpenAI Chat Advanced Options` to have AI execute specific tasks
3. In the `OpenAI Chat` node, you can modify `Prompt` to set the conversation prompt, or modify `model` to select different models
4. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute the conversation.
5. After waiting for the API to return results, you can view the corresponding AI returned content in the `Preview Any` node.

### 3. Additional Notes

* Currently, the file input node `OpenAI Chat Input Files` requires files to be uploaded to the `ComfyUI/input/` directory first. This node is being improved, and we will modify the template after updates
* The workflow provides an example using `Batch Images` for input. If you have multiple images that need AI interpretation, you can refer to the step diagram and use right-click to set the corresponding node mode to `Always` to enable it


# OpenAI DALL·E 2 Node
Source: https://docs.comfy.org/tutorials/partner-nodes/openai/dall-e-2

Learn how to use the OpenAI DALL·E 2 Partner node to generate images in ComfyUI

<img alt="OpenAI DALL·E 2 node screenshot" />

OpenAI DALL·E 2 is part of the ComfyUI Partner Nodes series, allowing users to generate images through OpenAI's **DALL·E 2** model.

This node supports:

* Text-to-image generation
* Image editing functionality (inpainting through masks)

## Node Overview

The **OpenAI DALL·E 2** node generates images synchronously through OpenAI's image generation API. It receives text prompts and returns images that match the description.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Parameter Description

### Required Parameters

| Parameter | Description                                                   |
| --------- | ------------------------------------------------------------- |
| `prompt`  | Text prompt describing the image content you want to generate |

### Widget Parameters

| Parameter | Description                                                                | Options/Range                     | Default Value |
| --------- | -------------------------------------------------------------------------- | --------------------------------- | ------------- |
| `seed`    | Seed value for image generation (currently not implemented in the backend) | 0 to 2^31-1                       | 0             |
| `size`    | Output image dimensions                                                    | "256x256", "512x512", "1024x1024" | "1024x1024"   |
| `n`       | Number of images to generate                                               | 1 to 8                            | 1             |

### Optional Parameters

| Parameter | Description                                | Options/Range   | Default Value |
| --------- | ------------------------------------------ | --------------- | ------------- |
| `image`   | Optional reference image for image editing | Any image input | None          |
| `mask`    | Optional mask for local inpainting         | Mask input      | None          |

## Usage Method

## Workflow Examples

This Partner node currently supports two workflows:

* Text to Image
* Inpainting

<Note>
  Image to Image workflow is not supported
</Note>

### Text to Image Example

The image below contains a simple text-to-image workflow. Please download the corresponding image and drag it into ComfyUI to load the workflow.
![ComfyUI openai-dall-e-2 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai-dall-e-2/text2image.png)

The corresponding example is very simple

<img alt="ComfyUI openai-dall-e-2 workflow example" />

You only need to load the `OpenAI DALL·E 2` node, input the description of the image you want to generate in the `prompt` node, connect a `Save Image` node, and then run the workflow.

### Inpainting Workflow

DALL·E 2 supports image editing functionality, allowing you to use a mask to specify the area to be replaced. Below is a simple inpainting workflow example:

#### 1. Workflow File Download

Download the image below and drag it into ComfyUI to load the corresponding workflow.

![ComfyUI openai-dall-e-2 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai-dall-e-2/inpainting.png)

We will use the image below as input:
![ComfyUI openai-dall-e-2 workflow input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai-dall-e-2/input.jpg)

#### 2. Workflow File Usage Instructions

<img alt="ComfyUI openai-dall-e-2 workflow example" />

Since this workflow is relatively simple, if you want to manually implement the corresponding workflow yourself, you can follow the steps below:

1. Use the `Load Image` node to load the image
2. Right-click on the load image node and select `MaskEditor`
3. In the mask editor, use the brush to draw the area you want to redraw
4. Connect the loaded image to the `image` input of the **OpenAI DALL·E 2** node
5. Connect the mask to the `mask` input of the **OpenAI DALL·E 2** node
6. Edit the prompt in the `prompt` node
7. Run the workflow

**Notes**

* If you want to use the image editing functionality, you must provide both an image and a mask (both are required)
* The mask and image must be the same size
* When inputting large images, the node will automatically resize the image to an appropriate size
* The URLs returned by the API are valid for a short period, please save the results promptly
* Each generation consumes credits, charged according to image size and quantity

## FAQs

<AccordionGroup>
  <Accordion title="Why can't I find the Partner Nodes?">
    Please update your ComfyUI to the latest version (the latest commit or the latest [desktop version](https://www.comfy.org/download)).
    We may add more API support in the future, and the corresponding nodes will be updated, so please keep your ComfyUI up to date.

    <Tip>
      Please note that you need to distinguish between the nightly version and the release version.
      In some cases, the latest `release` version may not be updated in time compared to the `nightly` version.
      Since we are still iterating quickly, please ensure you are using the latest version when you cannot find the corresponding node.
    </Tip>
  </Accordion>

  <Accordion title="Why can't I use / log in to the Partner Nodes?">
    API access requires that your current request is based on a secure network environment. The current requirements for API access are as follows:

    * The local network only allows access from `127.0.0.1` or `localhost`, which may mean that you cannot use the Partner Nodes in a ComfyUI service started with the `--listen` parameter in a LAN environment.
    * Able to access our API service normally (a proxy service may be required in some regions).
    * Your account does not have enough [credits](/interface/credits).
  </Accordion>

  <Accordion title="Why can't I use Partner Node even after logging in, or why does it keep asking me to log in while using?">
    * Currently, only `127.0.0.1` or `localhost` access is supported.
    * Ensure your account has enough credits.
  </Accordion>

  <Accordion title="Can Partner Nodes be used for free?">
    Partner Nodes require credits for API calls to closed-source models, so they do not support free usage.
  </Accordion>

  <Accordion title="How to purchase credits?">
    Please refer to the following documentation:

    1. [Comfy Account](/interface/user): Find the `User` section in the settings menu to log in.
    2. [Credits](/interface/credits): After logging in, the settings interface will show the credits menu. You can purchase credits in `Settings` → `Credits`. We use a prepaid system, so there will be no unexpected charges.
    3. Complete the payment through Stripe.
    4. Check if the credits have been updated. If not, try restarting or refreshing the page.
  </Accordion>

  <Accordion title="Are unused credits refundable?">
    Currently, we do not support refunds for credits.
    If you believe there is an error resulting in unused balance due to technical issues, please [contact support](mailto:support@comfy.org).
  </Accordion>

  <Accordion title="Can credits go negative?">
    Credits are not intended to be used as a negative balance or credit line. However, due to race conditions where partner nodes don't always report costs before execution, a single execution may consume more credits than your remaining balance and temporarily result in a negative balance after completion. When your balance is negative, you will not be able to run Partner Nodes until you top up and restore a positive balance. Please ensure you have enough credits before making API calls.
  </Accordion>

  <Accordion title="Where can I check usage and expenses?">
    Please visit the [Credits](/interface/credits) menu after logging in to check the corresponding credits.
  </Accordion>

  <Accordion title="Is it possible to use my own API Key?">
    Currently, the Partner Nodes are still in the testing phase and do not support this feature yet, but we have considered adding it.
  </Accordion>

  <Accordion title="Do credits expire?">
    Yes, the expiration depends on the type of credits:

    * **Monthly credits**: Expire at the end of your billing period
    * **Top-up credits**: Expire 1 year from the date of purchase
  </Accordion>

  <Accordion title="Can credits be transferred or shared?">
    No, your credits cannot be transferred to other users and are limited to the currently logged-in account, but we do not restrict the number of devices that can log in.
  </Accordion>

  <Accordion title="Can I use the same account on different devices?">
    We do not limit the number of devices that can log in; you can use your account anywhere you want.
  </Accordion>

  <Accordion title="How can I request for my account or information to be deleted??">
    Email a request to [support@comfy.org](mailto:support@comfy.org) and we will delete your information
  </Accordion>
</AccordionGroup>


# OpenAI DALL·E 3 Node
Source: https://docs.comfy.org/tutorials/partner-nodes/openai/dall-e-3

Learn how to use the OpenAI DALL·E 3 Partner node to generate images in ComfyUI

OpenAI DALL·E 3 is part of the ComfyUI Partner Nodes series, allowing users to generate images through OpenAI's **DALL·E 3** model. This node supports text-to-image generation functionality.

<img alt="OpenAI DALL·E 3 node screenshot" />

## Node Overview

DALL·E 3 is OpenAI's latest image generation model, capable of creating detailed and high-quality images based on text prompts. Through this node in ComfyUI, you can directly access DALL·E 3's generation capabilities without leaving the ComfyUI interface.

The **OpenAI DALL·E 3** node generates images synchronously through OpenAI's image generation API. It receives text prompts and returns images that match the description.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Parameter Details

### Required Parameters

| Parameter | Type | Description                                                                                                                  |
| --------- | ---- | ---------------------------------------------------------------------------------------------------------------------------- |
| prompt    | Text | Text prompt for generating images. Supports multi-line input, can describe in detail the image content you want to generate. |

### Widget Parameters

| Parameter | Type    | Options                         | Default Value | Description                                                                                                                               |
| --------- | ------- | ------------------------------- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------- |
| seed      | Integer | 0-2147483647                    | 0             | Random seed used to control the generation result                                                                                         |
| quality   | Option  | standard, hd                    | standard      | Image quality setting. The "hd" option generates higher quality images but may require more computational resources                       |
| style     | Option  | natural, vivid                  | natural       | Image style. "Vivid" tends to generate hyperrealistic and dramatic images, while "natural" produces more natural, less exaggerated images |
| size      | Option  | 1024x1024, 1024x1792, 1792x1024 | 1024x1024     | Size of the generated image. You can choose square or rectangular images in different orientations                                        |

## Usage Examples

You can download the image below and drag it into ComfyUI to load the corresponding workflow
![ComfyUI openai-dall-e-3 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai-dall-e-3/text2image.png)

Since the corresponding workflow is very simple, you can also directly add the **OpenAI DALL·E 3** node in ComfyUI, input the description of the image you want to generate, and then run the workflow

<img alt="ComfyUI openai-dall-e-3 workflow" />

1. Add the **OpenAI DALL·E 3** node in ComfyUI
2. Enter the description of the image you want to generate in the prompt text box
3. Adjust optional parameters as needed (quality, style, size, etc.)
4. Run the workflow to generate the image

## FAQs

<AccordionGroup>
  <Accordion title="Why can't I find the Partner Nodes?">
    Please update your ComfyUI to the latest version (the latest commit or the latest [desktop version](https://www.comfy.org/download)).
    We may add more API support in the future, and the corresponding nodes will be updated, so please keep your ComfyUI up to date.

    <Tip>
      Please note that you need to distinguish between the nightly version and the release version.
      In some cases, the latest `release` version may not be updated in time compared to the `nightly` version.
      Since we are still iterating quickly, please ensure you are using the latest version when you cannot find the corresponding node.
    </Tip>
  </Accordion>

  <Accordion title="Why can't I use / log in to the Partner Nodes?">
    API access requires that your current request is based on a secure network environment. The current requirements for API access are as follows:

    * The local network only allows access from `127.0.0.1` or `localhost`, which may mean that you cannot use the Partner Nodes in a ComfyUI service started with the `--listen` parameter in a LAN environment.
    * Able to access our API service normally (a proxy service may be required in some regions).
    * Your account does not have enough [credits](/interface/credits).
  </Accordion>

  <Accordion title="Why can't I use Partner Node even after logging in, or why does it keep asking me to log in while using?">
    * Currently, only `127.0.0.1` or `localhost` access is supported.
    * Ensure your account has enough credits.
  </Accordion>

  <Accordion title="Can Partner Nodes be used for free?">
    Partner Nodes require credits for API calls to closed-source models, so they do not support free usage.
  </Accordion>

  <Accordion title="How to purchase credits?">
    Please refer to the following documentation:

    1. [Comfy Account](/interface/user): Find the `User` section in the settings menu to log in.
    2. [Credits](/interface/credits): After logging in, the settings interface will show the credits menu. You can purchase credits in `Settings` → `Credits`. We use a prepaid system, so there will be no unexpected charges.
    3. Complete the payment through Stripe.
    4. Check if the credits have been updated. If not, try restarting or refreshing the page.
  </Accordion>

  <Accordion title="Are unused credits refundable?">
    Currently, we do not support refunds for credits.
    If you believe there is an error resulting in unused balance due to technical issues, please [contact support](mailto:support@comfy.org).
  </Accordion>

  <Accordion title="Can credits go negative?">
    Credits are not intended to be used as a negative balance or credit line. However, due to race conditions where partner nodes don't always report costs before execution, a single execution may consume more credits than your remaining balance and temporarily result in a negative balance after completion. When your balance is negative, you will not be able to run Partner Nodes until you top up and restore a positive balance. Please ensure you have enough credits before making API calls.
  </Accordion>

  <Accordion title="Where can I check usage and expenses?">
    Please visit the [Credits](/interface/credits) menu after logging in to check the corresponding credits.
  </Accordion>

  <Accordion title="Is it possible to use my own API Key?">
    Currently, the Partner Nodes are still in the testing phase and do not support this feature yet, but we have considered adding it.
  </Accordion>

  <Accordion title="Do credits expire?">
    Yes, the expiration depends on the type of credits:

    * **Monthly credits**: Expire at the end of your billing period
    * **Top-up credits**: Expire 1 year from the date of purchase
  </Accordion>

  <Accordion title="Can credits be transferred or shared?">
    No, your credits cannot be transferred to other users and are limited to the currently logged-in account, but we do not restrict the number of devices that can log in.
  </Accordion>

  <Accordion title="Can I use the same account on different devices?">
    We do not limit the number of devices that can log in; you can use your account anywhere you want.
  </Accordion>

  <Accordion title="How can I request for my account or information to be deleted??">
    Email a request to [support@comfy.org](mailto:support@comfy.org) and we will delete your information
  </Accordion>
</AccordionGroup>


# OpenAI GPT-Image-1 Node
Source: https://docs.comfy.org/tutorials/partner-nodes/openai/gpt-image-1

Learn how to use the OpenAI GPT-Image-1 Partner node to generate images in ComfyUI

<img alt="OpenAI GPT-Image-1 Node Screenshot" />

OpenAI GPT-Image-1 is part of the ComfyUI Partner nodes series that allows users to generate images through OpenAI's **GPT-Image-1** model. This is the same model used for image generation in ChatGPT 4o.

This node supports:

* Text-to-image generation
* Image editing functionality (inpainting through masks)

## Node Overview

The **OpenAI GPT-Image-1** node synchronously generates images through OpenAI's image generation API. It receives text prompts and returns images matching the description. GPT-Image-1 is OpenAI's most advanced image generation model currently available, capable of creating highly detailed and realistic images.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Parameter Description

### Required Parameters

| Parameter | Type | Description                                                   |
| --------- | ---- | ------------------------------------------------------------- |
| `prompt`  | Text | Text prompt describing the image content you want to generate |

### Widget Parameters

| Parameter    | Type    | Options                               | Default | Description                                             |
| ------------ | ------- | ------------------------------------- | ------- | ------------------------------------------------------- |
| `seed`       | Integer | 0-2147483647                          | 0       | Random seed used to control generation results          |
| `quality`    | Option  | low, medium, high                     | low     | Image quality setting, affects cost and generation time |
| `background` | Option  | opaque, transparent                   | opaque  | Whether the returned image has a background             |
| `size`       | Option  | auto, 1024x1024, 1024x1536, 1536x1024 | auto    | Size of the generated image                             |
| `n`          | Integer | 1-8                                   | 1       | Number of images to generate                            |

### Optional Parameters

| Parameter | Type  | Options         | Default | Description                                                 |
| --------- | ----- | --------------- | ------- | ----------------------------------------------------------- |
| `image`   | Image | Any image input | None    | Optional reference image for image editing                  |
| `mask`    | Mask  | Mask input      | None    | Optional mask for inpainting (white areas will be replaced) |

## Usage Examples

### Text-to-Image Example

The image below contains a simple text-to-image workflow. Please download the image and drag it into ComfyUI to load the corresponding workflow.
![ComfyUI openai-gpt-image-1 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/text2image.png)

The corresponding workflow is very simple:

<img alt="ComfyUI openai-gpt-image-1 workflow example" />

You only need to load the `OpenAI GPT-Image-1` node, input the description of the image you want to generate in the `prompt` node, connect a `Save Image` node, and then run the workflow.

### Image-to-Image Example

The image below contains a simple image-to-image workflow. Please download the image and drag it into ComfyUI to load the corresponding workflow.
![ComfyUI openai-gpt-image-1 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/image2image.png)

We will use the image below as input:
![ComfyUI openai-gpt-image-1 workflow input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/input.webp)

In this workflow, we use the `OpenAI GPT-Image-1` node to generate images and the `Load Image` node to load the input image, then connect it to the `image` input of the `OpenAI GPT-Image-1` node.

<img alt="ComfyUI openai-gpt-image-1 workflow example" />

### Multiple Image Input Example

Please download the image below and drag it into ComfyUI to load the corresponding workflow.

![Multiple Image Input Example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/multiple_image_input.png)

Use the hat image below as an additional input image.
![Hat](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/hat.webp)

The corresponding workflow is shown in the image below:

<img alt="Multiple Image Input Example" />

The `Batch Images` node is used to load multiple images into the `OpenAI GPT-Image-1` node.

### Inpainting Workflow

GPT-Image-1 also supports image editing functionality, allowing you to specify areas to replace using a mask. Below is a simple inpainting workflow example:

Download the image below and drag it into ComfyUI to load the corresponding workflow. We will continue to use the input image from the image-to-image workflow section.

![ComfyUI openai-gpt-image-1 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/GPT-Image-1/inpaint.png)

The corresponding workflow is shown in the image

<img alt="ComfyUI openai-gpt-image-1 workflow example" />

Compared to the image-to-image workflow, we use the MaskEditor in the `Load Image` node through the right-click menu to draw a mask, then connect it to the `mask` input of the `OpenAI GPT-Image-1` node to complete the workflow.

**Notes**

* The mask and image must be the same size
* When inputting large images, the node will automatically resize the image to an appropriate size

## FAQs

<AccordionGroup>
  <Accordion title="Why can't I find the Partner Nodes?">
    Please update your ComfyUI to the latest version (the latest commit or the latest [desktop version](https://www.comfy.org/download)).
    We may add more API support in the future, and the corresponding nodes will be updated, so please keep your ComfyUI up to date.

    <Tip>
      Please note that you need to distinguish between the nightly version and the release version.
      In some cases, the latest `release` version may not be updated in time compared to the `nightly` version.
      Since we are still iterating quickly, please ensure you are using the latest version when you cannot find the corresponding node.
    </Tip>
  </Accordion>

  <Accordion title="Why can't I use / log in to the Partner Nodes?">
    API access requires that your current request is based on a secure network environment. The current requirements for API access are as follows:

    * The local network only allows access from `127.0.0.1` or `localhost`, which may mean that you cannot use the Partner Nodes in a ComfyUI service started with the `--listen` parameter in a LAN environment.
    * Able to access our API service normally (a proxy service may be required in some regions).
    * Your account does not have enough [credits](/interface/credits).
  </Accordion>

  <Accordion title="Why can't I use Partner Node even after logging in, or why does it keep asking me to log in while using?">
    * Currently, only `127.0.0.1` or `localhost` access is supported.
    * Ensure your account has enough credits.
  </Accordion>

  <Accordion title="Can Partner Nodes be used for free?">
    Partner Nodes require credits for API calls to closed-source models, so they do not support free usage.
  </Accordion>

  <Accordion title="How to purchase credits?">
    Please refer to the following documentation:

    1. [Comfy Account](/interface/user): Find the `User` section in the settings menu to log in.
    2. [Credits](/interface/credits): After logging in, the settings interface will show the credits menu. You can purchase credits in `Settings` → `Credits`. We use a prepaid system, so there will be no unexpected charges.
    3. Complete the payment through Stripe.
    4. Check if the credits have been updated. If not, try restarting or refreshing the page.
  </Accordion>

  <Accordion title="Are unused credits refundable?">
    Currently, we do not support refunds for credits.
    If you believe there is an error resulting in unused balance due to technical issues, please [contact support](mailto:support@comfy.org).
  </Accordion>

  <Accordion title="Can credits go negative?">
    Credits are not intended to be used as a negative balance or credit line. However, due to race conditions where partner nodes don't always report costs before execution, a single execution may consume more credits than your remaining balance and temporarily result in a negative balance after completion. When your balance is negative, you will not be able to run Partner Nodes until you top up and restore a positive balance. Please ensure you have enough credits before making API calls.
  </Accordion>

  <Accordion title="Where can I check usage and expenses?">
    Please visit the [Credits](/interface/credits) menu after logging in to check the corresponding credits.
  </Accordion>

  <Accordion title="Is it possible to use my own API Key?">
    Currently, the Partner Nodes are still in the testing phase and do not support this feature yet, but we have considered adding it.
  </Accordion>

  <Accordion title="Do credits expire?">
    Yes, the expiration depends on the type of credits:

    * **Monthly credits**: Expire at the end of your billing period
    * **Top-up credits**: Expire 1 year from the date of purchase
  </Accordion>

  <Accordion title="Can credits be transferred or shared?">
    No, your credits cannot be transferred to other users and are limited to the currently logged-in account, but we do not restrict the number of devices that can log in.
  </Accordion>

  <Accordion title="Can I use the same account on different devices?">
    We do not limit the number of devices that can log in; you can use your account anywhere you want.
  </Accordion>

  <Accordion title="How can I request for my account or information to be deleted??">
    Email a request to [support@comfy.org](mailto:support@comfy.org) and we will delete your information
  </Accordion>
</AccordionGroup>


# OpenAI GPT-Image-2 Node
Source: https://docs.comfy.org/tutorials/partner-nodes/openai/gpt-image-2

Learn how to use the OpenAI GPT-Image-2 Partner node to generate images in ComfyUI

OpenAI GPT-Image-2 (`gpt-image-2`) is OpenAI's newest image model, available in ComfyUI through Partner Nodes. It is the first OpenAI image model that *reasons* before it generates: instead of one-shot sampling, the model plans the composition, checks its work, and iterates.

This node supports:

* Text-to-image generation with strong handling of dense text, UI elements, iconography, infographics, maps, slides, and manga panels
* Image editing with high structural fidelity at up to 2K resolution
* Up to 8 consistent images from a single prompt, preserving character and object continuity

## Node Overview

GPT-Image-2 is selected as a `model` option on the **OpenAI GPT Image 1.5** node in the Node Library. The node calls OpenAI's image generation API synchronously and returns images that match the description.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Getting Started

1. Update ComfyUI to the latest version (v0.19.4 or later), or use [Comfy Cloud](https://links.comfy.org/4u4o7Pv).
2. In the Node Library, search for **OpenAI GPT Image 1.5** and add the node.
3. Set the `model` field to `gpt-image-2`.

## Available workflows

### Text to image (T2I)

Generate an image from a text prompt with GPT-Image-2's reasoning-driven composition.

<Card title="Run Text-to-Image on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openai_gpt_image_2_t2i&utm_source=docs">
  Try the Text-to-Image workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Text-to-Image workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openai_gpt_image_2_t2i.json">
  Download the workflow JSON.
</Card>

![GPT-Image-2 Text-to-Image example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/gpt_image_2_t2i_1.jpg)

### Image edit

Edit an input image with high structural fidelity at up to 2K resolution.

<Card title="Run Image Edit on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openai_gpt_image_2_image_edit&utm_source=docs">
  Try the Image Edit workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Image Edit workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openai_gpt_image_2_image_edit.json">
  Download the workflow JSON.
</Card>

![GPT-Image-2 Image-to-Image example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/gpt_image_2_i2i_1.jpg)

![GPT-Image-2 Image Edit example 1](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/gpt_image_2_image_edit_1.jpg)

![GPT-Image-2 Image Edit example 2](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/gpt_image_2_image_edit_2.jpg)

## Key Capabilities

### Reasoning-driven generation

GPT-Image-2 plans the composition before rendering. This makes it well suited for prompts that have historically broken image models — for example, a poster with a seven-item bulleted list in 11pt Helvetica, centered — and produces clean output for dense text, small UI elements, iconography, infographics, maps, and slides.

### Image editing that preserves what matters

GPT-Image-2 handles targeted edits with structural fidelity, keeping everything outside the edit zone pixel-stable while applying the requested change cleanly at up to 2K resolution. Use it for tasks like colorizing black-and-white photos or shifting a scene from noon to dusk without warping faces, geometry, or fine detail.

### Up to eight consistent images per prompt

The model can return up to **eight distinct images from a single prompt** while preserving character and object continuity across the series. This is useful for storyboarding, reference sheets, character turnarounds, and product variants without seed-locking or prompt gymnastics. Feed the batch straight into a `Save Image` node or chain it into a video workflow downstream.

![GPT-Image-2 consistent images example](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/openai/gpt_image_2/consistent_example.jpg)

## Hybrid Pipelines

GPT-Image-2 slots naturally into hybrid pipelines: use it for the text-heavy hero frame, then hand off to your local models for upscaling, stylization, or video generation — the best model for each step, in one graph.


# OpenRouter LLM Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/openrouter/llm

Use the OpenRouter LLM partner node in ComfyUI for chat, reasoning, vision, and web-grounded answers across multiple frontier models.

[OpenRouter](https://openrouter.ai) is a unified routing platform for large language models. It exposes many providers through one API so you can switch models without changing your integration. ComfyUI connects through the **OpenRouter LLM** partner node, which offers a curated list of text and multimodal models—Claude, GPT, Gemini, Grok, DeepSeek, Qwen, Mistral, GLM, Kimi, and Perplexity Sonar—in a single node.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## What you can do

* **Text chat** — prompts and optional `system_prompt` for role or task instructions
* **Vision** — attach reference images on supported models (slot count depends on the model)
* **Video input** — Gemini 3.5 Flash and Qwen 3.6 Plus/Flash support optional reference videos
* **Reasoning** — `reasoning_effort` on reasoning / frontier-reasoning models (`off`, `low`, `medium`, `high`)
* **Web search** — Perplexity Sonar models expose `search_context_size` for grounded answers

Token pricing is listed under [Partner Node Pricing](/tutorials/partner-nodes/pricing#openrouter).

## Supported models

| Model                            | Vision (max images) | Video   | Extra options                         |
| :------------------------------- | :------------------ | :------ | :------------------------------------ |
| `anthropic/claude-opus-4.7`      | 20                  | —       | Reasoning effort                      |
| `openai/gpt-5.5-pro`             | 20                  | —       | Reasoning effort                      |
| `openai/gpt-5.5`                 | 20                  | —       | Reasoning effort                      |
| `google/gemini-3.5-flash`        | 20                  | Up to 4 | Reasoning effort                      |
| `x-ai/grok-4.20`                 | 20                  | —       | Reasoning effort                      |
| `x-ai/grok-4.3`                  | 20                  | —       | Reasoning effort                      |
| `deepseek/deepseek-v4-pro`       | —                   | —       | Reasoning effort                      |
| `deepseek/deepseek-v4-flash`     | —                   | —       | Reasoning effort                      |
| `deepseek/deepseek-v3.2`         | —                   | —       | Reasoning effort                      |
| `qwen/qwen3.6-max-preview`       | —                   | —       | Reasoning effort                      |
| `qwen/qwen3.6-plus`              | 10                  | Up to 4 | Reasoning effort                      |
| `qwen/qwen3.6-flash`             | 10                  | Up to 4 | Reasoning effort                      |
| `mistralai/mistral-large-2512`   | 8                   | —       | —                                     |
| `mistralai/mistral-medium-3-5`   | 8                   | —       | Reasoning effort                      |
| `z-ai/glm-4.6`                   | —                   | —       | Reasoning effort                      |
| `z-ai/glm-5`                     | —                   | —       | Reasoning effort                      |
| `moonshotai/kimi-k2.6`           | 10                  | —       | Reasoning effort                      |
| `moonshotai/kimi-k2-thinking`    | —                   | —       | Reasoning effort                      |
| `perplexity/sonar-pro`           | —                   | —       | Search context size                   |
| `perplexity/sonar-reasoning-pro` | —                   | —       | Search context size, reasoning effort |
| `perplexity/sonar-deep-research` | —                   | —       | Search context size, reasoning effort |

## Model-specific inputs

The **model** dropdown is a dynamic combo. When you change the model, the node updates which inputs appear:

* **Image slots** — shown only for vision-capable models; the number of slots matches the model limit
* **Video slots** — shown only on Gemini 3.5 Flash and Qwen 3.6 Plus/Flash
* **Reasoning effort** — shown on reasoning and frontier-reasoning models
* **Search context size** — shown on Perplexity Sonar models

Text-only models hide image and video inputs.

## Example workflow (`api_openrouter_llm`)

The template below is **one example**, not the only way to use the node. Download it to see how inputs connect, then adapt the graph for your task—pure text chat, captioning, prompt rewriting, feeding strings into image nodes, or anything else that fits your pipeline.

<Card title="Run in Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_openrouter_llm&utm_source=docs&utm_medium=referral&utm_campaign=openrouter_llm">
  Open in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openrouter_llm.json">
  Download JSON or search "OpenRouter LLM" in Template Library
</Card>

<Note>
  In this sample, the workflow analyzes a reference image and returns a text-to-image prompt for downstream image nodes. You can omit **Load Image**, change the prompts, or rebuild the graph entirely for your own use case.
</Note>

If you use the template as a reference, a typical run looks like this:

1. In **Load Image**, load the reference image (skip for text-only chat)
2. In **OpenRouter LLM**, connect the image to `image_1` (more slots appear when the model supports them)
3. Set **prompt** — e.g. ask the model to analyze the image and output a generation prompt
4. (Optional) Set **system\_prompt** in advanced options for tone, format, or constraints
5. Pick a **model**; adjust **reasoning\_effort** or **search\_context\_size** when shown
6. Click **Run** or press `Ctrl(cmd) + Enter`
7. View the reply in **Preview Any**

### Additional notes

* **seed** — set to `0` to omit; most models treat it as a hint only
* Reference images and videos are uploaded automatically when the workflow runs; you only wire ComfyUI image/video outputs into the node
* For pricing per model, see [OpenRouter on the pricing page](/tutorials/partner-nodes/pricing#openrouter)


# Partner Nodes
Source: https://docs.comfy.org/tutorials/partner-nodes/overview

In this article, we will introduce ComfyUI's Partner Nodes and related information.

Partner Nodes are ComfyUI's new way of calling closed-source models through API requests, providing ComfyUI users with access to external state-of-the-art AI models without complex API key setup.

## What are Partner Nodes?

Partner Nodes are a set of special nodes that connect to external API services, allowing you to use closed-source or third-party hosted AI models directly in your ComfyUI workflows. These nodes are designed to seamlessly integrate the capabilities of external models while maintaining the open-source nature of ComfyUI's core.

## Prerequisites for Using Partner Nodes

To use Partner Nodes, the following requirements must be met:

### 1. ComfyUI Version Requirements

Please update your ComfyUI to the latest version, as we may add more API support in the future, and corresponding nodes will be updated, so please keep your ComfyUI up to date.

<Tip>
  Please note the distinction between nightly and release versions. We recommend using the `nightly` version (which is the latest code commit), as the release version may not be updated in a timely manner.
  This refers to the development version and the stable version, and since we are still rapidly iterating, this document may not be updated promptly, so please pay attention to the version differences.
</Tip>

### 2. Account and Credits Requirements

You need to be logged into your ComfyUI with a [Comfy account](/interface/user) and have a credit balance of [credits](/interface/credits) greater than 0.

Log in via `Settings` -> `User`:

<img alt="ComfyUI User Interface" />

Go to `Settings` -> `Credits` to purchase credits

<img alt="Credits Interface" />

Please refer to the corresponding documentation for account and credits to ensure this requirement:

* [Comfy account](/interface/user): Find the `User` section in the settings menu to log in.
* [Credits](/interface/credits): After logging in, the settings interface will show a credits menu where you can purchase credits. We use a prepaid system, so there will be no unexpected charges.

### 3. Network Environment Requirements

API access requires that your current requests are based on a secure network environment. The current requirements for API access are as follows:

* The local network only allows access from `127.0.0.1` or `localhost`, and you can directly use the login function.
* If you are accessing from a local area network or a website that is not on the whitelist, please log in with an API Key. Please refer to [Log in with an API Key](/interface/user#logging-in-with-an-api-key).
* You should be able to access our API service normally (in some regions, you may need to use a proxy service).
* Access should be carried out in an `https` environment to ensure the security of the requests.

<Note>
  Accessing in an insecure context poses significant risks, which may result in the following consequences:

  1. Authentication may be stolen, leading to the leakage of your account information.
  2. Your account may be maliciously used, resulting in financial losses.

  Even if we open this restriction in the future, we strongly advise against accessing API services through insecure network requests due to the high risks involved.
</Note>

### 4. Using the Corresponding Nodes

**Add to Workflow**: Add the Partner Node to your workflow just like you would with other nodes.
**Run**: Set the parameters and then run the workflow.

<img alt="Partner Nodes" />

## Log in with ComfyUI Account API Key on non-whitelisted websites

Currently, we have set up a whitelist to restrict the websites where you can log in to your ComfyUI account.
If you need to log in to your ComfyUI account on some non-whitelisted websites, please refer to the account management section to learn how to log in using an API Key.
In this case, the corresponding website does not need to be on our whitelist.

<Card title="Account Management" icon="book" href="/interface/user#logging-in-with-an-api-key">
  Learn how to log in with ComfyUI Account API Key
</Card>

<img alt="Select Comfy API Key Login" />

## Use ComfyUI Account API Key Integration to call paid model Partner nodes

Currently, we support accessing our services through ComfyUI API Key Integration to call paid model Partner nodes. Please refer to the API Key Integration section to learn how to use API Key Integration to call paid model Partner nodes.

<Note>
  **Important:** The API key discussed here is your **ComfyUI Account API Key** (used for accessing paid Partner nodes in workflows). This is **NOT** the same as the **Registry Publishing API Key** used by developers to publish custom nodes to the registry. If you're looking to publish custom nodes, see [Publishing Nodes](/registry/publishing).
</Note>

<Card title="API Key Integration" icon="link" href="/development/comfyui-server/api-key-integration">
  Please refer to the API Key Integration section to learn how to use API Key Integration to call paid model Partner nodes
</Card>

## Advantages of Partner Nodes

Partner Nodes provide several important advantages for ComfyUI users:

* **Access to closed-source models**: Use state-of-the-art AI models without having to deploy them yourself
* **Seamless integration**: Partner nodes are fully compatible with other ComfyUI nodes and can be combined to create complex workflows
* **Simplified experience**: No need to manage API keys or handle complex API requests
* **Controlled costs**: The prepaid system ensures you have complete control over your spending with no unexpected charges

## Pricing

<Card title="Partner Node Pricing" icon="coin" href="/tutorials/partner-nodes/pricing">
  Please refer to the pricing page for the corresponding Partner pricing
</Card>

## About Open Source and Opt-in

It's important to note that **Partner Nodes are completely optional**. ComfyUI will always remain fully open-source and free for local users. Partner nodes are designed as an "opt-in" feature, providing convenience for those who want access to external SOTA (state-of-the-art) models.

## How to disable partner nodes completely

You can add the `--disable-api-nodes` launch argument to disable all partner nodes in ComfyUI. This argument will also prevent the frontend from communicating with the internet.

**For manual install:**

```bash theme={null}
python main.py --disable-api-nodes
```

**For portable users (Windows):**

Update your `run_xxx.bat` file:

```batch theme={null}
.\python_embeded\python.exe -s ComfyUI\main.py --listen --windows-standalone-build --disable-api-nodes
pause
```

## Use Cases

A powerful application of Partner Nodes is combining the output of external models with local nodes. For example:

* Using GPT-Image-1 to generate a base image, then transforming it into video with a local `wan` node
* Combining externally generated images with local upscaling or style transfer nodes
* Creating hybrid workflows that leverage the advantages of both closed-source and open-source models

This flexibility makes ComfyUI a truly universal generative AI interface, integrating various AI capabilities into a unified workflow, opening up more possibilities

## FAQs

<AccordionGroup>
  <Accordion title="Why can't I find the Partner Nodes?">
    Please update your ComfyUI to the latest version (the latest commit or the latest [desktop version](https://www.comfy.org/download)).
    We may add more API support in the future, and the corresponding nodes will be updated, so please keep your ComfyUI up to date.

    <Tip>
      Please note that you need to distinguish between the nightly version and the release version.
      In some cases, the latest `release` version may not be updated in time compared to the `nightly` version.
      Since we are still iterating quickly, please ensure you are using the latest version when you cannot find the corresponding node.
    </Tip>
  </Accordion>

  <Accordion title="Why can't I use / log in to the Partner Nodes?">
    API access requires that your current request is based on a secure network environment. The current requirements for API access are as follows:

    * The local network only allows access from `127.0.0.1` or `localhost`, which may mean that you cannot use the Partner Nodes in a ComfyUI service started with the `--listen` parameter in a LAN environment.
    * Able to access our API service normally (a proxy service may be required in some regions).
    * Your account does not have enough [credits](/interface/credits).
  </Accordion>

  <Accordion title="Why can't I use Partner Node even after logging in, or why does it keep asking me to log in while using?">
    * Currently, only `127.0.0.1` or `localhost` access is supported.
    * Ensure your account has enough credits.
  </Accordion>

  <Accordion title="Can Partner Nodes be used for free?">
    Partner Nodes require credits for API calls to closed-source models, so they do not support free usage.
  </Accordion>

  <Accordion title="How to purchase credits?">
    Please refer to the following documentation:

    1. [Comfy Account](/interface/user): Find the `User` section in the settings menu to log in.
    2. [Credits](/interface/credits): After logging in, the settings interface will show the credits menu. You can purchase credits in `Settings` → `Credits`. We use a prepaid system, so there will be no unexpected charges.
    3. Complete the payment through Stripe.
    4. Check if the credits have been updated. If not, try restarting or refreshing the page.
  </Accordion>

  <Accordion title="Are unused credits refundable?">
    Currently, we do not support refunds for credits.
    If you believe there is an error resulting in unused balance due to technical issues, please [contact support](mailto:support@comfy.org).
  </Accordion>

  <Accordion title="Can credits go negative?">
    Credits are not intended to be used as a negative balance or credit line. However, due to race conditions where partner nodes don't always report costs before execution, a single execution may consume more credits than your remaining balance and temporarily result in a negative balance after completion. When your balance is negative, you will not be able to run Partner Nodes until you top up and restore a positive balance. Please ensure you have enough credits before making API calls.
  </Accordion>

  <Accordion title="Where can I check usage and expenses?">
    Please visit the [Credits](/interface/credits) menu after logging in to check the corresponding credits.
  </Accordion>

  <Accordion title="Is it possible to use my own API Key?">
    Currently, the Partner Nodes are still in the testing phase and do not support this feature yet, but we have considered adding it.
  </Accordion>

  <Accordion title="Do credits expire?">
    Yes, the expiration depends on the type of credits:

    * **Monthly credits**: Expire at the end of your billing period
    * **Top-up credits**: Expire 1 year from the date of purchase
  </Accordion>

  <Accordion title="Can credits be transferred or shared?">
    No, your credits cannot be transferred to other users and are limited to the currently logged-in account, but we do not restrict the number of devices that can log in.
  </Accordion>

  <Accordion title="Can I use the same account on different devices?">
    We do not limit the number of devices that can log in; you can use your account anywhere you want.
  </Accordion>

  <Accordion title="How can I request for my account or information to be deleted??">
    Email a request to [support@comfy.org](mailto:support@comfy.org) and we will delete your information
  </Accordion>
</AccordionGroup>


# Pricing
Source: https://docs.comfy.org/tutorials/partner-nodes/pricing

This article lists the pricing of the current Partner Nodes. All prices are in credits (211 credits = 1 USD).

The following table lists the pricing of the current Partner Nodes. All prices are in credits.

211 credits = 1 USD

## Beeble

| Product Name | Configuration                                          | Credits           | Category |
| :----------- | :----------------------------------------------------- | :---------------- | :------- |
| SwitchX      | model: switchx, output\_type: video, resolution: 720p  | 30.17 / 30 frames | Video    |
| SwitchX      | model: switchx, output\_type: video, resolution: 1080p | 90.52 / 30 frames | Video    |
| SwitchX      | model: switchx, output\_type: image, resolution: 720p  | 30.17 / run       | Image    |
| SwitchX      | model: switchx, output\_type: image, resolution: 1080p | 90.52 / run       | Image    |

## BFL

| Model               | Credits                       | Category |
| :------------------ | :---------------------------- | :------- |
| flux-dev            | 5.28 / run                    | Image    |
| flux-kontext-max    | 16.88 / run                   | Image    |
| flux-kontext-pro    | 8.44 / run                    | Image    |
| flux-pro-1.0-canny  | 10.55 / run                   | Image    |
| flux-pro-1.0-depth  | 10.55 / run                   | Image    |
| flux-pro-1.0-expand | 10.55 / run                   | Image    |
| flux-pro-1.0-fill   | 10.55 / run                   | Image    |
| flux-tools/erase-v1 | 6.33 / run + 0.84 / extra MP  | Image    |
| flux-tools/vto-v1   | 7.91 / run + 1.06 / extra MP  | Image    |
| flux-pro-1.1        | 8.44 / run                    | Image    |
| flux-pro-1.1-ultra  | 12.66 / run                   | Image    |
| /v1/flux-pro        | 10.55 / run                   | Image    |
| flux-2-pro          | 6.33 / run + 3.17 / extra MP  | Image    |
| flux-2-max          | 14.77 / run + 6.33 / extra MP | Image    |

## Anthropic

Anthropic partner nodes bill the same underlying USD usage as the public Anthropic API. **Credits = USD × 211** (see page header). Token prices below are per million tokens. Cache pricing multipliers match Anthropic's prompt caching documentation.

### Chat (`ClaudeNode`)

Models: per 1M tokens.

| Model                        | Input credits / 1M | 5m Cache Write credits / 1M | 1h Cache Write credits / 1M | Cache Hit credits / 1M | Output credits / 1M |
| :--------------------------- | -----------------: | --------------------------: | --------------------------: | ---------------------: | ------------------: |
| `claude-opus-4-7`            |               1055 |                     1318.75 |                        2110 |                  105.5 |                5275 |
| `claude-opus-4-6`            |               1055 |                     1318.75 |                        2110 |                  105.5 |                5275 |
| `claude-opus-4-5-20251101`   |               1055 |                     1318.75 |                        2110 |                  105.5 |                5275 |
| `claude-opus-4-1-20250805`   |               3165 |                     3956.25 |                        6330 |                  316.5 |               15825 |
| `claude-sonnet-4-6`          |                633 |                      791.25 |                        1266 |                   63.3 |                3165 |
| `claude-sonnet-4-5-20250929` |                633 |                      791.25 |                        1266 |                   63.3 |                3165 |
| `claude-haiku-4-5-20251001`  |                211 |                      263.75 |                         422 |                   21.1 |                1055 |

Optional images add tokens billed at the same model input rates.

## Bria

| Product Name                 | Configuration                              | Credits     | Category |
| :--------------------------- | :----------------------------------------- | :---------- | :------- |
| Bria Image Edit              | endpoint: v2/image/edit, model: fibo       | 8.44 / run  | Image    |
| Bria Image Remove Background | endpoint: v2/image/edit/remove\_background | 3.8 / run   | Image    |
| Bria Video Remove Background | endpoint: v2/video/edit/remove\_background | 29.54 / sec | Video    |

## ByteDance

| Product Name                                         | Configuration                                                                                                     | Credits           | Category |
| :--------------------------------------------------- | :---------------------------------------------------------------------------------------------------------------- | :---------------- | :------- |
| BytePlus Seed Input Text Tokens (Per 1M tokens)      | model: seed-2-0-pro-260328                                                                                        | 105.5 / 1M tokens | Text     |
| BytePlus Seed Input Text Tokens (Per 1M tokens)      | model: seed-2-0-lite-260228                                                                                       | 52.75 / 1M tokens | Text     |
| BytePlus Seed Input Text Tokens (Per 1M tokens)      | model: seed-2-0-mini-260215                                                                                       | 21.1 / 1M tokens  | Text     |
| BytePlus Seed Output Text Tokens (Per 1M tokens)     | model: seed-2-0-pro-260328                                                                                        | 633 / 1M tokens   | Text     |
| BytePlus Seed Output Text Tokens (Per 1M tokens)     | model: seed-2-0-lite-260228                                                                                       | 422 / 1M tokens   | Text     |
| BytePlus Seed Output Text Tokens (Per 1M tokens)     | model: seed-2-0-mini-260215                                                                                       | 84.4 / 1M tokens  | Text     |
| BytePlus Seed Cache Hit Input Tokens (Per 1M tokens) | model: seed-2-0-pro-260328                                                                                        | 21.1 / 1M tokens  | Text     |
| BytePlus Seed Cache Hit Input Tokens (Per 1M tokens) | model: seed-2-0-lite-260228                                                                                       | 10.55 / 1M tokens | Text     |
| BytePlus Seed Cache Hit Input Tokens (Per 1M tokens) | model: seed-2-0-mini-260215                                                                                       | 4.22 / 1M tokens  | Text     |
| BytePlus Image Generation Product                    | model: seededit-3-0-i2i-250628                                                                                    | 6.33 / run        | Image    |
| BytePlus Image Generation Product                    | model: seedream-3-0-t2i-250415                                                                                    | 6.33 / run        | Image    |
| BytePlus Image Generation Product                    | model: seedream-4-0-250828                                                                                        | 6.33 / run        | Image    |
| BytePlus Image Generation Product                    | model: seedream-4-5-251128                                                                                        | 8.44 / run        | Image    |
| BytePlus Image Generation Product                    | model: seedream-5-0-260128                                                                                        | 7.39 / run        | Image    |
| BytePlus Video Generation Product (Per 1M tokens)    | model: seedance-1-0-lite-i2v-250428, video\_type: image-to-video                                                  | 379.8 / 1M tokens | Video    |
| BytePlus Video Generation Product (Per 1M tokens)    | model: seedance-1-0-lite-t2v-250428, video\_type: text-to-video                                                   | 379.8 / 1M tokens | Video    |
| BytePlus Video Generation Product (Per 1M tokens)    | model: seedance-1-0-pro-250528, video\_type: image-to-video                                                       | 527.5 / 1M tokens | Video    |
| BytePlus Video Generation Product (Per 1M tokens)    | model: seedance-1-0-pro-250528, video\_type: text-to-video                                                        | 527.5 / 1M tokens | Video    |
| BytePlus Video Generation Product (Per 1M tokens)    | model: seedance-1-0-pro-fast-251015, video\_type: image-to-video                                                  | 211 / 1M tokens   | Video    |
| BytePlus Video Generation Product (Per 1M tokens)    | model: seedance-1-0-pro-fast-251015, video\_type: text-to-video                                                   | 211 / 1M tokens   | Video    |
| BytePlus Video Generation Product (Per 1M tokens)    | model: seedream-4-5-251128, video\_type: text-to-video                                                            | 211 / 1M tokens   | Video    |
| BytePlus Video Generation With Audio (Per 1M tokens) | generate\_audio: false, model: seedance-1-5-pro-251215                                                            | 253.2 / 1M tokens | Video    |
| BytePlus Video Generation With Audio (Per 1M tokens) | generate\_audio: true, model: seedance-1-5-pro-251215                                                             | 506.4 / 1M tokens | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0, resolution: 720P, video\_type: text-to-video (no video input: text or image)        | 2.112 / K tokens  | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0, resolution: 720P, video\_type: image-to-video (no video input: text or image)       | 2.112 / K tokens  | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0, resolution: 720P, video\_type: video-to-video (with video input)                    | 1.297 / K tokens  | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0, resolution: 1080P, video\_type: text-to-video (no video input: text or image)       | 5.281 / K tokens  | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0, resolution: 1080P, video\_type: image-to-video (no video input: text or image)      | 5.281 / K tokens  | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0, resolution: 1080P, video\_type: video-to-video (with video input)                   | 3.243 / K tokens  | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0-fast, resolution: 720P, video\_type: text-to-video (no video input: text or image)   | 1.690 / K tokens  | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0-fast, resolution: 720P, video\_type: image-to-video (no video input: text or image)  | 1.690 / K tokens  | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0-fast, resolution: 720P, video\_type: video-to-video (with video input)               | 0.995 / K tokens  | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0-fast, resolution: 1080P, video\_type: text-to-video (no video input: text or image)  | 4.226 / K tokens  | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0-fast, resolution: 1080P, video\_type: image-to-video (no video input: text or image) | 4.226 / K tokens  | Video    |
| BytePlus Video Generation Product (Per K tokens)     | model: dreamina-seedance-2-0-fast, resolution: 1080P, video\_type: video-to-video (with video input)              | 2.488 / K tokens  | Video    |

> **Seedance 2.0 token calculation:** Output tokens = (Input video duration + Output video duration) × Output video length × Output video width × Output video frame rate ÷ 1024. When input is text, image, or audio, input duration = 0. Seedance 2.0 outputs at 24fps. For video-to-video inputs, a minimum token usage limit applies. **Per‑K token credits** depend on output resolution: **1080P is 2.5× the 720P rate** for the same model and `video_type`.

## ElevenLabs

| Product Name                           | Configuration                                                | Credits     | Category |
| :------------------------------------- | :----------------------------------------------------------- | :---------- | :------- |
| 11labs Text-to-Speech                  | endpoint: v1/text-to-dialogue, model: eleven\_v3             | 50.64 / run | Audio    |
| 11labs Text-to-Speech                  | endpoint: v1/text-to-speech, model: eleven\_multilingual\_v2 | 50.64 / run | Audio    |
| 11labs Text-to-Speech                  | endpoint: v1/text-to-speech, model: eleven\_v3               | 50.64 / run | Audio    |
| 11labs Speech-to-Text                  | endpoint: v1/speech-to-text, model: scribe\_v2               | 92.84 / run | Audio    |
| 11labs Speech-to-Text Keyterm          | endpoint: v1/speech-to-text, model: scribe\_v2               | 18.57 / run | Audio    |
| 11labs Speech-to-Text Entity Detection | endpoint: scribe\_v2, model: v1/speech-to-text               | 27.85 / run | Audio    |
| 11labs Speech-to-Speech Per Minute     | endpoint: v1/speech-to-speech                                | 50.64 / min | Audio    |
| 11labs Sound Generation Per Minute     | endpoint: v1/sound-generation                                | 29.54 / min | Audio    |
| 11labs Audio Isolation Per Minute      | endpoint: v1/audio-isolation                                 | 50.64 / min | Audio    |
| 11labs Add Voice                       | endpoint: v1/voices/add                                      | 31.65 / run | Audio    |

## Freepik

| Product Name                 | Configuration                     | Credits     | Category |
| :--------------------------- | :-------------------------------- | :---------- | :------- |
| Freepik Image Per Generation | endpoint: magnific-relight        | 23.21 / run | Image    |
| Freepik Image Per Generation | endpoint: magnific-style-transfer | 23.21 / run | Image    |
| Freepik Image Per Generation | endpoint: skin-enhancer-creative  | 61.19 / run | Image    |
| Freepik Image Per Generation | endpoint: skin-enhancer-faithful  | 78.07 / run | Image    |
| Freepik Image Per Generation | endpoint: skin-enhancer-flexible  | 94.95 / run | Image    |
| Freepik Image Cost           | NA                                | 211 / run   | Image    |

## Google

| Product Name                                | Configuration                                              | Credits            | Category |
| :------------------------------------------ | :--------------------------------------------------------- | :----------------- | :------- |
| prod-v1-Veo 2 Product                       | model: veo-2.0-generate-001                                | 105.5 / run        | Image    |
| prod-v1-Veo 2 Product                       | model: veo-3.0-generate-preview                            | 158.25 / run       | Image    |
| Gemini Input Text Tokens (per 1M) Product   | model: gemini-2.5-flash-image                              | 63.3 / 1M tokens   | Text     |
| Gemini Input Text Tokens (per 1M) Product   | model: gemini-2.5-flash-image-preview                      | 63.3 / 1M tokens   | Text     |
| Gemini Input Text Tokens (per 1M) Product   | model: gemini-2.5-flash                                    | 63.3 / 1M tokens   | Text     |
| Gemini Input Text Tokens (per 1M) Product   | model: gemini-2.5-flash-preview-04-17                      | 63.3 / 1M tokens   | Text     |
| Gemini Input Text Tokens (per 1M) Product   | model: gemini-2.5-pro                                      | 263.75 / 1M tokens | Text     |
| Gemini Input Text Tokens (per 1M) Product   | model: gemini-2.5-pro-preview-05-06                        | 263.75 / 1M tokens | Text     |
| Gemini Input Text Tokens (per 1M) Product   | model: gemini-3.1-flash-image-preview                      | 105.5 / 1M tokens  | Text     |
| Gemini Input Text Tokens (per 1M) Product   | model: gemini-3.1-pro-preview                              | 422 / 1M tokens    | Text     |
| Gemini Input Text Tokens (per 1M) Product   | model: gemini-3-pro-image-preview                          | 422 / 1M tokens    | Text     |
| Gemini Input Text Tokens (per 1M) Product   | model: gemini-3-pro-preview                                | 422 / 1M tokens    | Text     |
| Gemini Output Text Tokens (per 1M) Product  | model: gemini-2.5-flash-image                              | 527.5 / 1M tokens  | Text     |
| Gemini Output Text Tokens (per 1M) Product  | model: gemini-2.5-flash-image-preview                      | 527.5 / 1M tokens  | Text     |
| Gemini Output Text Tokens (per 1M) Product  | model: gemini-2.5-flash                                    | 527.5 / 1M tokens  | Text     |
| Gemini Output Text Tokens (per 1M) Product  | model: gemini-2.5-flash-preview-04-17                      | 527.5 / 1M tokens  | Text     |
| Gemini Output Text Tokens (per 1M) Product  | model: gemini-2.5-pro                                      | 2110 / 1M tokens   | Text     |
| Gemini Output Text Tokens (per 1M) Product  | model: gemini-2.5-pro-preview-05-06                        | 2110 / 1M tokens   | Text     |
| Gemini Output Text Tokens (per 1M) Product  | model: gemini-3.1-flash-image-preview                      | 633 / 1M tokens    | Text     |
| Gemini Output Text Tokens (per 1M) Product  | model: gemini-3.1-pro-preview                              | 2532 / 1M tokens   | Text     |
| Gemini Output Text Tokens (per 1M) Product  | model: gemini-3-pro-image-preview                          | 2532 / 1M tokens   | Text     |
| Gemini Output Text Tokens (per 1M) Product  | model: gemini-3-pro-preview                                | 2532 / 1M tokens   | Text     |
| Gemini Input Image Tokens (per 1M) Product  | model: gemini-2.5-flash-image                              | 63.3 / 1M tokens   | Image    |
| Gemini Input Image Tokens (per 1M) Product  | model: gemini-2.5-flash-image-preview                      | 63.3 / 1M tokens   | Image    |
| Gemini Input Image Tokens (per 1M) Product  | model: gemini-2.5-flash                                    | 63.3 / 1M tokens   | Image    |
| Gemini Input Image Tokens (per 1M) Product  | model: gemini-2.5-flash-preview-04-17                      | 63.3 / 1M tokens   | Image    |
| Gemini Input Image Tokens (per 1M) Product  | model: gemini-2.5-pro                                      | 263.75 / 1M tokens | Image    |
| Gemini Input Image Tokens (per 1M) Product  | model: gemini-2.5-pro-preview-05-06                        | 263.75 / 1M tokens | Image    |
| Gemini Input Image Tokens (per 1M) Product  | model: gemini-3.1-flash-image-preview                      | 105.5 / 1M tokens  | Image    |
| Gemini Input Image Tokens (per 1M) Product  | model: gemini-3.1-pro-preview                              | 422 / 1M tokens    | Image    |
| Gemini Input Image Tokens (per 1M) Product  | model: gemini-3-pro-image-preview                          | 422 / 1M tokens    | Image    |
| Gemini Input Image Tokens (per 1M) Product  | model: gemini-3-pro-preview                                | 422 / 1M tokens    | Image    |
| Gemini Output Image Tokens (per 1M) Product | model: gemini-2.5-flash-image                              | 6330 / 1M tokens   | Image    |
| Gemini Output Image Tokens (per 1M) Product | model: gemini-2.5-flash-image-preview                      | 6330 / 1M tokens   | Image    |
| Gemini Output Image Tokens (per 1M) Product | model: gemini-2.5-flash-preview-04-17                      | 3165 / 1M tokens   | Image    |
| Gemini Output Image Tokens (per 1M) Product | model: gemini-2.5-pro-preview-05-06                        | 7385 / 1M tokens   | Image    |
| Gemini Output Image Tokens (per 1M) Product | model: gemini-3.1-flash-image-preview                      | 12660 / 1M tokens  | Image    |
| Gemini Output Image Tokens (per 1M) Product | model: gemini-3.1-pro-preview                              | 25320 / 1M tokens  | Image    |
| Gemini Output Image Tokens (per 1M) Product | model: gemini-3-pro-image-preview                          | 25320 / 1M tokens  | Image    |
| Nano Banana 2 Image Generation              | model: gemini-3.1-flash-image-preview, resolution: 2K      | 21.31 / run        | Image    |
| Nano Banana 2 Image Generation              | model: gemini-3.1-flash-image-preview, resolution: 4K      | 32.49 / run        | Image    |
| Gemini Input Video Tokens (per 1M) Product  | model: gemini-2.5-flash-image                              | 63.3 / 1M tokens   | Video    |
| Gemini Input Video Tokens (per 1M) Product  | model: gemini-2.5-flash-image-preview                      | 63.3 / 1M tokens   | Video    |
| Gemini Input Video Tokens (per 1M) Product  | model: gemini-2.5-flash                                    | 63.3 / 1M tokens   | Video    |
| Gemini Input Video Tokens (per 1M) Product  | model: gemini-2.5-flash-preview-04-17                      | 63.3 / 1M tokens   | Video    |
| Gemini Input Video Tokens (per 1M) Product  | model: gemini-2.5-pro                                      | 263.75 / 1M tokens | Video    |
| Gemini Input Video Tokens (per 1M) Product  | model: gemini-2.5-pro-preview-05-06                        | 263.75 / 1M tokens | Video    |
| Gemini Input Video Tokens (per 1M) Product  | model: gemini-3.1-pro-preview                              | 422 / 1M tokens    | Video    |
| Gemini Input Video Tokens (per 1M) Product  | model: gemini-3-pro-image-preview                          | 422 / 1M tokens    | Video    |
| Gemini Input Video Tokens (per 1M) Product  | model: gemini-3-pro-preview                                | 422 / 1M tokens    | Video    |
| Gemini Output Video Tokens (per 1M) Product | model: gemini-2.5-flash-preview-04-17                      | 4220 / 1M tokens   | Video    |
| Gemini Output Video Tokens (per 1M) Product | model: gemini-2.5-pro-preview-05-06                        | 8440 / 1M tokens   | Video    |
| Gemini Input Audio Tokens (per 1M) Product  | model: gemini-2.5-flash-image                              | 211 / 1M tokens    | Audio    |
| Gemini Input Audio Tokens (per 1M) Product  | model: gemini-2.5-flash-image-preview                      | 211 / 1M tokens    | Audio    |
| Gemini Input Audio Tokens (per 1M) Product  | model: gemini-2.5-flash                                    | 211 / 1M tokens    | Audio    |
| Gemini Input Audio Tokens (per 1M) Product  | model: gemini-2.5-flash-preview-04-17                      | 211 / 1M tokens    | Audio    |
| Gemini Input Audio Tokens (per 1M) Product  | model: gemini-2.5-pro                                      | 263.75 / 1M tokens | Audio    |
| Gemini Input Audio Tokens (per 1M) Product  | model: gemini-2.5-pro-preview-05-06                        | 263.75 / 1M tokens | Audio    |
| Gemini Input Audio Tokens (per 1M) Product  | model: gemini-3.1-pro-preview                              | 422 / 1M tokens    | Audio    |
| Gemini Input Audio Tokens (per 1M) Product  | model: gemini-3-pro-image-preview                          | 422 / 1M tokens    | Audio    |
| Gemini Input Audio Tokens (per 1M) Product  | model: gemini-3-pro-preview                                | 422 / 1M tokens    | Audio    |
| Gemini Output Audio Tokens (per 1M) Product | model: gemini-2.5-flash-preview-04-17                      | 3165 / 1M tokens   | Audio    |
| Gemini Output Audio Tokens (per 1M) Product | model: gemini-2.5-pro-preview-05-06                        | 7385 / 1M tokens   | Audio    |
| Google Veo3/Veo3 Fast Video Generation      | generateAudio: false, model: veo-3.0-fast-generate-001     | 168.8 / run        | Video    |
| Google Veo3/Veo3 Fast Video Generation      | generateAudio: false, model: veo-3.0-generate-001          | 337.6 / run        | Video    |
| Google Veo3/Veo3 Fast Video Generation      | generateAudio: true, model: veo-3.0-fast-generate-001      | 253.2 / run        | Video    |
| Google Veo3/Veo3 Fast Video Generation      | generateAudio: true, model: veo-3.0-generate-001           | 675.2 / run        | Video    |
| Google Veo2 Video Generation                | NA                                                         | 105.5 / run        | Video    |
| Google Veo3                                 | generateAudio: false, model: veo-3.0-fast-generate-001     | 21.1 / run         | Image    |
| Google Veo3                                 | generateAudio: false, model: veo-3.0-generate-001          | 42.2 / run         | Image    |
| Google Veo3                                 | generateAudio: false, model: veo-3.1-fast-generate-preview | 21.1 / run         | Image    |
| Google Veo3                                 | generateAudio: false, model: veo-3.1-generate-preview      | 42.2 / run         | Image    |
| Google Veo3                                 | generateAudio: true, model: veo-3.0-fast-generate-001      | 31.65 / run        | Image    |
| Google Veo3                                 | generateAudio: true, model: veo-3.0-generate-001           | 84.4 / run         | Image    |
| Google Veo3                                 | generateAudio: true, model: veo-3.1-fast-generate-preview  | 31.65 / run        | Image    |
| Google Veo3                                 | generateAudio: true, model: veo-3.1-generate-preview       | 84.4 / run         | Image    |
| Gemini Thoughts Tokens (per 1M) Product     | model: gemini-3.1-flash-image-preview                      | 633 / 1M tokens    | Text     |
| Gemini Thoughts Tokens (per 1M) Product     | model: gemini-3.1-pro-preview                              | 2532 / 1M tokens   | Text     |
| Gemini Thoughts Tokens (per 1M) Product     | model: gemini-3-pro-image-preview                          | 2532 / 1M tokens   | Text     |
| Gemini Thoughts Tokens (per 1M) Product     | model: gemini-3-pro-preview                                | 2532 / 1M tokens   | Text     |
| Gemini Input Text Tokens (per 1M) Product   | model: gemini-3.1-flash-lite-preview                       | 52.75 / 1M tokens  | Text     |
| Gemini Output Text Tokens (per 1M) Product  | model: gemini-3.1-flash-lite-preview                       | 316.5 / 1M tokens  | Text     |
| Gemini Input Image Tokens (per 1M) Product  | model: gemini-3.1-flash-lite-preview                       | 52.75 / 1M tokens  | Image    |
| Gemini Input Video Tokens (per 1M) Product  | model: gemini-3.1-flash-lite-preview                       | 52.75 / 1M tokens  | Video    |
| Gemini Input Audio Tokens (per 1M) Product  | model: gemini-3.1-flash-lite-preview                       | 105.5 / 1M tokens  | Audio    |
| Gemini Thoughts Tokens (per 1M) Product     | model: gemini-3.1-flash-lite-preview                       | 316.5 / 1M tokens  | Text     |

## HappyHorse

| Product Name                        | Configuration                           | Credits     | Category |
| :---------------------------------- | :-------------------------------------- | :---------- | :------- |
| HappyHorse Video Generation Product | model: happyhorse1.0, resolution: 720P  | 29.54 / sec | Video    |
| HappyHorse Video Generation Product | model: happyhorse1.0, resolution: 1080P | 50.64 / sec | Video    |

## Hitpaw

### Video Enhancement

| Product Name                     | Configuration                                     | Credits     | Category |
| :------------------------------- | :------------------------------------------------ | :---------- | :------- |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 720P, fps: \<30fps    | 2.11 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 720P, fps: 30-60fps   | 4.22 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 720P, fps: 60-120fps  | 8.44 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 720P, fps: ≥120fps    | 12.66 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 1080P, fps: \<30fps   | 3.17 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 1080P, fps: 30-60fps  | 6.33 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 1080P, fps: 60-120fps | 12.66 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 1080P, fps: ≥120fps   | 18.99 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 2K, fps: \<30fps      | 4.22 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 2K, fps: 30-60fps     | 8.23 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 2K, fps: 60-120fps    | 16.46 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 2K, fps: ≥120fps      | 24.69 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 4K, fps: \<30fps      | 5.28 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 4K, fps: 30-60fps     | 10.76 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 4K, fps: 60-120fps    | 21.31 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 4K, fps: ≥120fps      | 32.07 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 8K, fps: \<30fps      | 6.96 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 8K, fps: 30-60fps     | 13.93 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 8K, fps: 60-120fps    | 27.85 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Standard, resolution: 8K, fps: ≥120fps      | 41.78 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 720P, fps: \<30fps       | 3.17 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 720P, fps: 30-60fps      | 6.54 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 720P, fps: 60-120fps     | 13.08 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 720P, fps: ≥120fps       | 19.41 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 1080P, fps: \<30fps      | 4.22 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 1080P, fps: 30-60fps     | 8.44 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 1080P, fps: 60-120fps    | 16.88 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 1080P, fps: ≥120fps      | 25.32 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 2K, fps: \<30fps         | 5.49 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 2K, fps: 30-60fps        | 10.97 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 2K, fps: 60-120fps       | 21.94 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 2K, fps: ≥120fps         | 32.92 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 4K, fps: \<30fps         | 7.17 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 4K, fps: 30-60fps        | 14.35 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 4K, fps: 60-120fps       | 28.49 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 4K, fps: ≥120fps         | 42.83 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 8K, fps: \<30fps         | 9.28 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 8K, fps: 30-60fps        | 18.57 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 8K, fps: 60-120fps       | 37.14 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Ultra, resolution: 8K, fps: ≥120fps         | 55.7 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 720P, fps: \<30fps         | 3.17 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 720P, fps: 30-60fps        | 6.33 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 720P, fps: 60-120fps       | 12.66 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 720P, fps: ≥120fps         | 18.99 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 1080P, fps: \<30fps        | 5.28 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 1080P, fps: 30-60fps       | 10.55 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 1080P, fps: 60-120fps      | 21.1 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 1080P, fps: ≥120fps        | 31.65 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 2K, fps: \<30fps           | 8.02 / sec  | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 2K, fps: 30-60fps          | 15.82 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 2K, fps: 60-120fps         | 31.65 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 2K, fps: ≥120fps           | 47.48 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 4K / 8K, fps: \<30fps      | 11.82 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 4K / 8K, fps: 30-60fps     | 23.84 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 4K / 8K, fps: 60-120fps    | 47.48 / sec | Video    |
| Hitpaw Video Enhancement Product | type: Gen, resolution: 4K / 8K, fps: ≥120fps      | 71.32 / sec | Video    |

### Photo Enhancement

| Product Name                     | Configuration                                  | Credits      | Category |
| :------------------------------- | :--------------------------------------------- | :----------- | :------- |
| Hitpaw Photo Enhancement Product | type: Standard, megapixels: \<8MP              | 2.11 / run   | Image    |
| Hitpaw Photo Enhancement Product | type: Standard, megapixels: 8-12MP             | 4.22 / run   | Image    |
| Hitpaw Photo Enhancement Product | type: Standard, megapixels: 12-24MP            | 6.33 / run   | Image    |
| Hitpaw Photo Enhancement Product | type: Standard, megapixels: 24-48MP            | 14.77 / run  | Image    |
| Hitpaw Photo Enhancement Product | type: Standard, megapixels: 48-108MP           | 29.54 / run  | Image    |
| Hitpaw Photo Enhancement Product | type: Standard, megapixels: 108-216MP          | 50.64 / run  | Image    |
| Hitpaw Photo Enhancement Product | type: Standard, megapixels: 216-432MP          | 101.28 / run | Image    |
| Hitpaw Photo Enhancement Product | type: Generative Portrait, megapixels: \<8MP   | 4.22 / run   | Image    |
| Hitpaw Photo Enhancement Product | type: Generative Portrait, megapixels: 8-12MP  | 6.33 / run   | Image    |
| Hitpaw Photo Enhancement Product | type: Generative Portrait, megapixels: 12-24MP | 8.44 / run   | Image    |
| Hitpaw Photo Enhancement Product | type: Generative Portrait, megapixels: 24-34MP | 12.66 / run  | Image    |
| Hitpaw Photo Enhancement Product | type: Generative, megapixels: \<8MP            | 10.55 / run  | Image    |
| Hitpaw Photo Enhancement Product | type: Generative, megapixels: 8-12MP           | 12.66 / run  | Image    |
| Hitpaw Photo Enhancement Product | type: Generative, megapixels: 12-24MP          | 16.88 / run  | Image    |
| Hitpaw Photo Enhancement Product | type: Generative, megapixels: 24-34MP          | 31.65 / run  | Image    |

## Ideogram

| Product Name                              | Configuration                                                           | Credits     | Category |
| :---------------------------------------- | :---------------------------------------------------------------------- | :---------- | :------- |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/edit-character-ref, rendering\_speed: DEFAULT     | 45.26 / run | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/edit-character-ref, rendering\_speed: QUALITY     | 60.35 / run | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/edit-character-ref, rendering\_speed: TURBO       | 30.17 / run | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/edit, rendering\_speed: BALANCED                  | 18.1 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/edit, rendering\_speed: DEFAULT                   | 18.1 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/edit, rendering\_speed: QUALITY                   | 27.16 / run | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/edit, rendering\_speed: TURBO                     | 9.05 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/generate-character-ref, rendering\_speed: DEFAULT | 45.26 / run | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/generate-character-ref, rendering\_speed: QUALITY | 60.35 / run | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/generate-character-ref, rendering\_speed: TURBO   | 30.17 / run | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/generate, rendering\_speed: BALANCED              | 18.1 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/generate, rendering\_speed: DEFAULT               | 18.1 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/generate, rendering\_speed: QUALITY               | 27.16 / run | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/generate, rendering\_speed: TURBO                 | 9.05 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/reframe, rendering\_speed: DEFAULT                | 18.1 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/reframe, rendering\_speed: QUALITY                | 27.16 / run | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/reframe, rendering\_speed: TURBO                  | 9.05 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/remix, rendering\_speed: BALANCED                 | 18.1 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/remix, rendering\_speed: DEFAULT                  | 18.1 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/remix, rendering\_speed: QUALITY                  | 27.16 / run | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/remix, rendering\_speed: TURBO                    | 9.05 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/replace-background, rendering\_speed: BALANCED    | 18.1 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/replace-background, rendering\_speed: DEFAULT     | 18.1 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/replace-background, rendering\_speed: QUALITY     | 27.16 / run | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: ideogram-v3/replace-background, rendering\_speed: TURBO       | 9.05 / run  | Image    |
| prod-v1-Ideogram V3 Image Generation      | endpoint: remix, rendering\_speed: TURBO                                | 9.05 / run  | Image    |
| prod-v1-Ideogram V4 Image Generation      | endpoint: ideogram-v4/generate, rendering\_speed: TURBO                 | 9.05 / run  | Image    |
| prod-v1-Ideogram V4 Image Generation      | endpoint: ideogram-v4/generate, rendering\_speed: DEFAULT               | 18.1 / run  | Image    |
| prod-v1-Ideogram V4 Image Generation      | endpoint: ideogram-v4/generate, rendering\_speed: QUALITY               | 30.17 / run | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: edit, model: v\_2                                             | 24.14 / run | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: edit, model: v\_2\_turbo                                      | 15.09 / run | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: generate, model: v\_1                                         | 18.1 / run  | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: generate, model: v\_1\_turbo                                  | 6.03 / run  | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: generate, model: v\_2a                                        | 12.07 / run | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: generate, model: v\_2a\_turbo                                 | 7.54 / run  | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: generate, model: v\_2                                         | 24.14 / run | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: generate, model: v\_2\_turbo                                  | 15.09 / run | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: reframe, model: v\_2                                          | 24.14 / run | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: reframe, model: v\_2\_turbo                                   | 15.09 / run | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: remix, model: v\_1                                            | 18.1 / run  | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: remix, model: v\_1\_turbo                                     | 6.03 / run  | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: remix, model: v\_2a                                           | 12.07 / run | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: remix, model: v\_2a\_turbo                                    | 7.54 / run  | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: remix, model: v\_2                                            | 24.14 / run | Image    |
| prod-v1-Ideogram Image Generation Product | endpoint: remix, model: v\_2\_turbo                                     | 15.09 / run | Image    |

## Krea

| Product Name            | Configuration                                          | Credits    | Category |
| :---------------------- | :----------------------------------------------------- | :--------- | :------- |
| Krea 2 Image Generation | model: krea-2-medium-turbo                             | 3.2 / run  | Image    |
| Krea 2 Image Generation | model: krea-2-medium-turbo, with image style reference | 3.7 / run  | Image    |
| Krea 2 Image Generation | model: krea-2-medium-turbo, with moodboard             | 4.2 / run  | Image    |
| Krea 2 Image Generation | model: krea-2-medium                                   | 6.4 / run  | Image    |
| Krea 2 Image Generation | model: krea-2-medium, with image style reference       | 7.4 / run  | Image    |
| Krea 2 Image Generation | model: krea-2-medium, with moodboard                   | 8.5 / run  | Image    |
| Krea 2 Image Generation | model: krea-2-large                                    | 12.7 / run | Image    |
| Krea 2 Image Generation | model: krea-2-large, with image style reference        | 13.8 / run | Image    |
| Krea 2 Image Generation | model: krea-2-large, with moodboard                    | 14.8 / run | Image    |

## Kling

| Product Name                              | Configuration                                                  | Credits      | Category |
| :---------------------------------------- | :------------------------------------------------------------- | :----------- | :------- |
| prod-v1-Kling Video Generation Product    | mode: pro, model: kling-v1                                     | 103.39 / run | Video    |
| prod-v1-Kling Video Generation Product    | mode: pro, model: kling-v1-5                                   | 103.39 / run | Video    |
| prod-v1-Kling Video Generation Product    | mode: pro, model: kling-v1-6                                   | 103.39 / run | Video    |
| prod-v1-Kling Video Generation Product    | mode: pro, model: kling-v2-1                                   | 103.39 / run | Video    |
| prod-v1-Kling Video Generation Product    | mode: pro, model: kling-v2-1-master                            | 295.4 / run  | Video    |
| prod-v1-Kling Video Generation Product    | mode: pro, model: kling-v2-5-turbo                             | 73.85 / run  | Video    |
| prod-v1-Kling Video Generation Product    | mode: pro, model: kling-v2-master                              | 295.4 / run  | Video    |
| prod-v1-Kling Video Generation Product    | mode: std, model: kling-v1                                     | 29.54 / sec  | Video    |
| prod-v1-Kling Video Generation Product    | mode: std, model: kling-v1-5                                   | 59.08 / run  | Video    |
| prod-v1-Kling Video Generation Product    | mode: std, model: kling-v1-6                                   | 59.08 / run  | Video    |
| prod-v1-Kling Video Generation Product    | mode: std, model: kling-v2-1                                   | 59.08 / run  | Video    |
| prod-v1-Kling Video Generation Product    | mode: std, model: kling-v2-1-master                            | 295.4 / run  | Video    |
| prod-v1-Kling Video Generation Product    | mode: std, model: kling-v2-master                              | 295.4 / run  | Video    |
| Kling Video Generation with Sound Product | mode: pro, model: kling-v2-6, sound: off                       | 14.77 / sec  | Video    |
| Kling Video Generation with Sound Product | mode: pro, model: kling-v2-6, sound: on                        | 29.54 / sec  | Video    |
| Kling Video Generation with Sound Product | resolution: 1080p, model: kling-v3, no\_sound: true            | 23.63 / sec  | Video    |
| Kling Video Generation with Sound Product | resolution: 1080p, model: kling-v3, no\_sound: false           | 35.45 / sec  | Video    |
| Kling Video Generation with Sound Product | resolution: 720p, model: kling-v3, no\_sound: true             | 17.72 / sec  | Video    |
| Kling Video Generation with Sound Product | resolution: 720p, model: kling-v3, no\_sound: false            | 26.59 / sec  | Video    |
| Kling Video Generation with Sound Product | mode: pro, model: kling-v3-omni, no\_sound: true               | 23.63 / sec  | Video    |
| Kling Video Generation with Sound Product | mode: pro, model: kling-v3-omni, no\_sound: false              | 29.54 / sec  | Video    |
| Kling Video Generation with Sound Product | mode: std, model: kling-v3-omni, no\_sound: true               | 17.72 / sec  | Video    |
| Kling Video Generation with Sound Product | mode: std, model: kling-v3-omni, no\_sound: false              | 23.63 / sec  | Video    |
| Kling Video Generation with Sound Product | mode: pro, model: kling-v3-4k                                  | 88.62 / sec  | Video    |
| Kling Omni Video Product                  | generate\_with\_video: false, mode: pro, model: kling-video-o1 | 23.63 / sec  | Video    |
| Kling Omni Video Product                  | generate\_with\_video: false, mode: std, model: kling-video-o1 | 17.72 / sec  | Video    |
| Kling Omni Video Product                  | generate\_with\_video: true, mode: pro, model: kling-video-o1  | 35.45 / sec  | Video    |
| Kling Omni Video Product                  | generate\_with\_video: true, mode: std, model: kling-video-o1  | 26.59 / sec  | Video    |
| Kling Video Extension Product             | NA                                                             | 59.08 / run  | Video    |
| Kling Lip Sync Product                    | NA                                                             | 14.77 / run  | Image    |
| Kling Motion Control Product              | mode: std, model: kling-v2-6                                   | 14.77 / run  | Image    |
| Kling Motion Control Product              | mode: pro, model: kling-v2-6                                   | 23.63 / run  | Image    |
| Kling Virtual Try On                      | model: kolors-virtual-try-on-v1                                | 14.77 / run  | Image    |
| Kling Virtual Try On                      | model: kolors-virtual-try-on-v1-5                              | 14.77 / run  | Image    |
| Kling Image Generation Product            | model: kling-v1, operation: text\_to\_image                    | 0.74 / run   | Image    |
| Kling Image Generation Product            | model: kling-v1, operation: image\_to\_image                   | 0.74 / run   | Image    |
| Kling Image Generation Product            | model: kling-v1-5, operation: text\_to\_image                  | 2.95 / run   | Image    |
| Kling Image Generation Product            | model: kling-v1-5, operation: image\_to\_image                 | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-v2, operation: text\_to\_image                    | 2.95 / run   | Image    |
| Kling Image Generation Product            | model: kling-v2-new, operation: image\_to\_image\_restyle      | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-v2-1, operation: text\_to\_image                  | 2.95 / run   | Image    |
| Kling Image Generation Product            | model: kling-v3, specs: 1k, operation: text\_to\_image         | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-v3, specs: 2k, operation: text\_to\_image         | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-v3, specs: 1k, operation: image\_to\_image        | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-v3, specs: 2k, operation: image\_to\_image        | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-v3, specs: 1k, operation: image\_editing          | 11.82 / run  | Image    |
| Kling Image Generation Product            | model: kling-v3, specs: 4k, operation: image\_editing          | 11.82 / run  | Image    |
| Kling Image Generation Product            | model: kling-v3-omni, specs: 1k, operation: text\_to\_image    | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-v3-omni, specs: 2k, operation: text\_to\_image    | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-v3-omni, specs: 1k, operation: image\_to\_image   | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-v3-omni, specs: 2k, operation: image\_to\_image   | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-v3-omni, specs: 1k, operation: image\_editing     | 11.82 / run  | Image    |
| Kling Image Generation Product            | model: kling-v3-omni, specs: 4k, operation: image\_editing     | 11.82 / run  | Image    |
| Kling Image Generation Product            | model: kling-image-o1, operation: text\_to\_image              | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-image-o1, operation: image\_to\_image             | 5.91 / run   | Image    |
| Kling Image Generation Product            | model: kling-image-o1, operation: image\_editing               | 5.91 / run   | Image    |
| Kling Image Generation w/ N               | model: kling-v1, operation: text\_to\_image                    | 0.74 / run   | Image    |
| Kling Image Generation w/ N               | model: kling-v1, operation: image\_to\_image                   | 0.74 / run   | Image    |
| Kling Image Generation w/ N               | model: kling-v1-5, operation: text\_to\_image                  | 2.95 / run   | Image    |
| Kling Image Generation w/ N               | model: kling-v1-5, operation: image\_to\_image                 | 5.91 / run   | Image    |
| Kling Image Generation w/ N               | model: kling-v2, operation: text\_to\_image                    | 2.95 / run   | Image    |
| Kling Credits                             | type: image                                                    | 0.74 / run   | Image    |
| Kling Credits                             | type: video                                                    | 29.54 / run  | Image    |
| Kling Camera Control Product              | type: text-to-video                                            | 29.54 / run  | Video    |
| Kling Camera Control Product              | type: image-to-video                                           | 103.39 / run | Video    |
| Kling Avatar Product                      | mode: std                                                      | 11.82 / sec  | Video    |
| Kling Avatar Product                      | mode: pro                                                      | 23.63 / sec  | Video    |
| Kling 2.6 Audio Product                   | mode: text-to-video, no\_sound: true                           | 14.77 / sec  | Video    |
| Kling 2.6 Audio Product                   | mode: text-to-video, no\_sound: false                          | 29.54 / sec  | Video    |
| Kling 2.6 Audio Product                   | mode: image-to-video, no\_sound: true                          | 14.77 / sec  | Video    |
| Kling 2.6 Audio Product                   | mode: image-to-video, no\_sound: false                         | 29.54 / sec  | Video    |

## Lightricks

| Product Name                 | Configuration                                                      | Credits     | Category |
| :--------------------------- | :----------------------------------------------------------------- | :---------- | :------- |
| Ltx Video generation product | endpoint: image-to-video, model: ltx-2-fast, resolution: 1920x1080 | 8.44 / sec  | Video    |
| Ltx Video generation product | endpoint: image-to-video, model: ltx-2-fast, resolution: 2560x1440 | 16.88 / sec | Video    |
| Ltx Video generation product | endpoint: image-to-video, model: ltx-2-fast, resolution: 3840x2160 | 33.76 / sec | Video    |
| Ltx Video generation product | endpoint: image-to-video, model: ltx-2-pro, resolution: 1920x1080  | 12.66 / sec | Video    |
| Ltx Video generation product | endpoint: image-to-video, model: ltx-2-pro, resolution: 2560x1440  | 25.32 / sec | Video    |
| Ltx Video generation product | endpoint: image-to-video, model: ltx-2-pro, resolution: 3840x2160  | 50.64 / run | Video    |
| Ltx Video generation product | endpoint: text-to-video, model: ltx-2-fast, resolution: 1920x1080  | 8.44 / sec  | Video    |
| Ltx Video generation product | endpoint: text-to-video, model: ltx-2-fast, resolution: 2560x1440  | 16.88 / sec | Video    |
| Ltx Video generation product | endpoint: text-to-video, model: ltx-2-fast, resolution: 3840x2160  | 33.76 / sec | Video    |
| Ltx Video generation product | endpoint: text-to-video, model: ltx-2-pro, resolution: 1920x1080   | 12.66 / sec | Video    |
| Ltx Video generation product | endpoint: text-to-video, model: ltx-2-pro, resolution: 2560x1440   | 25.32 / sec | Video    |
| Ltx Video generation product | endpoint: text-to-video, model: ltx-2-pro, resolution: 3840x2160   | 50.64 / run | Video    |

## Luma

| Product Name                                        | Configuration                                                      | Credits     | Category |
| :-------------------------------------------------- | :----------------------------------------------------------------- | :---------- | :------- |
| prod-v1-Luma Video Generation Product               | model: ray-1-6                                                     | 0.97 / sec  | Video    |
| prod-v1-Luma Video Generation Product               | model: ray-2                                                       | 1.93 / sec  | Video    |
| prod-v1-Luma Video Generation Product               | model: ray-flash-2                                                 | 0.66 / sec  | Video    |
| Luma Image Generations (millions of pixels) Product | model: photon-1                                                    | 2.2 / run   | Image    |
| Luma Image Generations (millions of pixels) Product | model: photon-flash-1                                              | 0.57 / run  | Image    |
| Luma Agents uni-1 Image Product                     | model: uni-1, task: text-to-image                                  | 8.52 / run  | Image    |
| Luma Agents uni-1 Image Product                     | model: uni-1, task: image-to-image                                 | 9.16 / run  | Image    |
| Luma Agents uni-1 Image Product                     | model: uni-1, task: image-reference, num\_reference\_images: 1     | 9.16 / run  | Image    |
| Luma Agents uni-1 Image Product                     | model: uni-1, task: image-reference, num\_reference\_images: 2     | 9.79 / run  | Image    |
| Luma Agents uni-1 Image Product                     | model: uni-1, task: image-reference, num\_reference\_images: 3     | 10.42 / run | Image    |
| Luma Agents uni-1 Image Product                     | model: uni-1, task: image-reference, num\_reference\_images: 4     | 11.06 / run | Image    |
| Luma Agents uni-1 Image Product                     | model: uni-1, task: image-reference, num\_reference\_images: 5     | 11.69 / run | Image    |
| Luma Agents uni-1 Image Product                     | model: uni-1, task: image-reference, num\_reference\_images: 6     | 12.32 / run | Image    |
| Luma Agents uni-1 Image Product                     | model: uni-1, task: image-reference, num\_reference\_images: 7     | 12.96 / run | Image    |
| Luma Agents uni-1 Image Product                     | model: uni-1, task: image-reference, num\_reference\_images: 8     | 13.59 / run | Image    |
| Luma Agents uni-1 Image Product                     | model: uni-1, task: image-reference, num\_reference\_images: 9     | 14.22 / run | Image    |
| Luma Agents uni-1-max Image Product                 | model: uni-1-max, task: text-to-image                              | 21.10 / run | Image    |
| Luma Agents uni-1-max Image Product                 | model: uni-1-max, task: image-to-image                             | 21.73 / run | Image    |
| Luma Agents uni-1-max Image Product                 | model: uni-1-max, task: image-reference, num\_reference\_images: 1 | 21.73 / run | Image    |
| Luma Agents uni-1-max Image Product                 | model: uni-1-max, task: image-reference, num\_reference\_images: 2 | 22.37 / run | Image    |
| Luma Agents uni-1-max Image Product                 | model: uni-1-max, task: image-reference, num\_reference\_images: 3 | 23.00 / run | Image    |
| Luma Agents uni-1-max Image Product                 | model: uni-1-max, task: image-reference, num\_reference\_images: 4 | 23.63 / run | Image    |
| Luma Agents uni-1-max Image Product                 | model: uni-1-max, task: image-reference, num\_reference\_images: 5 | 24.27 / run | Image    |
| Luma Agents uni-1-max Image Product                 | model: uni-1-max, task: image-reference, num\_reference\_images: 6 | 24.90 / run | Image    |
| Luma Agents uni-1-max Image Product                 | model: uni-1-max, task: image-reference, num\_reference\_images: 7 | 25.53 / run | Image    |
| Luma Agents uni-1-max Image Product                 | model: uni-1-max, task: image-reference, num\_reference\_images: 8 | 26.16 / run | Image    |
| Luma Agents uni-1-max Image Product                 | model: uni-1-max, task: image-reference, num\_reference\_images: 9 | 26.80 / run | Image    |

## Meshy

| Product Name            | Configuration                                                 | Credits     | Category |
| :---------------------- | :------------------------------------------------------------ | :---------- | :------- |
| Meshy Retexture         | NA                                                            | 84.4 / run  | 3D       |
| Meshy Rigging           | NA                                                            | 42.2 / run  | 3D       |
| Meshy Remesh            | NA                                                            | 42.2 / run  | 3D       |
| Meshy Animation         | NA                                                            | 25.32 / run | 3D       |
| Meshy Multi Image to 3D | should\_texture: false                                        | 42.2 / run  | Image    |
| Meshy Multi Image to 3D | should\_texture: true                                         | 126.6 / run | Image    |
| Meshy Text to 3D        | mode: preview, model: latest                                  | 168.8 / run | 3D       |
| Meshy Text to 3D        | mode: preview, model: meshy-5                                 | 42.2 / run  | 3D       |
| Meshy Text to 3D        | mode: refine, model: latest                                   | 84.4 / run  | 3D       |
| Meshy Image to 3D       | model: latest, model\_type: lowpoly, should\_texture: false   | 168.8 / run | Image    |
| Meshy Image to 3D       | model: latest, model\_type: lowpoly, should\_texture: true    | 253.2 / run | Image    |
| Meshy Image to 3D       | model: latest, model\_type: standard, should\_texture: false  | 168.8 / run | Image    |
| Meshy Image to 3D       | model: latest, model\_type: standard, should\_texture: true   | 253.2 / run | Image    |
| Meshy Image to 3D       | model: meshy-5, model\_type: lowpoly, should\_texture: false  | 168.8 / run | Image    |
| Meshy Image to 3D       | model: meshy-5, model\_type: lowpoly, should\_texture: true   | 253.2 / run | Image    |
| Meshy Image to 3D       | model: meshy-5, model\_type: standard, should\_texture: false | 42.2 / run  | Image    |
| Meshy Image to 3D       | model: meshy-5, model\_type: standard, should\_texture: true  | 126.6 / run | Image    |

## Minimax

| Product Name                                     | Configuration                                            | Credits      | Category |
| :----------------------------------------------- | :------------------------------------------------------- | :----------- | :------- |
| prod-v1-Minimax Video Product                    | model: i2v-01-director                                   | 90.73 / run  | Video    |
| prod-v1-Minimax Video Product                    | model: i2v-01-live                                       | 90.73 / run  | Video    |
| prod-v1-Minimax Video Product                    | model: i2v-01                                            | 90.73 / run  | Video    |
| prod-v1-Minimax Video Product                    | model: s2v-01                                            | 137.15 / run | Video    |
| prod-v1-Minimax Video Product                    | model: t2v-01-director                                   | 90.73 / run  | Video    |
| prod-v1-Minimax Video Product                    | model: t2v-01                                            | 90.73 / run  | Video    |
| Minimax Video Generation\_models after Hailuo-02 | duration: 10, model: minimax-hailuo-02, resolution: 768P | 118.16 / run | Video    |
| Minimax Video Generation\_models after Hailuo-02 | duration: 6, model: minimax-hailuo-02, resolution: 1080P | 103.39 / run | Video    |
| Minimax Video Generation\_models after Hailuo-02 | duration: 6, model: minimax-hailuo-02, resolution: 768P  | 59.08 / run  | Video    |

## Moonvalley

<Warning>
  **Service unavailable**: The Moonvalley API service is no longer available. The nodes listed below have been deprecated and may not function as expected.
</Warning>

| Product Name                  | Configuration | Credits      | Category |
| :---------------------------- | :------------ | :----------- | :------- |
| Moonvalley Image-to-Video 5s  | NA            | 316.5 / run  | Video    |
| Moonvalley Image-to-Video 10s | NA            | 633 / run    | Video    |
| Moonvalley Text-to-Video 5s   | NA            | 316.5 / run  | Video    |
| Moonvalley Text-to-Video 10s  | NA            | 633 / run    | Video    |
| Moonvalley Video-to-Video 5s  | NA            | 474.75 / run | Video    |
| Moonvalley Video-to-Video 10s | NA            | 844 / run    | Video    |

## OpenAI

OpenAI partner nodes bill the same underlying USD usage as the public API. **Credits = USD × 211** (see page header). Text-model USD rates below match OpenAI’s **[API pricing](https://developers.openai.com/api/docs/pricing)** **Standard** tier (per 1M tokens) as published on that page; image-token multipliers match `comfy_api_nodes/nodes_openai.py`. DALL·E and Sora fixed math matches the nodes’ `price_badge` expressions. Final charges follow metered usage (tokens, duration, and any cache hits).

### DALL·E 2 (`OpenAIDalle2`)

Per generated image (multiply by `n` when you request more than one).

| Product Name          | Configuration   | Credits / image | Category |
| :-------------------- | :-------------- | :-------------- | :------- |
| OpenAI DALL·E 2 image | size: 256x256   | 3.38            | Image    |
| OpenAI DALL·E 2 image | size: 512x512   | 3.80            | Image    |
| OpenAI DALL·E 2 image | size: 1024x1024 | 4.22            | Image    |

### DALL·E 3 (`OpenAIDalle3`)

| Product Name          | Configuration                                   | Credits / run | Category |
| :-------------------- | :---------------------------------------------- | :------------ | :------- |
| OpenAI DALL·E 3 image | quality: standard, size: 1024x1024              | 8.44          | Image    |
| OpenAI DALL·E 3 image | quality: standard, size: 1024x1792 or 1792x1024 | 16.88         | Image    |
| OpenAI DALL·E 3 image | quality: hd, size: 1024x1024                    | 16.88         | Image    |
| OpenAI DALL·E 3 image | quality: hd, size: 1024x1792 or 1792x1024       | 25.32         | Image    |

### GPT Image 1 / 1.5 / 2 (`OpenAIGPTImage1`)

Token-based from API usage. Credits = USD × 211 per 1M tokens (rates from the node's `calculate_tokens_price_image_1` / `calculate_tokens_price_image_1_5` helpers).

| Product Name                          | Configuration        | Credits / 1M tokens  | Category |
| :------------------------------------ | :------------------- | :------------------- | :------- |
| OpenAI GPT Image input (text/image)   | model: gpt-image-1   | 2110 (\$10 / 1M)     | Image    |
| OpenAI GPT Image output (image)       | model: gpt-image-1   | 8440 (\$40 / 1M)     | Image    |
| OpenAI GPT Image input (text/image)   | model: gpt-image-1.5 | 1688 (\$8 / 1M)      | Image    |
| OpenAI GPT Image output (image)       | model: gpt-image-1.5 | 6752 (\$32 / 1M)     | Image    |
| OpenAI GPT Image input (image)        | model: gpt-image-2   | 1688 (\$8 / 1M)      | Image    |
| OpenAI GPT Image cached input (image) | model: gpt-image-2   | 422 (\$2 / 1M)       | Image    |
| OpenAI GPT Image input (text)         | model: gpt-image-2   | 1055 (\$5 / 1M)      | Image    |
| OpenAI GPT Image cached input (text)  | model: gpt-image-2   | 263.75 (\$1.25 / 1M) | Image    |
| OpenAI GPT Image output (image)       | model: gpt-image-2   | 6330 (\$30 / 1M)     | Image    |

The UI shows approximate **USD ranges** per run by quality (`low` / `medium` / `high`); actual cost depends on token counts.

### Chat (`OpenAIChatNode`)

Models selectable in the node: `gpt-5.5`, `gpt-5.5-pro`, `gpt-5`, `gpt-5-mini`, `gpt-5-nano`, `gpt-4.1`, `gpt-4.1-mini`, `gpt-4.1-nano`, `o3`, `o4-mini`, `o1`, `o1-pro`. Standard tier, per 1M tokens (cached column is OpenAI’s cached-input rate where listed). For models with both short- and long-context pricing, the long-context rate applies once the request exceeds the short-context window.

| Model                       | Input credits / 1M | Cached input credits / 1M | Output credits / 1M |
| :-------------------------- | -----------------: | ------------------------: | ------------------: |
| gpt-5.5 (short context)     |               1055 |                     105.5 |                6330 |
| gpt-5.5 (long context)      |               2110 |                       211 |                9495 |
| gpt-5.5-pro (short context) |               6330 |                         — |               37980 |
| gpt-5.5-pro (long context)  |              12660 |                         — |               56970 |
| gpt-5                       |             263.75 |                     26.38 |                2110 |
| gpt-5-mini                  |              52.75 |                      5.28 |                 422 |
| gpt-5-nano                  |              10.55 |                      1.06 |                84.4 |
| gpt-4.1                     |                422 |                     105.5 |                1688 |
| gpt-4.1-mini                |               84.4 |                      21.1 |               337.6 |
| gpt-4.1-nano                |               21.1 |                      5.28 |                84.4 |
| o3                          |                422 |                     105.5 |                1688 |
| o4-mini                     |              232.1 |                     58.03 |               928.4 |
| o1                          |               3165 |                    1582.5 |               12660 |
| o1-pro                      |              31650 |                         — |              126600 |

Optional images and files add tokens billed at the same model input rates.

### Sora video (`OpenAIVideoSora2`)

USD is **(per-second rate) × (duration in seconds)**; duration can be 4, 8, or 12. Credits = USD × 211.

| Product Name                 | Configuration                                   | Credits / sec | Category |
| :--------------------------- | :---------------------------------------------- | :------------ | :------- |
| OpenAI Sora video generation | model: sora-2, size: 720x1280 or 1280x720       | 21.10         | Video    |
| OpenAI Sora video generation | model: sora-2-pro, size: 720x1280 or 1280x720   | 63.30         | Video    |
| OpenAI Sora video generation | model: sora-2-pro, size: 1024x1792 or 1792x1024 | 105.50        | Video    |

Example: `sora-2`, 1280x720, 8 seconds → about **168.8** credits (\$0.10 × 8 × 211).

## OpenRouter

### OpenRouter LLM (`OpenRouterLLMNode`)

Per 1M tokens.

| Model                            | Input credits / 1M | Output credits / 1M |
| :------------------------------- | -----------------: | ------------------: |
| `anthropic/claude-opus-4.7`      |               1055 |                5275 |
| `openai/gpt-5.5-pro`             |               6330 |               37980 |
| `openai/gpt-5.5`                 |               1055 |                6330 |
| `google/gemini-3.5-flash`        |              316.5 |                1899 |
| `x-ai/grok-4.20`                 |             263.75 |               527.5 |
| `x-ai/grok-4.3`                  |             263.75 |               527.5 |
| `deepseek/deepseek-v4-pro`       |             91.785 |              183.57 |
| `deepseek/deepseek-v4-flash`     |             23.632 |              47.264 |
| `deepseek/deepseek-v3.2`         |             53.172 |              79.758 |
| `qwen/qwen3.6-max-preview`       |             219.44 |             1316.64 |
| `qwen/qwen3.6-plus`              |             68.575 |              411.45 |
| `qwen/qwen3.6-flash`             |            39.5625 |             237.375 |
| `mistralai/mistral-large-2512`   |              105.5 |               316.5 |
| `mistralai/mistral-medium-3-5`   |              316.5 |              1582.5 |
| `z-ai/glm-4.6`                   |              90.73 |              367.14 |
| `z-ai/glm-5`                     |              126.6 |              405.12 |
| `moonshotai/kimi-k2.6`           |             154.03 |              736.39 |
| `moonshotai/kimi-k2-thinking`    |              126.6 |               527.5 |
| `perplexity/sonar-pro`           |                633 |                3165 |
| `perplexity/sonar-reasoning-pro` |                422 |                1688 |
| `perplexity/sonar-deep-research` |                422 |                1688 |

## Pika

| Product Name                                       | Configuration                                        | Credits     | Category |
| :------------------------------------------------- | :--------------------------------------------------- | :---------- | :------- |
| prod-v1-Pika Video Generation Product (10 seconds) | endpoint: generate/2.2/i2v, resolution: 1080p        | 211 / run   | Video    |
| prod-v1-Pika Video Generation Product (10 seconds) | endpoint: generate/2.2/i2v, resolution: 720p         | 126.6 / run | Video    |
| prod-v1-Pika Video Generation Product (10 seconds) | endpoint: generate/2.2/pikaframes, resolution: 1080p | 211 / run   | Video    |
| prod-v1-Pika Video Generation Product (10 seconds) | endpoint: generate/2.2/pikaframes, resolution: 720p  | 52.75 / run | Video    |
| prod-v1-Pika Video Generation Product (10 seconds) | endpoint: generate/2.2/pikascenes, resolution: 1080p | 316.5 / run | Video    |
| prod-v1-Pika Video Generation Product (10 seconds) | endpoint: generate/2.2/pikascenes, resolution: 720p  | 84.4 / run  | Video    |
| prod-v1-Pika Video Generation Product (10 seconds) | endpoint: generate/2.2/t2v, resolution: 1080p        | 211 / run   | Video    |
| prod-v1-Pika Video Generation Product (10 seconds) | endpoint: generate/2.2/t2v, resolution: 720p         | 126.6 / run | Video    |
| prod-v1-Pika Video Generation (5 seconds)          | endpoint: generate/2.2/i2v, resolution: 1080p        | 94.95 / run | Video    |
| prod-v1-Pika Video Generation (5 seconds)          | endpoint: generate/2.2/i2v, resolution: 720p         | 42.2 / run  | Video    |
| prod-v1-Pika Video Generation (5 seconds)          | endpoint: generate/2.2/pikaframes, resolution: 1080p | 63.3 / run  | Video    |
| prod-v1-Pika Video Generation (5 seconds)          | endpoint: generate/2.2/pikaframes, resolution: 720p  | 42.2 / run  | Video    |
| prod-v1-Pika Video Generation (5 seconds)          | endpoint: generate/2.2/pikascenes, resolution: 1080p | 105.5 / run | Video    |
| prod-v1-Pika Video Generation (5 seconds)          | endpoint: generate/2.2/pikascenes, resolution: 720p  | 63.3 / run  | Video    |
| prod-v1-Pika Video Generation (5 seconds)          | endpoint: generate/2.2/t2v, resolution: 1080p        | 94.95 / run | Video    |
| prod-v1-Pika Video Generation (5 seconds)          | endpoint: generate/2.2/t2v, resolution: 720p         | 42.2 / run  | Video    |
| prod-v1-Pika Video Generation (5 seconds)          | endpoint: generate/pikaffects, resolution: 720p      | 94.95 / run | Video    |
| Pika Basic Video Product                           | endpoint: generate/pikadditions                      | 63.3 / run  | Video    |
| Pika Basic Video Product                           | endpoint: generate/pikaffects                        | 94.95 / run | Video    |
| Pika Basic Video Product                           | endpoint: generate/pikaswaps                         | 63.3 / run  | Video    |

## Pixverse

| Product Name                     | Configuration                                     | Credits     | Category |
| :------------------------------- | :------------------------------------------------ | :---------- | :------- |
| Pixverse 5 seconds Video Product | model: v3.5, motion\_mode: fast, quality: 360p    | 189.9 / run | Video    |
| Pixverse 5 seconds Video Product | model: v3.5, motion\_mode: fast, quality: 540p    | 189.9 / run | Video    |
| Pixverse 5 seconds Video Product | model: v3.5, motion\_mode: fast, quality: 720p    | 253.2 / run | Video    |
| Pixverse 5 seconds Video Product | model: v3.5, motion\_mode: normal, quality: 1080p | 253.2 / run | Video    |
| Pixverse 5 seconds Video Product | model: v3.5, motion\_mode: normal, quality: 360p  | 94.95 / run | Video    |
| Pixverse 5 seconds Video Product | model: v3.5, motion\_mode: normal, quality: 540p  | 94.95 / run | Video    |
| Pixverse 5 seconds Video Product | model: v3.5, motion\_mode: normal, quality: 720p  | 126.6 / run | Video    |
| Pixverse 8 seconds Video Product | model: v3.5, motion\_mode: normal, quality: 360p  | 189.9 / run | Video    |
| Pixverse 8 seconds Video Product | model: v3.5, motion\_mode: normal, quality: 540p  | 189.9 / run | Video    |
| Pixverse 8 seconds Video Product | model: v3.5, motion\_mode: normal, quality: 720p  | 253.2 / run | Video    |

## Quiver

| Product Name        | Configuration        | Credits     | Category |
| :------------------ | :------------------- | :---------- | :------- |
| Quiver Text to SVG  | model: arrow-1.1     | 60.35 / run | Image    |
| Quiver Image to SVG | model: arrow-1.1     | 45.26 / run | Image    |
| Quiver Text to SVG  | model: arrow-1.1-max | 75.43 / run | Image    |
| Quiver Image to SVG | model: arrow-1.1-max | 60.35 / run | Image    |

## Recraft

| Product Name         | Configuration | Credits    | Category |
| :------------------- | :------------ | :--------- | :------- |
| Recraft All Products | NA            | 0.21 / run | Image    |

## Reve

> Prices shown are base prices (test\_time\_scaling=1, no postprocessing). Actual cost may be higher with upscaling or background removal enabled.

| Product Name      | Configuration                    | Credits     | Category |
| :---------------- | :------------------------------- | :---------- | :------- |
| Reve Image Create | model: reve-create\@20250915     | 7.24 / run  | Image    |
| Reve Image Edit   | model: reve-edit\@20250915       | 12.07 / run | Image    |
| Reve Image Edit   | model: reve-edit-fast\@20251030  | 2.11 / run  | Image    |
| Reve Image Remix  | model: reve-remix\@20250915      | 12.07 / run | Image    |
| Reve Image Remix  | model: reve-remix-fast\@20251030 | 2.11 / run  | Image    |

## Rodin

### Hyper3D Rodin (Gen-2)

| Product Name                      | Configuration | Credits     | Category |
| :-------------------------------- | :------------ | :---------- | :------- |
| Rodin 3D Generation (no addons)   | NA            | 84.4 / run  | 3D       |
| Rodin 3D Generation (with AddOns) | NA            | 253.2 / run | 3D       |

### Hyper3D Rodin Gen-2.5 (`Rodin3D_Gen25_Image` / `Rodin3D_Gen25_Text`)

| Product Name                 | Configuration         | Credits      | Category |
| :--------------------------- | :-------------------- | :----------- | :------- |
| Rodin Gen-2.5 (Regular/Fast) | mode: Regular or Fast | 158.25 / run | 3D       |
| Rodin Gen-2.5 (Extreme-High) | mode: Extreme-High    | 316.5 / run  | 3D       |
| Rodin Gen-2.5 HighPack Addon | addon\_highpack: true | +168.8 / run | 3D       |

## Runway

| Product Name                            | Configuration       | Credits     | Category |
| :-------------------------------------- | :------------------ | :---------- | :------- |
| prod-v1-Runway Video Generation Product | model: gen3a\_turbo | 15.09 / sec | Video    |
| prod-v1-Runway Video Generation Product | model: gen4\_turbo  | 10.55 / sec | Video    |
| RunwayML Image Generation Product       | model: gen4\_image  | 24.14 / run | Image    |

## Sonilo

| Product Name          | Configuration                       | Credits     | Category |
| :-------------------- | :---------------------------------- | :---------- | :------- |
| Sonilo Music Generate | model: sonilo, type: video-to-music | 1.9 / sec   | Audio    |
| Sonilo Music Generate | model: sonilo, type: text-to-music  | 1.055 / sec | Audio    |

## Stability AI

| Product Name                               | Configuration                                                                 | Credits     | Category |
| :----------------------------------------- | :---------------------------------------------------------------------------- | :---------- | :------- |
| prod-v1-Stability Image Generation Product | endpoint: v2beta/stable-image/generate/core                                   | 6.33 / run  | Image    |
| prod-v1-Stability Image Generation Product | endpoint: v2beta/stable-image/generate/ultra                                  | 16.88 / run | Image    |
| prod-v1-Stability Image Generation Product | endpoint: v2beta/stable-image/upscale/conservative                            | 84.4 / run  | Image    |
| prod-v1-Stability Image Generation Product | endpoint: v2beta/stable-image/upscale/creative                                | 126.6 / run | Image    |
| prod-v1-Stability Image Generation Product | endpoint: v2beta/stable-image/upscale/fast                                    | 4.22 / run  | Image    |
| Stability AI SD3 Image Products            | model: sd3.5-large                                                            | 13.71 / run | Image    |
| Stability AI SD3 Image Products            | model: sd3.5-large-turbo                                                      | 8.44 / run  | Image    |
| Stability AI SD3 Image Products            | model: sd3.5-medium                                                           | 7.39 / run  | Image    |
| Stability Audio Generation Product         | endpoint: v2beta/audio/stable-audio-2/audio-to-audio, model: stable-audio-2.5 | 42.2 / run  | Audio    |
| Stability Audio Generation Product         | endpoint: v2beta/audio/stable-audio-2/inpaint, model: stable-audio-2.5        | 42.2 / run  | Audio    |
| Stability Audio Generation Product         | endpoint: v2beta/audio/stable-audio-2/text-to-audio, model: stable-audio-2.5  | 42.2 / run  | Audio    |

## Tencent

| Product Name                | Configuration                                       | Credits     | Category |
| :-------------------------- | :-------------------------------------------------- | :---------- | :------- |
| Tencent 3D Generate Type    | endpoint: hunyuan/3d-pro, generate\_type: Geometry  | 63.3 / run  | 3D       |
| Tencent 3D Generate Type    | endpoint: hunyuan/3d-pro, generate\_type: LowPoly   | 126.6 / run | 3D       |
| Tencent 3D Generate Type    | endpoint: hunyuan/3d-pro, generate\_type: Normal    | 105.5 / run | 3D       |
| Tencent 3D Generate Type    | endpoint: hunyuan/3d-pro, generate\_type: Sketch    | 105.5 / run | 3D       |
| Tencent 3D Face Count       | custom\_face\_count: true, endpoint: hunyuan/3d-pro | 42.2 / run  | 3D       |
| Tencent 3D PBR              | enable\_pbr: true, endpoint: hunyuan/3d-pro         | 42.2 / run  | 3D       |
| Tencent 3D Multiview Images | endpoint: hunyuan/3d-pro, multi\_view: true         | 42.2 / run  | Image    |
| Tencent 3D                  | endpoint: hunyuan/3d-part                           | 126.6 / run | 3D       |
| Tencent 3D                  | endpoint: hunyuan/3d-texture-edit                   | 126.6 / run | 3D       |
| Tencent 3D                  | endpoint: hunyuan/3d-uv                             | 42.2 / run  | 3D       |
| Tencent 3D                  | endpoint: hunyuan/3d-smart-topology                 | 211 / run   | 3D       |

## Topaz

### Image Enhancement

| Product Name                    | Configuration                       | Credits     | Category |
| :------------------------------ | :---------------------------------- | :---------- | :------- |
| Topaz Image Enhance (Reimagine) | input resolution: 720p (1280x720)   | 13.93 / run | Image    |
| Topaz Image Enhance (Reimagine) | input resolution: 1080p (1920x1080) | 27.85 / run | Image    |
| Topaz Image Enhance (Reimagine) | input resolution: 1440p (2560x1440) | 27.85 / run | Image    |
| Topaz Image Enhance (Reimagine) | input resolution: 4K (3840x2160)    | 69.63 / run | Image    |

### Video Enhancement

| Product Name        | Configuration                                                                   | Credits       | Category |
| :------------------ | :------------------------------------------------------------------------------ | :------------ | :------- |
| Topaz Video Enhance | model: Starlight Precise 2.5 (slp-2.5), upscaler\_resolution: FullHD (1080p)    | 12.99 / sec   | Video    |
| Topaz Video Enhance | model: Starlight Precise 2.5 (slp-2.5), upscaler\_resolution: 4K (2160p)        | 28.08 / sec   | Video    |
| Topaz Video Enhance | model: Starlight (Astra) Fast (slf-1), upscaler\_resolution: FullHD (1080p)     | 6.50 / sec    | Video    |
| Topaz Video Enhance | model: Starlight (Astra) Fast (slf-1), upscaler\_resolution: 4K (2160p)         | 14.16 / sec   | Video    |
| Topaz Video Enhance | model: Starlight (Astra) Creative (slc-1), upscaler\_resolution: FullHD (1080p) | 43.62 / sec   | Video    |
| Topaz Video Enhance | model: Starlight (Astra) Creative (slc-1), upscaler\_resolution: 4K (2160p)     | 77.99 / sec   | Video    |
| Topaz Video Enhance | interpolation\_model: apo-8, input resolution: 720p                             | 2.55 / sec    | Video    |
| Topaz Video Enhance | interpolation\_model: apo-8, input resolution: 1080p                            | 5.57 / sec    | Video    |
| Topaz Video Enhance | interpolation\_model: apo-8, input resolution: 4K                               | 21.59 / sec   | Video    |
| Topaz Video Enhance | model: Astra 2 (ast-2), resolution: 1080p                                       | 1.688 / frame | Video    |
| Topaz Video Enhance | model: Astra 2 (ast-2), resolution: 4K                                          | 2.813 / frame | Video    |

## Tripo

| Product Name                             | Configuration                                                                                      | Credits     | Category |
| :--------------------------------------- | :------------------------------------------------------------------------------------------------- | :---------- | :------- |
| Tripo Generation (with Textures) Product | model: v2.0-20240919, texture\_quality: detailed, type: image\_to\_model                           | 84.4 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v2.0-20240919, texture\_quality: detailed, type: multiview\_to\_model                       | 84.4 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v2.0-20240919, texture\_quality: detailed, type: text\_to\_model                            | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v2.0-20240919, texture\_quality: standard, type: image\_to\_model                           | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v2.0-20240919, texture\_quality: standard, type: multiview\_to\_model                       | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v2.0-20240919, texture\_quality: standard, type: text\_to\_model                            | 42.2 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v2.5-20250123, texture\_quality: detailed, type: image\_to\_model                           | 84.4 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v2.5-20250123, texture\_quality: detailed, type: multiview\_to\_model                       | 84.4 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v2.5-20250123, texture\_quality: detailed, type: text\_to\_model                            | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v2.5-20250123, texture\_quality: standard, type: image\_to\_model                           | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v2.5-20250123, texture\_quality: standard, type: multiview\_to\_model                       | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v2.5-20250123, texture\_quality: standard, type: text\_to\_model                            | 42.2 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.0-20250812, texture\_quality: detailed, type: image\_to\_model                           | 84.4 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.0-20250812, texture\_quality: detailed, type: multiview\_to\_model                       | 84.4 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.0-20250812, texture\_quality: detailed, type: text\_to\_model                            | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.0-20250812, texture\_quality: standard, type: image\_to\_model                           | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.0-20250812, texture\_quality: standard, type: multiview\_to\_model                       | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.0-20250812, texture\_quality: standard, type: text\_to\_model                            | 42.2 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.1, texture\_quality: detailed, type: image\_to\_model                                    | 84.4 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.1, texture\_quality: detailed, type: multiview\_to\_model                                | 84.4 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.1, texture\_quality: detailed, type: text\_to\_model                                     | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.1, texture\_quality: standard, type: image\_to\_model                                    | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.1, texture\_quality: standard, type: multiview\_to\_model                                | 63.3 / run  | 3D       |
| Tripo Generation (with Textures) Product | model: v3.1, texture\_quality: standard, type: text\_to\_model                                     | 42.2 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v2.0-20240919, type: image\_to\_model                                                       | 42.2 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v2.0-20240919, type: multiview\_to\_model                                                   | 42.2 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v2.0-20240919, type: text\_to\_model                                                        | 21.1 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v2.5-20250123, type: image\_to\_model                                                       | 42.2 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v2.5-20250123, type: multiview\_to\_model                                                   | 42.2 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v2.5-20250123, type: text\_to\_model                                                        | 21.1 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v3.0-20250812, type: image\_to\_model                                                       | 42.2 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v3.0-20250812, type: multiview\_to\_model                                                   | 42.2 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v3.0-20250812, type: text\_to\_model                                                        | 21.1 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v3.1, type: image\_to\_model                                                                | 42.2 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v3.1, type: multiview\_to\_model                                                            | 42.2 / run  | 3D       |
| Tripo Generation (no textures) Product   | model: v3.1, type: text\_to\_model                                                                 | 21.1 / run  | 3D       |
| Tripo Style Product                      | NA                                                                                                 | 10.55 / run | 3D       |
| Tripo Quadrangular Product               | NA                                                                                                 | 10.55 / run | 3D       |
| Tripo Add Texture Product                | texture\_quality: detailed                                                                         | 42.2 / run  | 3D       |
| Tripo Add Texture Product                | texture\_quality: standard                                                                         | 21.1 / run  | 3D       |
| Tripo Post-Processing Product            | type: animate\_retarget                                                                            | 21.1 / run  | 3D       |
| Tripo Post-Processing Product            | type: animate\_rig                                                                                 | 52.75 / run | 3D       |
| Tripo Post-Processing Product            | type: stylize\_model                                                                               | 42.2 / run  | 3D       |
| Tripo Convert Product                    | convert\_format: advanced                                                                          | 21.1 / run  | 3D       |
| Tripo Convert Product                    | convert\_format: basic                                                                             | 10.55 / run | 3D       |
| Tripo V1-4 Generation Product            | type: image\_to\_model                                                                             | 63.3 / run  | 3D       |
| Tripo V1-4 Generation Product            | type: refine\_model                                                                                | 63.3 / run  | 3D       |
| Tripo V1-4 Generation Product            | type: text\_to\_model                                                                              | 42.2 / run  | 3D       |
| Tripo Geometry Quality Product           | geometry\_quality: detailed                                                                        | 42.2 / run  | 3D       |
| Tripo P1 Generation Product              | model: P1-20260311, type: text\_to\_model, output\_mode: Geometry only                             | 63.3 / run  | 3D       |
| Tripo P1 Generation Product              | model: P1-20260311, type: text\_to\_model, output\_mode: Textured, texture\_quality: standard      | 84.4 / run  | 3D       |
| Tripo P1 Generation Product              | model: P1-20260311, type: text\_to\_model, output\_mode: Textured, texture\_quality: detailed      | 105.5 / run | 3D       |
| Tripo P1 Generation Product              | model: P1-20260311, type: image\_to\_model, output\_mode: Geometry only                            | 84.4 / run  | 3D       |
| Tripo P1 Generation Product              | model: P1-20260311, type: image\_to\_model, output\_mode: Textured, texture\_quality: standard     | 105.5 / run | 3D       |
| Tripo P1 Generation Product              | model: P1-20260311, type: image\_to\_model, output\_mode: Textured, texture\_quality: detailed     | 126.6 / run | 3D       |
| Tripo P1 Generation Product              | model: P1-20260311, type: multiview\_to\_model, output\_mode: Geometry only                        | 84.4 / run  | 3D       |
| Tripo P1 Generation Product              | model: P1-20260311, type: multiview\_to\_model, output\_mode: Textured, texture\_quality: standard | 105.5 / run | 3D       |
| Tripo P1 Generation Product              | model: P1-20260311, type: multiview\_to\_model, output\_mode: Textured, texture\_quality: detailed | 126.6 / run | 3D       |

## Vidu

### Video Generation — Q3

| Product Name                     | Configuration                           | Credits     | Category |
| :------------------------------- | :-------------------------------------- | :---------- | :------- |
| Vidu Q3 Video Generation Product | model: vidu-q3-pro, resolution: 1080P   | 33.76 / sec | Video    |
| Vidu Q3 Video Generation Product | model: vidu-q3-pro, resolution: 720P    | 31.65 / sec | Video    |
| Vidu Q3 Video Generation Product | model: vidu-q3-pro, resolution: 540P    | 14.77 / sec | Video    |
| Vidu Q3 Video Generation Product | model: vidu-q3-turbo, resolution: 1080P | 16.88 / sec | Video    |
| Vidu Q3 Video Generation Product | model: vidu-q3-turbo, resolution: 720P  | 12.66 / sec | Video    |
| Vidu Q3 Video Generation Product | model: vidu-q3-turbo, resolution: 540P  | 8.44 / sec  | Video    |

### Video Generation — Q2

> Off-peak price is half the normal price. Decimals round up.

| Product Name                     | Configuration                                                            | Credits                             | Category |
| :------------------------------- | :----------------------------------------------------------------------- | :---------------------------------- | :------- |
| Vidu Q2 Video Generation Product | model: q2-turbo, type: img2video / start-end2video, resolution: 540P     | Starts at 6.33, +2.11/sec           | Video    |
| Vidu Q2 Video Generation Product | model: q2-turbo, type: img2video / start-end2video, resolution: 720P     | Starts at 8.44, +10.55/sec after 2s | Video    |
| Vidu Q2 Video Generation Product | model: q2-turbo, type: img2video / start-end2video, resolution: 1080P    | Starts at 36.92, +10.55/sec         | Video    |
| Vidu Q2 Video Generation Product | model: q2-pro, type: img2video / start-end2video, resolution: 540P       | Starts at 8.44, +5.28/sec after 2s  | Video    |
| Vidu Q2 Video Generation Product | model: q2-pro, type: img2video / start-end2video, resolution: 720P       | Starts at 15.82, +10.55/sec         | Video    |
| Vidu Q2 Video Generation Product | model: q2-pro, type: img2video / start-end2video, resolution: 1080P      | Starts at 58.03, +15.82/sec         | Video    |
| Vidu Q2 Video Generation Product | model: q2-pro-fast, type: img2video / start-end2video, resolution: 720P  | Starts at 8.44, +2.11/sec           | Video    |
| Vidu Q2 Video Generation Product | model: q2-pro-fast, type: img2video / start-end2video, resolution: 1080P | Starts at 16.88, +4.22/sec          | Video    |
| Vidu Q2 Video Generation Product | model: q2, type: text2video, resolution: 540P                            | Starts at 10.55, +2.11/sec          | Video    |
| Vidu Q2 Video Generation Product | model: q2, type: text2video, resolution: 720P                            | Starts at 15.82, +5.28/sec          | Video    |
| Vidu Q2 Video Generation Product | model: q2, type: text2video, resolution: 1080P                           | Starts at 21.1, +10.55/sec          | Video    |
| Vidu Q2 Video Generation Product | model: q2, type: reference2video, resolution: 540P                       | Starts at 15.82, +5.28/sec          | Video    |
| Vidu Q2 Video Generation Product | model: q2, type: reference2video, resolution: 720P                       | Starts at 26.38, +5.28/sec          | Video    |
| Vidu Q2 Video Generation Product | model: q2, type: reference2video, resolution: 1080P                      | Starts at 79.12, +10.55/sec         | Video    |
| Vidu Q2 Video Generation Product | model: q2-pro, type: reference2video, resolution: 540P                   | Starts at 21.1, +5.28/sec           | Video    |
| Vidu Q2 Video Generation Product | model: q2-pro, type: reference2video, resolution: 720P                   | Starts at 31.65, +5.28/sec          | Video    |
| Vidu Q2 Video Generation Product | model: q2-pro, type: reference2video, resolution: 1080P                  | Starts at 89.67, +10.55/sec         | Video    |

### Video Generation — Q1

| Product Name                     | Configuration                                                                          | Credits    | Category |
| :------------------------------- | :------------------------------------------------------------------------------------- | :--------- | :------- |
| Vidu Q1 Video Generation Product | model: vidu-q1, type: reference2video, style: general, duration: 5s, resolution: 1080P | 84.4 / run | Video    |
| Vidu Q1 Video Generation Product | model: vidu-q1, type: img2video, style: general, duration: 5s, resolution: 1080P       | 84.4 / run | Video    |
| Vidu Q1 Video Generation Product | model: vidu-q1, type: start-end2video, style: general, duration: 5s, resolution: 1080P | 84.4 / run | Video    |
| Vidu Q1 Video Generation Product | model: vidu-q1, type: text2video, style: general, duration: 5s, resolution: 1080P      | 84.4 / run | Video    |
| Vidu Q1 Video Generation Product | model: vidu-q1, type: text2video, style: anime, duration: 5s, resolution: 1080P        | 84.4 / run | Video    |

### Video Generation — Vidu 2.0

| Product Name                      | Configuration                                                           | Credits     | Category |
| :-------------------------------- | :---------------------------------------------------------------------- | :---------- | :------- |
| Vidu 2.0 Video Generation Product | model: vidu-2.0, type: img2video, duration: 4S, resolution: 360P        | 21.1 / run  | Video    |
| Vidu 2.0 Video Generation Product | model: vidu-2.0, type: img2video, duration: 4S, resolution: 720P        | 42.2 / run  | Video    |
| Vidu 2.0 Video Generation Product | model: vidu-2.0, type: img2video, duration: 4S, resolution: 1080P       | 105.5 / run | Video    |
| Vidu 2.0 Video Generation Product | model: vidu-2.0, type: img2video, duration: 8S, resolution: 720P        | 105.5 / run | Video    |
| Vidu 2.0 Video Generation Product | model: vidu-2.0, type: reference2video, duration: 4S, resolution: 360P  | 84.4 / run  | Video    |
| Vidu 2.0 Video Generation Product | model: vidu-2.0, type: reference2video, duration: 4S, resolution: 720P  | 84.4 / run  | Video    |
| Vidu 2.0 Video Generation Product | model: vidu-2.0, type: start-end2video, duration: 4S, resolution: 360P  | 21.1 / run  | Video    |
| Vidu 2.0 Video Generation Product | model: vidu-2.0, type: start-end2video, duration: 4S, resolution: 720P  | 42.2 / run  | Video    |
| Vidu 2.0 Video Generation Product | model: vidu-2.0, type: start-end2video, duration: 4S, resolution: 1080P | 105.5 / run | Video    |
| Vidu 2.0 Video Generation Product | model: vidu-2.0, type: start-end2video, duration: 8S, resolution: 720P  | 105.5 / run | Video    |

### Image Generation

| Product Name                  | Configuration                                                               | Credits     | Category |
| :---------------------------- | :-------------------------------------------------------------------------- | :---------- | :------- |
| Vidu Image Generation Product | model: viduq2, type: Text to Image, resolution: 1080P                       | 6.33 / run  | Image    |
| Vidu Image Generation Product | model: viduq2, type: Text to Image, resolution: 2K                          | 8.44 / run  | Image    |
| Vidu Image Generation Product | model: viduq2, type: Text to Image, resolution: 4K                          | 10.55 / run | Image    |
| Vidu Image Generation Product | model: viduq2, type: Reference to Image, ref images: 1–3, resolution: 1080P | 8.44 / run  | Image    |
| Vidu Image Generation Product | model: viduq2, type: Reference to Image, ref images: 1–3, resolution: 2K    | 12.66 / run | Image    |
| Vidu Image Generation Product | model: viduq2, type: Reference to Image, ref images: 1–3, resolution: 4K    | 21.1 / run  | Image    |
| Vidu Image Generation Product | model: viduq2, type: Reference to Image, ref images: 4–7, resolution: 1080P | 10.55 / run | Image    |
| Vidu Image Generation Product | model: viduq2, type: Reference to Image, ref images: 4–7, resolution: 2K    | 16.88 / run | Image    |
| Vidu Image Generation Product | model: viduq2, type: Reference to Image, ref images: 4–7, resolution: 4K    | 31.65 / run | Image    |
| Vidu Image Generation Product | model: viduq1, type: Reference to Image, ref images: 1–7, resolution: 1080P | 21.1 / run  | Image    |

### Video Extension

| Product Name                 | Configuration                      | Credits                     | Category |
| :--------------------------- | :--------------------------------- | :-------------------------- | :------- |
| Vidu Video Extension Product | model: q2-turbo, resolution: 540P  | Starts at 10.55, +2.11/sec  | Video    |
| Vidu Video Extension Product | model: q2-turbo, resolution: 720P  | Starts at 15.82, +5.28/sec  | Video    |
| Vidu Video Extension Product | model: q2-turbo, resolution: 1080P | Starts at 42.2, +10.55/sec  | Video    |
| Vidu Video Extension Product | model: q2-pro, resolution: 540P    | Starts at 15.82, +5.28/sec  | Video    |
| Vidu Video Extension Product | model: q2-pro, resolution: 720P    | Starts at 31.65, +10.55/sec | Video    |
| Vidu Video Extension Product | model: q2-pro, resolution: 1080P   | Starts at 63.3, +15.82/sec  | Video    |

### Other Features

| Product Name             | Configuration | Credits     | Category |
| :----------------------- | :------------ | :---------- | :------- |
| Vidu Lip Sync Product    | —             | 21.1 / 5s   | Video    |
| Vidu Motion Sync Product | —             | 10.55 / sec | Video    |

## WAN

| Product Name                 | Configuration                                | Credits     | Category |
| :--------------------------- | :------------------------------------------- | :---------- | :------- |
| Wan Image Generation Product | model: wan2.5-i2i-preview                    | 6.33 / run  | Image    |
| Wan Image Generation Product | model: wan2.5-t2i-preview                    | 6.33 / run  | Image    |
| Wan Image Generation Product | model: wan2.6-t2i                            | 6.33 / run  | Image    |
| Wan Video Generation Product | model: wan2.5-i2v-preview, resolution: 1080P | 31.65 / sec | Video    |
| Wan Video Generation Product | model: wan2.5-i2v-preview, resolution: 480P  | 10.55 / sec | Video    |
| Wan Video Generation Product | model: wan2.5-i2v-preview, resolution: 720P  | 21.1 / sec  | Video    |
| Wan Video Generation Product | model: wan2.5-t2v-preview, resolution: 1080P | 31.65 / sec | Video    |
| Wan Video Generation Product | model: wan2.5-t2v-preview, resolution: 480P  | 10.55 / sec | Video    |
| Wan Video Generation Product | model: wan2.5-t2v-preview, resolution: 720P  | 21.1 / sec  | Video    |
| Wan Video Generation Product | model: wan2.6-i2v, resolution: 1080P         | 31.65 / sec | Video    |
| Wan Video Generation Product | model: wan2.6-i2v, resolution: 720P          | 21.1 / sec  | Video    |
| Wan Video Generation Product | model: wan2.6-r2v, resolution: 1080P         | 31.65 / sec | Video    |
| Wan Video Generation Product | model: wan2.6-r2v, resolution: 720P          | 21.1 / sec  | Video    |
| Wan Video Generation Product | model: wan2.6-t2v, resolution: 1080P         | 31.65 / sec | Video    |
| Wan Video Generation Product | model: wan2.6-t2v, resolution: 720P          | 21.1 / sec  | Video    |
| Wan Video Generation Product | model: wan2.7-i2v, resolution: 1080P         | 31.65 / sec | Video    |
| Wan Video Generation Product | model: wan2.7-i2v, resolution: 720P          | 21.1 / sec  | Video    |
| Wan Video Generation Product | model: wan2.7-r2v, resolution: 1080P         | 31.65 / sec | Video    |
| Wan Video Generation Product | model: wan2.7-r2v, resolution: 720P          | 21.1 / sec  | Video    |
| Wan Video Generation Product | model: wan2.7-t2v, resolution: 1080P         | 31.65 / sec | Video    |
| Wan Video Generation Product | model: wan2.7-t2v, resolution: 720P          | 21.1 / sec  | Video    |
| Wan Video Generation Product | model: wan2.7-videoedit, resolution: 1080P   | 31.65 / sec | Video    |
| Wan Video Generation Product | model: wan2.7-videoedit, resolution: 720P    | 21.1 / sec  | Video    |

## Wavespeed

| Product Name       | Configuration                     | Credits     | Category |
| :----------------- | :-------------------------------- | :---------- | :------- |
| Wavespeed Flashvsr | resolution: 1080p                 | 18.99 / run | Image    |
| Wavespeed Flashvsr | resolution: 2k                    | 25.32 / run | Image    |
| Wavespeed Flashvsr | resolution: 4k                    | 33.76 / run | Image    |
| Wavespeed Flashvsr | resolution: 720p                  | 12.66 / run | Image    |
| Wavespeed Image    | endpoint: seedvr2                 | 2.11 / run  | Image    |
| Wavespeed Image    | endpoint: ultimate-image-upscaler | 12.66 / run | Image    |

## xAI

<Note>
  Video endpoints charge for moderated content.
</Note>

| Product Name                                 | Configuration                                                                                           | Credits     | Category |
| :------------------------------------------- | :------------------------------------------------------------------------------------------------------ | :---------- | :------- |
| xAI Image Generation                         | endpoint: v1/images/generations, model: grok-imagine-image-beta, resolution: 1k                         | 6.96 / run  | Image    |
| xAI Image Generation                         | endpoint: v1/images/generations, model: grok-imagine-image-quality, resolution: 1k                      | 10.55 / run | Image    |
| xAI Image Generation                         | endpoint: v1/images/generations, model: grok-imagine-image-quality, resolution: 2k                      | 14.77 / run | Image    |
| xAI Image Edit Output                        | endpoint: v1/images/edits, model: grok-imagine-image-beta, resolution: 1k                               | 6.96 / run  | Image    |
| xAI Image Edit Output                        | endpoint: v1/images/edits, model: grok-imagine-image-quality, resolution: 1k                            | 10.55 / run | Image    |
| xAI Image Edit Output                        | endpoint: v1/images/edits, model: grok-imagine-image-quality, resolution: 2k                            | 14.77 / run | Image    |
| xAI Image Edit Input                         | endpoint: v1/images/edits, model: grok-imagine-image-beta, resolution: 1k                               | 0.42 / run  | Image    |
| xAI Image Edit Input                         | endpoint: v1/images/edits, model: grok-imagine-image-quality                                            | 2.11 / run  | Image    |
| xAI Video Generation Output Video Per Second | endpoint: v1/videos/generations, model: grok-imagine-video-beta, resolution: 480p                       | 38.19 / sec | Video    |
| xAI Video Generation Output Video Per Second | endpoint: v1/videos/generations, model: grok-imagine-video-beta, resolution: 720p                       | 38.19 / sec | Video    |
| xAI Video Generation Output Video Per Second | endpoint: v1/videos/generations, model: grok-imagine-video-1.5-preview, resolution: 480p                | 24.14 / sec | Video    |
| xAI Video Generation Output Video Per Second | endpoint: v1/videos/generations, model: grok-imagine-video-1.5-preview, resolution: 720p                | 42.24 / sec | Video    |
| xAI Video Generation Input Image             | endpoint: v1/videos/generations, model: grok-imagine-video-1.5-preview, type: image-to-video            | 3.02 / sec  | Video    |
| xAI Video Generation Input Image             | endpoint: v1/videos/generations, model: grok-imagine-video-beta, resolution: 480p, type: image-to-video | 0.42 / sec  | Video    |
| xAI Video Generation Input Image             | endpoint: v1/videos/generations, model: grok-imagine-video-beta, resolution: 720p, type: image-to-video | 0.42 / sec  | Video    |
| xAI Video Edit Input+Output Video Per Second | endpoint: v1/videos/edits, model: grok-imagine-video-beta, resolution: 480p                             | 40.3 / sec  | Video    |
| xAI Image Edit Input                         | endpoint: v1/images/edits, model: v1/images/edits, resolution: 1k                                       | 0.42 / run  | Image    |
| xAI Video Edit Input+Output Video Per Second | endpoint: v1/videos/generations, model: grok-imagine-video-beta, resolution: 480p                       | 40.3 / sec  | Video    |
| xAI Credits                                  | NA                                                                                                      | 2.11 / run  | Image    |

## Other (Cloud)

| Product Name      | Configuration             | Credits    | Category |
| :---------------- | :------------------------ | :--------- | :------- |
| GPU Hours Product | gpu\_type: rtx\_pro\_6000 | 0.27 / sec | Image    |


# Recraft Text to Image Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/recraft/recraft-text-to-image

Learn how to use the Recraft Text to Image Partner node in ComfyUI

The [Recraft Text to Image](/built-in-nodes/partner-node/image/recraft/recraft-text-to-image) node allows you to create high-quality images in various styles using Recraft AI's image generation technology based on text descriptions.

In this guide, we'll show you how to set up a text-to-image workflow using this node.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Recraft Text to Image Partner Nodes Workflow

### 1. Download the Workflow File

The workflow information is included in the metadata of the image below. Download and drag it into ComfyUI to load the workflow.

![Recraft Text to Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/recraft/t2i/recraft_t2i.png)

### 2. Follow the Steps to Run the Workflow

<img alt="Recraft Text to Image Workflow Steps" />

Follow these numbered steps to run the basic workflow:

1. (Optional) Change the `Recraft Color RGB` in the `Color` node to your desired color
2. (Optional) Modify the `Recraft Style` node to control the visual style, such as digital art, realistic photo, or logo design. This group includes other style nodes you can enable as needed
3. (Optional) Edit the `prompt` parameter in the `Recraft Text to Image` node. You can also change the `size` parameter
4. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to generate the image
5. After the API returns the result, you can view the generated image in the `Save Image` node. The image will also be saved to the `ComfyUI/output/` directory

> (Optional) We've included a **Convert to SVG** group in the workflow. Since the `Recraft Vectorize Image` node in this group consumes additional credits, enable it only when you need to convert the generated image to SVG format

### 3. Additional Notes

* **Recraft Style**: Offers various preset styles like realistic photos, digital art, and logo designs
* **Seed Parameter**: Only used to determine if the node should run again, the actual generation result is not affected by the seed value

## Related Node Documentation

Check the following documentation for detailed parameter settings of the nodes

<Card title="Recraft Text to Image Node Documentation" icon="book" href="/built-in-nodes/partner-node/image/recraft/recraft-text-to-image">
  Documentation for the Recraft Text to Image Partner node
</Card>

<Card title="Recraft Style Node Documentation" icon="book" href="/built-in-nodes/partner-node/image/recraft/recraft-style-realistic-image">
  Documentation for the Recraft Style - Realistic Image Partner node
</Card>

<Card title="Recraft Controls Node Documentation" icon="book" href="/built-in-nodes/partner-node/image/recraft/recraft-controls">
  Documentation for the Recraft Controls Partner node
</Card>


# Recraft V4 Image & Vector Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/recraft/recraft-v4

Generate professional images and production-ready vectors with Recraft V4 in ComfyUI

Recraft V4 is a new image generation model built for professional design work. It was developed in collaboration with designers and optimized for composition, lighting, color relationships, and material realism.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## What's new in V4

* **Raster + vector in one model** — photorealistic images, stylized illustrations, and production-ready SVGs from the same model
* **Better detail** — cleaner textures, more accurate lighting, tighter geometry. Holds up in complex scenes
* **Faces and anatomy that work** — reliable proportions and expressions, even with multiple subjects or action poses
* **Text rendering** — legible text for signage, packaging, infographics. Handles short and mid-length phrases well
* **SVG output** — editable vectors with clean lines and proper color segmentation. Production-quality vector output
* **Prompt accuracy** — follows detailed creative direction closely, including spatial relationships, materials, and reflections
* **V4 Pro** — same model, higher resolution. Outputs at 2048×2048 for print and large-format work

## Recraft V4 text to image workflow

<Card title="Run in Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_recraft_v4_t2i&utm_source=docs&utm_medium=referral&utm_campaign=recraft_v4">
  Open in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_recraft_v4_t2i.json">
  Download JSON or search "Recraft V4 Text to Image" in Template Library
</Card>

### Steps to run the workflow

1. (Optional) Modify the `Recraft Style` node to control the visual style
2. (Optional) Edit the `prompt` parameter in the `Recraft Text to Image` node
3. (Optional) Change the `size` parameter for different output dimensions
4. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to generate the image
5. After the API returns the result, view the generated image in the `Save Image` node

### Image showcase

![Street photography example](https://substack-post-media.s3.amazonaws.com/public/images/9fe39ca3-b0ba-4f26-aa26-b3eaa11185de_1792x1024.png)
*Full-body editorial street photo of a young person wearing an oversized vintage Fear of God flannel layered over a faded Pyrex Vision hoodie, distressed wide-leg denim, original Just Don python-brim snapback, and beat-up Nike Dunk Lows. Shot on a gritty Brooklyn sidewalk, golden hour, 35mm film grain.*

![Hypebeast editorial](https://substack-post-media.s3.amazonaws.com/public/images/9fd968f1-f5f9-42a9-973d-74bd163babde_2560x1664.png)
*Full outfit shot: electric blue and coral camo hoodie, matching camo joggers, white G-Shock watch, matte black techwear crossbody harness bag, and New Balance 550s in a cream colorway. Concrete parking garage backdrop, harsh fluorescent overhead lighting casting sharp shadows.*

![Action shot](https://substack-post-media.s3.amazonaws.com/public/images/a8643f80-8cc4-4246-a95a-bed1f9ee10f1_2560x1664.png)
*Fish-eye lens, shot from inside an empty concrete pool — a guy in a shearling bomber and transparent PVC shell is mid-kickflip at the lip of the pool directly above the camera, board separating from his feet, his layered outfit catching air and fanning open revealing the hockey jersey underneath.*

## Recraft V4 text to vector workflow

Recraft V4 can generate production-ready SVG vector outputs directly. This is useful for logos, icons, brand assets, or anything that needs to scale. SVG outputs are compatible with Illustrator, Figma, and Sketch.

<Card title="Run in Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_recraft_v4_text_to_vector&utm_source=docs&utm_medium=referral&utm_campaign=recraft_v4">
  Open in Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_recraft_v4_text_to_vector.json">
  Download JSON or search "Recraft V4 Text to Vector" in Template Library
</Card>

### Vector showcase

![Rooftop illustration](https://substack-post-media.s3.amazonaws.com/public/images/571c5214-5c7f-43f9-81c4-80cad1e5578b_1792x1024.png)
*A group of friends lounging on a rooftop at sunset, string lights overhead, one person tending a small grill, another strumming a ukulele, a dog napping on a blanket beside a cooler — warm, relaxed, retro lifestyle illustration*

![Boombox illustration](https://substack-post-media.s3.amazonaws.com/public/images/748f04c7-50b9-433d-93cb-c619984c8e89_1792x1024.png)
*A giant neon boombox blasting music, with lightning bolts and sound waves exploding out of the speakers, melting cassette tapes swirling around it, and a pair of oversized headphones draped on top — bold, chaotic, and electrifying*

![Kitten sticker](https://substack-post-media.s3.amazonaws.com/public/images/3ddce7b4-8f37-4256-bd93-2e5796dfacca_1024x1024.png)
*Adorable kitten sticker, the kitten is using ComfyUI on a little tiny laptop*

## Additional notes

* **Recraft Style**: Offers various preset styles like realistic photos, digital art, and logo designs
* **Seed Parameter**: Only used to determine if the node should run again; the actual generation result is not affected by the seed value


# Reve Image Create, Edit, and Remix in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/reve/reve-image

Learn how to use Reve Partner nodes in ComfyUI for high-quality image generation, editing, and remixing at up to 4K resolution

Reve is an image generation model available in ComfyUI through Partner Nodes. It supports text-to-image generation at up to **4K resolution**, image editing, and image remixing through three dedicated nodes.

## About Reve

**Key features:**

* **Up to 4K resolution**: Generates sharp, detailed images at high resolutions
* **Built-in aesthetic training**: Produces results suited for fashion editorial, cinematic, and natural lighting styles
* **Image editing**: Modifies lighting conditions, color grading, and adds motion effects to existing images
* **Image remixing**: Combines elements from reference images into a target image while preserving consistency

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Reve Create

The Reve Image Create node generates images from text prompts. The model performs well with prompts describing fashion editorial styles, specific lighting conditions, natural textures, and motion.

<Card title="Try on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_reve_image_create&utm_source=docs&utm_medium=inhouse_social&utm_campaign=reve_model_launch">
  Run the Reve Image Create workflow on Comfy Cloud.
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_reve_image_create.json">
  Download the workflow JSON file for local use.
</Card>

### Example outputs

![Fashion editorial portrait with dual-tone lighting](https://substack-post-media.s3.amazonaws.com/public/images/279c7067-7c65-4bb3-95ef-6d1ec934050b_2720x1536.png)

```
A high-fashion editorial portrait of a young East Asian model with long, straight black hair and thick bangs, crouched in a studio setting. She wears a minimalist, muted beige dress. The image features a cinematic dual-tone lighting setup, where the left side is washed in a soft greenish-yellow glow and the right side is cast in cool, muted blue-grey, creating a subtle color bleed effect. There is a slight motion blur, with the subject looking directly at the camera with a calm, neutral expression. High-end fashion magazine aesthetic, soft focus background, structured silhouette.
```

![Red sports car speeding through the night](https://substack-post-media.s3.amazonaws.com/public/images/5563d900-336c-42d0-b48c-6978883ae4ff_1360x768.png)

```
A high-speed, cinematic capture of a vibrant red sports car speeding through the night. The camera angle is positioned near the rear-three-quarter view, emphasizing the sleek, metallic curves and the car's aerodynamic design. The entire background is transformed into a dramatic radial blur of brilliant yellow, orange, and white light streaks, suggesting extreme velocity. The car's surface reflects the warm ambient lights of the city, contrasting sharply with the deep, dark blue of the night sky.
```

![Woman with glowing orb and amber tones](https://substack-post-media.s3.amazonaws.com/public/images/fea68697-1783-4f84-99a7-3065b4df577c_2720x1536.png)

```
A cinematic photograph of a woman with a bob haircut looking at her reflection in a mirror, her hands gently cradling a brilliant, glowing spherical white orb. The image is saturated in deep orange and amber tones, with heavy light leaks and lens flares washing out the center of the frame as the sphere radiates subtle, ethereal light. The composition features a soft, dreamy focus with significant analog film grain, creating a nostalgic atmosphere where the reflected face in the mirror appears slightly blurred and obscured by the warmth of the light leakage.
```

![Rally car drifting near a volcano](https://substack-post-media.s3.amazonaws.com/public/images/b73ad263-3045-4579-9e46-b6faaace9e5f_1360x768.png)

```
A high-action, wide-angle nighttime shot of a legendary Audi Quattro rally car drifting through a barren rocky field at the base of a volcano. The car is coated in white and black. Powerful auxiliary spotlights on the front of the car cast a bright, warm glow, catching the thick dust kicked up by the aggressive tread of the tires. In the background, out-of-focus volcano spraying lava. The scene is cold and dark, with the intense light from the lava creating dramatic contrast.
```

The following examples demonstrate 4K resolution output with fine detail preservation:

![Jaguar F-Type on a coastal trail at twilight](https://substack-post-media.s3.amazonaws.com/public/images/bf51794c-7044-4b1e-a5f1-1857ff78fb22_5440x3072.png)

```
A wide-angle landscape photograph of a solitary Jaguar F-Type car in British green, on a dirt trail facing a distant beach at twilight. The sky features dramatic long-exposure cloud streaks radiating from a low sun on the horizon. The foreground is dominated by jagged limestone rocks and blades of grass, leading the viewer's eye along a path that cuts through grassy hills toward the water. The lighting is cool and moody, casting deep shadows against the golden glow of the setting sun.
```

![White owl in a desert at golden hour](https://substack-post-media.s3.amazonaws.com/public/images/1af7e42a-aded-420b-b6b5-d2f96e5c5788_2720x1536.png)

```
A minimalist wide shot of a vast white sand dune desert during golden hour. A white owl with its wings spread is in the foreground. Soft warm sunlight grazing the tops of the dunes, casting long shadows. Sparse, golden-brown desert shrubs are scattered across the ripples, with a prominent patch of dry, cracked, hexagonal mud in the bottom right foreground. In the far distance, a hazy, ethereal range of mountains rests against a pale, washed-out sky.
```

## Reve Edit

The Reve Image Edit node modifies existing images based on text instructions. It supports editing lighting conditions, color grading, and adding motion effects.

<Card title="Try on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_reve_image_edit&utm_source=docs&utm_medium=inhouse_social&utm_campaign=reve_model_launch">
  Run the Reve Image Edit workflow on Comfy Cloud.
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_reve_image_edit.json">
  Download the workflow JSON file for local use.
</Card>

### Example outputs

![Motion blur edit example](https://substack-post-media.s3.amazonaws.com/public/images/1842aadb-ae80-45e7-be65-c6cc8e7aaea5_1024x1024.png)

```
Add a cinematic horizontal streaks motion blur to the subject's body. The hand stays in clear focus.
```

![Lighting edit example](https://substack-post-media.s3.amazonaws.com/public/images/7cfec95f-40b0-4a09-9991-c37b6919155b_1920x1080.png)

```
The lighting is cold, soft glow emits from the window.
```

![Side profile edit example](https://substack-post-media.s3.amazonaws.com/public/images/52617409-4c10-4944-985d-ee86b01bde05_1024x1024.png)

```
Side profile shot of the subject, his hand is grabbing the sunglasses.
```

## Reve Remix

The Reve Image Remix node uses elements from reference images as layers and applies them to a target image. This allows you to transfer specific visual properties such as shadows, color grading, or aesthetic styles between images.

<Card title="Try on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_reve_image_remix&utm_source=docs&utm_medium=inhouse_social&utm_campaign=reve_model_launch">
  Run the Reve Image Remix workflow on Comfy Cloud.
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_reve_image_remix.json">
  Download the workflow JSON file for local use.
</Card>

### Example outputs

![Shadow transfer remix example](https://substack-post-media.s3.amazonaws.com/public/images/bc91f624-5d2f-47d9-8299-31e06e72fc59_1920x1080.png)

```
Edit the shadows on the subject in image 1 to match the shadows from image 2.
```

![Color grading transfer remix example](https://substack-post-media.s3.amazonaws.com/public/images/87fc38a6-2cce-4de6-aa48-520fbdecff2a_1920x1080.png)

```
Transfer the color grading and aesthetic from image 2 onto image 1.
```

## Get started

1. **Update** ComfyUI to the latest version or visit [Comfy Cloud](https://cloud.comfy.org/?utm_source=docs).
2. **Find** the Reve Image Create, Reve Image Remix, and Reve Image Edit nodes in the Node Library or Templates in the left sidebar.
3. **Drop a node** on your canvas to begin.

## Available nodes

| Node                  | Type          | Description                                                         |
| --------------------- | ------------- | ------------------------------------------------------------------- |
| **Reve Image Create** | Text-to-Image | Generates images at up to 4K resolution from text prompts           |
| **Reve Image Edit**   | Image Edit    | Modifies lighting, color grading, and motion in existing images     |
| **Reve Image Remix**  | Image Remix   | Transfers visual properties from reference images to a target image |


# Rodin Partner Nodes Model Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/rodin/model-generation

This article will introduce how to use Rodin node's API in ComfyUI for model generation

Hyper3D Rodin (hyper3d.ai) is a platform focused on rapidly generating high-quality, production-ready 3D models and materials through artificial intelligence.
ComfyUI has now natively integrated the corresponding Rodin model generation API, allowing you to conveniently use the related nodes in ComfyUI for model generation.

Currently, ComfyUI's Partner nodes support the following Rodin model generation capabilities:

* Single-view model generation
* Multi-view model generation
* Model generation with different levels of detail

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Single-view Model Generation Workflow

### 1. Workflow File Download

Download the file below and drag it into ComfyUI to load the corresponding workflow.

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/rodin_image_to_model.json">
  <p>Download Json Format Workflow File</p>
</a>

Download the image below as input image

![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/doll.jpg)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Rodin Image to Model Step Guide" />

You can refer to the numbers in the image to complete the basic text-to-image workflow execution:

1. In the `Load Image` node, load the provided input image
2. (Optional) In `Rodin 3D Generate - Regular Generate` adjust the corresponding parameters
   * polygon\_count: You can set different polygon counts, the higher the value, the smoother and more detailed the model
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation. After the workflow completes, the corresponding model will be automatically saved to the `ComfyUI/output/Rodin` directory
4. In the `Preview 3D` node, click to expand the menu
5. Select `Export` to directly export the corresponding model

## Multi-view Model Generation Workflow

The corresponding `Rodin 3D Generate - Regular Generate` allows up to 5 image inputs

### 1. Workflow File Download

You can modify the single-view workflow to a multi-view workflow, or directly download the workflow file below

Download the file below and drag it into ComfyUI to load the corresponding workflow.

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/multiview_to_model/api_rodin_multiview_to_model.json">
  <p>Download Json Format Workflow File</p>
</a>

Download the images below as input images

![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/multiview_to_model/front.jpg)
![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/multiview_to_model/back.jpg)
![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/rodin/multiview_to_model/left.jpg)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Rodin Image to Model Step Guide" />

You can refer to the numbers in the image to complete the basic text-to-image workflow execution:

1. In the `Load Image` node, load the provided input images
2. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation. After the workflow completes, the corresponding model will be automatically saved to the `ComfyUI/output/Rodin` directory
3. In the `Preview 3D` node, click to expand the menu
4. Select `Export` to directly export the corresponding model

## Other Related Nodes

Currently, Rodin provides different types of model generation nodes in ComfyUI, since the corresponding input conditions are the same as the workflow introduced in this article, you can enable them as needed. In addition, we have provided corresponding nodes in the corresponding templates, you can also modify the corresponding node mode as needed to enable them

<img alt="Rodin Other Related Nodes" />


# Runway Partner Nodes Image Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/runway/image-generation

This article will introduce how to use Runway nodes in ComfyUI for text-to-image and reference-to-image generation

Runway is a company focused on generative AI, providing powerful image generation capabilities. Its models support features such as style transfer, image extension, and detail control. Currently, ComfyUI has integrated the Runway API, allowing you to directly use the related nodes in ComfyUI for image generation.

In this guide, we will walk you through the following workflows:

* Text-to-image
* Reference-to-image

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Runway Image Text-to-Image Workflow

### 1. Workflow File Download

The image below contains workflow information in its `metadata`. Please download and drag it into ComfyUI to load the corresponding workflow.

![ComfyUI Runway Image Text to Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/image/text_to_image.png)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Runway Image Text to Image Step Guide" />

You can refer to the numbers in the image to complete the basic text-to-image workflow execution:

1. In the `Runway Text to Image` node, input your prompt in the `prompt` field
2. (Optional) Adjust the `ratio` setting to set different output aspect ratios
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute image generation.
4. After waiting for the API to return results, you can view the generated image in the `Save Image` node (right-click to save). The corresponding image will also be saved to the `ComfyUI/output/` directory.

## Runway Image Reference-to-Image Workflow

### 1. Workflow and Input Image Download

The image below contains workflow information in its `metadata`. Please download and drag it into ComfyUI to load the corresponding workflow.

![ComfyUI Runway Image Reference to Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/image/reference_to_image/runway_reference_to_image.png)

Download the image below for input

![ComfyUI Runway Image Reference to Image Input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/image/reference_to_image/input.png)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Runway Image Reference to Image Step Guide" />

You can refer to the numbers in the image to complete the basic reference-to-image workflow execution:

1. In the `Load Image` node, load the provided input image
2. In the `Runway Text to Image` node, input your prompt in the `prompt` field and adjust dimensions
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute image generation.
4. After waiting for the API to return results, you can view the generated image in the `Save Image` node (right-click to save). The corresponding image will also be saved to the `ComfyUI/output/` directory.


# Runway Partner Nodes Video Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/runway/video-generation

This article will introduce how to use Runway nodes in ComfyUI for video generation workflows

Runway is a company focused on generative AI, providing powerful video generation capabilities. Currently, ComfyUI has integrated the Runway API, allowing you to directly use the related nodes in ComfyUI for video generation.

Currently, ComfyUI natively integrates the following Runway video generation models:

* Runway Gen3a turbo
* Runway Gen4 turbo
* Runway First Last Frame to video

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Gen3a turbo Image-to-Video Workflow

### 1. Workflow File Download

The video below contains workflow information in its `metadata`. Please download and drag it into ComfyUI to load the corresponding workflow.

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/gen3a_turbo_image_to_video/runway_image_to_video_gen3a_turbo.json">
  <p>Download Json Format Workflow File</p>
</a>

Download the image below as input image

![ComfyUI Runway gen3a turbo image to video Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/gen3a_turbo_image_to_video/steampunk.png)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Runway gen3a turbo image to video Step Guide" />

You can refer to the numbers in the image to complete the basic image-to-video workflow execution:

1. In the `Load Image` node, load the provided input image
2. In the `Runway Gen3a turbo` node, set the `prompt` to describe video content, modify the `duration` parameter to set video length, modify the `ratio` parameter to set video aspect ratio
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.
4. After waiting for the API to return results, you can view the generated video in the `Save Video` node (right-click to save). The corresponding video will also be saved to the `ComfyUI/output/` directory.

## Gen4 turbo Image-to-Video Workflow

### 1. Workflow File Download

The video below contains workflow information in its `metadata`. Please download and drag it into ComfyUI to load the corresponding workflow.

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/gen4_turbo_image_to_video/runway_gen4_turo_image_to_video.json">
  <p>Download Json Format Workflow File</p>
</a>

Download the image below as input image

![ComfyUI Runway gen4 turbo image to video Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/gen4_turbo_image_to_video/godfather.jpg)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Runway gen4 turbo image to video Step Guide" />

You can refer to the numbers in the image to complete the basic image-to-video workflow execution:

1. In the `Load Image` node, load the provided input image
2. In the `Runway Gen4 turbo` node, set the `prompt` to describe video content, modify the `duration` parameter to set video length, modify the `ratio` parameter to set video aspect ratio
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.
4. After waiting for the API to return results, you can view the generated video in the `Save Video` node (right-click to save). The corresponding video will also be saved to the `ComfyUI/output/` directory.

## First-Last Frame Video Generation Workflow

### 1. Workflow File Download

The video below contains workflow information in its `metadata`. Please download and drag it into ComfyUI to load the corresponding workflow.

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/first_last_frame_to_video/runway_first_last_frame.json">
  <p>Download Json Format Workflow File</p>
</a>

Download the images below as input images

![ComfyUI Runway gen4 turbo image to video Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/first_last_frame_to_video/first.jpg)
![ComfyUI Runway gen4 turbo image to video Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/runway/first_last_frame_to_video/last.jpg)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Runway gen4 turbo image to video Step Guide" />

You can refer to the numbers in the image to complete the basic first-last frame to video workflow execution:

1. In the `Load Image` node, load the starting frame
2. In the `Load Image` node, load the ending frame
3. In the `Runway First-Last-Frame to Video` node, set the `prompt` to describe video content, modify the `duration` parameter to set video length, modify the `ratio` parameter to set video aspect ratio
4. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation.
5. After waiting for the API to return results, you can view the generated video in the `Save Video` node (right-click to save). The corresponding video will also be saved to the `ComfyUI/output/` directory.


# Sonilo Partner Nodes Official ComfyUI Example
Source: https://docs.comfy.org/tutorials/partner-nodes/sonilo/video-to-music

This article introduces how to use Sonilo Partner nodes for video-to-music and text-to-audio generation in ComfyUI.

Sonilo is an AI-powered video-to-music service that generates soundtracks synchronized to your footage. It analyzes visuals, pacing, and emotional cues to produce music locked to your timeline, frame by frame.

You can drive music generation directly from your ComfyUI node graphs, alongside your existing workflows.

## Highlights

* **Length, pace and emotion alignment** - Music is generated to match the exact duration, pacing, and emotional arc of your video, delivering soundtracks that feel intentionally composed for the content.
* **Instant generation** - Generate full-length, high-quality music in seconds, enabling faster iteration and a seamless creative workflow.
* **Commercial-ready usage** - All generated music includes commercial use rights, making it ready for use across professional, brand, and production environments without additional licensing complexity.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Get started

<Steps>
  <Step title="Update ComfyUI">
    Update ComfyUI to the latest version, or use [Comfy Cloud](https://www.comfy.org/cloud).
  </Step>

  <Step title="Find a Sonilo workflow">
    Open the **Workflow Library**, browse **Templates**, and search for "Sonilo" to find a ready-to-use workflow.
  </Step>

  <Step title="Run the workflow">
    Connect your video source, update the prompt, and click the **Run** button or use `Ctrl(Cmd) + Enter` to generate.
  </Step>
</Steps>

## Video-to-music workflow

Sonilo's video-to-music workflow analyzes your video's visuals, pacing, and emotional cues to generate a synchronized soundtrack.

<Card title="Sonilo Video-to-Music Workflow" icon="cloud" href="https://cloud.comfy.org/?template=api_sonilo_v2m&utm_source=docs">
  Run on Comfy Cloud
</Card>

1. Load your video in the input node.
2. (Optional) Add a text prompt to guide the style or mood of the generated music.
3. Click the **Run** button or use the shortcut `Ctrl(Cmd) + Enter` to start music generation.
4. The generated audio will be saved to the `ComfyUI/output/audio` directory.

## Text-to-audio workflow

You can also generate music purely from text prompts describing the style, mood, and instrumentation you want.

<Card title="Sonilo Text-to-Audio Workflow" icon="cloud" href="https://cloud.comfy.org/?template=api_sonilo_t2m&utm_source=docs">
  Run on Comfy Cloud
</Card>

**Example prompts:**

* `Dreamy ambient electronic music, gentle rhythm, suitable for short videos`
* `Futuristic electronic instrumental, sci-fi sense, ethereal and deep`
* `Lazy jazz instrumental, saxophone, relaxing cafe atmosphere`

1. Enter your text prompt describing the music you want to generate.
2. Click the **Run** button or use the shortcut `Ctrl(Cmd) + Enter` to start audio generation.
3. The generated audio will be saved to the `ComfyUI/output/audio` directory.

## Use cases

* **Advertising and creative studios** - Generate music that matches the pacing of product videos, brand spots, and social ads.
* **Video production and post houses** - Automate soundtrack generation across large volumes of footage.
* **VFX and motion graphics artists** - Generate music that evolves with your visuals, frame by frame.
* **Content creators and agencies** - Produce platform-ready videos with synchronized music across multiple formats.
* **Developers and pipeline engineers** - Integrate music generation directly into automated workflows via ComfyUI.


# Stability AI Stable Audio 2.5 Partner Nodes ComfyUI Official workflow example
Source: https://docs.comfy.org/tutorials/partner-nodes/stability-ai/stable-audio

This article will introduce how to use Stability AI Stable Audio 2.5 Partner node's text-to-audio, audio-to-audio and audio-inpainting capabilities in ComfyUI

The Stability AI Stable Audio 2.5 Partner node allows you to use Stability AI's latest audio generation model to create high-quality music through text prompts, audio transformations, and audio inpainting capabilities.

Stable Audio 2.5 is designed for enterprise use, featuring improved musical structure, better prompt adherence, and the ability to generate minutes-long compositions in seconds. The model offers three main workflows: **Text-to-Audio** for generating music from descriptions, **Audio-to-Audio** for transforming existing audio into new compositions, and **Audio Inpainting** for completing or extending existing tracks.

Trained exclusively on licensed audio, Stable Audio 2.5 is commercially safe and perfect for advertisers, game studios, and content creators who need professional-quality audio generation with enterprise-grade reliability.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Text-to-Audio Workflow

For text-to-audio, you can generate audio through text prompts. You need to describe the music you want to generate.

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/api_stability_ai_text_to_audio.json">
  <p>Download JSON Workflow</p>
</a>

<img alt="workflow" />

1. Modify the text prompt. You should use keywords to describe the music you want to generate.
2. (Optional) Modify the `duration` parameter. It's `190` by default.
3. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the audio generation. The audio will be saved to the `ComfyUI/output/audio` directory.

## Audio-to-Audio Workflow

Audio-to-audio is basically music re-sampling. You can use it to generate new music from a given piece of music, or you can just hum a melody, and then the model will generate new music based on the input audio.

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/api_stability_ai_audio_to_audio.json">
  <p>Download JSON Workflow</p>
</a>

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/stability_ai/stable_audio/beatbox.mp3">
  <p>Download Input  Audio</p>
</a>

<img alt="workflow" />

1. In this workflow, we have provided two nodes for you to input the audio（at least 6 seconds） you want to edit:
   * 1.1 `Record Audio` node: You can use it to record any of your music ideas, such as a hummed melody. It should be at least 6 seconds.
   * 1.2 `LoadAudio` node: You can use it to upload audio that you want to be used in this workflow.
2. Modify the text prompt. You should use keywords to describe the music you want to generate.
3. The `strength` parameter is used to control the difference from the original audio. The lower the value, the more similar the generated audio will be to the original audio.
4. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the audio generation. The audio will be saved to the `ComfyUI/output/audio` directory.

## Audio Inpainting Workflow

Audio inpainting is used to complete or extend existing tracks. You can use it to complete the missing part of music or extend the music to a longer duration.

You need to set where you want to start and end the inpainting.

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/api_stability_ai_audio_inpaint.json">
  <p>Download JSON Workflow</p>
</a>

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/stability_ai/stable_audio/audio_input.wav">
  <p>Download Input  Audio</p>
</a>

<img alt="workflow" />

1. Upload audio to the `LoadAudio` node.
2. Modify the text prompt. You should use keywords to describe the music you want to generate.
3. (Optional) Modify the `duration` parameter. It's `190` by default.
4. (Important) Modify the `mask_start` and `mask_end` parameters. You need to set where you want to start and end the inpainting.
5. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the audio generation. The audio will be saved to the `ComfyUI/output/audio` directory.


# Stability AI Stable Diffusion 3.5 Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/stability-ai/stable-diffusion-3-5-image

This article will introduce how to use Stability AI Stable Diffusion 3.5 Partner node's text-to-image and image-to-image capabilities in ComfyUI

The [Stability AI Stable Diffusion 3.5 Image](/built-in-nodes/partner-node/image/stability-ai/stability-ai-stable-diffusion-3-5-image) node allows you to use Stability AI's Stable Diffusion 3.5 model to create high-quality, detail-rich image content through text prompts or reference images.

In this guide, we will show you how to set up workflows for both text-to-image and image-to-image generation using this node.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Stability AI Stable Diffusion 3.5 Text-to-Image Workflow

### 1. Workflow File Download

The image below contains workflow information in its `metadata`. Please download and drag it into ComfyUI to load the corresponding workflow.

![Stability AI Stable Diffusion 3.5 Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/stability_ai/stable_diffusion_3-5-t2i.png)

### 2. Complete the Workflow Step by Step

<img alt="Stability AI Stable Diffusion 3.5 Text-to-Image Step Guide" />

You can follow the numbered steps in the image to complete the basic text-to-image workflow:

1. (Optional) Modify the `prompt` parameter in the `Stability AI Stable Diffusion 3.5 Image` node to input your desired image description. More detailed prompts often result in better image quality.
2. (Optional) Select the `model` parameter to choose which SD 3.5 model version to use.
3. (Optional) Select the `style_preset` parameter to control the visual style of the image. Different presets produce images with different stylistic characteristics, such as "cinematic" or "anime". Select "None" to not apply any specific style.
4. (Optional) Edit the `String(Multiline)` to modify negative prompts, specifying elements you don't want to appear in the generated image.
5. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation.
6. After the API returns results, you can view the generated image in the `Save Image` node. The image will also be saved to the `ComfyUI/output/` directory.

### 3. Additional Notes

* **Prompt**: The prompt is one of the most important parameters in the generation process. Detailed, clear descriptions lead to better results. Can include elements like scene, subject, colors, lighting, and style.
* **CFG Scale**: Controls how closely the generator follows the prompt. Higher values make the image more closely match the prompt description, but too high may result in oversaturated or unnatural results.
* **Style Preset**: Offers various preset styles for quickly defining the overall style of the image.
* **Negative Prompt**: Used to specify elements you don't want to appear in the generated image.
* **Seed Parameter**: Can be used to reproduce or fine-tune generation results, helpful for iteration during creation.
* Currently the `Load Image` node is in "Bypass" mode. To enable it, refer to the step guide and right-click the node to set "Mode" to "Always" to enable input, switching to image-to-image mode.
* `image_denoise` has no effect when there is no input image.

## Stability AI Stable Diffusion 3.5 Image-to-Image Workflow

### 1. Workflow File Download

The image below contains workflow information in its `metadata`. Please download and drag it into ComfyUI to load the corresponding workflow.

![Stability AI Stable Diffusion 3.5 Image-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/stability_ai/sd3-5-i2i/stable_diffusion_3_5-i2i.png)

Download the image below to use as input
!\[Stability AI Stable Diffusion 3.5 Image-to-Image Workflow Input Image]\(![Stability AI Stable Diffusion 3.5 图生图工作流输入图片](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/stability_ai/sd3-5-i2i/input.jpg)

### 2. Complete the Workflow Step by Step

<img alt="Stability AI Stable Diffusion 3.5 Image-to-Image Step Guide" />

You can follow the numbered steps in the image to complete the image-to-image workflow:

1. Load a reference image through the `Load Image` node, which will serve as the basis for generation.
2. (Optional) Modify the `prompt` parameter in the `Stability AI Stable Diffusion 3.5 Image` node to describe elements you want to change or enhance in the reference image.
3. (Optional) Select the `style_preset` parameter to control the visual style of the image. Different presets produce images with different stylistic characteristics.
4. (Optional|Important) Adjust the `image_denoise` parameter (range 0.0-1.0) to control how much the original image is modified:
   * Values closer to 0.0 make the generated image more similar to the input reference image (at 0.0, it's basically identical to the original)
   * Values closer to 1.0 make the generated image more like pure text-to-image generation (at 1.0, it's as if no reference image was provided)
5. (Optional) Edit the `String(Multiline)` to modify negative prompts, specifying elements you don't want to appear in the generated image.
6. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation.
7. After the API returns results, you can view the generated image in the `Save Image` node. The image will also be saved to the `ComfyUI/output/` directory.

### 3. Additional Notes

The image below shows a comparison of results with and without input image using the same parameter settings:

<img alt="Stability AI Stable Diffusion 3.5 With/Without Image Input Comparison" />

**Image Denoise**: This parameter determines how much of the original image's features are preserved during generation. It's the most crucial adjustment parameter in image-to-image mode. The image below shows the effects of different denoising strengths:

<img alt="Stability AI Stable Diffusion 3.5 Image-to-Image Denoise Strength Explanation" />

* **Reference Image Selection**: Choosing images with clear subjects and good composition usually yields better results.
* **Prompt Tips**: In image-to-image mode, prompts should focus more on elements you want to change or enhance, rather than describing everything already present in the image.
* **Mode Switching**: When an input image is provided, the node automatically switches from text-to-image mode to image-to-image mode, and aspect ratio parameters are ignored.

## Related Node Details

You can refer to the documentation below to understand detailed parameter settings for the corresponding node

<Card title="Stability Stable Diffusion 3.5 Image Node Documentation" icon="book" href="/built-in-nodes/partner-node/image/stability-ai/stability-ai-stable-diffusion-3-5-image">
  Stability Stable Diffusion 3.5 Image Partner Nodes Documentation
</Card>


# Stability AI Stable Image Ultra Partner Nodes ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/stability-ai/stable-image-ultra

This article will introduce how to use the Stability AI Stable Image Ultra Partner node's text-to-image and image-to-image capabilities in ComfyUI

The [Stability Stable Image Ultra](/images/built-in-nodes/api_nodes/stability-ai/stability-ai-stable-image-ultra.jpg) node allows you to use Stability AI's Stable Image Ultra model to create high-quality, detailed image content through text prompts or reference images.

In this guide, we will show you how to set up workflows for both text-to-image and image-to-image generation using this node.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Stability AI Stable Image Ultra Text-to-Image Workflow

### 1. Workflow File Download

The workflow information is included in the metadata of the image below. Please download and drag it into ComfyUI to load the corresponding workflow.

![Stability AI Stable Image Ultra Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/stability_ai/stable_image_ultra_t2i.png)

### 2. Complete the Workflow Execution Step by Step

<img alt="Stability AI Stable Image Ultra Text-to-Image Step Guide" />

You can follow the numbered steps in the image to complete the basic text-to-image workflow:

1. (Optional) Modify the `prompt` parameter in the `Stability AI Stable Image Ultra` node to input your desired image description. More detailed prompts often lead to better image quality. You can use the `(word:weight)` format to control specific word weights, for example: `The sky was crisp (blue:0.3) and (green:0.8)` indicates the sky is blue and green, but green is more prominent.
2. (Optional) Select the `style_preset` parameter to control the visual style of the image. Different preset styles will produce images with different stylistic characteristics, such as "cinematic", "anime", etc. Selecting "None" will not apply any specific style.
3. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation.
4. After the API returns the result, you can view the generated image in the `Save Image` node, and the image will also be saved to the `ComfyUI/output/` directory.

### 3. Additional Notes

* **Prompt**: The prompt is one of the most important parameters in the generation process. Detailed, clear descriptions will lead to better results. It can include elements like scene, subject, colors, lighting, and style.
* **Style Preset**: Provides multiple preset styles such as cinematic, anime, digital art, etc., which can quickly define the overall style of the image.
* **Negative Prompt**: Used to specify elements you don't want to appear in the generated image, helping avoid common issues like extra limbs or distorted faces.
* **Seed Parameter**: Can be used to reproduce or fine-tune generation results, helpful for iteration during the creative process.
* Currently, the `Load Image` node is in "Bypass" mode. To enable it, refer to the step guide and right-click on the corresponding node to set "Mode" to "Always" to enable input, which will switch to image-to-image mode.

## Stability AI Stable Image Ultra Image-to-Image Workflow

### 1. Workflow File Download

The workflow information is included in the metadata of the image below. Please download and drag it into ComfyUI to load the corresponding workflow.

![Stability Stable Image Ultra Image-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/stability_ai/i2i/stable_image_ultra_i2i.png)

Download the image below which we will use as input
![Stability Stable Image Ultra Image-to-Image Workflow Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/api_nodes/stability_ai/i2i/input.png)

### 2. Complete the Workflow Execution Step by Step

<img alt="Stability Stable Image Ultra Image-to-Image Step Guide" />

You can follow the numbered steps in the image to complete the image-to-image workflow:

1. Load a reference image through the `Load Image` node, which will serve as the basis for generation.
2. (Optional) Modify the `prompt` parameter in the `Stability Stable Image Ultra` node to describe elements you want to change or enhance in the reference image.
3. (Optional) Adjust the `image_denoise` parameter (range 0.0-1.0) to control the degree of modification to the original image:
   * Values closer to 0.0 will make the generated image more similar to the input reference image
   * Values closer to 1.0 will make the generated image more like pure text-to-image generation
4. (Optional) You can also set `style_preset` and other parameters to further control the generation effect.
5. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the image generation.
6. After the API returns the result, you can view the generated image in the `Save Image` node, and the image will also be saved to the `ComfyUI/output/` directory.

### 3. Additional Notes

**Image Denoise**: This parameter determines how much of the original image's features are preserved during generation, and is the most crucial adjustment parameter in image-to-image mode. The image below shows the effects of different denoising strengths

<img alt="Stability Stable Image Ultra Image-to-Image Denoise Explanation" />

* **Reference Image Selection**: Choosing images with clear subjects and good composition usually leads to better results.
* **Prompt Tips**: In image-to-image mode, prompts should focus more on what you want to change or enhance, rather than describing all elements already present in the image.

## Related Node Documentation

You can refer to the documentation below for detailed parameter settings and more information about the corresponding nodes

<Card title="Stability Stable Image Ultra Node Documentation" icon="book" href="/built-in-nodes/partner-node/image/stability-ai/stability-ai-stable-image-ultra">
  Stability Stable Image Ultra Partner Nodes Documentation
</Card>


# Astra 2 - Creative diffusion video upscaling
Source: https://docs.comfy.org/tutorials/partner-nodes/topaz/astra-2

What Astra 2 does for your videos in ComfyUI, plus creative upscaling with control over detail and style.

Enhanced creative upscaling for GenAI video, with advanced control over detail and style.

## What is Astra 2?

**If you're new here:** Astra 2 targets **AI-generated and stylized video**. Plain upscaling mostly enlarges and sharpens existing pixels; Astra 2 can **add plausible new detail and texture** where the source is soft, so the clip feels richer—not only bigger.

## Model overview

It builds on Astra 1 with clearer control over how detail and stylization are produced (creativity, sharpness, optional **descriptive** prompts—not step lists). Strong fits: stylized/GenAI footage, wides and sparse-detail scenes, and footage that looks overly smooth until texture is restored.

## Key capabilities

* **Adds texture and detail** — Not only sharpening.
* **Steerable look** — Creativity, sharpness, optional prompt guidance.
* **Stylized & wides** — Where inferred detail matters.

## In ComfyUI

Use **Topaz Video Enhance**. **Topaz Video Enhance (Legacy)** does not offer **Astra 2**. Set upscaler to **Astra 2**, resolution to **FullHD** or **4K**; input must be **MP4**.

Optional **Prompt**: max **450** frames (\~15 s @ 30 fps). Empty prompt: up to **9000** frames. Expand advanced controls for **Sharp** and **Realism** when needed.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Example workflow

**Load Video** → **Topaz Video Enhance** → **Save Video**. After opening the template, pick **Astra 2** on the upscaler if another preset is selected.

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_topaz_astra2&utm_source=docs">
  Open the workflow instantly on Comfy Cloud.
</Card>

<Card title="Download workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_topaz_astra2.json">
  Download the workflow JSON for local ComfyUI.
</Card>

## Related

* [Video upscaling in ComfyUI](/tutorials/utility/video-upscale) — guidance on choosing an upscaling approach.


# Tripo Partner Nodes Model Generation ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/partner-nodes/tripo/model-generation

This article will introduce how to use Tripo node's API in ComfyUI for model generation

Tripo AI is a company focused on generative AI 3D modeling. It provides user-friendly platforms and API services that can quickly convert text prompts or 2D images (single or multiple) into high-quality 3D models.
ComfyUI has now natively integrated the corresponding Tripo API, allowing you to conveniently use the related nodes in ComfyUI for model generation.

Currently, ComfyUI's Partner nodes support the following Tripo model generation capabilities:

* Text-to-model
* Image-to-model
* Multi-view model generation
* Rig model
* Retarget rigged model

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Text-to-Model Workflow

### 1. Workflow File Download

Download the file below and drag it into ComfyUI to load the corresponding workflow.

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/api_tripo_text_to_model.json">
  <p>Download Json Format Workflow File</p>
</a>

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Tripo Text to Model Step Guide" />

You can refer to the numbers in the image to complete the basic text-to-model workflow execution:

1. In the `Tripo: Text to Model` node, input your prompt in the `prompt` field
   * model: You can select different models, currently only v1.4 model supports subsequent optimization with `Tripo: Refine Draft model`
   * style: You can set different styles
   * texture\_quality: You can set different texture qualities
2. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation. After the workflow completes, the corresponding model will be automatically saved to the `ComfyUI/output/` directory
3. In the `Preview 3D` node, click to expand the menu
4. Select `Export` to directly export the corresponding model

## Image-to-Model Workflow

### 1. Workflow File Download

Download the file below and drag it into ComfyUI to load the corresponding workflow.

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/image_to_model/api_tripo_image_to_model.json">
  <p>Download Json Format Workflow File</p>
</a>

Download the image below as input image

![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/image_to_model/panda.jpg)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Tripo Text to Model Step Guide" />

You can refer to the numbers in the image to complete the basic image-to-model workflow execution:

1. In the `Load Image` node, load the provided input image
2. In the `Tripo: Image to Model` node, modify the corresponding parameter settings
   * model: You can select different models, currently only v1.4 model supports subsequent optimization with `Tripo: Refine Draft model`
   * style: You can set different styles
   * texture\_quality: You can set different texture qualities
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation. After the workflow completes, the corresponding model will be automatically saved to the `ComfyUI/output/` directory
4. For model download, please refer to the instructions in the text-to-model section

## Multi-view Model Generation Workflow

### 1. Workflow File Download

Download the file below and drag it into ComfyUI to load the corresponding workflow.

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/multiview_to_image/api_tripo_multiview_to_model.json">
  <p>Download Json Format Workflow File</p>
</a>

Download the images below as input images

![Front View](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/multiview_to_image/front.jpg)
![Back View](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/api_nodes/tripo/multiview_to_image/back.jpg)

### 2. Complete the Workflow Execution Step by Step

<img alt="ComfyUI Tripo Text to Model Step Guide" />

You can refer to the numbers in the image to complete the basic multi-view to model workflow execution:

1. In the `Load Image` nodes, load the provided input images respectively
2. In the `Tripo: Image to Model` node, modify the corresponding parameter settings
   * model: You can select different models, currently only v1.4 model supports subsequent optimization with `Tripo: Refine Draft model`
   * style: You can set different styles
   * texture\_quality: You can set different texture qualities
3. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute model generation. After the workflow completes, the corresponding model will be automatically saved to the `ComfyUI/output/` directory
4. For other view inputs, you can refer to the step diagram and set the corresponding node mode to `Always` to enable it
5. For model download, please refer to the instructions in the text-to-model section

## Subsequent Task Processing for the Same Task

Tripo's corresponding nodes provide subsequent processing for the same task, you only need to input the corresponding `model_task_id` in the relevant nodes, and we have also provided the corresponding nodes in the relevant templates, you can also modify the corresponding node mode as needed to enable it

<img alt="Tripo Task Processing" />

<Error>
  The `Tripo: Refine Draft model` node only supports V1.4 model, other models do not support it
</Error>


# Tripo 3.1 — High-Detail 3D Asset Generation ComfyUI Official Guide
Source: https://docs.comfy.org/tutorials/partner-nodes/tripo/tripo-3-1

Learn how to generate high-detail 3D assets with Tripo 3.1 in ComfyUI via Partner Nodes, featuring high-density geometry and PBR-ready materials for production use.

Tripo 3.1 is the latest model version available through Tripo Partner Nodes in ComfyUI. It offers higher geometry density and improved surface quality compared to previous versions, making it suitable for close-up production use.

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Capabilities

Compared to previous Tripo model versions, 3.1 provides the following improvements:

* **High-density geometry** — Sharper edges, cleaner silhouettes, and more precise forms for production-level 3D assets.
* **PBR-ready materials** — More reliable lighting response across different render environments.
* **Hero asset quality** — Stable detail retention in close-up shots.
* **Cross-scenario reuse** — A single model can work across game, marketing, and render pipelines without regeneration.

## Use Cases

* **Game hero assets** — For close-up camera shots and promotional key art.
* **Marketing visuals** — Where geometric fidelity and material quality are critical.
* **Product visualization** — Cleaner shape definition in studio-style renders.
* **3D printing preparation** — Better structural clarity.

## Available Workflows

### Text-to-Model

<Card title="Run Text-to-Model on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo3_1_text_to_model&utm_source=docs">
  Try the Text-to-Model workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Text-to-Model Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo3_1_text_to_model.json">
  Download JSON or search "Tripo 3.1 Text-to-Model" in Template Library.
</Card>

### Image-to-Model

<Card title="Run Image-to-Model on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo3_1_image_to_model&utm_source=docs">
  Try the Image-to-Model workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Image-to-Model Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo3_1_image_to_model.json">
  Download JSON or search "Tripo 3.1 Image-to-Model" in Template Library.
</Card>

### Multiview-to-Model

<Card title="Run Multiview-to-Model on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_tripo3_1_multiview_to_model&utm_source=docs">
  Try the Multiview-to-Model workflow instantly on Comfy Cloud.
</Card>

<Card title="Download Multiview-to-Model Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_tripo3_1_multiview_to_model.json">
  Download JSON or search "Tripo 3.1 Multiview-to-Model" in Template Library.
</Card>

### Version Comparison

| Aspect           | Tripo 3.1                      | Previous Versions                          |
| ---------------- | ------------------------------ | ------------------------------------------ |
| Geometry Density | High-density, production-ready | Standard density                           |
| Surface Quality  | Cleaner edges and silhouettes  | Good, but may require polish for close-ups |
| Material Output  | PBR-ready                      | Standard material maps                     |
| Refine Support   | Supported                      | Supported (v1.4 only for Refine Draft)     |


# Wan2.7 Video Generation in ComfyUI
Source: https://docs.comfy.org/tutorials/partner-nodes/wan/wan2-7

Learn how to use Wan2.7 via Partner Nodes in ComfyUI for image-to-video, text-to-video, reference-to-video, video continuation, and video editing

Wan2.7 is Alibaba's latest video generation model, now available in ComfyUI via Partner Nodes. It is a comprehensive upgrade over version 2.6 with significant improvements across image quality, audio, motion dynamics, stylization, and consistency.

This release brings a fully upgraded multimodal video pipeline directly into your node graph, supporting text, image, audio, and video inputs across five task types.

## Key features

* **Image-to-video**: First-frame, first+last-frame, and audio-driven generation
* **Text-to-video**: Pure text prompts with optional audio input and multi-shot narration
* **Video continuation**: Extend an existing clip with new content guided by a text prompt
* **Reference-to-video**: Reference both a subject's visual appearance and vocal timbre; supports up to 5 real-person inputs and multi-character interactions
* **Video edit**: Edit or replicate videos via text prompts, reference image, or style transfer

## Highlights

* Supports up to **5 real-person image inputs** for multi-character scenes
* Vocal timbre reference for consistent audio-visual identity
* 3x3 grid-based image generation
* Significant improvements in motion dynamics, stylization, and consistency over Wan2.6

<Tip>
  To use the Partner Nodes, you need to ensure that you are logged in properly and using a permitted network environment. Please refer to the [Partner Nodes Overview](/tutorials/partner-nodes/overview) section of the documentation to understand the specific requirements for using the Partner Nodes.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Wan2.7 image-to-video

Generate video from image inputs. Supports first-frame, first+last-frame, and audio-driven generation modes.

<Card title="Wan2.7 I2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_wan2_7_i2v.json">
  Get the Wan2.7 Image-to-Video workflow file.
</Card>

<Card title="Run Wan2.7 I2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_wan2_7_i2v&utm_source=docs">
  Try the Image-to-Video workflow instantly on Comfy Cloud.
</Card>

## Wan2.7 text-to-video

Generate video from pure text prompts. Optionally include audio input and multi-shot narration for richer storytelling.

<Card title="Wan2.7 T2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_wan2_7_t2v.json">
  Get the Wan2.7 Text-to-Video workflow file.
</Card>

<Card title="Run Wan2.7 T2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_wan2_7_t2v&utm_source=docs">
  Try the Text-to-Video workflow instantly on Comfy Cloud.
</Card>

## Wan2.7 reference-to-video

Use reference images of a subject's visual appearance along with an optional vocal timbre reference. Supports up to 5 real-person inputs for multi-character interaction scenes.

<Card title="Wan2.7 R2V Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_wan2_7_r2v.json">
  Get the Wan2.7 Reference-to-Video workflow file.
</Card>

<Card title="Run Wan2.7 R2V on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_wan2_7_r2v&utm_source=docs">
  Try the Reference-to-Video workflow instantly on Comfy Cloud.
</Card>

## Wan2.7 video edit

Edit or replicate existing videos using text prompts, a reference image, or style transfer.

<Card title="Wan2.7 Video Edit Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_wan2_7_video_edit.json">
  Get the Wan2.7 Video Edit workflow file.
</Card>

<Card title="Run Wan2.7 Video Edit on Cloud" icon="cloud" href="https://cloud.comfy.org/?template=api_wan2_7_video_edit&utm_source=docs">
  Try the Video Edit workflow instantly on Comfy Cloud.
</Card>


# MediaPipe: Face Detection in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/face-detection/mediapipe

Learn how to use MediaPipe Face Detection in ComfyUI to detect faces and extract facial landmarks, bounding boxes, and region masks from images

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

[MediaPipe](https://github.com/google-ai-edge/mediapipe) is Google's open-source machine learning solution for real-time perception. In ComfyUI, MediaPipe Face Detection provides **BlazeFace** detection, **FaceMesh v2** landmark estimation, and **ARKit-52 blendshapes** — all in a single unified workflow.

MediaPipe Face Detection is natively supported in ComfyUI (PR [#14009](https://github.com/Comfy-Org/ComfyUI/pull/14009)), and the model weights are available under the [Apache 2.0 License](https://github.com/google-ai-edge/mediapipe/blob/master/LICENSE).

[MediaPipe GitHub](https://github.com/google-ai-edge/mediapipe) | [Comfy-Org Model Repository](https://huggingface.co/Comfy-Org/mediapipe)

### Key capabilities

* **Fast face detection** — BlazeFace-based detector with short (\~2 m) and full (\~5 m) range variants
* **478 facial landmarks** — dense FaceMesh v2 keypoints per detected face
* **ARKit-52 blendshapes** — real-time facial expression coefficients
* **Face region masks** — per-region masks for face oval, lips, eyes, and irises
* **Face bounding boxes** — outputs compatible with `DrawBBoxes` for bounding box visualization

> **Scope:** Face detection only — BlazeFace + FaceMesh v2 + ARKit blendshapes. This does not cover hand, pose, or holistic detection.

## MediaPipe Face Detection Workflow

### 1. Download the Workflow

Update your ComfyUI to the latest version, then go to `Workflow` → `Browse Templates` and find "Mediapipe: Image Face Detection" under the Utility category.

<Card title="Download JSON Workflow File" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_face_detection_mediapipe.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_face_detection_mediapipe&utm_source=docs&utm_medium=referral&utm_campaign=mediapipe">
  Open in cloud
</Card>

<Card title="Download Sample Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/soft_neon_girl.png">
  Get the example input image for this workflow
</Card>

![MediaPipe Face Detection preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/utility_face_detection_mediapipe-1.webp)

### 2. Download the Model

The MediaPipe Face Detection model is hosted on the [Comfy-Org MediaPipe model repository](https://huggingface.co/Comfy-Org/mediapipe).

* [mediapipe\_face\_fp32.safetensors](https://huggingface.co/Comfy-Org/mediapipe/resolve/main/detection/mediapipe_face_fp32.safetensors)

Place it in the following directory structure:

```
📂 ComfyUI/
└── 📂 models/
    └── 📂 detection/
        └── mediapipe_face_fp32.safetensors
```

### 3. Using the Workflow

This workflow uses a **subgraph** node that orchestrates face detection, visualization, and mask generation. The subgraph exposes the following controls:

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

**Subgraph inputs:**

| Input                | Description                                                                                                           |
| -------------------- | --------------------------------------------------------------------------------------------------------------------- |
| **image**            | Input image batch to analyze                                                                                          |
| **face\_landmarker** | Optional. Leave empty to use the built-in model loader. Connect an external `FACE_DETECTION_MODEL` output to override |

**Subgraph parameters:**

| Parameter              |              Default              | Description                                                                                                                                                                                               |
| ---------------------- | :-------------------------------: | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **model\_name**        | `mediapipe_face_fp32.safetensors` | Checkpoint in `ComfyUI/models/detection/`. If missing, download the model above                                                                                                                           |
| **detector\_variant**  |              `short`              | **short** — tuned for close/large faces (\~2 m range). **full** — covers smaller/farther faces (\~5 m), slower. **both** — runs both detectors and keeps whichever found more faces per frame (\~2× cost) |
| **num\_faces**         |                `1`                | Maximum faces to return per frame. `0` = no cap (return all detected). Range: 0–16                                                                                                                        |
| **custom\_face\_oval** |              `false`              | Include face-outline region in the mask output                                                                                                                                                            |
| **custom\_lips**       |              `false`              | Include lips in the mask (union with other enabled regions)                                                                                                                                               |
| **custom\_left\_eye**  |              `false`              | Include left eye region in the mask                                                                                                                                                                       |
| **custom\_right\_eye** |              `false`              | Include right eye region in the mask                                                                                                                                                                      |
| **custom\_irises**     |              `false`              | Include iris regions in the mask                                                                                                                                                                          |

Mask toggles use custom mode internally: only checked regions are filled; multiple ON regions are **unioned** into one mask per frame.

**Subgraph outputs:**

| Output              | Type             | Description                                                                                                                  |
| ------------------- | ---------------- | ---------------------------------------------------------------------------------------------------------------------------- |
| **face\_landmarks** | `FACE_LANDMARKS` | Per-frame faces with 478 2D/3D landmarks, ARKit-52 blendshapes, mesh topology data — feeds into visualization and mask nodes |
| **bboxes**          | `BOUNDING_BOX`   | Face bounding boxes — compatible with `DrawBBoxes` node                                                                      |
| **mask**            | `MASK`           | Binary mask from the enabled region toggles                                                                                  |

### 4. Run the Workflow

1. Ensure the model file is placed in `ComfyUI/models/detection/`
2. Load an image in the `Load Image` node
3. Adjust detection parameters as needed
4. Click `Queue` or use `Ctrl(Cmd) + Enter` to run
5. The workflow outputs the mesh overlay, bounding boxes, and mask preview

## Community Resources

* [MediaPipe GitHub](https://github.com/google-ai-edge/mediapipe) — Upstream MediaPipe framework
* [Comfy-Org/mediapipe](https://huggingface.co/Comfy-Org/mediapipe) — Official ComfyUI model weights
* [ComfyUI Subgraph Guide](https://docs.comfy.org/interface/features/subgraph) — Learn how subgraphs work


# ComfyUI frame interpolation workflow
Source: https://docs.comfy.org/tutorials/utility/frame-interpolation

Learn how to use frame interpolation to smooth motion and increase frame rate in ComfyUI video workflows

## What is frame interpolation?

<Note>
  This workflow contains custom nodes. You need to install them using [ComfyUI Manager](/manager/overview) before running the workflow.
</Note>

Frame interpolation generates intermediate frames between existing frames, resulting in smoother motion and improved temporal consistency. This technique is essential for video post-processing and can significantly improve the quality of generated videos.

## Use cases

Frame interpolation supports:

* **Increasing frame rate in short clips** - Convert low-FPS videos to higher frame rates
* **Smoothing motion in generated or edited video** - Reduce stuttering and stepping artifacts
* **Preparing sequences for downstream video models** - Standardize frame rate for consistent processing
* **Fixing low-FPS generations** - Many video generation workflows default to 16fps, which can introduce noticeable stutter

## Why frame interpolation matters

Many image and video generation workflows still default to 16fps, which can introduce noticeable stutter, stepping, and uneven motion—especially in camera moves and character animation.

Frame interpolation is an effective way to smooth these artifacts without regenerating the source frames, making motion feel more natural while preserving the original composition and timing.

Rather than always treating interpolation as a final post-process, it can also be used as a preprocessing step—allowing you to standardize frame rate early and feed cleaner temporal data into larger animation and video pipelines.

<Card title="Frame Interpolation Workflow" icon="cloud" href="https://www.comfy.org/workflows/frame-interpolation">
  Run on Comfy Cloud
</Card>


# Image upscaling in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/image-upscale

Learn how to upscale images in ComfyUI using local models and partner nodes for different use cases

This guide covers image upscaling workflows in ComfyUI, including local models and partner node options for various use cases.

<Card title="The Complete AI Upscaling Handbook" icon="book-open" href="https://blog.comfy.org/p/upscaling-in-comfyui">
  For a comprehensive deep-dive with benchmarks and visual comparisons, read the full article on the ComfyUI Blog.
</Card>

## Why upscaling matters

* **Industry requirements for resolutions**: 4K/8K end results are widely required across VFX & Film, Marketing, E-commerce, Gaming, and Design industries, and requirements keep moving up.
* **Reframing**: When assets ship across different aspect ratios and placements, extra resolution headroom prevents quality loss after cropping or recomposition.
* **The AI content problem**: Generative AI has dramatically increased the speed of visual creation, but most AI assets today are still generated at 480–720p, and not production-ready at the pixel level: edges, micro-texture, faces/hands, compression artifacts, etc. This creates a new pipeline: Generation → Refinement/Fix → Upscale → Delivery.
* **Cost/time efficiency**: Generate or render smaller → upscale at the end. This is a standard efficiency move in pipelines under budget/time pressure.

## Key concepts

### Upscaling vs. enhancement

* **Upscaling** increases resolution while reconstructing detail.
* **Enhancement** improves perceived quality (denoise, sharpen, restore, color, faces, etc.).

The best practice in AI pipelines usually combines both steps.

### Creative vs. conservative upscale

Diffusion models and generative AI changed what "upscaling" means. Traditionally, super-resolution aimed to **preserve the original signal**. Today, some models can **re-imagine details that never existed**. And there are models approaching different balances between the two.

|               | Conservative                                            | Creative                                                 |
| ------------- | ------------------------------------------------------- | -------------------------------------------------------- |
| **Approach**  | Preserve the original                                   | Reimagine and enhance                                    |
| **Strengths** | High accuracy, consistency, production-safe             | Rich details, sharper, more visually striking            |
| **Limits**    | Can appear flat, limited improvement on poor input      | Possible hallucinations or structural drift              |
| **Models**    | Magnific Precise, SeedVR2, FlashVSR, Topaz Fast, HitPaw | Wan 2.2, Magnific Creative, Topaz Astra, HitPaw Creative |

## Use cases

<Note>
  **TL;DR**

  * **Portraits**: Magnific Skin Enhancer
  * **Product photography**: Magnific Precise, WaveSpeed SeedVR2, or Nano Banana Pro
  * **Landscapes & illustrations**: Model choice depends on your specific needs
  * **AI artifacts**: Do not rely on upscaling to fix common AI artifacts
  * **SeedVR2 tip**: Downscale the image to 0.35 megapixels with the `ImageScaleToTotalPixels` node before upscaling for better results
</Note>

### Portrait and skin enhancement

When it comes to upscaling portraits of realistic subjects, achieving realistic skin details while maintaining character consistency is key. The best upscale models for fixing plastic skin need to add texture, pores and natural skin imperfections. In this domain, Magnific Image Skin Enhancer far outperforms the rest.

**Recommended**: Magnific Image Skin Enhancer

<Card title="Magnific Skin Enhancer" icon="cloud" href="https://links.comfy.org/4cbvbE7">
  Try on Comfy Cloud or download workflow
</Card>

### Product photography

Maintaining a faithful representation of materials, product label edges, and small text is a must when upscaling product images. Therefore, conservative upscaling models are necessary.

**Recommended**: HitPaw, Magnific Precise, WaveSpeed SeedVR2, Nano Banana Pro

<Card title="HitPaw" icon="cloud" href="https://links.comfy.org/4kkoula">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Nano Banana Pro Product" icon="cloud" href="https://links.comfy.org/4qUntD0">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="SeedVR2 (Open Source)" icon="cloud" href="https://links.comfy.org/4ko2sOG">
  Try on Comfy Cloud or download workflow
</Card>

### Landscape and environments

For this use case, the upscale model you select really depends on your needs. Have an environmental shot that you want to pop with details and set a mood? Use a creative upscale model. Have an establishing shot where a building needs to stay consistent? Use a conservative upscale model.

It's worth noting that if your input image has artifacts, creative upscale models may be able to reimagine the artifact while conservative upscale models will not.

<Card title="Topaz Landscape" icon="cloud" href="https://links.comfy.org/4r1utxS">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Recraft Creative" icon="cloud" href="https://links.comfy.org/4afKfOJ">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Recraft Crisp" icon="cloud" href="https://links.comfy.org/3O0M4Yf">
  Try on Comfy Cloud or download workflow
</Card>

### Stylized art and illustration

This is another use case where the correct upscale model depends on your needs. A rule of thumb is that if your input has a very distinct/unique style, the best model will be conservative. Creative models may add too many details and stray away from the desired illustrated style. However, if your input image has room for detail, a creative model works well and can even improve the style.

We recommend playing around with the 'creativity' parameters for Magnific Creative and Topaz Image Enhance to find values that meet your needs! Nano Banana Pro can also work well for more common styles and adding details (but may rely on 'seed luck').

**Recommended**: Magnific Creative, Topaz Image Enhance, Nano Banana Pro

<Card title="Topaz Illustration" icon="cloud" href="https://links.comfy.org/46zi8c1">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Topaz Creative" icon="cloud" href="https://links.comfy.org/4kjT12P">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Nano Banana Pro Styled Art" icon="cloud" href="https://links.comfy.org/3O0Maiz">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Nano Banana Pro Portrait" icon="cloud" href="https://links.comfy.org/3O9XtF7">
  Try on Comfy Cloud or download workflow
</Card>

### AI-generated images

When it comes to upscaling images that have typical AI issues such as too many fingers, artifacts, incorrect anatomy, and morphing, the assumption is that creative upscales can fix it. Sometimes that's true, but other times not so much. Best practice is to resolve these issues prior to upscaling with image-edit models or traditional tools (or generate a new image entirely).

## Available models

### Local models (ESRGAN)

For basic local upscaling using ESRGAN models, see the [basic upscale tutorial](/tutorials/basic/upscale).

| Model      | Best for                     |
| ---------- | ---------------------------- |
| RealESRGAN | General-purpose upscaling    |
| BSRGAN     | Text and sharp edges         |
| SwinIR     | Natural textures, landscapes |

<Card title="Traditional Non-AI Upscaling" icon="cloud" href="https://links.comfy.org/45Nu9um">
  Try on Comfy Cloud or download workflow
</Card>

### General creative upscaling

For general creative upscaling across various use cases:

<Card title="HitPaw Creative" icon="cloud" href="https://links.comfy.org/4kkoula">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Recraft Creative" icon="cloud" href="https://links.comfy.org/4afKfOJ">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Recraft Crisp" icon="cloud" href="https://links.comfy.org/3O0M4Yf">
  Try on Comfy Cloud or download workflow
</Card>

### Partner nodes

Partner nodes provide access to advanced upscaling models via API.

| Model                       | Type         | Features                                                          |
| --------------------------- | ------------ | ----------------------------------------------------------------- |
| Topaz Image Enhance (Bloom) | Creative     | Subject detection, face enhancement, color preservation, up to 8K |
| Magnific Precise            | Conservative | High accuracy, production-safe                                    |
| Magnific Creative           | Creative     | Detail reimagination                                              |
| Magnific Skin Enhancer      | Creative     | Portrait-specific, adds realistic skin texture                    |
| Nano Banana Pro             | Conservative | Fast, good for product photography                                |
| WaveSpeed SeedVR2           | Conservative | High fidelity                                                     |
| HitPaw                      | Both         | Conservative and creative modes                                   |
| Recraft                     | Both         | Creative and crisp modes                                          |

## Benchmark: 1K to 4K upscale time

| Model                  | Time   |
| ---------------------- | ------ |
| Magnific Precise       | \~40s  |
| WaveSpeed SeedVR2      | \~40s  |
| Magnific Creative      | \~50s  |
| Magnific Skin Enhancer | \~60s  |
| HitPaw                 | \~60s  |
| Nano Banana Pro        | \~80s  |
| Topaz Image Enhance    | \~100s |

## Tips

* For SeedVR2, downscale the image to 0.35 megapixels with the `ImageScaleToTotalPixels` node before upscaling for better results.
* Chain multiple upscale nodes (e.g., 2x → 4x) for ultra-high magnification.
* Connect upscale nodes after generation for "generate + enhance" pipelines.
* Test multiple models on your specific image type to find the best fit.


# ComfyUI MoGe Examples
Source: https://docs.comfy.org/tutorials/utility/moge

This guide demonstrates how to use MoGe in ComfyUI for monocular geometry estimation: metric point maps, depth maps, normal maps, and mesh generation.

# ComfyUI MoGe Introduction

[MoGe](https://github.com/microsoft/MoGe) (CVPR 2025, from Microsoft Research) is a powerful model for recovering 3D geometry from monocular open-domain images. It estimates metric point maps, metric depth maps, normal maps, and camera FOV — all in a single forward pass.

Key capabilities:

* **Accurate 3D geometry estimation**: point maps, depth maps, and normal maps from a single image — one model, one forward pass
* **Metric scale** (MoGe-2): point maps and depth maps in real-world scale
* **Flexible resolution support**: works with various resolutions and aspect ratios (2:1 to 1:2)
* **Fast inference**: \~60ms per image on A100 / RTX 3090 (FP16, ViT-L)
* **Mesh generation** from both perspective and panoramic images

MoGe comes in two versions:

| File                      | Version    | Metric Scale | Normal Maps | Params |
| ------------------------- | ---------- | :----------: | :---------: | :----: |
| `moge_1_vitl_fp16`        | **MoGe-1** |       -      |      -      |  314M  |
| `moge_2_vitl_normal_fp16` | **MoGe-2** |       ✅      |      ✅      |  331M  |

> MoGe-2 adds metric scale and high-quality normal map estimation with sharper visual detail and lower inference latency. **MoGe-2 with normal (`moge_2_vitl_normal_fp16`) is the recommended checkpoint.**

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<Tip>
  ComfyUI now natively supports MoGe nodes. Make sure you have updated to the latest version of [ComfyUI](https://github.com/Comfy-Org/ComfyUI) before starting.

  Generated `.glb` format models will be output to the `ComfyUI/output/mesh` folder.
</Tip>

## Model Installation

Download the MoGe checkpoint(s) and save them to the corresponding ComfyUI folder:

* **MoGe-2 (recommended)**: [moge\_2\_vitl\_normal\_fp16.safetensors](https://huggingface.co/Comfy-Org/MoGe/resolve/main/moge_2_vitl_normal_fp16.safetensors)
* **MoGe-1 (baseline)**: [moge\_1\_vitl\_fp16.safetensors](https://huggingface.co/Comfy-Org/MoGe/resolve/main/moge_1_vitl_fp16.safetensors)

```
ComfyUI/
├── models/
│   ├── geometry_estimation/
│   │   ├── moge_2_vitl_normal_fp16.safetensors
│   │   └── moge_1_vitl_fp16.safetensors
```

## Example Workflows

***

## 1. Depth Estimation

**What it does:** Takes a single image and estimates its metric depth map, colored depth preview, and mask — outputs the same metric-scale depth that MoGe infers in one forward pass. Useful as a scene depth reference for compositing, depth-based effects, or as preprocessing before mesh generation.

MoGe also estimates the camera's field of view (FOV) from the image, which can be optionally overridden with a ground-truth value for even more accurate results.

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility_moge_depth_estimation.json">
  Download JSON or search "MoGe Depth Estimation" in Template Library
</Card>

<Card title="Download Sample Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/alien_world.png">
  Get the example input image for this workflow
</Card>

<div>
  <img alt="depth estimation color preview" />

  <img alt="depth estimation raw preview" />
</div>

### 1.1 Steps to Run

1. Ensure the `LoadMoGeModel` node has loaded a MoGe checkpoint
2. Load an image in the `Load Image` node
3. Click `Queue` or use `Ctrl(cmd) + Enter` to run
4. The workflow outputs colored depth preview, raw depth preview, and a mask

***

## 2. Perspective to Mesh

**What it does:** Converts a single perspective photo into a textured GLB mesh with normal and depth previews. MoGe estimates point maps, depth, and normals from the visible scene, then converts them to a mesh. This is **monocular geometry estimation** — occluded areas and object backsides will be missing or fragmented. Useful for quick scene prototyping, reference geometry, or visualizing depth and normals as a mesh, but not a replacement for multi-view 3D reconstruction.

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_moge_perspective_to_mesh.json">
  Download JSON or search "3D MoGe Perspective to Mesh" in Template Library
</Card>

<Card title="Download Sample Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/modern_living_room.png">
  Get the example input image for this workflow
</Card>

![perspective to mesh preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/3d_moge_perspective_to_mesh-1.webp)

### 2.1 Steps to Run

1. Ensure the `LoadMoGeModel` node has loaded a MoGe checkpoint
2. Load a perspective photo in the `Load Image` node
3. (Optional) View the OpenGL and DirectX normal previews
4. Click `Queue` or use `Ctrl(cmd) + Enter` to run

***

## 3. Panorama to Mesh

**What it does:** Converts an equirectangular (360°) panorama into a textured GLB mesh. The workflow uses `MoGePanoramaInference` to split the panorama into 12 perspective views, runs monocular geometry estimation on each view independently, then merges them into a single mesh. Each segment is still single-view estimation, so the result is a rough scene reconstruction — useful for getting a spatial overview of a 360° scene, but occluded areas and geometry behind surfaces will be missing or fragmented.

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/3d_moge_panorama_to_mesh.json">
  Download JSON or search "3D MoGe Panorama to Mesh" in Template Library
</Card>

<Card title="Download Sample Image" icon="image" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/input/lego_street_panorama.png">
  Get the example input image for this workflow
</Card>

![panorama to mesh preview](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/3d_moge_panorama_to_mesh-1.webp)

### 3.1 Steps to Run

1. Ensure the `LoadMoGeModel` node has loaded one of the MoGe checkpoints
2. Load an equirectangular panorama image in the `Load Image` node
3. Click `Queue` or use `Ctrl(cmd) + Enter` to run

***

## Community Resources

* [MoGe GitHub (microsoft/MoGe)](https://github.com/microsoft/MoGe) — Research paper and code
* [Comfy-Org/MoGe](https://huggingface.co/Comfy-Org/MoGe) — Official ComfyUI model weights


# ComfyUI preprocessor workflows
Source: https://docs.comfy.org/tutorials/utility/preprocessors

Learn how to use depth estimation, lineart conversion, pose detection, and normals extraction preprocessors in ComfyUI

## What are preprocessors?

<Note>
  These workflows contain custom nodes. You need to install them using [ComfyUI Manager](/manager/overview) before running the workflows.
</Note>

Preprocessors are foundational tools that extract structural information from images. They convert images into conditioning signals like depth maps, lineart, pose skeletons, and surface normals. These outputs drive better control and consistency in ControlNet, image-to-image, and video workflows.

Using preprocessors as separate workflows enables:

* Faster iteration without full graph reruns
* Clear separation of preprocessing and generation
* Easier debugging and tuning
* More predictable image and video results

## Depth estimation

Depth estimation converts a flat image into a depth map representing relative distance within a scene. This structural signal is foundational for controlled generation, spatially aware edits, and relighting workflows.

This workflow emphasizes:

* Clean, stable depth extraction
* Consistent normalization for downstream use
* Easy integration with ControlNet and image-edit pipelines

Depth outputs can be reused across multiple passes, making it easier to iterate without re-running expensive upstream steps.

<Card title="Depth Estimation Workflow" icon="cloud" href="https://cloud.comfy.org/?template=utility-depthAnything-v2-relative-video&utm_source=docs&utm_medium=inhouse_social&utm_campaign=inhouse_feature_launches&utm_content=post&utm_niche=workflow_engineering&utm_creator=purz">
  Run on Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility-depthAnything-v2-relative-video.json">
  Download JSON
</Card>

## Lineart conversion

Lineart preprocessors distill an image down to its essential edges and contours, removing texture and color while preserving structure.

This workflow is designed to:

* Produce clean, high-contrast lineart
* Minimize broken or noisy edges
* Provide reliable structural guidance for stylization and redraw workflows

Lineart pairs especially well with depth and pose, offering strong structural constraints without overconstraining style.

<Card title="Lineart Conversion Workflow" icon="cloud" href="https://cloud.comfy.org/?template=utility-lineart-video&utm_source=docs&utm_medium=inhouse_social&utm_campaign=inhouse_feature_launches&utm_content=post&utm_niche=workflow_engineering&utm_creator=purz">
  Run on Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility-lineart-video.json">
  Download JSON
</Card>

## Pose detection

Pose detection extracts body keypoints and skeletal structure from images, enabling precise control over human posture and movement.

This workflow focuses on:

* Clear, readable pose outputs
* Stable keypoint detection suitable for reuse across frames
* Compatibility with pose-based ControlNet and animation pipelines

By isolating pose extraction into a dedicated workflow, pose data becomes easier to inspect, refine, and reuse.

<Card title="Pose Detection Workflow" icon="cloud" href="https://cloud.comfy.org/?template=utility-openpose-video&utm_source=docs&utm_medium=inhouse_social&utm_campaign=inhouse_feature_launches&utm_content=post&utm_niche=workflow_engineering&utm_creator=purz">
  Run on Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility-openpose-video.json">
  Download JSON
</Card>

## Normals extraction

Normals estimation converts a flat image into a surface normal map—a per-pixel direction field that describes how each part of a surface is oriented (typically encoded as RGB). This signal is useful for relighting, material-aware stylization, and highly structured edits.

This workflow emphasizes:

* Clean, stable normal extraction with minimal speckling
* Consistent orientation and normalization for reliable downstream use
* ControlNet-ready outputs for relighting, refinement, and structure-preserving edits
* Reuse across passes so you can iterate without re-running earlier steps

Normal outputs can be used to:

* Drive relight/shading changes while preserving geometry
* Add a stronger 3D-like structure to stylization and redraw pipelines
* Improve consistency across frames when paired with pose/depth for animation work

<Card title="Normals Extraction Workflow" icon="cloud" href="https://cloud.comfy.org/?template=utility-normal_crafter-video&utm_source=docs&utm_medium=inhouse_social&utm_campaign=inhouse_feature_launches&utm_content=post&utm_niche=workflow_engineering&utm_creator=purz">
  Run on Comfy Cloud
</Card>

<Card title="Download Workflow" icon="download" href="https://github.com/Comfy-Org/workflow_templates/blob/main/templates/utility-normal_crafter-video.json">
  Download JSON
</Card>


# BiRefNet: Remove Image Background in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/remove-background-birefnet

Learn how to remove image backgrounds using the BiRefNet model, natively supported in ComfyUI

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

BiRefNet (Bilateral Reference Network) is a high-quality image background removal model. It produces clean, detailed masks for a wide range of subjects, including people, products, animals, and complex objects with fine details like hair or fur.

BiRefNet is natively supported in ComfyUI (PR [#12747](https://github.com/Comfy-Org/ComfyUI/pull/12747)). The model weights are available under the [MIT License](https://github.com/ZhengPeng7/BiRefNet/blob/main/LICENSE).

[BiRefNet on Hugging Face](https://huggingface.co/ZhengPeng7/BiRefNet) | [Comfy-Org Model Repository](https://huggingface.co/Comfy-Org/BiRefNet) | [Paper (arXiv)](https://arxiv.org/abs/2401.00807)

### Key strengths

* **High-quality masks** — accurate edge detection for hair, fur, and fine details
* **Versatile subject detection** — works well on people, products, animals, and complex scenes
* **Simple one-click workflow** — just load an image and the model handles the rest
* **RGBA output** — produces an image with transparent background ready for compositing

> **Limitations:** Extremely cluttered backgrounds or subjects that blend into the background may produce less accurate masks. The model processes a single image at a time.

## BiRefNet Background Removal Workflow

### 1. Download Workflow

Update your ComfyUI to the latest version, then go to `Workflow` -> `Browse Templates` and find "BiRefNet: Remove Background" under the Utility category.

<Card title="Download JSON Workflow File" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/utility_birefnet_remove_background.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_birefnet_remove_background&utm_source=docs">
  Open in cloud
</Card>

### 2. Download Models

The BiRefNet model is hosted on the [Comfy-Org BiRefNet model repository](https://huggingface.co/Comfy-Org/BiRefNet).

* [birefnet.safetensors](https://huggingface.co/Comfy-Org/BiRefNet/resolve/main/background_removal/birefnet.safetensors)

Place it in the following directory structure:

```
📂 ComfyUI/
└── 📂 models/
    └── 📂 background_removal/
        └── birefnet.safetensors
```

### 3. Using the Workflow

* **Image** — Load an image via the `Load Image` node (place it in the ComfyUI `input/` folder)
* The `Remove Background (BiRefNet)` subgraph processes the image and outputs:
  * **IMAGE** — the result with a transparent background (RGBA)
  * **mask** — the extracted foreground mask

Outputs can be previewed and used as inputs to other nodes for compositing, further editing, or saving.

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Additional Notes

* **Model directory** — the model must be placed in `ComfyUI/models/background_removal/`, not the `checkpoints` folder
* **Update required** — BiRefNet support is available in recent ComfyUI versions. Make sure your ComfyUI is up to date.
* **RGBA output** — the transparent background result can be directly composited onto new backgrounds or used in downstream workflows


# SAM 3.1: Segment Anything in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/video-segment-sam3

Learn how to use Meta's SAM 3.1 model in ComfyUI to segment objects in images and videos using text prompts

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

[SAM 3](https://ai.meta.com/sam3) (Segment Anything Model 3) is Meta's unified foundation model for promptable segmentation in images and videos. It can detect, segment, and track objects using text or visual prompts such as points, boxes, and masks. Compared to its predecessor [SAM 2](https://github.com/facebookresearch/sam2), SAM 3 introduces the ability to exhaustively segment all instances of an open-vocabulary concept specified by a short text phrase.

[SAM 3.1 Multiplex](https://github.com/facebookresearch/sam3) is the latest checkpoint release that introduces a shared-memory approach for joint multi-object tracking — significantly faster without sacrificing accuracy.

SAM 3.1 is natively supported in ComfyUI (PR [#13408](https://github.com/Comfy-Org/ComfyUI/pull/13408)), and the model weights are available under the [SAM License](https://github.com/facebookresearch/sam3/blob/main/LICENSE).

[SAM 3 GitHub](https://github.com/facebookresearch/sam3) | [Paper (arXiv)](https://arxiv.org/abs/2604.02296) | [🤗 Model Hub](https://huggingface.co/Comfy-Org/sam3.1)

<video>
  <source type="video/mp4" />
</video>

SAM 3.1 segments and tracks objects across video frames based on text prompts. The example above shows the segmentation output with masks applied to the target objects throughout the video.

### Key strengths

* **Text-driven segmentation** — describe what to segment in natural language, no need for manual point/box annotations
* **Image and video support** — works on both single images and video sequences with tracking across frames
* **Multi-object support** — segment and track multiple objects simultaneously using comma-separated prompts
* **Open-vocabulary** — handles a vastly larger set of open-vocabulary concepts than prior works

> **Limitations:** The model has a max token limit of 32 for text prompts. For best results, keep prompts short and specific to the target object.

## SAM 3.1 Segment Workflows

### 1. Download Workflow

Update your ComfyUI to the latest version, then go to `Workflow` -> `Browse Templates` and find the SAM 3.1 workflows under the Utility category.

**Video Segmentation:**

<Card title="Download JSON Workflow File" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/utility_video_segment_sam3.json">
  Download video workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_video_segment_sam3&utm_source=docs">
  Open in cloud
</Card>

**Image Segmentation:**

<Card title="Download JSON Workflow File" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/utility_image_segment_sam3.json">
  Download image workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_image_segment_sam3&utm_source=docs">
  Open in cloud
</Card>

### 2. Download Models

The SAM 3.1 model is hosted on the [Comfy-Org SAM 3.1 model repository](https://huggingface.co/Comfy-Org/sam3.1).

* [sam3.1\_multiplex\_fp16.safetensors](https://huggingface.co/Comfy-Org/sam3.1/resolve/main/checkpoints/sam3.1_multiplex_fp16.safetensors)

Place it in the following directory structure:

```
📂 ComfyUI/
└── 📂 models/
    └── 📂 checkpoints/
        └── sam3.1_multiplex_fp16.safetensors
```

### 3. Using the Workflows

**Image Segmentation:**

* **Image** — Load an image via the `Load Image` node (place it in the ComfyUI `input/` folder)
* **Object Prompt** — A short text description of the object(s) to segment, e.g. `person`, `car`, `cat`
* The output is a mask applied to the image, with an RGBA preview showing the segmentation result

**Video Segmentation:**

* **Video** — Load a video via the `Load Video` node
* **Object Prompt** — Same as image, a short text prompt describing what to track and segment across frames
* The output provides masks and bounding boxes for each frame

**Prompt format:**

| Prompt             | Role                                                     |
| ------------------ | -------------------------------------------------------- |
| SAM3 object prompt | Short description of **what** to segment. Max 32 tokens. |

To prompt multiple subjects separately, separate with commas and use `:N` to specify the max amount of objects detected per prompt:
`eye:2, window panels:4`

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Additional Notes

* **Keep prompts short and specific** — the model has a 32-token limit per prompt
* **Multi-object detection** — use commas to separate different object types, and `:N` to cap detections per type
* **Segmentation masks** — the output mask can be used as input to other workflows (e.g., inpainting, background removal)
* **Update required** — make sure ComfyUI is updated to the latest version to access SAM 3.1 support


# Video upscaling in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/video-upscale

Learn how to upscale videos in ComfyUI using local models and partner nodes for different use cases

This guide covers video upscaling workflows in ComfyUI, including local models and partner node options for various use cases.

<Card title="The Complete AI Upscaling Handbook" icon="book" href="https://blog.comfy.org/p/upscaling-in-comfyui">
  For a comprehensive deep-dive with benchmarks and visual comparisons, see the full article on the ComfyUI Blog.
</Card>

## TL;DR

* **Quality mode**: SeedVR2 and HitPaw deliver the most accurate and consistent realism.
* **Speed mode**: FlashVSR and HitPaw are the fastest options.
* **AI video fix**: Topaz Astra Creative is strongest for cinematic polish and fixing AI-generated video.
* **Archival restoration**: SeedVR2 preserves original structure while enhancing clarity.
* **CGI/3D render**: Topaz, SeedVR2, and HitPaw all produce clean, sharp results.

## Key concepts

### Upscaling vs. enhancement

* **Upscaling** increases resolution while reconstructing detail.
* **Enhancement** improves perceived quality (denoise, sharpen, restore, temporal consistency, etc.).

Video upscaling adds temporal considerations—maintaining consistency across frames while improving resolution.

### Creative vs. conservative upscale

|               | Conservative                                         | Creative                                          |
| ------------- | ---------------------------------------------------- | ------------------------------------------------- |
| **Approach**  | Preserve the original                                | Reimagine and enhance                             |
| **Strengths** | High accuracy, temporal consistency, production-safe | Rich details, sharper, more visually striking     |
| **Limits**    | Can appear flat, limited improvement on poor input   | Possible hallucinations, temporal flickering      |
| **Models**    | Topaz Starlight Fast, FlashVSR, SeedVR2, HitPaw      | Topaz Starlight Creative (Astra), Wan 2.2, HitPaw |

## Use cases

### Quality mode

**SeedVR2** and **HitPaw** deliver the most accurate results, with strong image quality and excellent character consistency.

**Topaz** also upscales effectively, but it can sometimes be more creative than expected. This makes it especially suitable for cinematic footage where a stylized look is acceptable.

<Card title="SeedVR2 - Conservative (WaveSpeed API)" icon="cloud" href="https://links.comfy.org/4khbzjY">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="SeedVR2 - Conservative (Open Source)" icon="cloud" href="https://links.comfy.org/4tm2RoI">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="HitPaw - All-in-one" icon="cloud" href="https://links.comfy.org/4kthLWs">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Topaz Astra - Creative" icon="cloud" href="https://links.comfy.org/4tlbyQj">
  Try on Comfy Cloud or download workflow
</Card>

### Speed mode

**FlashVSR** performs extremely well when speed is the priority. Upscaling from 720p to 1080p takes about **41 seconds for a 10-second video**, making it one of the fastest options available.

**HitPaw** is also relatively fast. In **Topaz**, the Fast and Creative modes render at similar speeds, so using **Creative** mode is generally recommended for better visual results without sacrificing time.

<Card title="FlashVSR - Conservative (WaveSpeed API)" icon="cloud" href="https://links.comfy.org/4khbzjY">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="HitPaw - All-in-one" icon="cloud" href="https://links.comfy.org/4kthLWs">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Topaz Astra - Creative" icon="cloud" href="https://links.comfy.org/4tlbyQj">
  Try on Comfy Cloud or download workflow
</Card>

### AI video fix

**Topaz Astra Creative** produces very smooth and visually consistent outputs, making it a strong choice for repairing AI-generated videos.

A useful workflow tip is to first run a **fix or cleanup pass**, then upscale to **1080p**, and finally upscale gradually to **4K**. This step-by-step approach usually leads to better stability and detail.

<Card title="Topaz Astra - Creative" icon="cloud" href="https://links.comfy.org/4tlbyQj">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Wan 2.2 Upscale - Creative" icon="cloud" href="https://links.comfy.org/3NVEu1b">
  Try on Comfy Cloud or download workflow
</Card>

### Archival restoration

**SeedVR2** is particularly impressive for archival restoration. It preserves the original structure and detail of the source footage while enhancing clarity, avoiding the introduction of artificial or exaggerated features.

<Card title="SeedVR2 - Conservative (Open Source)" icon="cloud" href="https://links.comfy.org/4tm2RoI">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="SeedVR2 - Conservative (WaveSpeed API)" icon="cloud" href="https://links.comfy.org/4khbzjY">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="Fast GAN - Traditional" icon="cloud" href="https://links.comfy.org/46wNZtS">
  Try on Comfy Cloud or download workflow
</Card>

### CGI / 3D render

**Topaz, SeedVR2 and HitPaw** all perform very well on CGI and 3D-rendered footage. They produce clean, sharp results and maintain the crisp edges that are important for synthetic imagery.

<Card title="Topaz Astra - Creative" icon="cloud" href="https://links.comfy.org/4tlbyQj">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="SeedVR2 - Conservative (WaveSpeed API)" icon="cloud" href="https://links.comfy.org/4khbzjY">
  Try on Comfy Cloud or download workflow
</Card>

<Card title="HitPaw - All-in-one" icon="cloud" href="https://links.comfy.org/4kthLWs">
  Try on Comfy Cloud or download workflow
</Card>

### Animation and motion graphics

Clean lines and consistent colors are essential. Conservative upscaling preserves the intended style.

**Recommended**: Topaz Starlight Fast, Fast GAN

<Card title="Fast GAN - Traditional" icon="cloud" href="https://links.comfy.org/46wNZtS">
  Try on Comfy Cloud or download workflow
</Card>

## Upscale speed comparison (10s 720p clips)

| Model                 | Resolution | Time   |
| --------------------- | ---------- | ------ |
| FlashVSR (local)      | 1080p      | \~41s  |
| FlashVSR (local)      | 4K         | \~52s  |
| HitPaw                | 2K         | \~80s  |
| HitPaw                | 4K         | \~175s |
| SeedVR2 (local, 5090) | 1080p      | \~312s |
| Topaz Astra           | 1080p      | \~374s |
| Topaz Astra           | 4K         | \~560s |

## Available models

### Partner nodes

Partner nodes provide access to advanced video upscaling models via API.

| Model                            | Type         | Max resolution | Features                         |
| -------------------------------- | ------------ | -------------- | -------------------------------- |
| Topaz Starlight Fast             | Conservative | 4K             | Fast, precision upscale          |
| Topaz Starlight Creative (Astra) | Creative     | 4K             | Diffusion-based creative upscale |
| Topaz Apollo                     | -            | -              | Frame interpolation              |
| WaveSpeed SeedVR2                | Conservative | -              | High fidelity                    |
| WaveSpeed FlashVSR               | Conservative | -              | Fast video super-resolution      |
| HitPaw                           | Both         | -              | All-in-one video enhancement     |

### Topaz Video Enhance features

* **Upscaling**: Starlight (Astra) supports fast video upscaling to FullHD (1080p) or 4K while maintaining clarity.
* **Interpolation**: Apollo model for frame interpolation with slowmo settings and custom frame rates (e.g., 60fps).
* **Dynamic compression**: Intelligently identifies and handles compression artifacts to improve image purity.

## Getting started with Topaz Video Enhance

1. Update ComfyUI to the latest version.
2. Search for the `Topaz Video Enhance` node in the node list.
3. Connect your video input and configure the settings.
4. Run the workflow.

## Tips

* Combine upscaling with [frame interpolation](/tutorials/utility/frame-interpolation) for smoother, higher-resolution output.
* For AI-generated videos, consider fixing artifacts before upscaling rather than relying on creative upscaling to fix them.
* Test different models on sample clips before processing full videos.
* Use conservative upscaling for content that requires strict fidelity to the original.


# VOID: Video Inpainting in ComfyUI
Source: https://docs.comfy.org/tutorials/utility/void-video-inpainting

Learn how to remove objects from videos using the VOID video inpainting model by Netflix, natively supported in ComfyUI

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

VOID (Video Object Inpainting and Deletion) is a powerful video inpainting model open-sourced by Netflix. It uses a two-pass diffusion pipeline built on [CogVideoX](https://github.com/THUDM/CogVideo) to remove objects from videos and fill the resulting holes with temporally coherent content.

VOID removes objects along with **all interactions they induce on the scene** — not just secondary effects like shadows and reflections, but physical interactions like objects falling when a person is removed. For example, if a person holding a guitar is removed, VOID also removes the person's effect on the guitar, causing it to fall naturally.

VOID is natively supported in ComfyUI (PR [#13403](https://github.com/Comfy-Org/ComfyUI/pull/13403)), and its complete model weights are available under the [Apache 2.0 License](https://github.com/Netflix/void-model?tab=Apache-2.0-1-ov-file).

[VOID Model - GitHub](https://github.com/Netflix/void-model) | [Paper (arXiv)](https://arxiv.org/abs/2604.02296) | [🤗 Diffusers Pipeline](https://huggingface.co/netflix/void-model)

<div>
  <video>
    <source type="video/mp4" />
  </video>

  <video>
    <source type="video/mp4" />
  </video>
</div>

**Before** (left) — the original footage with the snowboarder. **After** (right) — the processed result after removing the snowboarder from the scene. VOID removes unwanted objects while maintaining natural motion, lighting, and scene coherence across frames.

### Key strengths

* **Interaction-aware removal** — removes not just the object, but all physical interactions it caused on the scene (shadows, reflections, falling objects)
* **Object removal**, not single-frame patching — produces coherent motion and lighting across the entire clip
* **Two-pass refinement** — Pass 2 provides superior temporal stability (fewer jitters and flashes) compared to Pass 1 alone, especially on longer cuts or textured backgrounds

> **Limitations:** Unclear masks, chaotic motion, or targets that dominate the frame may still produce suboptimal results — prompting cannot fix fundamentally wrong segmentation.

## VOID Video Inpainting Workflow

### 1. Download Workflow

Update your ComfyUI to the latest version, then go to `Workflow` -> `Browse Templates` and find "VOID: Video Inpainting" under the Utility category.

<Card title="Download JSON Workflow File" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/utility_void_video_inpainting.json">
  Download workflow
</Card>

<Card title="Run on Comfy Cloud" icon="cloud" href="https://cloud.comfy.org/?template=utility_void_video_inpainting&utm_source=docs">
  Open in cloud
</Card>

### 2. Download Models

All models are hosted on the [Comfy-Org VOID model repository](https://huggingface.co/Comfy-Org/void-model).

**Diffusion Models** — the core two-pass inpainting model:

* [void\_pass2.safetensors](https://huggingface.co/Comfy-Org/void-model/resolve/main/diffusion_models/void_pass2.safetensors) — Refinement pass, better temporal stability
* [void\_pass1.safetensors](https://huggingface.co/Comfy-Org/void-model/resolve/main/diffusion_models/void_pass1.safetensors) — Primary pass

**VAE:**

* [cogvideox\_vae.safetensors](https://huggingface.co/Comfy-Org/void-model/resolve/main/vae/cogvideox_vae.safetensors)

**Optical Flow:**

* [raft\_large\_C\_T\_SKHT\_V2-ff5fadd5.safetensors](https://huggingface.co/Comfy-Org/void-model/resolve/main/optical_flow/raft_large_C_T_SKHT_V2-ff5fadd5.safetensors)

**SAM3 Checkpoint** — for segmentation:

* [sam3.1\_multiplex\_fp16.safetensors](https://huggingface.co/Comfy-Org/sam3.1/resolve/main/checkpoints/sam3.1_multiplex_fp16.safetensors)

**Text Encoder:**

* [t5xxl\_fp16.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors)

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 checkpoints/
│   │   └── sam3.1_multiplex_fp16.safetensors
│   ├── 📂 text_encoders/
│   │   └── t5xxl_fp16.safetensors
│   ├── 📂 vae/
│   │   └── cogvideox_vae.safetensors
│   ├── 📂 optical_flow/
│   │   └── raft_large_C_T_SKHT_V2-ff5fadd5.safetensors
│   └── 📂 diffusion_models/
│       ├── void_pass2.safetensors
│       └── void_pass1.safetensors
```

### 3. Using the Workflow

**Inputs:**

* **Source video** — Load a video via the `Load Video` node (place it in the ComfyUI `input/` folder)
* **Positive prompt (inpaint fill)** — Describe the scene **after** removal. Focus on what remains and how it looks, not on what was removed
  * Example: `empty kitchen counter, daylight, tiles visible`
* **Negative prompt** — Optional anti-artifact list; can be left empty
* **SAM3 object prompt** — A short label for **what** to mask out. SAM3 uses semantic understanding to create a segmentation mask for the target object.
  * Example: `person in blue jacket`, `red cup on table`
  * Max tokens for SAM3 prompts is **32**. To prompt multiple subjects separately, separate with commas and use `:N` to specify the max objects detected per prompt: `eye:2, window panels:4`

**Modes:**

| Prompt             | Role                                                                  |
| ------------------ | --------------------------------------------------------------------- |
| SAM3 object        | **What** is removed (SAM3 creates the mask via semantic segmentation) |
| Positive (inpaint) | **How** the hole is filled across time                                |

Use **Pass 2** (refinement pass) for longer clips or textured backgrounds where temporal stability matters. **Pass 1** alone is faster but may show more jitter.

<Card title="Learn about Subgraph" icon="book-open" href="/interface/features/subgraph">
  This workflow uses Subgraph nodes for modular video processing. Check out the Subgraph documentation to learn how to customize and extend the workflow.
</Card>

## Additional Notes

* **Mask quality matters** — a clean, tight mask around the target object produces the best results
* **Prompt writing tip** — describe the scene as it should appear *naturally* after removal, not the removal itself
* **Use negative prompt** only when you see repeating defects (watermarks, blur, extra limbs)
* **Two-pass workflow** — the template runs Pass 1 then Pass 2 automatically; you can also run just Pass 1 for faster iterations during testing


# Cosmos Predict2 Video2World  ComfyUI Official Example
Source: https://docs.comfy.org/tutorials/video/cosmos/cosmos-predict2-video2world

This guide demonstrates how to complete Cosmos-Predict2 Video2World workflows in ComfyUI

Cosmos-Predict2 is NVIDIA's next-generation physical world foundation model, specifically designed for high-quality visual generation and prediction tasks in physical AI scenarios.
The model features exceptional physical accuracy, environmental interactivity, and detail reproduction capabilities, enabling realistic simulation of complex physical phenomena and dynamic scenes.

Cosmos-Predict2 supports various generation methods including Text-to-Image (Text2Image) and Video-to-World (Video2World),
and is widely used in industrial simulation, autonomous driving, urban planning, scientific research, and other fields.
It serves as a crucial foundational tool for promoting deep integration of intelligent vision and the physical world.

GitHub:[Cosmos-predict2](https://github.com/nvidia-cosmos/cosmos-predict2)
huggingface: [Cosmos-Predict2](https://huggingface.co/collections/nvidia/cosmos-predict2-68028efc052239369a0f2959)

This guide will walk you through completing **Video2World** generation in ComfyUI.

For the text-to-image section, please refer to the following part:

<Card title="Cosmos Predict2 Text to Image" icon="book" href="/tutorials/image/cosmos/cosmos-predict2-t2i">
  Using Cosmos-Predict2 for text-to-image generation
</Card>


# ComfyUI Hunyuan Video Examples
Source: https://docs.comfy.org/tutorials/video/hunyuan/hunyuan-video

This guide shows how to use Hunyuan Text-to-Video and Image-to-Video workflows in ComfyUI

<video />

Hunyuan Video series is developed and open-sourced by [Tencent](https://huggingface.co/tencent), featuring a hybrid architecture that supports both [Text-to-Video](https://github.com/Tencent/HunyuanVideo) and [Image-to-Video](https://github.com/Tencent/HunyuanVideo-I2V) generation with a parameter scale of 13B.

Technical features:

* **Core Architecture:** Uses a DiT (Diffusion Transformer) architecture similar to Sora, effectively fusing text, image, and motion information to improve consistency, quality, and alignment between generated video frames. A unified full-attention mechanism enables multi-view camera transitions while ensuring subject consistency.
* **3D VAE:** The custom 3D VAE compresses videos into a compact latent space, making image-to-video generation more efficient.
* **Superior Image-Video-Text Alignment:** Utilizing MLLM text encoders that excel in both image and video generation, better following text instructions, capturing details, and performing complex reasoning.

You can learn more through the official repositories: [Hunyuan Video](https://github.com/Tencent/HunyuanVideo) and [Hunyuan Video-I2V](https://github.com/Tencent/HunyuanVideo-I2V).

This guide will walk you through setting up both **Text-to-Video** and **Image-to-Video** workflows in ComfyUI.

<Tip>
  The workflow images in this tutorial contain metadata with model download information.

  Simply drag them into ComfyUI or use the menu `Workflows` -> `Open (ctrl+o)` to load the corresponding workflow, which will prompt you to download the required models.

  Alternatively, this guide provides direct model links if automatic downloads fail or you are not using the Desktop version. All models are available [here](https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/tree/main/split_files) for download.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Common Models for All Workflows

The following models are used in both Text-to-Video and Image-to-Video workflows. Please download and save them to the specified directories:

* [clip\_l.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/resolve/main/split_files/text_encoders/clip_l.safetensors?download=true)
* [llava\_llama3\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/resolve/main/split_files/text_encoders/llava_llama3_fp8_scaled.safetensors?download=true)
* [hunyuan\_video\_vae\_bf16.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/resolve/main/split_files/vae/hunyuan_video_vae_bf16.safetensors?download=true)

Storage location:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors
│   │   └── llava_llama3_fp8_scaled.safetensors
│   ├── vae/
│   │   └── hunyuan_video_vae_bf16.safetensors
```

## Hunyuan Text-to-Video Workflow

Hunyuan Text-to-Video was open-sourced in December 2024, supporting 5-second short video generation through natural language descriptions in both Chinese and English.

### 1. Workflow

Download the image below and drag it into ComfyUI to load the workflow:
![ComfyUI Workflow - Hunyuan Text-to-Video](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hunyuan-video/t2v/kitchen.webp)

### 2. Manual Models Installation

Download [hunyuan\_video\_t2v\_720p\_bf16.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/resolve/main/split_files/diffusion_models/hunyuan_video_t2v_720p_bf16.safetensors?download=true) and save it to the `ComfyUI/models/diffusion_models` folder.

Ensure you have all these model files in the correct locations:

```
ComfyUI/
├── models/
│   ├── text_encoders/
│   │   ├── clip_l.safetensors                       // Shared model
│   │   └── llava_llama3_fp8_scaled.safetensors      // Shared model
│   ├── vae/
│   │   └── hunyuan_video_vae_bf16.safetensors       // Shared model
│   └── diffusion_models/
│       └── hunyuan_video_t2v_720p_bf16.safetensors  // T2V model
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI Hunyuan Video T2V Workflow" />

1. Ensure the `DualCLIPLoader` node has loaded these models:
   * clip\_name1: clip\_l.safetensors
   * clip\_name2: llava\_llama3\_fp8\_scaled.safetensors
2. Ensure the `Load Diffusion Model` node has loaded `hunyuan_video_t2v_720p_bf16.safetensors`
3. Ensure the `Load VAE` node has loaded `hunyuan_video_vae_bf16.safetensors`
4. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

<Tip>
  When the `length` parameter in the `EmptyHunyuanLatentVideo` node is set to 1, the model can generate a static image.
</Tip>

## Hunyuan Image-to-Video Workflow

Hunyuan Image-to-Video model was open-sourced on March 6, 2025, based on the HunyuanVideo framework. It transforms static images into smooth, high-quality videos and also provides LoRA training code to customize special video effects like hair growth, object transformation, etc.

Currently, the Hunyuan Image-to-Video model has two versions:

* v1 "concat": Better motion fluidity but less adherence to the image guidance
* v2 "replace": Updated the day after v1, with better image guidance but seemingly less dynamic compared to v1

<div>
  <div>
    <p>v1 "concat"</p>

    <img alt="HunyuanVideo v1" />
  </div>

  <div>
    <p>v2 "replace"</p>

    <img alt="HunyuanVideo v2" />
  </div>
</div>

### Shared Model for v1 and v2 Versions

Download the following file and save it to the `ComfyUI/models/clip_vision` directory:

* [llava\_llama3\_vision.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/resolve/main/split_files/clip_vision/llava_llama3_vision.safetensors?download=true)

### V1 "concat" Image-to-Video Workflow

#### 1. Workflow and Asset

Download the workflow image below and drag it into ComfyUI to load the workflow:
![ComfyUI Workflow - Hunyuan Image-to-Video v1](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hunyuan-video/i2v/v1_robot.webp)

Download the image below, which we'll use as the starting frame for the image-to-video generation:
![Starting Frame](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/hunyuan-video/i2v/robot-ballet.png)

#### 2. Related models manual installation

* [hunyuan\_video\_image\_to\_video\_720p\_bf16.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/resolve/main/split_files/diffusion_models/hunyuan_video_image_to_video_720p_bf16.safetensors?download=true)

Ensure you have all these model files in the correct locations:

```
ComfyUI/
├── models/
│   ├── clip_vision/
│   │   └── llava_llama3_vision.safetensors                     // I2V shared model
│   ├── text_encoders/
│   │   ├── clip_l.safetensors                                  // Shared model
│   │   └── llava_llama3_fp8_scaled.safetensors                 // Shared model
│   ├── vae/
│   │   └── hunyuan_video_vae_bf16.safetensors                  // Shared model
│   └── diffusion_models/
│       └── hunyuan_video_image_to_video_720p_bf16.safetensors  // I2V v1 "concat" version model
```

#### 3. Steps to Run the Workflow

<img alt="ComfyUI Hunyuan Video I2V v1 Workflow" />

1. Ensure that `DualCLIPLoader` has loaded these models:
   * clip\_name1: clip\_l.safetensors
   * clip\_name2: llava\_llama3\_fp8\_scaled.safetensors
2. Ensure that `Load CLIP Vision` has loaded `llava_llama3_vision.safetensors`
3. Ensure that `Load Image Model` has loaded `hunyuan_video_image_to_video_720p_bf16.safetensors`
4. Ensure that `Load VAE` has loaded `vae_name: hunyuan_video_vae_bf16.safetensors`
5. Ensure that `Load Diffusion Model` has loaded `hunyuan_video_image_to_video_720p_bf16.safetensors`
6. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

### v2 "replace" Image-to-Video Workflow

The v2 workflow is essentially the same as the v1 workflow. You just need to download the **replace** model and use it in the `Load Diffusion Model` node.

#### 1. Workflow and Asset

Download the workflow image below and drag it into ComfyUI to load the workflow:
![ComfyUI Workflow - Hunyuan Image-to-Video v2](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/hunyuan-video/i2v/v2_fennec_gril.webp)

Download the image below, which we'll use as the starting frame for the image-to-video generation:
![Starting Frame](https://comfyanonymous.github.io/ComfyUI_examples/flux/flux_dev_example.png)

#### 2. Related models manual installation

* [hunyuan\_video\_v2\_replace\_image\_to\_video\_720p\_bf16.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged/resolve/main/split_files/diffusion_models/hunyuan_video_v2_replace_image_to_video_720p_bf16.safetensors?download=true)

Ensure you have all these model files in the correct locations:

```
ComfyUI/
├── models/
│   ├── clip_vision/
│   │   └── llava_llama3_vision.safetensors                                // I2V shared model
│   ├── text_encoders/
│   │   ├── clip_l.safetensors                                             // Shared model
│   │   └── llava_llama3_fp8_scaled.safetensors                            // Shared model
│   ├── vae/
│   │   └── hunyuan_video_vae_bf16.safetensors                             // Shared model
│   └── diffusion_models/
│       └── hunyuan_video_v2_replace_image_to_video_720p_bf16.safetensors  // V2 "replace" version model
```

#### 3. Steps to Run the Workflow

<img alt="ComfyUI Hunyuan Video I2V v2 Workflow" />

1. Ensure the `DualCLIPLoader` node has loaded these models:
   * clip\_name1: clip\_l.safetensors
   * clip\_name2: llava\_llama3\_fp8\_scaled.safetensors
2. Ensure the `Load CLIP Vision` node has loaded `llava_llama3_vision.safetensors`
3. Ensure the `Load Image Model` node has loaded `hunyuan_video_image_to_video_720p_bf16.safetensors`
4. Ensure the `Load VAE` node has loaded `hunyuan_video_vae_bf16.safetensors`
5. Ensure the `Load Diffusion Model` node has loaded `hunyuan_video_v2_replace_image_to_video_720p_bf16.safetensors`
6. Click the `Queue` button or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Try it yourself

Here are some images and prompts we provide. Based on that content or make an adjustment to create your own video.

<img alt="example" />

```
Futuristic robot dancing ballet, dynamic motion, fast motion, fast shot, moving scene
```

***

<img alt="example" />

```
Samurai waving sword and hitting the camera. camera angle movement, zoom in, fast scene, super fast, dynamic
```

***

<img alt="example" />

```
flying car fastly moving and flying through the city
```

***

<img alt="example" />

```
cyberpunk car race in night city, dynamic, super fast, fast shot
```


# HunyuanVideo 1.5
Source: https://docs.comfy.org/tutorials/video/hunyuan/hunyuan-video-1-5

Learn how to use HunyuanVideo 1.5, a lightweight 8.3B parameter model for high-quality video generation on consumer GPUs

[HunyuanVideo 1.5](https://github.com/Tencent/HunyuanVideo) is a lightweight 8.3B parameter model developed by Tencent's Hunyuan team. It delivers flagship-quality video generation on consumer GPUs (24GB VRAM), dramatically lowering the barrier to entry without compromising on quality.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model highlights

* **Compact powerhouse**: Delivers SOTA performance comparable to larger models while running on consumer hardware.
* **Versatile generation**: Supports high-quality Text-to-Video and Image-to-Video (5-10s) with exceptional consistency.
* **Precise control**: Strong instruction following for camera movements, physics, and emotional expressions.
* **Cinematic quality**: Native 720p output (upscalable to 1080p) with professional aesthetics.
* **Rich features**: Supports diverse styles (realistic, anime, 3D) and in-video text rendering (Chinese/English).

## Workflow templates

[video\_hunyuan\_video\_1.5\_720p\_i2v.json](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_hunyuan_video_1.5_720p_i2v.json)

[video\_hunyuan\_video\_1.5\_720p\_t2v.json](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_hunyuan_video_1.5_720p_t2v.json)

## Model links

**text\_encoders**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)
* [byt5\_small\_glyphxl\_fp16.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/resolve/main/split_files/text_encoders/byt5_small_glyphxl_fp16.safetensors)

**diffusion\_models**

* [hunyuanvideo1.5\_1080p\_sr\_distilled\_fp16.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/resolve/main/split_files/diffusion_models/hunyuanvideo1.5_1080p_sr_distilled_fp16.safetensors)
* [hunyuanvideo1.5\_720p\_t2v\_fp16.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/resolve/main/split_files/diffusion_models/hunyuanvideo1.5_720p_t2v_fp16.safetensors)

**vae**

* [hunyuanvideo15\_vae\_fp16.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/resolve/main/split_files/vae/hunyuanvideo15_vae_fp16.safetensors)

Model Storage Location

```
:open_file_folder: ComfyUI/
├── :open_file_folder: models/
│   ├── :open_file_folder: text_encoders/
│   │      ├── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   │      └── byt5_small_glyphxl_fp16.safetensors
│   ├── :open_file_folder: diffusion_models/
│   │      ├── hunyuanvideo1.5_1080p_sr_distilled_fp16.safetensors
│   │      └── hunyuanvideo1.5_720p_t2v_fp16.safetensors
│   └── :open_file_folder: vae/
│          └── hunyuanvideo15_vae_fp16.safetensors
```


# Kandinsky 5.0
Source: https://docs.comfy.org/tutorials/video/kandinsky/kandinsky-5

This guide shows how to use Kandinsky 5.0 video generation workflows in ComfyUI

[Kandinsky 5.0](https://huggingface.co/kandinskylab/Kandinsky-5.0-I2V-Lite-5s) is a family of diffusion models for video and image generation developed by [Kandinsky Lab](https://huggingface.co/kandinskylab). The Kandinsky 5.0 T2V Lite is a lightweight 2B parameter model that ranks among the top open-source video generation models, capable of generating videos up to 10 seconds long.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Overview

Kandinsky 5.0 uses a latent diffusion pipeline with Flow Matching and features:

* **Diffusion Transformer (DiT):** Main generative backbone with cross-attention to text embeddings
* **Qwen2.5-VL and CLIP:** Provides high-quality text embeddings
* **HunyuanVideo 3D VAE:** Encodes and decodes video into a latent space

The model family includes multiple variants optimized for different use cases:

* **SFT model:** Highest generation quality
* **CFG-distilled:** 2× faster inference
* **Diffusion-distilled:** 6× faster with minimal quality loss (16 steps)
* **Pretrain model:** Designed for fine-tuning

All models are available in 5-second and 10-second video generation versions.

## Model variants

| Model                          | Video Duration | NFE | Latency (H100) |
| ------------------------------ | -------------- | --- | -------------- |
| Kandinsky 5.0 T2V Lite SFT     | 5s / 10s       | 100 | 139s / 224s    |
| Kandinsky 5.0 T2V Lite no-CFG  | 5s / 10s       | 50  | 77s / 124s     |
| Kandinsky 5.0 T2V Lite distill | 5s / 10s       | 16  | 35s / 61s      |
| Kandinsky 5.0 I2V Lite         | 5s             | 100 | 673s           |

## Text-to-Video workflow

### 1. Download workflow file

Please update your ComfyUI to the latest version, and through the menu `Workflow` -> `Browse Templates` -> `Video`, find "Kandinsky 5.0 T2V" to load the workflow.

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_kandinsky5_t2v.json">
  <p>Download JSON Workflow File</p>
</a>

### 2. Manually download models

**Text Encoders**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)
* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors)

**Diffusion Model**

* [kandinsky5lite\_t2v\_sft\_5s.safetensors](https://huggingface.co/kandinskylab/Kandinsky-5.0-T2V-Lite-sft-5s/resolve/main/model/kandinsky5lite_t2v_sft_5s.safetensors)

**VAE**

* [hunyuan\_video\_vae\_bf16.safetensors](https://huggingface.co/Kijai/HunyuanVideo_comfy/resolve/main/hunyuan_video_vae_bf16.safetensors)

```
ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      ├── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   │      └── clip_l.safetensors
│   ├── 📂 diffusion_models/
│   │      └── kandinsky5lite_t2v_sft_5s.safetensors
│   └── 📂 vae/
│          └── hunyuan_video_vae_bf16.safetensors
```

## Image-to-Video workflow

### 1. Download workflow file

Please update your ComfyUI to the latest version, and through the menu `Workflow` -> `Browse Templates` -> `Video`, find "Kandinsky 5.0 I2V" to load the workflow.

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_kandinsky5_i2v.json">
  <p>Download JSON Workflow File</p>
</a>

### 2. Manually download models

**Text Encoders**

* [qwen\_2.5\_vl\_7b\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/HunyuanVideo_1.5_repackaged/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)
* [clip\_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors)

**Diffusion Model**

* [kandinsky5lite\_i2v\_5s.safetensors](https://huggingface.co/kandinskylab/Kandinsky-5.0-I2V-Lite-5s/resolve/main/model/kandinsky5lite_i2v_5s.safetensors)

**VAE**

* [hunyuan\_video\_vae\_bf16.safetensors](https://huggingface.co/Kijai/HunyuanVideo_comfy/resolve/main/hunyuan_video_vae_bf16.safetensors)

```
ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      ├── qwen_2.5_vl_7b_fp8_scaled.safetensors
│   │      └── clip_l.safetensors
│   ├── 📂 diffusion_models/
│   │      └── kandinsky5lite_i2v_5s.safetensors
│   └── 📂 vae/
│          └── hunyuan_video_vae_bf16.safetensors
```

## Resources

* [HuggingFace Model Collection](https://huggingface.co/collections/kandinskylab/kandinsky-50-video-lite)
* [GitHub Repository](https://github.com/ai-forever/Kandinsky-5)
* [ComfyUI Integration](https://github.com/ai-forever/Kandinsky-5/blob/main/comfyui/README.md)
* [Project Page](https://ai-forever.github.io/Kandinsky-5/)


# ComfyUI Wan2.1 Fun Camera Official Examples
Source: https://docs.comfy.org/tutorials/video/wan/fun-camera

This guide demonstrates how to use Wan2.1 Fun Camera in ComfyUI for video generation

## About Wan2.1 Fun Camera

**Wan2.1 Fun Camera** is a video generation project launched by the Alibaba team, focusing on controlling video generation effects through camera motion.

**Model Weights Download**:

* [14B Version](https://huggingface.co/alibaba-pai/Wan2.1-Fun-V1.1-14B-Control-Camera)
* [1.3B Version](https://huggingface.co/alibaba-pai/Wan2.1-Fun-V1.1-1.3B-Control-Camera)

**Code Repository**: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

**ComfyUI now natively supports the Wan2.1 Fun Camera model**.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model Installation

These models only need to be installed once. Additionally, model download information is included in the corresponding workflow images, so you can choose your preferred way to download the models.

All of the following models can be found at [Wan\_2.1\_ComfyUI\_repackaged](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged)

**Diffusion Models** choose either 1.3B or 14B:

* [wan2.1\_fun\_camera\_v1.1\_1.3B\_bf16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_fun_camera_v1.1_1.3B_bf16.safetensors)
* [wan2.1\_fun\_camera\_v1.1\_14B\_bf16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_fun_camera_v1.1_14B_bf16.safetensors)

If you've used Wan2.1 related models before, you should already have the following models. If not, please download them:

**Text Encoders** choose one:

* [umt5\_xxl\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp16.safetensors)
* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors)

**CLIP Vision**

* [clip\_vision\_h.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors)

File Storage Location:

```
📂 ComfyUI/
├── 📂 models/
│ ├── 📂 diffusion_models/
│ │   ├── wan2.1_fun_camera_v1.1_1.3B_bf16.safetensors # 1.3B version
│ │   └── wan2.1_fun_camera_v1.1_14B_bf16.safetensors # 14B version
│ ├── 📂 text_encoders/
│ │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│ ├── 📂 vae/
│ │   └── wan_2.1_vae.safetensors
│ └── 📂 clip_vision/
│     └── clip_vision_h.safetensors
```

## ComfyUI Wan2.1 Fun Camera 1.3B Native Workflow Example

### 1. Workflow Related Files Download

#### 1.1 Workflow File

Download the video below and drag it into ComfyUI to load the corresponding workflow:

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/fun-camera/v1.1/wan2.1_fun_camera_1.3B.json">
  <p>Download Json Workflow File</p>
</a>

<Note>
  If you want to use the 14B version, simply replace the model file with the 14B version, but please be aware of the VRAM requirements.
</Note>

#### 1.2 Input Image Download

Please download the image below, which we will use as the starting frame:

![Input Reference Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/fun-camera/v1.1/wan2.1_fun_camera_1.3B_input.jpg)

### 2. Complete the Workflow Step by Step

<img alt="Wan2.1 Fun Camera Workflow Steps" />

1. Ensure the correct version of model file is loaded:
   * 1.3B version: `wan2.1_fun_camera_v1.1_1.3B_bf16.safetensors`
   * 14B version: `wan2.1_fun_camera_v1.1_14B_bf16.safetensors`
2. Ensure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`
4. Ensure the `Load CLIP Vision` node has loaded `clip_vision_h.safetensors`
5. Upload the starting frame to the `Load Image` node
6. Modify the Prompt if you're using your own input image
7. Set camera motion in the `WanCameraEmbedding` node
8. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute generation

## ComfyUI Wan2.1 Fun Camera 14B Workflow and Input Image

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/fun-camera/v1.1/wan2.1_fun_camera_14B.json">
  <p>Download Json Workflow File</p>
</a>

**Input Image**
![Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/fun-camera/v1.1/wan2.1_fun_camera_14B_input.jpg)

## Performance Reference

**1.3B Version**:

* 512×512 resolution on RTX 4090 takes about 72 seconds to generate 81 frames

**14B Version**:

* RTX4090 24GB VRAM may experience insufficient memory when generating 512×512 resolution, and memory issues have also occurred on A100 when using larger sizes


# ComfyUI Wan2.1 Fun Control Video Examples
Source: https://docs.comfy.org/tutorials/video/wan/fun-control

This guide demonstrates how to use Wan2.1 Fun Control in ComfyUI to generate videos with control videos

## About Wan2.1-Fun-Control

**Wan2.1-Fun-Control** is an open-source video generation and control project developed by Alibaba team.
It introduces innovative Control Codes mechanisms combined with deep learning and multimodal conditional inputs to generate high-quality videos that conform to preset control conditions. The project focuses on precisely guiding generated video content through multimodal control conditions.

Currently, the Fun Control model supports various control conditions, including **Canny (line art), Depth, OpenPose (human posture), MLSD (geometric edges), and trajectory control.**
The model also supports multi-resolution video prediction with options for 512, 768, and 1024 resolutions at 16 frames per second, generating videos up to 81 frames (approximately 5 seconds) in length.

Model versions:

* **1.3B** Lightweight: Suitable for local deployment and quick inference with **lower VRAM requirements**
* **14B** High-performance: Model size reaches 32GB+, offering better results but **requiring higher VRAM**

Here are the relevant code repositories:

* [Wan2.1-Fun-1.3B-Control](https://huggingface.co/alibaba-pai/Wan2.1-Fun-1.3B-Control)
* [Wan2.1-Fun-14B-Control](https://huggingface.co/alibaba-pai/Wan2.1-Fun-14B-Control)
* Code repository: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

ComfyUI now **natively supports** the Wan2.1 Fun Control model. Before starting this tutorial, please update your ComfyUI to ensure you're using a version after [this commit](https://github.com/Comfy-Org/ComfyUI/commit/3661c833bcc41b788a7c9f0e7bc48524f8ee5f82).

In this guide, we'll provide two workflows:

1. A workflow using only native Comfy Core nodes
2. A workflow using custom nodes

<Tip>
  Due to current limitations in native nodes for video support, the native-only workflow ensures users can complete the process without installing custom nodes.
  However, we've found that providing a good user experience for video generation is challenging without custom nodes, so we're providing both workflow versions in this guide.
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model Installation

You only need to install these models once. The workflow images also contain model download information, so you can choose your preferred download method.

The following models can be found at [Wan\_2.1\_ComfyUI\_repackaged](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged) and [Wan2.1-Fun](https://huggingface.co/collections/alibaba-pai/wan21-fun-67e4fb3b76ca01241eb7e334)

Click the corresponding links to download. If you've used Wan-related workflows before, you only need to download the **Diffusion models**.

**Diffusion models** - choose 1.3B or 14B. The 14B version has a larger file size (32GB) and higher VRAM requirements:

* [wan2.1\_fun\_control\_1.3B\_bf16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_fun_control_1.3B_bf16.safetensors?download=true)
* [Wan2.1-Fun-14B-Control](https://huggingface.co/alibaba-pai/Wan2.1-Fun-14B-Control/blob/main/diffusion_pytorch_model.safetensors?download=true): Rename to `Wan2.1-Fun-14B-Control.safetensors` after downloading

**Text encoders** - choose one of the following models (fp16 precision has a larger size and higher performance requirements):

* [umt5\_xxl\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp16.safetensors?download=true)
* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true)

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors?download=true)

**CLIP Vision**

* [clip\_vision\_h.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors?download=true)

File storage location:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── wan2.1_fun_control_1.3B_bf16.safetensors
│   ├── 📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   └── 📂 vae/
│   │   └── wan_2.1_vae.safetensors
│   └── 📂 clip_vision/
│       └──  clip_vision_h.safetensors                 
```

## ComfyUI Native Workflow

In this workflow, we use videos converted to **WebP format** since the `Load Image` node doesn't currently support mp4 format. We also use **Canny Edge** to preprocess the original video.
Because many users encounter installation failures and environment issues when installing custom nodes, this version of the workflow uses only native nodes to ensure a smoother experience.

Thanks to our powerful ComfyUI authors who provide feature-rich nodes. If you want to directly check the related version, see [Workflow Using Custom Nodes](#workflow-using-custom-nodes).

### 1. Workflow File Download

#### 1.1 Workflow File

Download the image below and drag it into ComfyUI to load the workflow:

![Wan2.1 Fun Control Native Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/wan2.1_fun_control/wan2.1_fun_control_native.webp)

#### 1.2 Input Images and Videos Download

Please download the following image and video for input:

![Input Reference Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/wan2.1_fun_control/input/01-portrait_remix.png)

![Input Reference Video](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/wan2.1_fun_control/input/01-portrait_video.webp)

### 2. Complete the Workflow Step by Step

<img alt="Wan2.1 Fun Control Workflow Steps" />

1. Ensure the `Load Diffusion Model` node has loaded `wan2.1_fun_control_1.3B_bf16.safetensors`
2. Ensure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`
4. Ensure the `Load CLIP Vision` node has loaded `clip_vision_h.safetensors`
5. Upload the starting frame to the `Load Image` node (renamed to `Start_image`)
6. Upload the control video to the second `Load Image` node. Note: This node currently doesn't support mp4, only WebP videos
7. (Optional) Modify the prompt (both English and Chinese are supported)
8. (Optional) Adjust the video size in `WanFunControlToVideo`, avoiding overly large dimensions
9. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation

### 3. Usage Notes

* Since we need to input the same number of frames as the control video into the `WanFunControlToVideo` node, if the specified frame count exceeds the actual control video frames, the excess frames may display scenes not conforming to control conditions. We'll address this issue in the [Workflow Using Custom Nodes](#workflow-using-custom-nodes)
* Avoid setting overly large dimensions, as this can make the sampling process very time-consuming. Try generating smaller images first, then upscale
* Use your imagination to build upon this workflow by adding text-to-image or other types of workflows to achieve direct text-to-video generation or style transfer
* Use tools like [ComfyUI-comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) for richer control options

## Workflow Using Custom Nodes

We'll need to install the following two custom nodes:

* [ComfyUI-VideoHelperSuite](https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite)
* [ComfyUI-comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux)

You can use [ComfyUI Manager](https://github.com/Comfy-Org/ComfyUI-Manager) to install missing nodes or follow the installation instructions for each custom node package.

### 1. Workflow File Download

#### 1.1 Workflow File

Download the image below and drag it into ComfyUI to load the workflow:

![Workflow File](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/wan2.1_fun_control/wan2.1_fun_control_use_custom_nodes.webp)

<Note>
  Due to the large size of video files, you can also click [here](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/wan2.1_fun_control/wan2.1_fun_control_use_custom_nodes.json) to download the workflow file in JSON format.
</Note>

#### 1.2 Input Images and Videos Download

Please download the following image and video for input:
![Input Reference Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/wan2.1_fun_control/input/02-robot's_eye.png)

<video />

### 2. Complete the Workflow Step by Step

<img alt="Wan2.1 Fun Control Workflow Using Custom Nodes Steps" />

> The model part is essentially the same. If you've already experienced the native-only workflow, you can directly upload the corresponding images and run it.

1. Ensure the `Load Diffusion Model` node has loaded `wan2.1_fun_control_1.3B_bf16.safetensors`
2. Ensure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`
4. Ensure the `Load CLIP Vision` node has loaded `clip_vision_h.safetensors`
5. Upload the starting frame to the `Load Image` node
6. Upload an mp4 format video to the `Load Video(Upload)` custom node. Note that the workflow has adjusted the default `frame_load_cap`
7. For the current image, the `DWPose Estimator` only uses the `detect_face` option
8. (Optional) Modify the prompt (both English and Chinese are supported)
9. (Optional) Adjust the video size in `WanFunControlToVideo`, avoiding overly large dimensions
10. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation

### 3. Workflow Notes

Thanks to the ComfyUI community authors for their custom node packages:

* This example uses `Load Video(Upload)` to support mp4 videos
* The `video_info` obtained from `Load Video(Upload)` allows us to maintain the same `fps` for the output video
* You can replace `DWPose Estimator` with other preprocessors from the `ComfyUI-comfyui_controlnet_aux` node package
* Prompts support multiple languages

## Usage Tips

<img alt="Apply Multi Control Videos" />

* A useful tip is that you can combine multiple image preprocessing techniques and then use the `Image Blend` node to achieve the goal of applying multiple control methods simultaneously.

* You can use the `Video Combine` node from `ComfyUI-VideoHelperSuite` to save videos in mp4 format

* We use `SaveAnimatedWEBP` because we currently don't support embedding workflow into **mp4** and some other custom nodes may not support embedding workflow too. To preserve the workflow in the video, we choose  `SaveAnimatedWEBP` node.

* In the `WanFunControlToVideo` node, `control_video` is not mandatory, so sometimes you can skip using a control video, first generate a very small video size like 320x320, and then use them as control video input to achieve consistent results.

* [ComfyUI-WanVideoWrapper](https://github.com/kijai/ComfyUI-WanVideoWrapper)

* [ComfyUI-KJNodes](https://github.com/kijai/ComfyUI-KJNodes)


# ComfyUI Wan2.1 Fun InP Video Examples
Source: https://docs.comfy.org/tutorials/video/wan/fun-inp

This guide demonstrates how to use Wan2.1 Fun InP in ComfyUI to generate videos with first and last frame control

## About Wan2.1-Fun-InP

**Wan-Fun InP** is an open-source video generation model released by Alibaba, part of the Wan2.1-Fun series, focusing on generating videos from images with first and last frame control.

**Key features**:

* **First and last frame control**: Supports inputting both first and last frame images to generate transitional video between them, enhancing video coherence and creative freedom. Compared to earlier community versions, Alibaba's official model produces more stable and significantly higher quality results.
* **Multi-resolution support**: Supports generating videos at 512×512, 768×768, 1024×1024 and other resolutions to accommodate different scenario requirements.

**Model versions**:

* **1.3B** Lightweight: Suitable for local deployment and quick inference with **lower VRAM requirements**
* **14B** High-performance: Model size reaches 32GB+, offering better results but requiring **higher VRAM**

Below are the relevant model weights and code repositories:

* [Wan2.1-Fun-1.3B-Input](https://huggingface.co/alibaba-pai/Wan2.1-Fun-1.3B-Input)
* [Wan2.1-Fun-14B-Input](https://huggingface.co/alibaba-pai/Wan2.1-Fun-14B-Input)
* Code repository: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

<Tip>
  Currently, ComfyUI natively supports the Wan2.1 Fun InP model. Before starting this tutorial, please update your ComfyUI to ensure your version is after [this commit](https://github.com/Comfy-Org/ComfyUI/commit/0a1f8869c9998bbfcfeb2e97aa96a6d3e0a2b5df).
</Tip>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Wan2.1 Fun InP Workflow

Download the image below and drag it into ComfyUI to load the workflow:

![Workflow File](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/wan2.1_fun_inp/wan2.1_fun_inp.webp)

### 1. Workflow File Download

### 2. Manual Model Installation

If automatic model downloading is ineffective, please download the models manually and save them to the corresponding folders.

The following models can be found at [Wan\_2.1\_ComfyUI\_repackaged](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged) and [Wan2.1-Fun](https://huggingface.co/collections/alibaba-pai/wan21-fun-67e4fb3b76ca01241eb7e334)

**Diffusion models** - choose 1.3B or 14B. The 14B version has a larger file size (32GB) and higher VRAM requirements:

* [wan2.1\_fun\_inp\_1.3B\_bf16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_fun_inp_1.3B_bf16.safetensors?download=true)
* [Wan2.1-Fun-14B-InP](https://huggingface.co/alibaba-pai/Wan2.1-Fun-14B-InP/resolve/main/diffusion_pytorch_model.safetensors?download=true): Rename to `Wan2.1-Fun-14B-InP.safetensors` after downloading

**Text encoders** - choose one of the following models (fp16 precision has a larger size and higher performance requirements):

* [umt5\_xxl\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp16.safetensors?download=true)
* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true)

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors?download=true)

**CLIP Vision**

* [clip\_vision\_h.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors?download=true)

File storage location:

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── wan2.1_fun_inp_1.3B_bf16.safetensors
│   ├── 📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   └── 📂 vae/
│   │   └── wan_2.1_vae.safetensors
│   └── 📂 clip_vision/
│       └──  clip_vision_h.safetensors                 
```

### 3. Complete the Workflow Step by Step

<img alt="ComfyUI Wan2.1 Fun InP Video Generation Workflow Diagram" />

1. Ensure the `Load Diffusion Model` node has loaded `wan2.1_fun_inp_1.3B_bf16.safetensors`
2. Ensure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`
4. Ensure the `Load CLIP Vision` node has loaded `clip_vision_h.safetensors`
5. Upload the starting frame to the `Load Image` node (renamed to `Start_image`)
6. Upload the ending frame to the second `Load Image` node
7. (Optional) Modify the prompt (both English and Chinese are supported)
8. (Optional) Adjust the video size in `WanFunInpaintToVideo`, avoiding overly large dimensions
9. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation

### 4. Workflow Notes

<Tip>
  Please make sure to use the correct model, as `wan2.1_fun_inp_1.3B_bf16.safetensors` and `wan2.1_fun_control_1.3B_bf16.safetensors` are stored in the same folder and have very similar names. Ensure you're using the right model.
</Tip>

* When using Wan Fun InP, you may need to frequently modify prompts to ensure the accuracy of the corresponding scene transitions.

## Other Wan2.1 Fun InP or video-related custom node packages

* [ComfyUI-VideoHelperSuite](https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite)
* [ComfyUI-WanVideoWrapper](https://github.com/kijai/ComfyUI-WanVideoWrapper)
* [ComfyUI-KJNodes](https://github.com/kijai/ComfyUI-KJNodes)


# ComfyUI Wan2.1 VACE Video Examples
Source: https://docs.comfy.org/tutorials/video/wan/vace

This article introduces how to complete Wan VACE video generation examples in ComfyUI

<Warning>
  As we have made adjustments to the template and added related usage and instructions for CausVid LoRA, this document needs to be updated and requires some preparation time. Until then, please refer to the notes in the template for usage
</Warning>

## About VACE

VACE 14B is an open-source unified video editing model launched by the Alibaba Tongyi Wanxiang team. Through integrating multi-task capabilities, supporting high-resolution processing and flexible multi-modal input mechanisms, this model significantly improves the efficiency and quality of video creation.

The model is open-sourced under the [Apache-2.0](https://github.com/ali-vilab/VACE?tab=Apache-2.0-1-ov-file) license and can be used for personal or commercial purposes.

Here is a comprehensive analysis of its core features and technical highlights:

* Multi-modal input: Supports multiple input forms including text, images, video, masks, and control signals
* Unified architecture: Single model supports multiple tasks with freely combinable functions
* Motion transfer: Generates coherent actions based on reference videos
* Local replacement: Replaces specific areas in videos through masks
* Video extension: Completes actions or extends backgrounds
* Background replacement: Preserves subjects while changing environmental backgrounds

Currently VACE has released two versions - 1.3B and 14B. Compared to the 1.3B version, the 14B version supports 720P resolution output with better image details and stability.

| Model                                                       | 480P | 720P |
| ----------------------------------------------------------- | ---- | ---- |
| [VACE-1.3B](https://huggingface.co/Wan-AI/Wan2.1-VACE-1.3B) | ✅    | ❌    |
| [VACE-14B](https://huggingface.co/Wan-AI/Wan2.1-VACE-14B)   | ✅    | ✅    |

Related model weights and code repositories:

* [VACE-1.3B](https://huggingface.co/Wan-AI/Wan2.1-VACE-1.3B)
* [VACE-14B](https://huggingface.co/Wan-AI/Wan2.1-VACE-14B)
* [Github](https://github.com/ali-vilab/VACE)
* [VACE Project Homepage](https://ali-vilab.github.io/VACE-Page/)

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model Download and Loading in Workflows

Since the workflows covered in this document all use the same workflow template, we can first complete the model download and loading information introduction, then enable/disable different inputs through Bypassing different nodes to achieve different workflows.
The model download information is already embedded in the workflow information in specific examples, so you can also complete the model download when downloading specific example workflows.

### Model Download

**diffusion\_models**
[wan2.1\_vace\_14B\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_vace_14B_fp16.safetensors)
[wan2.1\_vace\_1.3B\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_vace_1.3B_fp16.safetensors)

<Tip>
  If you have used Wan Video related workflows before, you have already downloaded the following model files.
</Tip>

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors?download=true)

Choose one version from **Text encoders** to download

* [umt5\_xxl\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp16.safetensors?download=true)
* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true)

File save location

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └─── wan2.1_vace_14B_fp16.safetensors
│   ├── 📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors # or umt5_xxl_fp16.safetensors
│   └── 📂 vae/
│       └──  wan_2.1_vae.safetensors
```

### Model Loading

Since the models used in the workflows covered in this document are consistent, the workflows are also the same, and only the nodes are bypassed to enable/disable different inputs, please refer to the following image to ensure that the corresponding models are correctly loaded in different workflows.

<img alt="Wan2.1 VACE Model Loading" />

1. Make sure the `Load Diffusion Model` node has loaded `wan2.1_vace_14B_fp16.safetensors`
2. Make sure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors` or `umt5_xxl_fp16.safetensors`
3. Make sure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`

### How to toggle Node Bypass Status

When a node is set to Bypass status, data passing through the node will not be affected by the node and will be output directly. We often set nodes to Bypass status when we don't need them.
Here are three ways to toggle a node's Bypass status:

<img alt="Toggle Bypass" />

1. After selecting the node, click the arrow in the indicator section of the selection toolbox to quickly toggle the node's Bypass status
2. After selecting the node, right-click the node and select `Mode` -> `Always` to switch to Always mode
3. After selecting the node, right-click the node and select the `Bypass` option to toggle the Bypass status

## VACE Text-to-Video Workflow

<Tip>
  If you cannot load the workflow from mp4 file, please ensure that your ComfyUI front-end version is up to date version in [requirements.txt](https://github.com/Comfy-Org/ComfyUI/blob/master/requirements.txt) , make sure you can load the workflow from mp4 file.

  Currently 1.19.9 is the latest ComfyUI front-end version in the requirements.txt file.
</Tip>

### 1. Workflow Download

Download the video below and drag it into ComfyUI to load the corresponding workflow

<video />

### 2. Complete the Workflow Step by Step

<img alt="image" />

Please follow the numbered steps in the image to ensure smooth workflow execution

1. Enter positive prompts in the `CLIP Text Encode (Positive Prompt)` node
2. Enter negative prompts in the `CLIP Text Encode (Negative Prompt)` node
3. Set the image dimensions (640x640 resolution recommended for first run) and frame count (video duration) in `WanVaceToVideo`
4. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation
5. Once generated, the video will automatically save to `ComfyUI/output/video` directory (subfolder location depends on `save video` node settings)

<Tip>
  During testing with a 4090 GPU:

  * 720x1280 resolution, generating 81 frames takes about 40 minutes
  * 640x640 resolution, generating 49 frames takes about 7 minutes

  However, 720P video quality is better.
</Tip>

## VACE Image-to-Video Workflow

You can continue using the workflow above, just unbypass the `Load image` node in **Load reference image** and input your image. You can also use the image below - in this file we've already set up the corresponding parameters.

### 1. Workflow Download

Download the video below and drag it into ComfyUI to load the corresponding workflow

<video />

Please download the image below as input

![vace-i2v-input](https://github.com/Comfy-Org/example_workflows/raw/refs/heads/main/video/wan/vace/i2v/input.jpg)

### 2. Complete the Workflow Step by Step

<img alt="Workflow Steps" />

Please follow the numbered steps in the image to ensure smooth workflow execution

1. Input the corresponding image in the `Load image` node
2. You can modify and edit prompts like in the text-to-video workflow
3. Set the image dimensions (640x640 resolution recommended for first run) and frame count (video duration) in `WanVaceToVideo`
4. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation
5. Once generated, the video will automatically save to `ComfyUI/output/video` directory (subfolder location depends on `save video` node settings)

<Tip>
  You may want to use nodes like getting image dimensions to set the resolution, but due to width and height step requirements of the corresponding nodes, you may get error messages if your image dimensions are not divisible by 16.
</Tip>

### 3. Additional Workflow Notes

VACE also supports inputting multiple reference images in a single image to generate corresponding videos. You can see related examples on the VACE project [page](https://ali-vilab.github.io/VACE-Page/)

## VACE Video-to-Video Workflow

### 1. Workflow Download

Download the video below and drag it into ComfyUI to load the corresponding workflow

<video />

We will use the following materials as input:

1. Input image for reference
   ![v2v-input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/vace/v2v/input.jpg)

2. The video below has been preprocessed and will be used to control video generation

<video />

3. The video below is the original video. You can download these materials and use preprocessing nodes like [comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) to preprocess the images

<video />

### 2. Complete the Workflow Step by Step

<img alt="Workflow Steps" />

Please follow the numbered steps in the image to ensure smooth workflow execution

1. Input the reference image in the `Load Image` node under `Load reference image`
2. Input the control video in the `Load Video` node under `Load control video`. Since the provided video is preprocessed, no additional processing is needed
3. If you need to preprocess the original video yourself, you can modify the `Image preprocessing` group or use `comfyui_controlnet_aux` nodes to complete the preprocessing
4. Modify prompts
5. Set the image dimensions (640x640 resolution recommended for first run) and frame count (video duration) in `WanVaceToVideo`
6. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation
7. Once generated, the video will automatically save to `ComfyUI/output/video` directory (subfolder location depends on `save video` node settings)

## VACE Video Outpainting Workflow

\[To be updated]

## VACE First-Last Frame Video Generation

\[To be updated]

To ensure that the first and last frames are effective, the video `length` setting must satisfy that `length-1` is divisible by 4.

The corresponding `Batch_size` setting must satisfy `Batch_size = length - 2`

## Related Node Documentation

Please refer to the documentation below to learn about related nodes

<Card title="WanVaceToVideo Node Documentation" icon="book" href="/built-in-nodes/conditioning/video-models/wan-vace-to-video">
  WanVaceToVideo Node Documentation
</Card>

<Card title="TrimVideoLatent Node Documentation" icon="book" href="/built-in-nodes/latent/video/trim-video-latent">
  ComfyUI TrimVideoLatent Node Documentation
</Card>


# Wan-Alpha Tutorial
Source: https://docs.comfy.org/tutorials/video/wan/wan-alpha

Learn how to generate videos with alpha channel transparency using Wan-Alpha in ComfyUI

Wan-Alpha is a specialized text-to-video model that generates high-quality videos with alpha channel transparency. Built on the Wan2.1-14B-T2V base model, it creates videos with transparent backgrounds and semi-transparent objects, perfect for compositing workflows.

The model excels at generating transparent backgrounds, semi-transparent objects (bubbles, glass, water), glowing effects, and fine details with proper alpha channels (hair, smoke, particles).

# Video tutorial

<iframe title="YouTube video player" />

[Download workflow](https://github.com/Comfy-Org/workflows/blob/main/tutorial_workflows/Get_Comfy_With_Comfy_Wan_Alpha.json)

## Resources

* [Wan-Alpha GitHub](https://github.com/WeChatCV/Wan-Alpha)
* [Hugging Face Model](https://huggingface.co/htdong/Wan-Alpha)
* [ComfyUI Version](https://huggingface.co/htdong/Wan-Alpha_ComfyUI)
* [Research Paper](https://arxiv.org/pdf/2509.24979)


# Wan ATI ComfyUI Native Workflow Tutorial
Source: https://docs.comfy.org/tutorials/video/wan/wan-ati

Using trajectory control for video generation.

**ATI (Any Trajectory Instruction)** is a controllable video generation framework proposed by the ByteDance team. ATI is implemented based on Wan2.1 and supports unified control of objects, local regions, and camera motion in videos through arbitrary trajectory instructions.

Project URL: [https://github.com/bytedance/ATI](https://github.com/bytedance/ATI)

## Key Features

* **Unified Motion Control**: Supports trajectory control for multiple motion types including objects, local regions, and camera movements.
* **Interactive Trajectory Editor**: Visual tool that allows users to freely draw and edit motion trajectories on images.
* **Wan2.1 Compatible**: Based on the official Wan2.1 implementation, compatible with environments and model structures.
* **Rich Visualization Tools**: Supports visualization of input trajectories, output videos, and trajectory overlays.

## WAN ATI Trajectory Control Workflow Example

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

### 1. Workflow Download

Download the video below and drag it into ComfyUI to load the corresponding workflow

<video />

We will use the following image as input:
![v2v-input](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/ati/input.jpg)

### 2. Model Download

If you haven't successfully downloaded the model files from the workflow, you can try downloading them manually using the links below

**Diffusion Model**

* [Wan2\_1-I2V-ATI-14B\_fp8\_e4m3fn.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/resolve/main/Wan2_1-I2V-ATI-14B_fp8_e4m3fn.safetensors)

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors?download=true)

**Text encoders**   Chose one of following model

* [umt5\_xxl\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp16.safetensors?download=true)
* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true)

**clip\_vision**

* [clip\_vision\_h.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors)

File save location

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   └───Wan2_1-I2V-ATI-14B_fp8_e4m3fn.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors # or other version
│   ├───📂 clip_vision/
│   │   └─── clip_vision_h.safetensors
│   └───📂 vae/
│       └──  wan_2.1_vae.safetensors
```

### 3. Complete the workflow execution step by step

<img alt="Workflow step diagram" />

Please follow the numbered steps in the image to ensure smooth execution of the corresponding workflow

1. Ensure the `Load Diffusion Model` node has loaded the `Wan2_1-I2V-ATI-14B_fp8_e4m3fn.safetensors` model
2. Ensure the `Load CLIP` node has loaded the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
3. Ensure the `Load VAE` node has loaded the `wan_2.1_vae.safetensors` model
4. Ensure the `Load CLIP Vision` node has loaded the `clip_vision_h.safetensors` model
5. Upload the provided input image in the `Load Image` node
6. Trajectory editing: Currently there is no corresponding trajectory editor in ComfyUI yet, you can use the following link to complete trajectory editing
   * [Online Trajectory Editing Tool](https://comfyui-wiki.github.io/Trajectory-Annotation-Tool/)
7. If you need to modify the prompts (positive and negative), please make changes in the `CLIP Text Encoder` node numbered `5`
8. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation


# ComfyUI Wan2.1 FLF2V Native Example
Source: https://docs.comfy.org/tutorials/video/wan/wan-flf

This guide explains how to complete Wan2.1 FLF2V video generation examples in ComfyUI

Wan FLF2V (First-Last Frame Video Generation) is an open-source video generation model developed by the Alibaba Tongyi Wanxiang team. Its open-source license is [Apache 2.0](https://github.com/Wan-Video/Wan2.1?tab=Apache-2.0-1-ov-file).
Users only need to provide two images as the starting and ending frames, and the model automatically generates intermediate transition frames, outputting a logically coherent and naturally flowing 720p high-definition video.

**Core Technical Highlights**

1. **Precise First-Last Frame Control**: The matching rate of first and last frames reaches 98%, defining video boundaries through starting and ending scenes, intelligently filling intermediate dynamic changes to achieve scene transitions and object morphing effects.
2. **Stable and Smooth Video Generation**: Using CLIP semantic features and cross-attention mechanisms, the video jitter rate is reduced by 37% compared to similar models, ensuring natural and smooth transitions.
3. **Multi-functional Creative Capabilities**: Supports dynamic embedding of Chinese and English subtitles, generation of anime/realistic/fantasy and other styles, adapting to different creative needs.
4. **720p HD Output**: Directly generates 1280×720 resolution videos without post-processing, suitable for social media and commercial applications.
5. **Open-source Ecosystem Support**: Model weights, code, and training framework are fully open-sourced, supporting deployment on mainstream AI platforms.

**Technical Principles and Architecture**

1. **DiT Architecture**: Based on diffusion models and Diffusion Transformer architecture, combined with Full Attention mechanism to optimize spatiotemporal dependency modeling, ensuring video coherence.
2. **3D Causal Variational Encoder**: Wan-VAE technology compresses HD frames to 1/128 size while retaining subtle dynamic details, significantly reducing memory requirements.
3. **Three-stage Training Strategy**: Starting from 480P resolution pre-training, gradually upgrading to 720P, balancing generation quality and computational efficiency through phased optimization.

**Related Links**

* **GitHub Repository**: [GitHub](https://github.com/Wan-Video/Wan2.1)
* **Hugging Face Model Page**: [Hugging Face](https://huggingface.co/Wan-AI/Wan2.1-FLF2V-14B-720P)
* **ModelScope Community**: [ModelScope](https://www.modelscope.cn/models/Wan-AI/Wan2.1-FLF2V-14B-720P)

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Wan2.1 FLF2V 720P ComfyUI Native Workflow Example

### 1. Download Workflow Files and Related Input Files

<Tip>
  Since this model is trained on high-resolution images, using smaller sizes may not yield good results. In the example, we use a size of 720 \* 1280, which may cause users with lower VRAM hard to run smoothly and will take a long time to generate.
  If needed, please adjust the video generation size for testing. A small generation size may not produce good output with this model, please notice that.
</Tip>

Please download the WebP file below, and drag it into ComfyUI to load the corresponding workflow. The workflow has embedded the corresponding model download file information.

![Wan2.1 FLF2V 720P f16 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/wan2.1_flf2v/wan2.1_flf2v_720_f16.webp)

Please download the two images below, which we will use as the starting and ending frames of the video

![start\_image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/wan2.1_flf2v/input/start_image.png)
![end\_image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/wan2.1_flf2v/input/end_image.png)

### 2. Manual Model Installation

If corresponding

All models involved in this guide can be found [here](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files).

**diffusion\_models** Choose one version based on your hardware conditions

* FP16:[wan2.1\_flf2v\_720p\_14B\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_flf2v_720p_14B_fp16.safetensors?download=true)
* FP8:[wan2.1\_flf2v\_720p\_14B\_fp8\_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_flf2v_720p_14B_fp8_e4m3fn.safetensors)

<Tip>
  If you have previously tried Wan Video related workflows, you may already have the following files.
</Tip>

Choose one version from **Text encoders** for download,

* [umt5\_xxl\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp16.safetensors?download=true)
* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true)

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors?download=true)

**CLIP Vision**

* [clip\_vision\_h.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors?download=true)

File Storage Location

```
ComfyUI/
├── models/
│   ├── diffusion_models/
│   │   └─── wan2.1_flf2v_720p_14B_fp16.safetensors           # or FP8 version
│   ├── text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors           # or your chosen version
│   ├── vae/
│   │   └──  wan_2.1_vae.safetensors
│   └── clip_vision/
│       └──  clip_vision_h.safetensors   
```

### 3. Complete Workflow Execution Step by Step

<img alt="Wan2.1 FLF2V 720P Native Workflow Steps" />

1. Ensure the `Load Diffusion Model` node has loaded `wan2.1_flf2v_720p_14B_fp16.safetensors` or `wan2.1_flf2v_720p_14B_fp8_e4m3fn.safetensors`
2. Ensure the `Load CLIP` node has loaded `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
3. Ensure the `Load VAE` node has loaded `wan_2.1_vae.safetensors`
4. Ensure the `Load CLIP Vision` node has loaded `clip_vision_h.safetensors`
5. Upload the starting frame to the `Start_image` node
6. Upload the ending frame to the `End_image` node
7. (Optional) Modify the positive and negative prompts, both Chinese and English are supported
8. (**Important**) In `WanFirstLastFrameToVideo` we use 720*1280 as default size.because it's a 720P model, so using a small size will not yield good output. Please use size around 720*1280 for good generation.
9. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation


# ComfyUI Wan-Move Workflow Example
Source: https://docs.comfy.org/tutorials/video/wan/wan-move

Wan-Move is a motion-controllable video generation model via latent trajectory guidance, enabling fine-grained point-level motion control for image-to-video generation.

**Wan-Move** is a motion-controllable video generation framework developed by Alibaba's Tongyi Lab. It enables users to control object motion in generated videos by specifying point trajectories on the input image, making image-to-video generation more precise and controllable.

**Key Features**:

* **High-Quality 5s 480p Motion Control**: Generates 5-second, 480p videos with fine-grained motion controllability
* **Latent Trajectory Guidance**: Represents motion conditions by propagating first frame features along trajectories
* **Fine-grained Point-level Control**: Object motions are represented with dense point trajectories, enabling precise region-level control
* **No Architecture Changes**: Seamlessly integrates into Wan-I2V-14B without extra motion modules

**Related Links**:

* [GitHub](https://github.com/ali-vilab/Wan-Move)
* [Hugging Face](https://huggingface.co/Ruihang/Wan-Move-14B-480P)
* [Paper](https://arxiv.org/abs/2512.08765)

## Wan-Move image-to-video workflow

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_wanmove_480p.json">
  <p>Download JSON Workflow File</p>
</a>

<a href="https://cloud.comfy.org/?template=video_wanmove_480p&utm_source=docs">
  <p>Run on ComfyUI Cloud</p>
</a>

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

## Model links

**text\_encoders**

* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)

**clip\_vision**

* [clip\_vision\_h.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors)

**loras**

* [lightx2v\_I2V\_14B\_480p\_cfg\_step\_distill\_rank64\_bf16.safetensors](https://huggingface.co/Kijai/WanVideo_comfy/resolve/main/Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors)

**diffusion\_models**

* [Wan21-WanMove\_fp8\_scaled\_e4m3fn\_KJ.safetensors](https://huggingface.co/Kijai/WanVideo_comfy_fp8_scaled/resolve/main/WanMove/Wan21-WanMove_fp8_scaled_e4m3fn_KJ.safetensors)

**vae**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors)

**Model Storage Location**

```
📂 ComfyUI/
├── 📂 models/
│   ├── 📂 text_encoders/
│   │      └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   ├── 📂 clip_vision/
│   │      └── clip_vision_h.safetensors
│   ├── 📂 loras/
│   │      └── lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors
│   ├── 📂 diffusion_models/
│   │      └── Wan21-WanMove_fp8_scaled_e4m3fn_KJ.safetensors
│   └── 📂 vae/
│          └── wan_2.1_vae.safetensors
```


# ComfyUI Wan2.1 Video Examples
Source: https://docs.comfy.org/tutorials/video/wan/wan-video

This guide demonstrates how to generate videos with first and last frames using Wan2.1 Video in ComfyUI

Wan2.1 Video series is a video generation model open-sourced by Alibaba in February 2025 under the [Apache 2.0 license](https://github.com/Wan-Video/Wan2.1?tab=Apache-2.0-1-ov-file).
It offers two versions:

* 14B (14 billion parameters)
* 1.3B (1.3 billion parameters)
  Covering multiple tasks including text-to-video (T2V) and image-to-video (I2V).
  The model not only outperforms existing open-source models in performance but more importantly, its lightweight version requires only 8GB of VRAM to run, significantly lowering the barrier to entry.

<video>
  <source type="video/mp4" />
</video>

* [Wan2.1 Code Repository](https://github.com/Wan-Video/Wan2.1)
* [Wan2.1 Model Repository](https://huggingface.co/Wan-AI)

<UpdateReminder />

## Wan2.1 ComfyUI Native Workflow Examples

<Tip>
  Please update ComfyUI to the latest version before starting the examples to make sure you have native Wan Video support.
</Tip>

## Model Installation

All models mentioned in this guide can be found [here](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files). Below are the common models you'll need for the examples in this guide, which you can download in advance:

Choose one version from **Text encoders** to download:

* [umt5\_xxl\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp16.safetensors?download=true)
* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors?download=true)

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors?download=true)

**CLIP Vision**

* [clip\_vision\_h.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors?download=true)

File storage locations:

```
ComfyUI/
├── models/
│   ├── diffusion_models/
│   ├── ...                  # Let's download the models in the corresponding workflow
│   ├── text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors
│   └── vae/
│   │   └──  wan_2.1_vae.safetensors
│   └── clip_vision/
│       └──  clip_vision_h.safetensors   
```

<Note>
  For diffusion models, we'll use the fp16 precision models in this guide because we've found that they perform better than the bf16 versions. If you need other precision versions, please visit [here](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files/diffusion_models) to download them.
</Note>

## Wan2.1 Text-to-Video Workflow

Before starting the workflow, please download [wan2.1\_t2v\_1.3B\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_1.3B_fp16.safetensors?download=true) and save it to the `ComfyUI/models/diffusion_models/` directory.

> If you need other t2v precision versions, please visit [here](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files/diffusion_models) to download them.

### 1. Workflow File Download

Download the file below and drag it into ComfyUI to load the corresponding workflow:

![Wan2.1 Text-to-Video Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/wan2.1/wan2.1_t2v_1.3b.webp)

### 2. Complete the Workflow Step by Step

<img alt="ComfyUI Wan2.1 Workflow Steps" />

1. Make sure the `Load Diffusion Model` node has loaded the `wan2.1_t2v_1.3B_fp16.safetensors` model
2. Make sure the `Load CLIP` node has loaded the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
3. Make sure the `Load VAE` node has loaded the `wan_2.1_vae.safetensors` model
4. (Optional) You can modify the video dimensions in the `EmptyHunyuanLatentVideo` node if needed
5. (Optional) If you need to modify the prompts (positive and negative), make changes in the `CLIP Text Encoder` node at number `5`
6. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the video generation

## Wan2.1 Image-to-Video Workflow

**Since Wan Video separates the 480P and 720P models**, we'll need to provide examples for both resolutions in this guide. In addition to using different models, they also have slight parameter differences.

### 480P Version

#### 1. Workflow and Input Image

Download the image below and drag it into ComfyUI to load the corresponding workflow:
![Wan2.1 Image-to-Video Workflow 14B 480P Workflow Example Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/wan2.1/wan2.1_i2v_14b_480P.webp)

We'll use the following image as input:

![Wan2.1 Image-to-Video Workflow 14B 480P Workflow Example Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/wan2.1/input/flux_dev_example.png)

#### 2. Model Download

Please download [wan2.1\_i2v\_480p\_14B\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_i2v_480p_14B_fp16.safetensors?download=true) and save it to the `ComfyUI/models/diffusion_models/` directory.

#### 3. Complete the Workflow Step by Step

<img alt="ComfyUI Wan2.1 Workflow Steps" />

1. Make sure the `Load Diffusion Model` node has loaded the `wan2.1_i2v_480p_14B_fp16.safetensors` model
2. Make sure the `Load CLIP` node has loaded the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
3. Make sure the `Load VAE` node has loaded the `wan_2.1_vae.safetensors` model
4. Make sure the `Load CLIP Vision` node has loaded the `clip_vision_h.safetensors` model
5. Upload the provided input image in the `Load Image` node
6. (Optional) Enter the video description content you want to generate in the `CLIP Text Encoder` node
7. (Optional) You can modify the video dimensions in the `WanImageToVideo` node if needed
8. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the video generation

### 720P Version

#### 1. Workflow and Input Image

Download the image below and drag it into ComfyUI to load the corresponding workflow:
![Wan2.1 Image-to-Video Workflow 14B 720P Workflow Example Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/wan2.1/wan2.1_i2v_14b_720P.webp)

We'll use the following image as input:

![Wan2.1 Image-to-Video Workflow 14B 720P Workflow Example Input Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/wan2.1/input/magician.png)

#### 2. Model Download

Please download [wan2.1\_i2v\_720p\_14B\_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_i2v_720p_14B_fp16.safetensors?download=true) and save it to the `ComfyUI/models/diffusion_models/` directory.

#### 3. Complete the Workflow Step by Step

<img alt="ComfyUI Wan2.1 Workflow Steps" />

1. Make sure the `Load Diffusion Model` node has loaded the `wan2.1_i2v_720p_14B_fp16.safetensors` model
2. Make sure the `Load CLIP` node has loaded the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
3. Make sure the `Load VAE` node has loaded the `wan_2.1_vae.safetensors` model
4. Make sure the `Load CLIP Vision` node has loaded the `clip_vision_h.safetensors` model
5. Upload the provided input image in the `Load Image` node
6. (Optional) Enter the video description content you want to generate in the `CLIP Text Encoder` node
7. (Optional) You can modify the video dimensions in the `WanImageToVideo` node if needed
8. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute the video generation


# ComfyUI Wan2.2 Fun Camera Control: Video Generation Workflow Example
Source: https://docs.comfy.org/tutorials/video/wan/wan2-2-fun-camera

This article demonstrates how to use camera control for video generation with Wan2.2 Fun Camera Control in ComfyUI.

**Wan2.2-Fun-Camera-Control** is a next-generation video generation and camera control model developed by Alibaba PAI. By introducing innovative Camera Control Codes and combining deep learning with multimodal conditional inputs, it generates high-quality videos that adhere to predefined camera motion conditions. The model is released under the **Apache 2.0 license**, allowing for commercial use.

**Key Features**:

* **Camera Motion Control**: Supports various camera motion modes, including **Pan Up**, **Pan Down**, **Pan Left**, **Pan Right**, **Zoom In**, **Zoom Out**, and combinations thereof.
* **High-Quality Video Generation**: Based on the Wan2.2 architecture, it outputs cinematic-quality videos.

Here are the relevant model weights and code repository:

* [🤗Wan2.2-Fun-A14B-Control-Camera](https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-Control-Camera)
* Code Repository: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

## Wan2.2 Fun Camera Control: Video Generation Workflow Example

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

The workflow provided includes two versions:

1. Using the [Wan2.2-Lightning](https://huggingface.co/lightx2v/Wan2.2-Lightning) 4-step LoRA via lightx2v: This may result in reduced video dynamics but offers faster generation.
2. The fp8\_scaled version without the acceleration LoRA.

Below are the timing results tested on an RTX4090D 24GB GPU for 640\*640 resolution and 81-frame length:

| Model Type                | Resolution | VRAM Usage | First Generation Time | Second Generation Time |
| ------------------------- | ---------- | ---------- | --------------------- | ---------------------- |
| fp8\_scaled               | 640×640    | 84%        | ≈ 536 seconds         | ≈ 513 seconds          |
| fp8\_scaled + 4-step LoRA | 640×640    | 89%        | ≈ 108 seconds         | ≈ 71 seconds           |

While the 4-step LoRA improves initial user experience, it may reduce video dynamism. By default, the accelerated LoRA version is enabled. To switch workflows, select the nodes and press **Ctrl+B**.

### 1. Workflow and Asset Download

Download the video or JSON file below and drag it into ComfyUI to load the corresponding workflow. The workflow will prompt you to download the models.

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_wan2_2_14B_fun_camera.json">
  <p>Download JSON Workflow</p>
</a>

Please download the image below, which we will use as input.

![Input Starting Image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/wan2.2_fun_camera/input.jpg)

### 2. Model Links

The following models can be found in [Wan\_2.2\_ComfyUI\_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged):

**Diffusion Model**

* [wan2.2\_fun\_camera\_high\_noise\_14B\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_fun_camera_high_noise_14B_fp8_scaled.safetensors)
* [wan2.2\_fun\_camera\_low\_noise\_14B\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_fun_camera_low_noise_14B_fp8_scaled.safetensors)

**Wan2.2-Lightning LoRA (Optional, for acceleration)**

* [wan2.2\_i2v\_lightx2v\_4steps\_lora\_v1\_high\_noise.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors)
* [wan2.2\_i2v\_lightx2v\_4steps\_lora\_v1\_low\_noise.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors)

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors)

**Text Encoder**

* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)

File save location

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_fun_camera_low_noise_14B_fp8_scaled.safetensors
│   │   └─── wan2.2_fun_camera_high_noise_14B_fp8_scaled.safetensors
│   ├───📂 loras/
│   │   ├─── wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors
│   │   └─── wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Complete the Workflow Step-by-Step

<img alt="Wan2.2 Fun Camera Control Workflow Steps" />

<Note>
  This workflow uses LoRA. Ensure the Diffusion model and LoRA are consistent; high noise and low noise models and LoRA must be paired accordingly.
</Note>

1. **High noise** model and **LoRA** loading

* Ensure the `Load Diffusion Model` node loads `wan2.2_fun_camera_high_noise_14B_fp8_scaled.safetensors`
* Ensure the `LoraLoaderModelOnly` node loads `wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors`

2. **Low noise** model and **LoRA** loading

* Ensure the `Load Diffusion Model` node loads `wan2.2_fun_camera_low_noise_14B_fp8_scaled.safetensors`
* Ensure the `LoraLoaderModelOnly` node loads `wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors`

3. Ensure the `Load CLIP` node loads `umt5_xxl_fp8_e4m3fn_scaled.safetensors`
4. Ensure the `Load VAE` node loads `wan_2.1_vae.safetensors`
5. Upload the starting frame in the `Load Image` node
6. Modify the Prompt (both Chinese and English are acceptable)
7. Set camera control parameters in the `WanCameraEmbedding` node:
   * **Camera Motion**: Select the camera motion type (Zoom In, Zoom Out, Pan Up, Pan Down, Pan Left, Pan Right, Static, etc.)
   * **Width/Height**: Set video resolution
   * **Length**: Set the number of video frames (default is 81 frames)
   * **Speed**: Set video speed (default is 1.0)
8. Click the `Run` button or use the shortcut `Ctrl(cmd) + Enter` to execute video generation


# ComfyUI Wan2.2 Fun Control Video Generation Example
Source: https://docs.comfy.org/tutorials/video/wan/wan2-2-fun-control

This article introduces how to use ComfyUI to complete the Wan2.2 Fun Control video generation using control videos

**Wan2.2-Fun-Control** is a next-generation video generation and control model launched by Alibaba PAI team. Through innovative Control Codes mechanism combined with deep learning and multi-modal conditional inputs, it can generate high-quality videos that comply with preset control conditions. The model is released under the **Apache 2.0 license** and supports commercial use.

**Key Features**:

* **Multi-modal Control**: Supports multiple control conditions including **Canny (line art)**, **Depth**, **OpenPose (human pose)**, **MLSD (geometric edges)**, and **trajectory control**
* **High-Quality Video Generation**: Based on the Wan2.2 architecture, outputs film-level quality videos
* **Multi-language Support**: Supports multi-language prompts including Chinese and English

Below are the relevant model weights and code repositories:

* [🤗Wan2.2-Fun-A14B-Control](https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-Control)
* Code repository: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

## ComfyOrg Wan2.2 Fun InP & Control Youtube Live Stream Replay

<iframe title="ComfyUI Selection Toolbox New Features" />

## Wan2.2 Fun Control Video Generation Workflow Example

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

This workflow provides two versions:

1. A version using [Wan2.2-Lightning](https://huggingface.co/lightx2v/Wan2.2-Lightning) 4-step LoRA from lightx2v: may cause some loss in video dynamics but offers faster speed
2. A fp8\_scaled version without acceleration LoRA

Below are the test results using an RTX4090D 24GB VRAM GPU at 640×640 resolution with 81 frames

| Model Type                | VRAM Usage | First Generation Time | Second Generation Time |
| ------------------------- | ---------- | --------------------- | ---------------------- |
| fp8\_scaled               | 83%        | ≈ 524s                | ≈ 520s                 |
| fp8\_scaled + 4-step LoRA | 89%        | ≈ 138s                | ≈ 79s                  |

Since using the 4-step LoRA provides a better experience for first-time workflow users, but may cause some loss in video dynamics, we have enabled the accelerated LoRA version by default. If you want to enable the other workflow, select it and use **Ctrl+B** to activate.

### 1. Download Workflow and Materials

Download the video below or JSON file and drag it into ComfyUI to load the workflow

<video />

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_wan2_2_14B_fun_control.json">
  <p>Download JSON Workflow</p>
</a>

Please download the following images and videos as input materials.

![Input start image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/wan2.2_fun_control/input.jpg)

<video />

> We use a preprocessed video here.

### 2. Models

You can find the models below at [Wan\_2.2\_ComfyUI\_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged)

**Diffusion Model**

* [wan2.2\_fun\_control\_high\_noise\_14B\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_fun_control_high_noise_14B_fp8_scaled.safetensors)
* [wan2.2\_fun\_control\_low\_noise\_14B\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_fun_control_low_noise_14B_fp8_scaled.safetensors)

**Wan2.2-Lightning LoRA (Optional, for acceleration)**

* [wan2.2\_i2v\_lightx2v\_4steps\_lora\_v1\_high\_noise.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors)
* [wan2.2\_i2v\_lightx2v\_4steps\_lora\_v1\_low\_noise.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors)

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors)

**Text Encoder**

* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_fun_control_low_noise_14B_fp8_scaled.safetensors
│   │   └─── wan2.2_fun_control_high_noise_14B_fp8_scaled.safetensors
│   ├───📂 loras/
│   │   ├─── wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors
│   │   └─── wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Workflow Guide

<img alt="Wan2.2 Fun Control Workflow Steps" />

<Note>
  This workflow uses LoRA. Please ensure the corresponding Diffusion model and LoRA are matched - high noise and low noise models and LoRAs need to be used correspondingly.
</Note>

1. **High noise** model and **LoRA** loading
   * Ensure the `Load Diffusion Model` node loads the `wan2.2_fun_control_high_noise_14B_fp8_scaled.safetensors` model
   * Ensure the `LoraLoaderModelOnly` node loads the `wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors`
2. **Low noise** model and **LoRA** loading
   * Ensure the `Load Diffusion Model` node loads the `wan2.2_fun_control_low_noise_14B_fp8_scaled.safetensors` model
   * Ensure the `LoraLoaderModelOnly` node loads the `wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors`
3. Ensure the `Load CLIP` node loads the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
4. Ensure the `Load VAE` node loads the `wan_2.1_vae.safetensors` model
5. Upload the start frame in the `Load Image` node
6. In the second `Load video` node, load the pose control video. The provided video has been preprocessed and can be used directly
7. Since we provide a preprocessed pose video, the corresponding video image preprocessing node needs to be disabled. You can select it and use `Ctrl + B` to disable it
8. Modify the Prompt - you can use both Chinese and English
9. In `Wan22FunControlToVideo`, modify the video dimensions. The default is set to 640×640 resolution to avoid excessive processing time for users with low VRAM
10. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation

### Additional Notes

Since ComfyUI's built-in nodes only include Canny preprocessor, you can use tools like [ComfyUI-comfyui\_controlnet\_aux](https://github.com/Fannovel16/comfyui_controlnet_aux) to implement other types of image preprocessing


# ComfyUI Wan2.2 Fun Inp Start-End Frame Video Generation Example
Source: https://docs.comfy.org/tutorials/video/wan/wan2-2-fun-inp

This article introduces how to use ComfyUI to complete the Wan2.2 Fun Inp start-end frame video generation example

**Wan2.2-Fun-Inp** is a start-end frame controlled video generation model launched by Alibaba PAI team. It supports inputting **start and end frame images** to generate intermediate transition videos, providing creators with greater creative control. The model is released under the **Apache 2.0 license** and supports commercial use.

**Key Features**:

* **Start-End Frame Control**: Supports inputting start and end frame images to generate intermediate transition videos, enhancing video coherence and creative freedom
* **High-Quality Video Generation**: Based on the Wan2.2 architecture, outputs film-level quality videos
* **Multi-Resolution Support**: Supports generating videos at 512×512, 768×768, 1024×1024 and other resolutions to suit different scenarios

**Model Version**:

* **14B High-Performance Version**: Model size exceeds 32GB, with better results but requires high VRAM

Below are the relevant model weights and code repositories:

* [🤗Wan2.2-Fun-Inp-14B](https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-InP)
* Code repository: [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)

## ComfyOrg Wan2.2 Fun InP & Control Youtube Live Stream Replay

<iframe title="ComfyUI Selection Toolbox New Features" />

## Wan2.2 Fun Inp Start-End Frame Video Generation Workflow Example

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

This workflow provides two versions:

1. A version using [Wan2.2-Lightning](https://huggingface.co/lightx2v/Wan2.2-Lightning) 4-step LoRA from lightx2v for accelerated video generation
2. A fp8\_scaled version without acceleration LoRA

Below are the test results using an RTX4090D 24GB VRAM GPU at 640×640 resolution with 81 frames

| Model Type                | VRAM Usage | First Generation Time | Second Generation Time |
| ------------------------- | ---------- | --------------------- | ---------------------- |
| fp8\_scaled               | 83%        | ≈ 524s                | ≈ 520s                 |
| fp8\_scaled + 4-step LoRA | 89%        | ≈ 138s                | ≈ 79s                  |

Since the acceleration with LoRA is significant but the video dynamic is lost,  the provided workflows enable the accelerated LoRA version by default. If you want to enable the other workflow, select it and use **Ctrl+B** to activate.

### 1. Download Workflow File

Please update your ComfyUI to the latest version, and find "**Wan2.2 Fun Inp**" under the menu `Workflow` -> `Browse Templates` -> `Video` to load the workflow.

Or, after updating ComfyUI to the latest version, download the workflow below and drag it into ComfyUI to load.

<a href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/video_wan2_2_14B_animate.json">
  <p>Download JSON Workflow</p>
</a>

<a href="https://cloud.comfy.org/?template=video_wan2_2_14B_fun_inpaint&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

Use the following materials as the start and end frames

![Wan2.2 Fun Control ComfyUI Workflow Start Frame Material](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/wan2.2_fun_inp/start_image.png)
![Wan2.2 Fun Control ComfyUI Workflow End Frame Material](https://raw.githubusercontent.com/Comfy-Org/example_workflows/refs/heads/main/video/wan/wan2.2_fun_inp/end_image.png)

### 2. Models

**Diffusion Model**

* [wan2.2\_fun\_inpaint\_high\_noise\_14B\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_fun_inpaint_high_noise_14B_fp8_scaled.safetensors)
* [wan2.2\_fun\_inpaint\_low\_noise\_14B\_fp8\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_fun_inpaint_low_noise_14B_fp8_scaled.safetensors)

**Lightning LoRA (Optional, for acceleration)**

* [wan2.2\_i2v\_lightx2v\_4steps\_lora\_v1\_high\_noise.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors)
* [wan2.2\_i2v\_lightx2v\_4steps\_lora\_v1\_low\_noise.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors)

**VAE**

* [wan\_2.1\_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors)

**Text Encoder**

* [umt5\_xxl\_fp8\_e4m3fn\_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)

```
ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_fun_inpaint_high_noise_14B_fp8_scaled.safetensors
│   │   └─── wan2.2_fun_inpaint_low_noise_14B_fp8_scaled.safetensors
│   ├───📂 loras/
│   │   ├─── wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors
│   │   └─── wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors
```

### 3. Workflow Guide

<img alt="Workflow Step Image" />

<Note>
  This workflow uses LoRA. Please make sure the corresponding Diffusion model and LoRA are matched.
</Note>

1. **High noise** model and **LoRA** loading
   * Ensure the `Load Diffusion Model` node loads the `wan2.2_fun_inpaint_high_noise_14B_fp8_scaled.safetensors` model
   * Ensure the `LoraLoaderModelOnly` node loads the `wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors`
2. **Low noise** model and **LoRA** loading
   * Ensure the `Load Diffusion Model` node loads the `wan2.2_fun_inpaint_low_noise_14B_fp8_scaled.safetensors` model
   * Ensure the `LoraLoaderModelOnly` node loads the `wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors`
3. Ensure the `Load CLIP` node loads the `umt5_xxl_fp8_e4m3fn_scaled.safetensors` model
4. Ensure the `Load VAE` node loads the `wan_2.1_vae.safetensors` model
5. Upload the start and end frame images as materials
6. Enter your prompt in the Prompt group
7. Adjust the size and video length in the `WanFunInpaintToVideo` node
   * Adjust the `width` and `height` parameters. The default is `640`. We set a smaller size, but you can modify it as needed.
   * Adjust the `length`, which is the total number of frames. The current workflow fps is 16. For example, if you want to generate a 5-second video, you should set it to 5\*16 = 80.
8. Click the `Run` button, or use the shortcut `Ctrl(cmd) + Enter` to execute video generation


# CFGNorm - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CFGNorm

Complete documentation for the CFGNorm node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CFGNorm/en.md)

The CFGNorm node applies a normalization technique to the classifier-free guidance (CFG) process in diffusion models. It adjusts the scale of the denoised prediction by comparing the norms of the conditional and unconditional outputs, then applies a strength multiplier to control the effect. This helps stabilize the generation process by preventing extreme values in the guidance scaling.

## Inputs

| Parameter  | Data Type | Required | Range        | Description                                                                                  |
| ---------- | --------- | -------- | ------------ | -------------------------------------------------------------------------------------------- |
| `model`    | MODEL     | Yes      | -            | The diffusion model to apply CFG normalization to                                            |
| `strength` | FLOAT     | Yes      | 0.0 to 100.0 | Controls the intensity of the normalization effect applied to the CFG scaling (default: 1.0) |

## Outputs

| Output Name     | Data Type | Description                                                                       |
| --------------- | --------- | --------------------------------------------------------------------------------- |
| `patched_model` | MODEL     | Returns the modified model with CFG normalization applied to its sampling process |

***

**Source fingerprint (SHA-256):** `adbcea5c02277a7bd93866eaae75fe150b5b310dbc6e0a3a31c4e4ee0f71e57c`


# CFGZeroStar - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CFGZeroStar

Complete documentation for the CFGZeroStar node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CFGZeroStar/en.md)

The CFGZeroStar node applies a specialized guidance scaling technique to diffusion models. It modifies the classifier-free guidance process by calculating an optimized scale factor based on the difference between conditional and unconditional predictions. This approach adjusts the final output to provide enhanced control over the generation process while maintaining model stability.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                        |
| --------- | --------- | -------- | ----- | ---------------------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -     | The diffusion model to be modified with the CFGZeroStar guidance scaling technique |

## Outputs

| Output Name     | Data Type | Description                                                  |
| --------------- | --------- | ------------------------------------------------------------ |
| `patched_model` | MODEL     | The modified model with CFGZeroStar guidance scaling applied |

***

**Source fingerprint (SHA-256):** `4ec70f67eed8aaca964ce3dfb5b650af2f44d34bcde3b74c3886c91e1e8e8cc0`


# CLIPTextEncodeHiDream - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodeHiDream

Complete documentation for the CLIPTextEncodeHiDream node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeHiDream/en.md)

The CLIPTextEncodeHiDream node processes four separate text inputs using different language models (CLIP-L, CLIP-G, T5-XXL, and LLaMA) and combines them into a single conditioning output. It tokenizes each text input with its corresponding model and encodes them together using a scheduled encoding approach, enabling more sophisticated text conditioning by leveraging multiple language models simultaneously.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                          |
| --------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------ |
| `clip`    | CLIP      | Yes      | -     | The CLIP model used for tokenization and encoding                                    |
| `clip_l`  | STRING    | Yes      | -     | Text input for CLIP-L model processing. Supports multiline text and dynamic prompts. |
| `clip_g`  | STRING    | Yes      | -     | Text input for CLIP-G model processing. Supports multiline text and dynamic prompts. |
| `t5xxl`   | STRING    | Yes      | -     | Text input for T5-XXL model processing. Supports multiline text and dynamic prompts. |
| `llama`   | STRING    | Yes      | -     | Text input for LLaMA model processing. Supports multiline text and dynamic prompts.  |

**Note:** All four text inputs (`clip_l`, `clip_g`, `t5xxl`, and `llama`) are required for proper functioning, as each contributes to the final conditioning output through the scheduled encoding process.

## Outputs

| Output Name    | Data Type    | Description                                                                                                  |
| -------------- | ------------ | ------------------------------------------------------------------------------------------------------------ |
| `CONDITIONING` | CONDITIONING | The combined conditioning output from all processed text inputs, encoded using the scheduled encoding method |

***

**Source fingerprint (SHA-256):** `4d0febcfc7fa8035d817a6b36ec80b9bdf176ede8446b49f291efd96b9d1371c`


# CLIPTextEncodeKandinsky5 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodeKandinsky5

Complete documentation for the CLIPTextEncodeKandinsky5 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeKandinsky5/en.md)

The CLIPTextEncodeKandinsky5 node prepares text prompts for use with the Kandinsky 5 model. It takes two separate text inputs, tokenizes them using a provided CLIP model, and combines them into a single conditioning output. This output is used to guide the image generation process.

## Inputs

| Parameter   | Data Type | Required | Range | Description                                                                      |
| ----------- | --------- | -------- | ----- | -------------------------------------------------------------------------------- |
| `clip`      | CLIP      | Yes      |       | The CLIP model used to tokenize and encode the text prompts.                     |
| `clip_l`    | STRING    | Yes      |       | The primary text prompt. This input supports multiline text and dynamic prompts. |
| `qwen25_7b` | STRING    | Yes      |       | A secondary text prompt. This input supports multiline text and dynamic prompts. |

## Outputs

| Output Name    | Data Type    | Description                                                                                                                     |
| -------------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The combined conditioning data generated from both text prompts, ready to be fed into a Kandinsky 5 model for image generation. |

***

**Source fingerprint (SHA-256):** `f033b1924336ccb15d300eb713e859f9f08f48552b409c45b0a8a168d1ba51c2`


# CLIPTextEncodePixArtAlpha - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodePixArtAlpha

Complete documentation for the CLIPTextEncodePixArtAlpha node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodePixArtAlpha/en.md)

Encodes text and sets the resolution conditioning for PixArt Alpha. This node processes text input and adds width and height information to create conditioning data specifically for PixArt Alpha models. It does not apply to PixArt Sigma models.

## Inputs

| Parameter | Data Type | Required | Range                | Description                                                            |
| --------- | --------- | -------- | -------------------- | ---------------------------------------------------------------------- |
| `width`   | INT       | Yes      | 0 to MAX\_RESOLUTION | The width dimension for resolution conditioning (default: 1024)        |
| `height`  | INT       | Yes      | 0 to MAX\_RESOLUTION | The height dimension for resolution conditioning (default: 1024)       |
| `text`    | STRING    | Yes      | -                    | Text input to be encoded, supports multiline input and dynamic prompts |
| `clip`    | CLIP      | Yes      | -                    | CLIP model used for tokenization and encoding                          |

## Outputs

| Output Name    | Data Type    | Description                                                           |
| -------------- | ------------ | --------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | Encoded conditioning data with text tokens and resolution information |

***

**Source fingerprint (SHA-256):** `d2ed9de57b9b9579162687e1ffaf859e18a0585bbe75888496a42772337b6746`


# CLIPTextEncodeSD3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodeSD3

Complete documentation for the CLIPTextEncodeSD3 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeSD3/en.md)

The CLIPTextEncodeSD3 node processes text inputs for Stable Diffusion 3 models by encoding multiple text prompts using different CLIP models. It handles three separate text inputs (clip\_g, clip\_l, and t5xxl) and provides options for managing empty text padding. The node ensures proper token alignment between different text inputs and returns conditioning data suitable for SD3 generation pipelines.

## Inputs

| Parameter       | Data Type | Required | Range                          | Description                                                                                                                                                                                                                |
| --------------- | --------- | -------- | ------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip`          | CLIP      | Yes      | -                              | The CLIP model used for text encoding                                                                                                                                                                                      |
| `clip_l`        | STRING    | Yes      | -                              | Text input for the local CLIP model. Supports multiline text and dynamic prompts.                                                                                                                                          |
| `clip_g`        | STRING    | Yes      | -                              | Text input for the global CLIP model. Supports multiline text and dynamic prompts.                                                                                                                                         |
| `t5xxl`         | STRING    | Yes      | -                              | Text input for the T5-XXL model. Supports multiline text and dynamic prompts.                                                                                                                                              |
| `empty_padding` | COMBO     | Yes      | `"none"`<br />`"empty_prompt"` | Controls how empty text inputs are handled. When set to "none", empty text inputs for `clip_g`, `clip_l`, or `t5xxl` will result in empty token lists instead of padding. This is an advanced parameter (default: "none"). |

**Parameter Constraints:**

* When `empty_padding` is set to "none", empty text inputs for `clip_g`, `clip_l`, or `t5xxl` will result in empty token lists instead of padding
* The node automatically balances token lengths between `clip_l` and `clip_g` inputs by padding the shorter one with empty tokens when lengths differ
* All text inputs support dynamic prompts and multiline text entry

## Outputs

| Output Name    | Data Type    | Description                                                                  |
| -------------- | ------------ | ---------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The encoded text conditioning data ready for use in SD3 generation pipelines |

***

**Source fingerprint (SHA-256):** `2086e7c0fe910a94c04173ecfe35a2e04ecb306526b9089c527bb874e97b20c4`


# CheckpointLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CheckpointLoader

Complete documentation for the CheckpointLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CheckpointLoader/en.md)

The CheckpointLoader node loads a pre-trained model checkpoint along with its configuration file. It takes a configuration file and a checkpoint file as inputs and returns the loaded model components including the main model, CLIP model, and VAE model for use in the workflow.

## Inputs

| Parameter     | Data Type | Required | Range                      | Description                                                             |
| ------------- | --------- | -------- | -------------------------- | ----------------------------------------------------------------------- |
| `config_name` | STRING    | Yes      | Available config files     | The configuration file that defines the model architecture and settings |
| `ckpt_name`   | STRING    | Yes      | Available checkpoint files | The checkpoint file containing the trained model weights and parameters |

**Note:** This node requires both a configuration file and a checkpoint file to be selected. The configuration file must match the architecture of the checkpoint file being loaded.

## Outputs

| Output Name | Data Type | Description                                                    |
| ----------- | --------- | -------------------------------------------------------------- |
| `MODEL`     | MODEL     | The loaded main model component ready for inference            |
| `CLIP`      | CLIP      | The loaded CLIP model component for text encoding              |
| `VAE`       | VAE       | The loaded VAE model component for image encoding and decoding |

**Important Note:** This node has been marked as deprecated and may be removed in future versions. Consider using alternative loading nodes for new workflows.

***

**Source fingerprint (SHA-256):** `9977bda5e124a9d10566839cbee868c74fab120c454141f27ce145efa60105e9`


# CLIPLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipLoader

Complete documentation for the CLIPLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPLoader/en.md)

The CLIPLoader node loads a text encoder model (CLIP, T5, or similar) from a file, making it available for use in other nodes that need to convert text prompts into numerical representations. It supports a wide variety of model architectures, each requiring a specific encoder type.

## Inputs

| Parameter   | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                        | Description                                                                                                                                                    |
| ----------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip_name` | STRING    | Yes      | List of files found in the `text_encoders` folder                                                                                                                                                                                                                                                                                                            | The filename of the text encoder model to load. This must be a file located in the `ComfyUI/models/text_encoders/` or `ComfyUI/models/clip/` directory.        |
| `type`      | STRING    | Yes      | `"stable_diffusion"`<br />`"stable_cascade"`<br />`"sd3"`<br />`"stable_audio"`<br />`"mochi"`<br />`"ltxv"`<br />`"pixart"`<br />`"cosmos"`<br />`"lumina2"`<br />`"wan"`<br />`"hidream"`<br />`"chroma"`<br />`"ace"`<br />`"omnigen2"`<br />`"qwen_image"`<br />`"hunyuan_image"`<br />`"flux2"`<br />`"ovis"`<br />`"longcat_image"`<br />`"cogvideox"` | The architecture type of the model being loaded. This determines which specific encoder variant to use. The default is `"stable_diffusion"`.                   |
| `device`    | STRING    | No       | `"default"`<br />`"cpu"`                                                                                                                                                                                                                                                                                                                                     | The device to load the model onto. `"default"` uses the GPU if available, while `"cpu"` forces CPU loading. This is an advanced option (default: `"default"`). |

### Supported Type-to-Encoder Mappings

The `type` parameter selects the correct encoder for a given model architecture. The following are common mappings:

| Type              | Encoder                       |
| ----------------- | ----------------------------- |
| stable\_diffusion | clip-l                        |
| stable\_cascade   | clip-g                        |
| sd3               | t5 xxl / clip-g / clip-l      |
| stable\_audio     | t5 base                       |
| mochi             | t5 xxl                        |
| cogvideox         | t5 xxl (226-token padding)    |
| cosmos            | old t5 xxl                    |
| lumina2           | gemma 2 2B                    |
| wan               | umt5 xxl                      |
| hidream           | llama-3.1 (recommended) or t5 |
| omnigen2          | qwen vl 2.5 3B                |

## Outputs

| Output Name | Data Type | Description                                                                                             |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------- |
| `clip`      | CLIP      | The loaded text encoder model, ready to be connected to other nodes for text encoding and conditioning. |

***

**Source fingerprint (SHA-256):** `1051bfe5570dff81719682cb09938bae4c03e94e0e72f7a2be84867cccb48017`


# CLIPTextEncodeFlux - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipTextEncodeFlux

Complete documentation for the CLIPTextEncodeFlux node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeFlux/en.md)

`CLIPTextEncodeFlux` is an advanced text encoding node designed for the Flux architecture. It processes two separate text inputs through different encoders—CLIP-L and T5XXL—and combines them with a guidance scale to produce a unified conditioning output for image generation.

## Inputs

| Parameter  | Data Type | Required | Range       | Description                                                                                                                                                                          |
| ---------- | --------- | -------- | ----------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `clip`     | CLIP      | Yes      | -           | A CLIP model that supports the Flux architecture, including both CLIP-L and T5XXL encoders.                                                                                          |
| `clip_l`   | STRING    | Yes      | -           | Text input processed by the CLIP-L encoder. Suitable for concise keyword descriptions, such as style or theme. Supports multiline input and dynamic prompts.                         |
| `t5xxl`    | STRING    | Yes      | -           | Text input processed by the T5XXL encoder. Suitable for detailed natural language descriptions, expressing complex scenes and details. Supports multiline input and dynamic prompts. |
| `guidance` | FLOAT     | Yes      | 0.0 - 100.0 | Controls the influence of text conditions on the generation process. Higher values mean stricter adherence to the text. Default: 3.5.                                                |

## Outputs

| Output Name    | Data Type    | Description                                                                                                         |
| -------------- | ------------ | ------------------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | Contains the fused embeddings from both encoders and the guidance parameter, used for conditional image generation. |

***

**Source fingerprint (SHA-256):** `63027b4a7c1868da27fb2644b0d6599d241fa0206a78d169110ce57f0cebf148`


# CLIPTextEncodeHunyuanDiT - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipTextEncodeHunyuanDit

Complete documentation for the CLIPTextEncodeHunyuanDiT node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeHunyuanDiT/en.md)

The `CLIPTextEncodeHunyuanDiT` node converts text descriptions into a format that the HunyuanDiT model can understand. It is an advanced conditioning node designed for the dual text encoder architecture of HunyuanDiT, processing two separate text inputs through different tokenizers.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                                                                                                   |
| --------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip`    | CLIP      | Yes      | -     | A CLIP model instance used for text tokenization and encoding, which is core to generating conditions.                                                        |
| `bert`    | STRING    | Yes      | -     | Text input for encoding via the BERT tokenizer. Prefers phrases and keywords. Supports multiline and dynamic prompts.                                         |
| `mt5xl`   | STRING    | Yes      | -     | Text input for encoding via the mT5-XL tokenizer. Supports multiline and dynamic prompts (multilingual). Can use complete sentences and complex descriptions. |

## Outputs

| Output Name    | Data Type    | Description                                                                                                                      |
| -------------- | ------------ | -------------------------------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The encoded conditioning output, combining both BERT and mT5-XL tokenized text, used for further processing in generation tasks. |

***

**Source fingerprint (SHA-256):** `bde7c884f72829491090965bd9af34ad59ec326f96e88bb7cdb9ddc47592137e`


# CLIPTextEncodeSDXL - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipTextEncodeSdxl

Complete documentation for the CLIPTextEncodeSDXL node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to encode text input using a CLIP model specifically customized for the SDXL architecture. It uses a dual encoder system (CLIP-L and CLIP-G) to process text descriptions, resulting in more accurate image generation.

## Inputs

| Parameter       | Data Type | Description                                            |
| --------------- | --------- | ------------------------------------------------------ |
| `clip`          | CLIP      | CLIP model instance used for text encoding.            |
| `width`         | INT       | Specifies the image width in pixels, default 1024.     |
| `height`        | INT       | Specifies the image height in pixels, default 1024.    |
| `crop_w`        | INT       | Width of the crop area in pixels, default 0.           |
| `crop_h`        | INT       | Height of the crop area in pixels, default 0.          |
| `target_width`  | INT       | Target width for the output image, default 1024.       |
| `target_height` | INT       | Target height for the output image, default 1024.      |
| `text_g`        | STRING    | Global text description for overall scene description. |
| `text_l`        | STRING    | Local text description for detail description.         |

## Outputs

| Parameter      | Data Type    | Description                                                                    |
| -------------- | ------------ | ------------------------------------------------------------------------------ |
| `CONDITIONING` | CONDITIONING | Contains encoded text and conditional information needed for image generation. |


# CLIPTextEncodeSDXLRefiner - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipTextEncodeSdxlRefiner

Complete documentation for the CLIPTextEncodeSDXLRefiner node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is specifically designed for the SDXL Refiner model to convert text prompts into conditioning information by incorporating aesthetic scores and dimensional information to enhance the conditions for generation tasks, thereby improving the final refinement effect. It acts like a professional art director, not only conveying your creative intent but also injecting precise aesthetic standards and specification requirements into the work.

## About SDXL Refiner

SDXL Refiner is a specialized refinement model that focuses on enhancing image details and quality based on the SDXL base model. This process is like having an art retoucher:

1. First, it receives preliminary images or text descriptions generated by the base model
2. Then, it guides the refinement process through precise aesthetic scoring and dimensional parameters
3. Finally, it focuses on processing high-frequency image details to improve overall quality

Refiner can be used in two ways:

* As a standalone refinement step for post-processing images generated by the base model
* As part of an expert integration system, taking over processing during the low-noise phase of generation

## Inputs

| Parameter Name | Data Type | Input Type | Default Value | Value Range | Description                                                                                                                                                                                                                                                                                                |
| -------------- | --------- | ---------- | ------------- | ----------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip`         | CLIP      | Required   | -             | -           | CLIP model instance used for text tokenization and encoding, the core component for converting text into model-understandable format                                                                                                                                                                       |
| `ascore`       | FLOAT     | Optional   | 6.0           | 0.0-1000.0  | Controls the visual quality and aesthetics of generated images, similar to setting quality standards for artwork:<br />- High scores(7.5-8.5): Pursues more refined, detail-rich effects<br />- Medium scores(6.0-7.0): Balanced quality control<br />- Low scores(2.0-3.0): Suitable for negative prompts |
| `width`        | INT       | Required   | 1024          | 64-16384    | Specifies output image width (pixels), must be multiple of 8. SDXL performs best when total pixel count is close to 1024×1024 (about 1M pixels)                                                                                                                                                            |
| `height`       | INT       | Required   | 1024          | 64-16384    | Specifies output image height (pixels), must be multiple of 8. SDXL performs best when total pixel count is close to 1024×1024 (about 1M pixels)                                                                                                                                                           |
| `text`         | STRING    | Required   | -             | -           | Text prompt description, supports multi-line input and dynamic prompt syntax. In Refiner, text prompts should focus more on describing desired visual quality and detail characteristics                                                                                                                   |

## Outputs

| Output Name    | Data Type    | Description                                                                                                                                                                                            |
| -------------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `CONDITIONING` | CONDITIONING | Refined conditional output containing integrated encoding of text semantics, aesthetic standards, and dimensional information, specifically for guiding SDXL Refiner model in precise image refinement |

## Notes

1. This node is specifically optimized for the SDXL Refiner model and differs from regular CLIPTextEncode nodes
2. An aesthetic score of 7.5 is recommended as the baseline, which is the standard setting used in SDXL training
3. All dimensional parameters must be multiples of 8, and total pixel count close to 1024×1024 (about 1M pixels) is recommended
4. The Refiner model focuses on enhancing image details and quality, so text prompts should emphasize desired visual effects rather than scene content
5. In practical use, Refiner is typically used in the later stages of generation (approximately the last 20% of steps), focusing on detail optimization


# CombineHooks - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CombineHooks

Complete documentation for the CombineHooks node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CombineHooks/en.md)

The Combine Hooks \[2] node merges two hook groups into a single combined hook group. It takes two optional hook inputs and combines them using ComfyUI's hook combination functionality. This allows you to consolidate multiple hook configurations for streamlined processing.

## Inputs

| Parameter | Data Type | Required | Range | Description                  |
| --------- | --------- | -------- | ----- | ---------------------------- |
| `hooks_A` | HOOKS     | No       | -     | First hook group to combine  |
| `hooks_B` | HOOKS     | No       | -     | Second hook group to combine |

**Note:** Both inputs are optional, but at least one hook group must be provided for the node to function. If only one hook group is provided, it will be returned unchanged.

## Outputs

| Output Name | Data Type | Description                                                     |
| ----------- | --------- | --------------------------------------------------------------- |
| `hooks`     | HOOKS     | Combined hook group containing all hooks from both input groups |

***

**Source fingerprint (SHA-256):** `558ceef1cebedd0b7e045b7d1eb1afa4316ea6a3c35f982968af132dca164126`


# CombineHooksEight - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CombineHooksEight

Complete documentation for the CombineHooksEight node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CombineHooksEight/en.md)

The Combine Hooks \[8] node merges up to eight different hook groups into a single combined hook group. It takes multiple hook inputs and combines them using ComfyUI's hook combination functionality. This allows you to consolidate multiple hook configurations for streamlined processing in advanced workflows.

## Inputs

| Parameter | Data Type | Input Type | Default | Range | Description                   |
| --------- | --------- | ---------- | ------- | ----- | ----------------------------- |
| `hooks_A` | HOOKS     | optional   | None    | -     | First hook group to combine   |
| `hooks_B` | HOOKS     | optional   | None    | -     | Second hook group to combine  |
| `hooks_C` | HOOKS     | optional   | None    | -     | Third hook group to combine   |
| `hooks_D` | HOOKS     | optional   | None    | -     | Fourth hook group to combine  |
| `hooks_E` | HOOKS     | optional   | None    | -     | Fifth hook group to combine   |
| `hooks_F` | HOOKS     | optional   | None    | -     | Sixth hook group to combine   |
| `hooks_G` | HOOKS     | optional   | None    | -     | Seventh hook group to combine |
| `hooks_H` | HOOKS     | optional   | None    | -     | Eighth hook group to combine  |

**Note:** All input parameters are optional. The node will combine only the hook groups that are provided, ignoring any that are left empty. You can provide anywhere from one to eight hook groups for combination.

## Outputs

| Output Name | Data Type | Description                                                                  |
| ----------- | --------- | ---------------------------------------------------------------------------- |
| `HOOKS`     | HOOKS     | A single combined hook group containing all the provided hook configurations |

***

**Source fingerprint (SHA-256):** `8cd13ec6710a9b2905c14301cfd15be616c00f1b4140451cdf0915f091c77197`


# CombineHooksFour - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CombineHooksFour

Complete documentation for the CombineHooksFour node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CombineHooksFour/en.md)

The Combine Hooks \[4] node merges up to four separate hook groups into a single combined hook group. It takes any combination of the four available hook inputs and combines them using ComfyUI's hook combination system. This allows you to consolidate multiple hook configurations for streamlined processing in advanced workflows.

## Inputs

| Parameter | Data Type | Input Type | Default | Range | Description                  |
| --------- | --------- | ---------- | ------- | ----- | ---------------------------- |
| `hooks_A` | HOOKS     | optional   | None    | -     | First hook group to combine  |
| `hooks_B` | HOOKS     | optional   | None    | -     | Second hook group to combine |
| `hooks_C` | HOOKS     | optional   | None    | -     | Third hook group to combine  |
| `hooks_D` | HOOKS     | optional   | None    | -     | Fourth hook group to combine |

**Note:** All four hook inputs are optional. The node will combine only the hook groups that are provided, and will return an empty hook group if no inputs are connected.

## Outputs

| Output Name | Data Type | Description                                                     |
| ----------- | --------- | --------------------------------------------------------------- |
| `HOOKS`     | HOOKS     | Combined hook group containing all provided hook configurations |

***

**Source fingerprint (SHA-256):** `92a8038e7b5a7491afcbd48830a1e278fe4d697321fb874821ebf7edd09d5815`


# ConditioningSetDefaultAndCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetDefaultAndCombine

Complete documentation for the ConditioningSetDefaultAndCombine node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetDefaultAndCombine/en.md)

This node combines a primary conditioning input with a default conditioning input using a hook-based system. It merges the two conditioning sources into a single output, allowing the default conditioning to serve as a fallback or base when the primary conditioning is incomplete.

## Inputs

| Parameter      | Data Type    | Input Type | Default | Range | Description                                                                                   |
| -------------- | ------------ | ---------- | ------- | ----- | --------------------------------------------------------------------------------------------- |
| `cond`         | CONDITIONING | Required   | -       | -     | The primary conditioning input to be processed and combined                                   |
| `cond_DEFAULT` | CONDITIONING | Required   | -       | -     | The default conditioning data to be combined with the primary conditioning                    |
| `hooks`        | HOOKS        | Optional   | -       | -     | Optional hook configuration that controls how the conditioning data is processed and combined |

## Outputs

| Output Name    | Data Type    | Description                                                                                       |
| -------------- | ------------ | ------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The combined conditioning data resulting from merging the primary and default conditioning inputs |

***

**Source fingerprint (SHA-256):** `5e6c95f454c7e262878cc362c6b199e01abff10f803c81afe6e76a317c30d039`


# ConditioningSetProperties - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetProperties

Complete documentation for the ConditioningSetProperties node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetProperties/en.md)

The ConditioningSetProperties node modifies the properties of conditioning data by adjusting strength, area settings, and applying optional masks, hooks, or timestep ranges. It allows you to control how conditioning influences the generation process by setting specific parameters that affect the application of conditioning data during image generation.

## Inputs

| Parameter       | Data Type        | Input Type | Default | Range                       | Description                                                                                                                             |
| --------------- | ---------------- | ---------- | ------- | --------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
| `cond_NEW`      | CONDITIONING     | Required   | -       | -                           | The conditioning data to modify                                                                                                         |
| `strength`      | FLOAT            | Required   | 1.0     | 0.0 - 10.0 (step: 0.01)     | Controls the intensity of the conditioning effect                                                                                       |
| `set_cond_area` | STRING           | Required   | default | \["default", "mask bounds"] | Determines how the conditioning area is applied. Choose "default" for standard behavior or "mask bounds" to restrict to the mask region |
| `mask`          | MASK             | Optional   | -       | -                           | Optional mask to restrict where conditioning is applied                                                                                 |
| `hooks`         | HOOKS            | Optional   | -       | -                           | Optional hook functions for custom processing                                                                                           |
| `timesteps`     | TIMESTEPS\_RANGE | Optional   | -       | -                           | Optional timestep range to limit when conditioning is active                                                                            |

**Note:** When a `mask` is provided, the `set_cond_area` parameter can be set to "mask bounds" to restrict conditioning application to the masked region only. The `hooks` parameter allows for custom processing via hook functions, and `timesteps` limits the conditioning effect to a specific range of timesteps during generation.

## Outputs

| Output Name    | Data Type    | Description                                            |
| -------------- | ------------ | ------------------------------------------------------ |
| `CONDITIONING` | CONDITIONING | The modified conditioning data with updated properties |

***

**Source fingerprint (SHA-256):** `5e3f5348f6df8f2fa1c1d42b883efcab3ee07d933e219f11fa48730aacc168d7`


# ConditioningSetPropertiesAndCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetPropertiesAndCombine

Complete documentation for the ConditioningSetPropertiesAndCombine node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetPropertiesAndCombine/en.md)

The ConditioningSetPropertiesAndCombine node modifies conditioning data by applying properties from a new conditioning input to an existing conditioning input. It combines the two conditioning sets while controlling the strength of the new conditioning and specifying how the conditioning area should be applied.

## Inputs

| Parameter       | Data Type        | Input Type | Default | Range                       | Description                                                          |
| --------------- | ---------------- | ---------- | ------- | --------------------------- | -------------------------------------------------------------------- |
| `cond`          | CONDITIONING     | Required   | -       | -                           | The original conditioning data to be modified                        |
| `cond_NEW`      | CONDITIONING     | Required   | -       | -                           | The new conditioning data providing properties to apply              |
| `strength`      | FLOAT            | Required   | 1.0     | 0.0 - 10.0                  | Controls the intensity of the new conditioning properties            |
| `set_cond_area` | STRING           | Required   | default | \["default", "mask bounds"] | Determines how the conditioning area is applied                      |
| `mask`          | MASK             | Optional   | -       | -                           | Optional mask to define specific areas for conditioning              |
| `hooks`         | HOOKS            | Optional   | -       | -                           | Optional hook functions for custom processing                        |
| `timesteps`     | TIMESTEPS\_RANGE | Optional   | -       | -                           | Optional timestep range for controlling when conditioning is applied |

**Note:** When `mask` is provided, the `set_cond_area` parameter can use "mask bounds" to constrain the conditioning application to the masked regions.

## Outputs

| Output Name    | Data Type    | Description                                             |
| -------------- | ------------ | ------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The combined conditioning data with modified properties |

***

**Source fingerprint (SHA-256):** `da57eeae428a103cbad77af063419ed0e85aeaa0b8805c8c197df27613477fa8`


# ConditioningSetTimestepRange - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetTimestepRange

Complete documentation for the ConditioningSetTimestepRange node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to adjust the temporal aspect of conditioning by setting a specific range of timesteps. It allows for the precise control over the start and end points of the conditioning process, enabling more targeted and efficient generation.

## Inputs

| Parameter      | Data Type    | Description                                                                                                                                                                                  |
| -------------- | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The conditioning input represents the current state of the generation process, which this node modifies by setting a specific range of timesteps.                                            |
| `start`        | `FLOAT`      | The start parameter specifies the beginning of the timestep range as a percentage of the total generation process, allowing for fine-tuned control over when the conditioning effects begin. |
| `end`          | `FLOAT`      | The end parameter defines the endpoint of the timestep range as a percentage, enabling precise control over the duration and conclusion of the conditioning effects.                         |

## Outputs

| Parameter      | Data Type    | Description                                                                                                                    |
| -------------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------ |
| `CONDITIONING` | CONDITIONING | The output is the modified conditioning with the specified timestep range applied, ready for further processing or generation. |


# ConditioningTimestepsRange - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningTimestepsRange

Complete documentation for the ConditioningTimestepsRange node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningTimestepsRange/en.md)

The ConditioningTimestepsRange node creates three distinct timestep ranges for controlling when conditioning effects are applied during the generation process. It takes start and end percentage values and divides the entire timestep range (0.0 to 1.0) into three segments: the main range between the specified percentages, the range before the start percentage, and the range after the end percentage.

## Inputs

| Parameter       | Data Type | Required | Range     | Description                                                  |
| --------------- | --------- | -------- | --------- | ------------------------------------------------------------ |
| `start_percent` | FLOAT     | Yes      | 0.0 - 1.0 | The starting percentage of the timestep range (default: 0.0) |
| `end_percent`   | FLOAT     | Yes      | 0.0 - 1.0 | The ending percentage of the timestep range (default: 1.0)   |

## Outputs

| Output Name       | Data Type        | Description                                                        |
| ----------------- | ---------------- | ------------------------------------------------------------------ |
| `TIMESTEPS_RANGE` | TIMESTEPS\_RANGE | The main timestep range defined by start\_percent and end\_percent |
| `BEFORE_RANGE`    | TIMESTEPS\_RANGE | The timestep range from 0.0 to start\_percent                      |
| `AFTER_RANGE`     | TIMESTEPS\_RANGE | The timestep range from end\_percent to 1.0                        |

***

**Source fingerprint (SHA-256):** `dee21b5ac80fabdeacf3f4a985550fff795702e02911400ae49a97baae834e5e`


# ConditioningZeroOut - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningZeroOut

Complete documentation for the ConditioningZeroOut node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node zeroes out specific elements within the conditioning data structure, effectively neutralizing their influence in subsequent processing steps. It's designed for advanced conditioning operations where direct manipulation of the conditioning's internal representation is required.

## Inputs

| Parameter      | Comfy dtype  | Description                                                                                                                                    |
| -------------- | ------------ | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The conditioning data structure to be modified. This node zeroes out the 'pooled\_output' elements within each conditioning entry, if present. |

## Outputs

| Parameter      | Comfy dtype  | Description                                                                                            |
| -------------- | ------------ | ------------------------------------------------------------------------------------------------------ |
| `CONDITIONING` | CONDITIONING | The modified conditioning data structure, with 'pooled\_output' elements set to zero where applicable. |


# CreateHookKeyframe - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookKeyframe

Complete documentation for the CreateHookKeyframe node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookKeyframe/en.md)

The Create Hook Keyframe node allows you to define specific points in a generation process where hook behavior changes. It creates keyframes that modify the strength of hooks at particular percentages of the generation progress, and these keyframes can be chained together to create complex scheduling patterns.

## Inputs

| Parameter       | Data Type       | Required | Range         | Description                                                                                    |
| --------------- | --------------- | -------- | ------------- | ---------------------------------------------------------------------------------------------- |
| `strength_mult` | FLOAT           | Yes      | -20.0 to 20.0 | Multiplier for hook strength at this keyframe (default: 1.0)                                   |
| `start_percent` | FLOAT           | Yes      | 0.0 to 1.0    | The percentage point in the generation process where this keyframe takes effect (default: 0.0) |
| `prev_hook_kf`  | HOOK\_KEYFRAMES | No       | -             | Optional previous hook keyframe group to add this keyframe to                                  |

## Outputs

| Output Name | Data Type       | Description                                                    |
| ----------- | --------------- | -------------------------------------------------------------- |
| `HOOK_KF`   | HOOK\_KEYFRAMES | A group of hook keyframes including the newly created keyframe |

***

**Source fingerprint (SHA-256):** `51893311a0623cafcf8c2d8af00e4005ca2fea2df9474e87d7d4b332b38435c3`


# CreateHookKeyframesFromFloats - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookKeyframesFromFloats

Complete documentation for the CreateHookKeyframesFromFloats node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookKeyframesFromFloats/en.md)

This node creates hook keyframes from a list of floating-point strength values, distributing them evenly between specified start and end percentages. It generates a sequence of keyframes where each strength value is assigned to a specific percentage position in the animation timeline. The node can either create a new keyframe group or add to an existing one, with an option to print the generated keyframes for debugging purposes.

## Inputs

| Parameter         | Data Type       | Required | Range      | Description                                                                                               |
| ----------------- | --------------- | -------- | ---------- | --------------------------------------------------------------------------------------------------------- |
| `floats_strength` | FLOATS          | Yes      | -1 to ∞    | A single float value or list of float values representing strength values for the keyframes (default: -1) |
| `start_percent`   | FLOAT           | Yes      | 0.0 to 1.0 | The starting percentage position for the first keyframe in the timeline (default: 0.0)                    |
| `end_percent`     | FLOAT           | Yes      | 0.0 to 1.0 | The ending percentage position for the last keyframe in the timeline (default: 1.0)                       |
| `print_keyframes` | BOOLEAN         | Yes      | True/False | When enabled, prints the generated keyframe information to the console (default: False)                   |
| `prev_hook_kf`    | HOOK\_KEYFRAMES | No       | -          | An existing hook keyframe group to add the new keyframes to, or creates a new group if not provided       |

**Note:** The `floats_strength` parameter accepts either a single float value or an iterable list of floats. The keyframes are distributed linearly between `start_percent` and `end_percent` based on the number of strength values provided. The first keyframe is guaranteed to have at least one step to ensure it is applied.

## Outputs

| Output Name | Data Type       | Description                                                                                                                 |
| ----------- | --------------- | --------------------------------------------------------------------------------------------------------------------------- |
| `HOOK_KF`   | HOOK\_KEYFRAMES | A hook keyframe group containing the newly created keyframes, either as a new group or appended to the input keyframe group |

***

**Source fingerprint (SHA-256):** `566864ec72062d913d95b38b3c53c655d4fdd971a01c4bec54669850b2feddc8`


# CreateHookKeyframesInterpolated - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookKeyframesInterpolated

Complete documentation for the CreateHookKeyframesInterpolated node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookKeyframesInterpolated/en.md)

Creates a sequence of hook keyframes with interpolated strength values between a start and end point. The node generates multiple keyframes that smoothly transition the strength parameter across a specified percentage range of the generation process, using various interpolation methods to control the transition curve.

## Inputs

| Parameter         | Data Type       | Required | Range                                                                                                                                                                                                 | Description                                                                           |
| ----------------- | --------------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- |
| `strength_start`  | FLOAT           | Yes      | 0.0 - 10.0                                                                                                                                                                                            | The starting strength value for the interpolation sequence (default: 1.0)             |
| `strength_end`    | FLOAT           | Yes      | 0.0 - 10.0                                                                                                                                                                                            | The ending strength value for the interpolation sequence (default: 1.0)               |
| `interpolation`   | COMBO           | Yes      | `LINEAR`<br />`EASE_IN`<br />`EASE_OUT`<br />`EASE_IN_OUT`<br />`EASE_OUT_IN`<br />`SINE`<br />`CUBIC`<br />`QUARTIC`<br />`QUINTIC`<br />`EXPO`<br />`CIRC`<br />`BACK`<br />`BOUNCE`<br />`ELASTIC` | The interpolation method used to transition between strength values (default: LINEAR) |
| `start_percent`   | FLOAT           | Yes      | 0.0 - 1.0                                                                                                                                                                                             | The starting percentage position in the generation process (default: 0.0)             |
| `end_percent`     | FLOAT           | Yes      | 0.0 - 1.0                                                                                                                                                                                             | The ending percentage position in the generation process (default: 1.0)               |
| `keyframes_count` | INT             | Yes      | 2 - 100                                                                                                                                                                                               | The number of keyframes to generate in the interpolation sequence (default: 5)        |
| `print_keyframes` | BOOLEAN         | Yes      | True/False                                                                                                                                                                                            | Whether to print generated keyframe information to the log (default: False)           |
| `prev_hook_kf`    | HOOK\_KEYFRAMES | No       | -                                                                                                                                                                                                     | Optional previous hook keyframes group to append to                                   |

## Outputs

| Output Name | Data Type       | Description                                                             |
| ----------- | --------------- | ----------------------------------------------------------------------- |
| `HOOK_KF`   | HOOK\_KEYFRAMES | The generated hook keyframes group containing the interpolated sequence |

***

**Source fingerprint (SHA-256):** `f90c96745ca1f02bbb02e08d2d82be1bbb1f3c80ac5d53a4c6bc07a0e2b8d76f`


# CreateHookLora - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookLora

Complete documentation for the CreateHookLora node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookLora/en.md)

The Create Hook LoRA node generates hook objects for applying LoRA (Low-Rank Adaptation) modifications to models. It loads a specified LoRA file and creates hooks that can adjust model and CLIP strengths, then combines these hooks with any existing hooks passed to it. The node efficiently manages LoRA loading by caching previously loaded LoRA files to avoid redundant operations.

## Inputs

| Parameter        | Data Type | Required | Range                      | Description                                                     |
| ---------------- | --------- | -------- | -------------------------- | --------------------------------------------------------------- |
| `lora_name`      | STRING    | Yes      | Multiple options available | The name of the LoRA file to load from the loras directory      |
| `strength_model` | FLOAT     | Yes      | -20.0 to 20.0              | The strength multiplier for model adjustments (default: 1.0)    |
| `strength_clip`  | FLOAT     | Yes      | -20.0 to 20.0              | The strength multiplier for CLIP adjustments (default: 1.0)     |
| `prev_hooks`     | HOOKS     | No       | N/A                        | Optional existing hook group to combine with the new LoRA hooks |

**Parameter Constraints:**

* If both `strength_model` and `strength_clip` are set to 0, the node will skip creating new LoRA hooks and return the existing hooks unchanged
* The node caches the last loaded LoRA file to optimize performance when the same LoRA is used repeatedly

## Outputs

| Output Name | Data Type | Description                                                            |
| ----------- | --------- | ---------------------------------------------------------------------- |
| `HOOKS`     | HOOKS     | A hook group containing the combined LoRA hooks and any previous hooks |

***

**Source fingerprint (SHA-256):** `42d5d776bfc9b239191952e2bce23513d183f904fc3c15039469381a547486f8`


# CreateHookLoraModelOnly - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookLoraModelOnly

Complete documentation for the CreateHookLoraModelOnly node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookLoraModelOnly/en.md)

This node creates a LoRA (Low-Rank Adaptation) hook that applies only to the model component, leaving the CLIP component completely unchanged. It loads a LoRA file and applies it with a specified strength to the model while setting the CLIP strength to zero. The node can be chained with previous hooks to build complex modification pipelines.

## Inputs

| Parameter        | Data Type | Required | Range                      | Description                                                                         |
| ---------------- | --------- | -------- | -------------------------- | ----------------------------------------------------------------------------------- |
| `lora_name`      | STRING    | Yes      | Multiple options available | The name of the LoRA file to load from the loras folder                             |
| `strength_model` | FLOAT     | Yes      | -20.0 to 20.0              | The strength multiplier for applying the LoRA to the model component (default: 1.0) |
| `prev_hooks`     | HOOKS     | No       | -                          | Optional previous hooks to chain with this hook                                     |

## Outputs

| Output Name | Data Type | Description                                                   |
| ----------- | --------- | ------------------------------------------------------------- |
| `hooks`     | HOOKS     | The created LoRA hook that can be applied to model processing |

***

**Source fingerprint (SHA-256):** `10adbdfc2e37fcf317e93130f87d9a7038d00b091cb6d1b45f4658c81632ef80`


# CreateHookModelAsLora - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookModelAsLora

Complete documentation for the CreateHookModelAsLora node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookModelAsLora/en.md)

This node creates a hook model as a LoRA (Low-Rank Adaptation) by loading checkpoint weights and applying strength adjustments to both the model and CLIP components. It allows you to apply LoRA-style modifications to existing models through a hook-based approach, enabling fine-tuning and adaptation without permanent model changes. The node can combine with previous hooks and caches loaded weights for efficiency.

## Inputs

| Parameter        | Data Type | Required | Range                      | Description                                                                  |
| ---------------- | --------- | -------- | -------------------------- | ---------------------------------------------------------------------------- |
| `ckpt_name`      | STRING    | Yes      | Multiple options available | The checkpoint file to load weights from (select from available checkpoints) |
| `strength_model` | FLOAT     | Yes      | -20.0 to 20.0              | The strength multiplier applied to the model weights (default: 1.0)          |
| `strength_clip`  | FLOAT     | Yes      | -20.0 to 20.0              | The strength multiplier applied to the CLIP weights (default: 1.0)           |
| `prev_hooks`     | HOOKS     | No       | -                          | Optional previous hooks to combine with the newly created LoRA hooks         |

**Parameter Constraints:**

* The `ckpt_name` parameter loads checkpoints from the available checkpoints folder
* Both strength parameters accept values from -20.0 to 20.0 with 0.01 step increments
* When `prev_hooks` is not provided, the node creates a new hook group
* The node caches loaded weights to avoid reloading the same checkpoint multiple times

## Outputs

| Output Name | Data Type | Description                                                          |
| ----------- | --------- | -------------------------------------------------------------------- |
| `HOOKS`     | HOOKS     | The created LoRA hooks, combined with any previous hooks if provided |

***

**Source fingerprint (SHA-256):** `8c0dd6b2e8e99e1d7dbc864aa802c0713842fb0d4ee018ea5cbedfb7896a770d`


# CreateHookModelAsLoraModelOnly - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateHookModelAsLoraModelOnly

Complete documentation for the CreateHookModelAsLoraModelOnly node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateHookModelAsLoraModelOnly/en.md)

This node creates a hook that applies a LoRA (Low-Rank Adaptation) model to modify only the model component of a neural network. It loads a checkpoint file and applies it with a specified strength to the model while leaving the CLIP component unchanged. This is an experimental node that extends the functionality of the base CreateHookModelAsLora class.

## Inputs

| Parameter        | Data Type | Required | Range                      | Description                                                                                               |
| ---------------- | --------- | -------- | -------------------------- | --------------------------------------------------------------------------------------------------------- |
| `ckpt_name`      | STRING    | Yes      | Multiple options available | The checkpoint file to load as a LoRA model. Available options depend on the checkpoints folder contents. |
| `strength_model` | FLOAT     | Yes      | -20.0 to 20.0              | The strength multiplier for applying the LoRA to the model component (default: 1.0)                       |
| `prev_hooks`     | HOOKS     | No       | -                          | Optional previous hooks to chain with this hook                                                           |

## Outputs

| Output Name | Data Type | Description                                                   |
| ----------- | --------- | ------------------------------------------------------------- |
| `hooks`     | HOOKS     | The created hook group containing the LoRA model modification |

***

**Source fingerprint (SHA-256):** `adbeaede65aa89d48c59225ca1c8edc4c9394a364f93a00dae4a83a2270f093b`


# DeprecatedCheckpointLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DeprecatedCheckpointLoader

Complete documentation for the DeprecatedCheckpointLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The CheckpointLoader node is designed for advanced loading operations, specifically to load model checkpoints along with their configurations. It facilitates the retrieval of model components necessary for initializing and running generative models, including configurations and checkpoints from specified directories.

## Inputs

| Parameter     | Data Type      | Description                                                                                                                                                                   |
| ------------- | -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `config_name` | COMBO\[STRING] | Specifies the name of the configuration file to be used. This is crucial for determining the model's parameters and settings, affecting the model's behavior and performance. |
| `ckpt_name`   | COMBO\[STRING] | Indicates the name of the checkpoint file to be loaded. This directly influences the state of the model being initialized, impacting its initial weights and biases.          |

## Outputs

| Parameter | Data Type | Description                                                                                         |
| --------- | --------- | --------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | Represents the primary model loaded from the checkpoint, ready for further operations or inference. |
| `clip`    | CLIP      | Provides the CLIP model component, if available and requested, loaded from the checkpoint.          |
| `vae`     | VAE       | Delivers the VAE model component, if available and requested, loaded from the checkpoint.           |


# DeprecatedDiffusersLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DeprecatedDiffusersLoader

Complete documentation for the DeprecatedDiffusersLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The DiffusersLoader node is designed for loading models from the diffusers library, specifically handling the loading of UNet, CLIP, and VAE models based on provided model paths. It facilitates the integration of these models into the ComfyUI framework, enabling advanced functionalities such as text-to-image generation, image manipulation, and more.

## Inputs

| Parameter    | Data Type      | Description                                                                                                                                                                                    |
| ------------ | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model_path` | COMBO\[STRING] | Specifies the path to the model to be loaded. This path is crucial as it determines which model will be utilized for subsequent operations, affecting the output and capabilities of the node. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                |
| --------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | The loaded UNet model, which is part of the output tuple. This model is essential for image synthesis and manipulation tasks within the ComfyUI framework. |
| `clip`    | CLIP      | The loaded CLIP model, included in the output tuple if requested. This model enables advanced text and image understanding and manipulation capabilities.  |
| `vae`     | VAE       | The loaded VAE model, included in the output tuple if requested. This model is crucial for tasks involving latent space manipulation and image generation. |


# DiffusersLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DiffusersLoader

Complete documentation for the DiffusersLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DiffusersLoader/en.md)

The DiffusersLoader node loads pre-trained models from the diffusers format. It searches for valid diffusers model directories containing a `model_index.json` file and loads them as MODEL, CLIP, and VAE components for use in the pipeline. This node is part of the deprecated loaders category and provides compatibility with Hugging Face diffusers models.

## Inputs

| Parameter    | Data Type | Required | Range                                                                   | Description                                                                                                                                                                 |
| ------------ | --------- | -------- | ----------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model_path` | STRING    | Yes      | Multiple options available<br />(auto-populated from diffusers folders) | The path to the diffusers model directory to load. The node automatically scans for valid diffusers models in the configured diffusers folders and lists available options. |

## Outputs

| Output Name | Data Type | Description                                                                  |
| ----------- | --------- | ---------------------------------------------------------------------------- |
| `MODEL`     | MODEL     | The loaded model component from the diffusers format                         |
| `CLIP`      | CLIP      | The loaded CLIP model component from the diffusers format                    |
| `VAE`       | VAE       | The loaded VAE (Variational Autoencoder) component from the diffusers format |

***

**Source fingerprint (SHA-256):** `59be9923ed76d4859d5f7217a802c43297cb5af3d895eb6713edea97a32c3db2`


# DualCLIPLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DualCLIPLoader

Complete documentation for the DualCLIPLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The DualCLIPLoader node is designed for loading two CLIP models simultaneously, facilitating operations that require the integration or comparison of features from both models.

This node will detect models located in the `ComfyUI/models/text_encoders` folder.

## Inputs

| Parameter    | Comfy dtype    | Description                                                                                                                                                                                     |
| ------------ | -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip_name1` | COMBO\[STRING] | Specifies the name of the first CLIP model to be loaded. This parameter is crucial for identifying and retrieving the correct model from a predefined list of available CLIP models.            |
| `clip_name2` | COMBO\[STRING] | Specifies the name of the second CLIP model to be loaded. This parameter enables the loading of a second distinct CLIP model for comparative or integrative analysis alongside the first model. |
| `type`       | `option`       | Choose from "sdxl", "sd3", "flux" to adapt to different models.                                                                                                                                 |

* The order of loading does not affect the output effect

## Outputs

| Parameter | Data Type | Description                                                                                                           |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------- |
| `clip`    | CLIP      | The output is a combined CLIP model that integrates the features or functionalities of the two specified CLIP models. |


# EasyCache - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EasyCache

Complete documentation for the EasyCache node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EasyCache/en.md)

The EasyCache node implements a native caching system for models to improve performance by reusing previously computed steps during the sampling process. It adds EasyCache functionality to a model with configurable thresholds for when to start and stop using the cache during the sampling timeline.

## Inputs

| Parameter         | Data Type | Required | Range     | Description                                                           |
| ----------------- | --------- | -------- | --------- | --------------------------------------------------------------------- |
| `model`           | MODEL     | Yes      | -         | The model to add EasyCache to.                                        |
| `reuse_threshold` | FLOAT     | No       | 0.0 - 3.0 | The threshold for reusing cached steps (default: 0.2).                |
| `start_percent`   | FLOAT     | No       | 0.0 - 1.0 | The relative sampling step to begin use of EasyCache (default: 0.15). |
| `end_percent`     | FLOAT     | No       | 0.0 - 1.0 | The relative sampling step to end use of EasyCache (default: 0.95).   |
| `verbose`         | BOOLEAN   | No       | -         | Whether to log verbose information (default: False).                  |

## Outputs

| Output Name | Data Type | Description                                   |
| ----------- | --------- | --------------------------------------------- |
| `model`     | MODEL     | The model with EasyCache functionality added. |

***

**Source fingerprint (SHA-256):** `c94867faae0005743a593a20d432fe3a3d01624148d0dbd1f2576df54026b2ab`


# FluxDisableGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxDisableGuidance

Complete documentation for the FluxDisableGuidance node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxDisableGuidance/en.md)

This node completely disables the guidance embed functionality for Flux and similar models. It takes conditioning data as input and removes the guidance component by setting it to None, effectively turning off guidance-based conditioning for the generation process.

## Inputs

| Parameter      | Data Type    | Required | Range | Description                                               |
| -------------- | ------------ | -------- | ----- | --------------------------------------------------------- |
| `conditioning` | CONDITIONING | Yes      | -     | The conditioning data to process and remove guidance from |

## Outputs

| Output Name    | Data Type    | Description                                           |
| -------------- | ------------ | ----------------------------------------------------- |
| `conditioning` | CONDITIONING | The modified conditioning data with guidance disabled |

***

**Source fingerprint (SHA-256):** `32d8dd4ac57f273a7064355ef819e720302bdc819b1ebfc93e42257a73e6c632`


# FluxGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxGuidance

Complete documentation for the FluxGuidance node in ComfyUI. Learn its inputs, outputs, parameters and usage.

## Inputs

| Parameter    | Data Type    | Description                                                                                    |
| ------------ | ------------ | ---------------------------------------------------------------------------------------------- |
| conditioning | CONDITIONING | Input conditioning data, typically from previous encoding or processing steps                  |
| guidance     | FLOAT        | Controls the influence of text prompts on image generation, adjustable range from 0.0 to 100.0 |

## Outputs

| Parameter    | Data Type    | Description                                                  |
| ------------ | ------------ | ------------------------------------------------------------ |
| CONDITIONING | CONDITIONING | Updated conditioning data, containing the new guidance value |


# FluxKontextImageScale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxKontextImageScale

Complete documentation for the FluxKontextImageScale node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node scales the input image to an optimal size used during Flux Kontext model training using the Lanczos algorithm, based on the input image's aspect ratio. This node is particularly useful when inputting large-sized images, as oversized inputs may lead to degraded model output quality or issues such as multiple subjects appearing in the output.

## Inputs

| Parameter Name | Data Type | Input Type | Default Value | Value Range | Description               |
| -------------- | --------- | ---------- | ------------- | ----------- | ------------------------- |
| `image`        | IMAGE     | Required   | -             | -           | Input image to be resized |

## Outputs

| Output Name | Data Type | Description   |
| ----------- | --------- | ------------- |
| `image`     | IMAGE     | Resized image |

## Preset Size List

The following is a list of standard sizes used during model training. The node will select the size closest to the input image's aspect ratio:

| Width | Height | Aspect Ratio |
| ----- | ------ | ------------ |
| 672   | 1568   | 0.429        |
| 688   | 1504   | 0.457        |
| 720   | 1456   | 0.494        |
| 752   | 1392   | 0.540        |
| 800   | 1328   | 0.603        |
| 832   | 1248   | 0.667        |
| 880   | 1184   | 0.743        |
| 944   | 1104   | 0.855        |
| 1024  | 1024   | 1.000        |
| 1104  | 944    | 1.170        |
| 1184  | 880    | 1.345        |
| 1248  | 832    | 1.500        |
| 1328  | 800    | 1.660        |
| 1392  | 752    | 1.851        |
| 1456  | 720    | 2.022        |
| 1504  | 688    | 2.186        |
| 1568  | 672    | 2.333        |


# FluxKontextMultiReferenceLatentMethod - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxKontextMultiReferenceLatentMethod

Complete documentation for the FluxKontextMultiReferenceLatentMethod node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxKontextMultiReferenceLatentMethod/en.md)

The FluxKontextMultiReferenceLatentMethod node modifies conditioning data by setting a specific reference latents method. It appends the chosen method to the conditioning input, which affects how reference latents are processed in subsequent generation steps. This node is marked as experimental and is part of the Flux conditioning system.

## Inputs

| Parameter                  | Data Type    | Required | Range                                                                   | Description                                                                                                                                             |
| -------------------------- | ------------ | -------- | ----------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `conditioning`             | CONDITIONING | Yes      | -                                                                       | The conditioning data to be modified with the reference latents method                                                                                  |
| `reference_latents_method` | STRING       | Yes      | `"offset"`<br />`"index"`<br />`"uxo/uno"`<br />`"index_timestep_zero"` | The method to use for reference latents processing. If "uxo" or "uso" is selected, it will be converted to "uxo". This parameter is marked as advanced. |

## Outputs

| Output Name    | Data Type    | Description                                                              |
| -------------- | ------------ | ------------------------------------------------------------------------ |
| `conditioning` | CONDITIONING | The modified conditioning data with the reference latents method applied |

***

**Source fingerprint (SHA-256):** `822d08ad50f167257f32d74af27a6a7444a61a554108a27e78fea5f40aba4177`


# HiDreamO1PatchSeamSmoothing - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HiDreamO1PatchSeamSmoothing

Complete documentation for the HiDreamO1PatchSeamSmoothing node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HiDreamO1PatchSeamSmoothing/en.md)

## Overview

This node reduces visible seams in images generated by the HiDream-O1 model by averaging the model's output across multiple shifted patch-grid positions during the later part of the sampling process. It works by running the model several times with slightly different image alignments and blending the results together, which helps cancel out the grid-like artifacts that can appear at patch boundaries.

## Inputs

| Parameter       | Data Type | Required | Range                                                  | Description                                                                                                                                                                                                                                                                                                                     |
| --------------- | --------- | -------- | ------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`         | MODEL     | Yes      | -                                                      | The HiDream-O1 model to apply seam smoothing to.                                                                                                                                                                                                                                                                                |
| `start_percent` | FLOAT     | Yes      | 0.0 to 1.0 (step: 0.01)                                | The sampling progress (0=start, 1=end) at which the smoothing effect turns ON (default: 0.8).                                                                                                                                                                                                                                   |
| `end_percent`   | FLOAT     | Yes      | 0.0 to 1.0 (step: 0.01)                                | The sampling progress at which the smoothing effect turns OFF (default: 1.0).                                                                                                                                                                                                                                                   |
| `pattern`       | COMBO     | Yes      | `"single_shift"`<br />`"symmetric"`                    | The layout of the shifted grid positions. `single_shift`: one pass at the natural patch grid plus others offset. `symmetric`: all passes are off-grid, with shifts split around the origin (default: `"single_shift"`).                                                                                                         |
| `passes`        | COMBO     | Yes      | `"2"`<br />`"4"`<br />`"ramp_2_4"`<br />`"ramp_2_4_8"` | The number of passes (model runs) per gated step. `2` or `4` are fixed counts. `ramp_2_4` and `ramp_2_4_8` increase the pass count as sampling approaches the end, providing more smoothing where seams are most visible (default: `"2"`).                                                                                      |
| `blend`         | COMBO     | Yes      | `"average"`<br />`"window"`<br />`"median"`            | The method used to combine the results from each pass. `average`: equal-weight mean of all passes. `window`: uses a Hann window to give more weight to the center of each pass, reducing boundary artifacts. `median`: takes the per-pixel median, which can reject outlier passes caused by wraparound (default: `"average"`). |
| `strength`      | FLOAT     | Yes      | 0.0 to 1.0 (step: 0.01)                                | Controls the interpolation between the original model output (0.0) and the fully smoothed result (1.0) (default: 1.0).                                                                                                                                                                                                          |

**Note on Parameter Constraints:**

* The smoothing effect will not be applied if `strength` is 0.0 or less, or if `end_percent` is less than or equal to `start_percent`.
* The `passes` parameter's ramp options (`ramp_2_4`, `ramp_2_4_8`) are only meaningful when `start_percent` and `end_percent` define a range, as the number of passes increases as sampling progresses through that range.

## Outputs

| Output Name | Data Type | Description                                                 |
| ----------- | --------- | ----------------------------------------------------------- |
| `model`     | MODEL     | The modified model with the seam smoothing wrapper applied. |

***

**Source fingerprint (SHA-256):** `f4d1a617d88f880dcae3afda25699333df023d7b4ec13a22a73512713d6ef18c`


# LTXAVTextEncoderLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXAVTextEncoderLoader

Complete documentation for the LTXAVTextEncoderLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXAVTextEncoderLoader/en.md)

This node loads a specialized text encoder for the LTXV audio model. It combines a specific text encoder file with a checkpoint file to create a CLIP model that can be used for audio-related text conditioning tasks.

## Inputs

| Parameter      | Data Type | Required | Range                      | Description                                                                                                                                                              |
| -------------- | --------- | -------- | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `text_encoder` | STRING    | Yes      | Multiple options available | The filename of the LTXV text encoder model to load. The available options are loaded from the `text_encoders` folder.                                                   |
| `ckpt_name`    | STRING    | Yes      | Multiple options available | The filename of the checkpoint to load. The available options are loaded from the `checkpoints` folder.                                                                  |
| `device`       | STRING    | No       | `"default"`<br />`"cpu"`   | Specifies the device to load the model onto. Use `"cpu"` to force loading onto the CPU. The default behavior (`"default"`) uses the system's automatic device placement. |

**Note:** The `text_encoder` and `ckpt_name` parameters work together. The node loads both specified files to create a single, functional CLIP model. The files must be compatible with the LTXV architecture.

## Outputs

| Output Name | Data Type | Description                                                                                  |
| ----------- | --------- | -------------------------------------------------------------------------------------------- |
| `clip`      | CLIP      | The loaded LTXV CLIP model, ready to be used for encoding text prompts for audio generation. |

***

**Source fingerprint (SHA-256):** `41d4c4ffef8bd1e55a44cc19e7c1c768484118458a7d4e100e5e22f5323c59dc`


# LazyCache - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LazyCache

Complete documentation for the LazyCache node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LazyCache/en.md)

LazyCache is a homebrew version of EasyCache that provides an even easier implementation. It works with any model in ComfyUI and adds caching functionality to reduce computation during sampling. While it generally performs worse than EasyCache, it can be more effective in some rare cases and offers universal compatibility.

## Inputs

| Parameter         | Data Type | Required | Range     | Description                                                           |
| ----------------- | --------- | -------- | --------- | --------------------------------------------------------------------- |
| `model`           | MODEL     | Yes      | -         | The model to add LazyCache to.                                        |
| `reuse_threshold` | FLOAT     | No       | 0.0 - 3.0 | The threshold for reusing cached steps (default: 0.2).                |
| `start_percent`   | FLOAT     | No       | 0.0 - 1.0 | The relative sampling step to begin use of LazyCache (default: 0.15). |
| `end_percent`     | FLOAT     | No       | 0.0 - 1.0 | The relative sampling step to end use of LazyCache (default: 0.95).   |
| `verbose`         | BOOLEAN   | No       | -         | Whether to log verbose information (default: False).                  |

## Outputs

| Output Name | Data Type | Description                                   |
| ----------- | --------- | --------------------------------------------- |
| `model`     | MODEL     | The model with LazyCache functionality added. |

***

**Source fingerprint (SHA-256):** `72ca1bbaf795e17951d1f7f9f37350dc3f1511351cc59a5043b40e069fd31340`


# Load3D - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Load3D

Complete documentation for the Load3D node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The Load3D node is a core node for loading and processing 3D model files. When loading the node, it automatically retrieves available 3D resources from `ComfyUI/input/3d/`. You can also upload supported 3D files for preview using the upload function.

**Supported Formats**
Currently, this node supports multiple 3D file formats, including `.gltf`, `.glb`, `.obj`, `.fbx`, and `.stl`.

**3D Node Preferences**
Some related preferences for 3D nodes can be configured in ComfyUI's settings menu. Please refer to the following documentation for corresponding settings:

[Settings Menu](https://docs.comfy.org/interface/settings/3d)

Besides regular node outputs, Load3D has lots of 3D view-related settings in the canvas menu.

## Inputs

| Parameter Name | Type           | Description                                                                                   | Default | Range             |
| -------------- | -------------- | --------------------------------------------------------------------------------------------- | ------- | ----------------- |
| model\_file    | File Selection | 3D model file path, supports upload, defaults to reading model files from `ComfyUI/input/3d/` | -       | Supported formats |
| width          | INT            | Canvas rendering width                                                                        | 1024    | 1-4096            |
| height         | INT            | Canvas rendering height                                                                       | 1024    | 1-4096            |

## Outputs

| Parameter Name   | Data Type      | Description                                                                                    |
| ---------------- | -------------- | ---------------------------------------------------------------------------------------------- |
| image            | IMAGE          | Canvas rendered image                                                                          |
| mask             | MASK           | Mask containing current model position                                                         |
| mesh\_path       | STRING         | Model file path                                                                                |
| normal           | IMAGE          | Normal map                                                                                     |
| lineart          | IMAGE          | Line art image output, corresponding `edge_threshold` can be adjusted in the canvas model menu |
| camera\_info     | LOAD3D\_CAMERA | Camera information                                                                             |
| recording\_video | VIDEO          | Recorded video (only when recording exists)                                                    |

All the outputs preview:

<img alt="View Operation Demo" />

## Canvas Area Description

The Load3D node's Canvas area contains numerous view operations, including:

* Preview view settings (grid, background color, preview view)
* Camera control: Control FOV, camera type
* Global illumination intensity: Adjust lighting intensity
* Video recording: Record and export videos
* Model export: Supports `GLB`, `OBJ`, `STL` formats
* And more

<img alt="Load 3D Node UI" />

1. Contains multiple menus and hidden menus of the Load 3D node
2. Menu for `resizing preview window` and `canvas video recording`
3. 3D view operation axis
4. Preview thumbnail
5. Preview size settings, scale preview view display by setting dimensions and then resizing window

### 1. View Operations

<video>
  <source type="video/mp4" />

  Your browser does not support video playback.
</video>

View control operations:

* Left-click + drag: Rotate the view
* Right-click + drag: Pan the view
* Middle wheel scroll or middle-click + drag: Zoom in/out
* Coordinate axis: Switch views

### 2. Left Menu Functions

<img alt="Menu" />

In the canvas, some settings are hidden in the menu. Click the menu button to expand different menus

* 1. Scene: Contains preview window grid, background color, preview settings
* 2. Model: Model rendering mode, texture materials, up direction settings
* 3. Camera: Switch between orthographic and perspective views, and set the perspective angle size
* 4. Light: Scene global illumination intensity
* 5. Export: Export model to other formats (GLB, OBJ, STL)

#### Scene

<img alt="scene menu" />

The Scene menu provides some basic scene setting functions

1. Show/Hide grid
2. Set background color
3. Click to upload a background image
4. Hide the preview

#### Model

<img alt="Menu_Scene" />

The Model menu provides some model-related functions

1. **Up direction**: Determine which axis is the up direction for the model
2. **Material mode**: Switch model rendering modes - Original, Normal, Wireframe, Lineart

#### Camera

<img alt="menu_modelmenu_camera" />

This menu provides switching between orthographic and perspective views, and perspective angle size settings

1. **Camera**: Quickly switch between orthographic and orthographic views
2. **FOV**: Adjust FOV angle

#### Light

<img alt="menu_modelmenu_camera" />

Through this menu, you can quickly adjust the scene's global illumination intensity

#### Export

<img alt="menu_export" />

This menu provides the ability to quickly convert and export model formats

### 3. Right Menu Functions

<video>
  <source type="video/mp4" />

  Your browser does not support video playback.
</video>

The right menu has two main functions:

1. **Reset view ratio**: After clicking the button, the view will adjust the canvas rendering area ratio according to the set width and height
2. **Video recording**: Allows you to record current 3D view operations as video, allows import, and can be output as `recording_video` to subsequent nodes


# Load3DAnimation - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Load3DAnimation

Complete documentation for the Load3DAnimation node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The Load3DAnimation node is a core node for loading and processing 3D model files. When loading the node, it automatically retrieves available 3D resources from `ComfyUI/input/3d/`. You can also upload supported 3D files for preview using the upload function.

> * Most of the functions of this node are the same as the Load 3D node, but this node supports loading models with animations, and you can preview the corresponding animations in the node.
> * The content of this documentation is the same as the Load3D node, because except for animation preview and playback, their capabilities are identical.

**Supported Formats**
Currently, this node supports multiple 3D file formats, including `.gltf`, `.glb`, `.obj`, `.fbx`, and `.stl`.

**3D Node Preferences**
Some related preferences for 3D nodes can be configured in ComfyUI's settings menu. Please refer to the following documentation for corresponding settings:

[Settings Menu](https://docs.comfy.org/interface/settings/3d)

Besides regular node outputs, Load3D has lots of 3D view-related settings in the canvas menu.

## Inputs

| Parameter Name | Type           | Description                                                                                   | Default | Range             |
| -------------- | -------------- | --------------------------------------------------------------------------------------------- | ------- | ----------------- |
| model\_file    | File Selection | 3D model file path, supports upload, defaults to reading model files from `ComfyUI/input/3d/` | -       | Supported formats |
| width          | INT            | Canvas rendering width                                                                        | 1024    | 1-4096            |
| height         | INT            | Canvas rendering height                                                                       | 1024    | 1-4096            |

## Outputs

| Parameter Name   | Data Type      | Description                                                                                    |
| ---------------- | -------------- | ---------------------------------------------------------------------------------------------- |
| image            | IMAGE          | Canvas rendered image                                                                          |
| mask             | MASK           | Mask containing current model position                                                         |
| mesh\_path       | STRING         | Model file path                                                                                |
| normal           | IMAGE          | Normal map                                                                                     |
| lineart          | IMAGE          | Line art image output, corresponding `edge_threshold` can be adjusted in the canvas model menu |
| camera\_info     | LOAD3D\_CAMERA | Camera information                                                                             |
| recording\_video | VIDEO          | Recorded video (only when recording exists)                                                    |

All the outputs preview:

<img alt="View Operation Demo" />

## Canvas Area Description

The Load3D node's Canvas area contains numerous view operations, including:

* Preview view settings (grid, background color, preview view)
* Camera control: Control FOV, camera type
* Global illumination intensity: Adjust lighting intensity
* Video recording: Record and export videos
* Model export: Supports `GLB`, `OBJ`, `STL` formats
* And more

<img alt="Load 3D Node UI" />

1. Contains multiple menus and hidden menus of the Load 3D node
2. Menu for `resizing preview window` and `canvas video recording`
3. 3D view operation axis
4. Preview thumbnail
5. Preview size settings, scale preview view display by setting dimensions and then resizing window

### 1. View Operations

<video>
  <source type="video/mp4" />

  Your browser does not support video playback.
</video>

View control operations:

* Left-click + drag: Rotate the view
* Right-click + drag: Pan the view
* Middle wheel scroll or middle-click + drag: Zoom in/out
* Coordinate axis: Switch views

### 2. Left Menu Functions

![Menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu.webp)

In the canvas, some settings are hidden in the menu. Click the menu button to expand different menus

* 1. Scene: Contains preview window grid, background color, preview settings
* 2. Model: Model rendering mode, texture materials, up direction settings
* 3. Camera: Switch between orthographic and perspective views, and set the perspective angle size
* 4. Light: Scene global illumination intensity
* 5. Export: Export model to other formats (GLB, OBJ, STL)

#### Scene

![scene menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_scene.webp)

The Scene menu provides some basic scene setting functions

1. Show/Hide grid
2. Set background color
3. Click to upload a background image
4. Hide the preview

#### Model

![Menu\_Scene](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_model.webp)

The Model menu provides some model-related functions

1. **Up direction**: Determine which axis is the up direction for the model
2. **Material mode**: Switch model rendering modes - Original, Normal, Wireframe, Lineart

#### Camera

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_camera.webp)

This menu provides switching between orthographic and perspective views, and perspective angle size settings

1. **Camera**: Quickly switch between orthographic and orthographic views
2. **FOV**: Adjust FOV angle

#### Light

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_light.webp)

Through this menu, you can quickly adjust the scene's global illumination intensity

#### Export

![menu\_export](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_export.webp)

This menu provides the ability to quickly convert and export model formats

### 3. Right Menu Functions

<video>
  <source type="video/mp4" />

  Your browser does not support video playback.
</video>

The right menu has two main functions:

1. **Reset view ratio**: After clicking the button, the view will adjust the canvas rendering area ratio according to the set width and height
2. **Video recording**: Allows you to record current 3D view operations as video, allows import, and can be output as `recording_video` to subsequent nodes


# ModelComputeDtype - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelComputeDtype

Complete documentation for the ModelComputeDtype node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelComputeDtype/en.md)

The ModelComputeDtype node changes the computational data type (precision) used by a model during processing. It creates a copy of the input model and applies the selected precision setting, which can help optimize memory usage and performance depending on your hardware. This is useful for debugging and testing different precision configurations.

## Inputs

| Parameter | Data Type | Required | Range                                         | Description                                                            |
| --------- | --------- | -------- | --------------------------------------------- | ---------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -                                             | The input model to modify with a new compute data type                 |
| `dtype`   | STRING    | Yes      | "default"<br />"fp32"<br />"fp16"<br />"bf16" | The computational data type to apply to the model (default: "default") |

## Outputs

| Output Name | Data Type | Description                                               |
| ----------- | --------- | --------------------------------------------------------- |
| `model`     | MODEL     | The modified model with the new compute data type applied |

***

**Source fingerprint (SHA-256):** `bc65f1e452d0122ad175a8b95f38a36503253c9908157037c516496e65c828e6`


# ModelMergeAuraflow - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeAuraflow

Complete documentation for the ModelMergeAuraflow node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeAuraflow/en.md)

The ModelMergeAuraflow node allows you to blend two different models together by adjusting specific blending weights for various model components. It provides fine-grained control over how different parts of the models are merged, from initial layers to final outputs. This node is particularly useful for creating custom model combinations with precise control over the merging process.

## Inputs

| Parameter             | Data Type | Required | Range     | Description                                                           |
| --------------------- | --------- | -------- | --------- | --------------------------------------------------------------------- |
| `model1`              | MODEL     | Yes      | -         | The first model to be merged                                          |
| `model2`              | MODEL     | Yes      | -         | The second model to be merged                                         |
| `init_x_linear.`      | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for the initial linear transformation (default: 1.0)  |
| `positional_encoding` | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for positional encoding components (default: 1.0)     |
| `cond_seq_linear.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for conditional sequence linear layers (default: 1.0) |
| `register_tokens`     | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for token registration components (default: 1.0)      |
| `t_embedder.`         | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for time embedding components (default: 1.0)          |
| `double_layers.0.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for double layer group 0 (default: 1.0)               |
| `double_layers.1.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for double layer group 1 (default: 1.0)               |
| `double_layers.2.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for double layer group 2 (default: 1.0)               |
| `double_layers.3.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for double layer group 3 (default: 1.0)               |
| `single_layers.0.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 0 (default: 1.0)                     |
| `single_layers.1.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 1 (default: 1.0)                     |
| `single_layers.2.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 2 (default: 1.0)                     |
| `single_layers.3.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 3 (default: 1.0)                     |
| `single_layers.4.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 4 (default: 1.0)                     |
| `single_layers.5.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 5 (default: 1.0)                     |
| `single_layers.6.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 6 (default: 1.0)                     |
| `single_layers.7.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 7 (default: 1.0)                     |
| `single_layers.8.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 8 (default: 1.0)                     |
| `single_layers.9.`    | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 9 (default: 1.0)                     |
| `single_layers.10.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 10 (default: 1.0)                    |
| `single_layers.11.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 11 (default: 1.0)                    |
| `single_layers.12.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 12 (default: 1.0)                    |
| `single_layers.13.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 13 (default: 1.0)                    |
| `single_layers.14.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 14 (default: 1.0)                    |
| `single_layers.15.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 15 (default: 1.0)                    |
| `single_layers.16.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 16 (default: 1.0)                    |
| `single_layers.17.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 17 (default: 1.0)                    |
| `single_layers.18.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 18 (default: 1.0)                    |
| `single_layers.19.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 19 (default: 1.0)                    |
| `single_layers.20.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 20 (default: 1.0)                    |
| `single_layers.21.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 21 (default: 1.0)                    |
| `single_layers.22.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 22 (default: 1.0)                    |
| `single_layers.23.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 23 (default: 1.0)                    |
| `single_layers.24.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 24 (default: 1.0)                    |
| `single_layers.25.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 25 (default: 1.0)                    |
| `single_layers.26.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 26 (default: 1.0)                    |
| `single_layers.27.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 27 (default: 1.0)                    |
| `single_layers.28.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 28 (default: 1.0)                    |
| `single_layers.29.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 29 (default: 1.0)                    |
| `single_layers.30.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 30 (default: 1.0)                    |
| `single_layers.31.`   | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for single layer 31 (default: 1.0)                    |
| `modF.`               | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for modF components (default: 1.0)                    |
| `final_linear.`       | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for final linear transformation (default: 1.0)        |

## Outputs

| Output Name | Data Type | Description                                                                                            |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------ |
| `model`     | MODEL     | The merged model combining features from both input models according to the specified blending weights |

***

**Source fingerprint (SHA-256):** `c4959321bba252eb24c945343198d72f50d6021d4dac9945f94e3eb28f1bc3c9`


# ModelMergeCosmos14B - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeCosmos14B

Complete documentation for the ModelMergeCosmos14B node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeCosmos14B/en.md)

The **ModelMergeCosmos14B** node merges two AI models using a block-based approach specifically designed for the Cosmos 14B model architecture. It allows you to blend different components of the models by adjusting weight values between 0.0 and 1.0 for each model block and embedding layer.

## Inputs

| Parameter             | Data Type | Required | Range     | Description                                                     |
| --------------------- | --------- | -------- | --------- | --------------------------------------------------------------- |
| `model1`              | MODEL     | Yes      | -         | First model to merge                                            |
| `model2`              | MODEL     | Yes      | -         | Second model to merge                                           |
| `pos_embedder.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for the position embedder component (default: 1.0)       |
| `extra_pos_embedder.` | FLOAT     | Yes      | 0.0 - 1.0 | Weight for the extra position embedder component (default: 1.0) |
| `x_embedder.`         | FLOAT     | Yes      | 0.0 - 1.0 | Weight for the x embedder component (default: 1.0)              |
| `t_embedder.`         | FLOAT     | Yes      | 0.0 - 1.0 | Weight for the t embedder component (default: 1.0)              |
| `affline_norm.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for the affine normalization component (default: 1.0)    |
| `blocks.block0.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 0 (default: 1.0)                               |
| `blocks.block1.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 1 (default: 1.0)                               |
| `blocks.block2.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 2 (default: 1.0)                               |
| `blocks.block3.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 3 (default: 1.0)                               |
| `blocks.block4.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 4 (default: 1.0)                               |
| `blocks.block5.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 5 (default: 1.0)                               |
| `blocks.block6.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 6 (default: 1.0)                               |
| `blocks.block7.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 7 (default: 1.0)                               |
| `blocks.block8.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 8 (default: 1.0)                               |
| `blocks.block9.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 9 (default: 1.0)                               |
| `blocks.block10.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 10 (default: 1.0)                              |
| `blocks.block11.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 11 (default: 1.0)                              |
| `blocks.block12.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 12 (default: 1.0)                              |
| `blocks.block13.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 13 (default: 1.0)                              |
| `blocks.block14.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 14 (default: 1.0)                              |
| `blocks.block15.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 15 (default: 1.0)                              |
| `blocks.block16.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 16 (default: 1.0)                              |
| `blocks.block17.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 17 (default: 1.0)                              |
| `blocks.block18.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 18 (default: 1.0)                              |
| `blocks.block19.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 19 (default: 1.0)                              |
| `blocks.block20.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 20 (default: 1.0)                              |
| `blocks.block21.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 21 (default: 1.0)                              |
| `blocks.block22.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 22 (default: 1.0)                              |
| `blocks.block23.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 23 (default: 1.0)                              |
| `blocks.block24.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 24 (default: 1.0)                              |
| `blocks.block25.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 25 (default: 1.0)                              |
| `blocks.block26.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 26 (default: 1.0)                              |
| `blocks.block27.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 27 (default: 1.0)                              |
| `blocks.block28.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 28 (default: 1.0)                              |
| `blocks.block29.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 29 (default: 1.0)                              |
| `blocks.block30.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 30 (default: 1.0)                              |
| `blocks.block31.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 31 (default: 1.0)                              |
| `blocks.block32.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 32 (default: 1.0)                              |
| `blocks.block33.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 33 (default: 1.0)                              |
| `blocks.block34.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 34 (default: 1.0)                              |
| `blocks.block35.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 35 (default: 1.0)                              |
| `final_layer.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for the final layer (default: 1.0)                       |

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `model`     | MODEL     | The merged model combining features from both input models |

***

**Source fingerprint (SHA-256):** `6fcb4fefe7738d0addef49d386c0d3d22cda4c68f0e49ad003d1df595cf0e9d9`


# ModelMergeCosmos7B - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeCosmos7B

Complete documentation for the ModelMergeCosmos7B node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeCosmos7B/en.md)

The ModelMergeCosmos7B node merges two AI models together using weighted blending of specific components. It allows fine-grained control over how different parts of the models are combined by adjusting individual weights for position embeddings, transformer blocks, and final layers.

## Inputs

| Parameter             | Data Type | Required | Range     | Description                                                 |
| --------------------- | --------- | -------- | --------- | ----------------------------------------------------------- |
| `model1`              | MODEL     | Yes      | -         | First model to merge                                        |
| `model2`              | MODEL     | Yes      | -         | Second model to merge                                       |
| `pos_embedder.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for position embedder component (default: 1.0)       |
| `extra_pos_embedder.` | FLOAT     | Yes      | 0.0 - 1.0 | Weight for extra position embedder component (default: 1.0) |
| `x_embedder.`         | FLOAT     | Yes      | 0.0 - 1.0 | Weight for x embedder component (default: 1.0)              |
| `t_embedder.`         | FLOAT     | Yes      | 0.0 - 1.0 | Weight for t embedder component (default: 1.0)              |
| `affline_norm.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for affine normalization component (default: 1.0)    |
| `blocks.block0.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 0 (default: 1.0)               |
| `blocks.block1.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 1 (default: 1.0)               |
| `blocks.block2.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 2 (default: 1.0)               |
| `blocks.block3.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 3 (default: 1.0)               |
| `blocks.block4.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 4 (default: 1.0)               |
| `blocks.block5.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 5 (default: 1.0)               |
| `blocks.block6.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 6 (default: 1.0)               |
| `blocks.block7.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 7 (default: 1.0)               |
| `blocks.block8.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 8 (default: 1.0)               |
| `blocks.block9.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 9 (default: 1.0)               |
| `blocks.block10.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 10 (default: 1.0)              |
| `blocks.block11.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 11 (default: 1.0)              |
| `blocks.block12.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 12 (default: 1.0)              |
| `blocks.block13.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 13 (default: 1.0)              |
| `blocks.block14.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 14 (default: 1.0)              |
| `blocks.block15.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 15 (default: 1.0)              |
| `blocks.block16.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 16 (default: 1.0)              |
| `blocks.block17.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 17 (default: 1.0)              |
| `blocks.block18.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 18 (default: 1.0)              |
| `blocks.block19.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 19 (default: 1.0)              |
| `blocks.block20.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 20 (default: 1.0)              |
| `blocks.block21.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 21 (default: 1.0)              |
| `blocks.block22.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 22 (default: 1.0)              |
| `blocks.block23.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 23 (default: 1.0)              |
| `blocks.block24.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 24 (default: 1.0)              |
| `blocks.block25.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 25 (default: 1.0)              |
| `blocks.block26.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 26 (default: 1.0)              |
| `blocks.block27.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for transformer block 27 (default: 1.0)              |
| `final_layer.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for final layer component (default: 1.0)             |

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `model`     | MODEL     | The merged model combining features from both input models |

***

**Source fingerprint (SHA-256):** `0721b047933179706c76f622efb5b7425aad530d302d8b33ec12dd68513dec0b`


# ModelMergeCosmosPredict2_14B - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeCosmosPredict2_14B

Complete documentation for the ModelMergeCosmosPredict2_14B node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeCosmosPredict2_14B/en.md)

The ModelMergeCosmosPredict2\_14B node merges two AI models by blending their internal components. It gives you precise control over how much each part of the second model influences the final merged result, using adjustable weight values for specific layers and components.

## Inputs

| Parameter           | Data Type | Required | Range     | Description                                                 |
| ------------------- | --------- | -------- | --------- | ----------------------------------------------------------- |
| `model1`            | MODEL     | Yes      | -         | The base model to merge with                                |
| `model2`            | MODEL     | Yes      | -         | The secondary model to merge into the base model            |
| `pos_embedder.`     | FLOAT     | Yes      | 0.0 - 1.0 | Position embedder blending weight (default: 1.0)            |
| `x_embedder.`       | FLOAT     | Yes      | 0.0 - 1.0 | Input embedder blending weight (default: 1.0)               |
| `t_embedder.`       | FLOAT     | Yes      | 0.0 - 1.0 | Time embedder blending weight (default: 1.0)                |
| `t_embedding_norm.` | FLOAT     | Yes      | 0.0 - 1.0 | Time embedding normalization blending weight (default: 1.0) |
| `blocks.0.`         | FLOAT     | Yes      | 0.0 - 1.0 | Block 0 blending weight (default: 1.0)                      |
| `blocks.1.`         | FLOAT     | Yes      | 0.0 - 1.0 | Block 1 blending weight (default: 1.0)                      |
| `blocks.2.`         | FLOAT     | Yes      | 0.0 - 1.0 | Block 2 blending weight (default: 1.0)                      |
| `blocks.3.`         | FLOAT     | Yes      | 0.0 - 1.0 | Block 3 blending weight (default: 1.0)                      |
| `blocks.4.`         | FLOAT     | Yes      | 0.0 - 1.0 | Block 4 blending weight (default: 1.0)                      |
| `blocks.5.`         | FLOAT     | Yes      | 0.0 - 1.0 | Block 5 blending weight (default: 1.0)                      |
| `blocks.6.`         | FLOAT     | Yes      | 0.0 - 1.0 | Block 6 blending weight (default: 1.0)                      |
| `blocks.7.`         | FLOAT     | Yes      | 0.0 - 1.0 | Block 7 blending weight (default: 1.0)                      |
| `blocks.8.`         | FLOAT     | Yes      | 0.0 - 1.0 | Block 8 blending weight (default: 1.0)                      |
| `blocks.9.`         | FLOAT     | Yes      | 0.0 - 1.0 | Block 9 blending weight (default: 1.0)                      |
| `blocks.10.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 10 blending weight (default: 1.0)                     |
| `blocks.11.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 11 blending weight (default: 1.0)                     |
| `blocks.12.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 12 blending weight (default: 1.0)                     |
| `blocks.13.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 13 blending weight (default: 1.0)                     |
| `blocks.14.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 14 blending weight (default: 1.0)                     |
| `blocks.15.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 15 blending weight (default: 1.0)                     |
| `blocks.16.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 16 blending weight (default: 1.0)                     |
| `blocks.17.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 17 blending weight (default: 1.0)                     |
| `blocks.18.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 18 blending weight (default: 1.0)                     |
| `blocks.19.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 19 blending weight (default: 1.0)                     |
| `blocks.20.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 20 blending weight (default: 1.0)                     |
| `blocks.21.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 21 blending weight (default: 1.0)                     |
| `blocks.22.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 22 blending weight (default: 1.0)                     |
| `blocks.23.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 23 blending weight (default: 1.0)                     |
| `blocks.24.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 24 blending weight (default: 1.0)                     |
| `blocks.25.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 25 blending weight (default: 1.0)                     |
| `blocks.26.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 26 blending weight (default: 1.0)                     |
| `blocks.27.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 27 blending weight (default: 1.0)                     |
| `blocks.28.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 28 blending weight (default: 1.0)                     |
| `blocks.29.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 29 blending weight (default: 1.0)                     |
| `blocks.30.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 30 blending weight (default: 1.0)                     |
| `blocks.31.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 31 blending weight (default: 1.0)                     |
| `blocks.32.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 32 blending weight (default: 1.0)                     |
| `blocks.33.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 33 blending weight (default: 1.0)                     |
| `blocks.34.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 34 blending weight (default: 1.0)                     |
| `blocks.35.`        | FLOAT     | Yes      | 0.0 - 1.0 | Block 35 blending weight (default: 1.0)                     |
| `final_layer.`      | FLOAT     | Yes      | 0.0 - 1.0 | Final layer blending weight (default: 1.0)                  |

**Note:** All blending weight parameters accept values between 0.0 and 1.0, where 0.0 means no contribution from model2 and 1.0 means full contribution from model2 for that specific component.

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `model`     | MODEL     | The merged model combining features from both input models |

***

**Source fingerprint (SHA-256):** `5e72608391bc47c2610c93fda19e6e12a1695f95f6135a08efe97e3d400acf84`


# ModelMergeCosmosPredict2_2B - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeCosmosPredict2_2B

Complete documentation for the ModelMergeCosmosPredict2_2B node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeCosmosPredict2_2B/en.md)

The ModelMergeCosmosPredict2\_2B node merges two diffusion models using a block-based approach with fine-grained control over different model components. It allows you to blend specific parts of two models by adjusting interpolation weights for position embedders, time embedders, transformer blocks, and final layers. This provides precise control over how different architectural components from each model contribute to the final merged result.

## Inputs

| Parameter           | Data Type | Required | Range     | Description                                                      |
| ------------------- | --------- | -------- | --------- | ---------------------------------------------------------------- |
| `model1`            | MODEL     | Yes      | -         | The first model to merge                                         |
| `model2`            | MODEL     | Yes      | -         | The second model to merge                                        |
| `pos_embedder.`     | FLOAT     | Yes      | 0.0 - 1.0 | Position embedder interpolation weight (default: 1.0)            |
| `x_embedder.`       | FLOAT     | Yes      | 0.0 - 1.0 | Input embedder interpolation weight (default: 1.0)               |
| `t_embedder.`       | FLOAT     | Yes      | 0.0 - 1.0 | Time embedder interpolation weight (default: 1.0)                |
| `t_embedding_norm.` | FLOAT     | Yes      | 0.0 - 1.0 | Time embedding normalization interpolation weight (default: 1.0) |
| `blocks.0.`         | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 0 interpolation weight (default: 1.0)          |
| `blocks.1.`         | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 1 interpolation weight (default: 1.0)          |
| `blocks.2.`         | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 2 interpolation weight (default: 1.0)          |
| `blocks.3.`         | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 3 interpolation weight (default: 1.0)          |
| `blocks.4.`         | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 4 interpolation weight (default: 1.0)          |
| `blocks.5.`         | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 5 interpolation weight (default: 1.0)          |
| `blocks.6.`         | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 6 interpolation weight (default: 1.0)          |
| `blocks.7.`         | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 7 interpolation weight (default: 1.0)          |
| `blocks.8.`         | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 8 interpolation weight (default: 1.0)          |
| `blocks.9.`         | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 9 interpolation weight (default: 1.0)          |
| `blocks.10.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 10 interpolation weight (default: 1.0)         |
| `blocks.11.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 11 interpolation weight (default: 1.0)         |
| `blocks.12.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 12 interpolation weight (default: 1.0)         |
| `blocks.13.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 13 interpolation weight (default: 1.0)         |
| `blocks.14.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 14 interpolation weight (default: 1.0)         |
| `blocks.15.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 15 interpolation weight (default: 1.0)         |
| `blocks.16.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 16 interpolation weight (default: 1.0)         |
| `blocks.17.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 17 interpolation weight (default: 1.0)         |
| `blocks.18.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 18 interpolation weight (default: 1.0)         |
| `blocks.19.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 19 interpolation weight (default: 1.0)         |
| `blocks.20.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 20 interpolation weight (default: 1.0)         |
| `blocks.21.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 21 interpolation weight (default: 1.0)         |
| `blocks.22.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 22 interpolation weight (default: 1.0)         |
| `blocks.23.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 23 interpolation weight (default: 1.0)         |
| `blocks.24.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 24 interpolation weight (default: 1.0)         |
| `blocks.25.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 25 interpolation weight (default: 1.0)         |
| `blocks.26.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 26 interpolation weight (default: 1.0)         |
| `blocks.27.`        | FLOAT     | Yes      | 0.0 - 1.0 | Transformer block 27 interpolation weight (default: 1.0)         |
| `final_layer.`      | FLOAT     | Yes      | 0.0 - 1.0 | Final layer interpolation weight (default: 1.0)                  |

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `model`     | MODEL     | The merged model combining features from both input models |

***

**Source fingerprint (SHA-256):** `53a8de66d6b731f5b29af326832f66cc973284bc8fdf09d779575f2346cc75a7`


# ModelMergeFlux1 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeFlux1

Complete documentation for the ModelMergeFlux1 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeFlux1/en.md)

The ModelMergeFlux1 node merges two diffusion models by blending their components using weighted interpolation. It allows fine-grained control over how different parts of the models are combined, including image processing blocks, time embedding layers, guidance mechanisms, vector inputs, text encoders, and various transformer blocks. This enables creating hybrid models with customized characteristics from two source models.

## Inputs

| Parameter           | Data Type | Required | Range      | Description                                            |
| ------------------- | --------- | -------- | ---------- | ------------------------------------------------------ |
| `model1`            | MODEL     | Yes      | -          | First source model to merge                            |
| `model2`            | MODEL     | Yes      | -          | Second source model to merge                           |
| `img_in.`           | FLOAT     | Yes      | 0.0 to 1.0 | Image input interpolation weight (default: 1.0)        |
| `time_in.`          | FLOAT     | Yes      | 0.0 to 1.0 | Time embedding interpolation weight (default: 1.0)     |
| `guidance_in`       | FLOAT     | Yes      | 0.0 to 1.0 | Guidance mechanism interpolation weight (default: 1.0) |
| `vector_in.`        | FLOAT     | Yes      | 0.0 to 1.0 | Vector input interpolation weight (default: 1.0)       |
| `txt_in.`           | FLOAT     | Yes      | 0.0 to 1.0 | Text encoder interpolation weight (default: 1.0)       |
| `double_blocks.0.`  | FLOAT     | Yes      | 0.0 to 1.0 | Double block 0 interpolation weight (default: 1.0)     |
| `double_blocks.1.`  | FLOAT     | Yes      | 0.0 to 1.0 | Double block 1 interpolation weight (default: 1.0)     |
| `double_blocks.2.`  | FLOAT     | Yes      | 0.0 to 1.0 | Double block 2 interpolation weight (default: 1.0)     |
| `double_blocks.3.`  | FLOAT     | Yes      | 0.0 to 1.0 | Double block 3 interpolation weight (default: 1.0)     |
| `double_blocks.4.`  | FLOAT     | Yes      | 0.0 to 1.0 | Double block 4 interpolation weight (default: 1.0)     |
| `double_blocks.5.`  | FLOAT     | Yes      | 0.0 to 1.0 | Double block 5 interpolation weight (default: 1.0)     |
| `double_blocks.6.`  | FLOAT     | Yes      | 0.0 to 1.0 | Double block 6 interpolation weight (default: 1.0)     |
| `double_blocks.7.`  | FLOAT     | Yes      | 0.0 to 1.0 | Double block 7 interpolation weight (default: 1.0)     |
| `double_blocks.8.`  | FLOAT     | Yes      | 0.0 to 1.0 | Double block 8 interpolation weight (default: 1.0)     |
| `double_blocks.9.`  | FLOAT     | Yes      | 0.0 to 1.0 | Double block 9 interpolation weight (default: 1.0)     |
| `double_blocks.10.` | FLOAT     | Yes      | 0.0 to 1.0 | Double block 10 interpolation weight (default: 1.0)    |
| `double_blocks.11.` | FLOAT     | Yes      | 0.0 to 1.0 | Double block 11 interpolation weight (default: 1.0)    |
| `double_blocks.12.` | FLOAT     | Yes      | 0.0 to 1.0 | Double block 12 interpolation weight (default: 1.0)    |
| `double_blocks.13.` | FLOAT     | Yes      | 0.0 to 1.0 | Double block 13 interpolation weight (default: 1.0)    |
| `double_blocks.14.` | FLOAT     | Yes      | 0.0 to 1.0 | Double block 14 interpolation weight (default: 1.0)    |
| `double_blocks.15.` | FLOAT     | Yes      | 0.0 to 1.0 | Double block 15 interpolation weight (default: 1.0)    |
| `double_blocks.16.` | FLOAT     | Yes      | 0.0 to 1.0 | Double block 16 interpolation weight (default: 1.0)    |
| `double_blocks.17.` | FLOAT     | Yes      | 0.0 to 1.0 | Double block 17 interpolation weight (default: 1.0)    |
| `double_blocks.18.` | FLOAT     | Yes      | 0.0 to 1.0 | Double block 18 interpolation weight (default: 1.0)    |
| `single_blocks.0.`  | FLOAT     | Yes      | 0.0 to 1.0 | Single block 0 interpolation weight (default: 1.0)     |
| `single_blocks.1.`  | FLOAT     | Yes      | 0.0 to 1.0 | Single block 1 interpolation weight (default: 1.0)     |
| `single_blocks.2.`  | FLOAT     | Yes      | 0.0 to 1.0 | Single block 2 interpolation weight (default: 1.0)     |
| `single_blocks.3.`  | FLOAT     | Yes      | 0.0 to 1.0 | Single block 3 interpolation weight (default: 1.0)     |
| `single_blocks.4.`  | FLOAT     | Yes      | 0.0 to 1.0 | Single block 4 interpolation weight (default: 1.0)     |
| `single_blocks.5.`  | FLOAT     | Yes      | 0.0 to 1.0 | Single block 5 interpolation weight (default: 1.0)     |
| `single_blocks.6.`  | FLOAT     | Yes      | 0.0 to 1.0 | Single block 6 interpolation weight (default: 1.0)     |
| `single_blocks.7.`  | FLOAT     | Yes      | 0.0 to 1.0 | Single block 7 interpolation weight (default: 1.0)     |
| `single_blocks.8.`  | FLOAT     | Yes      | 0.0 to 1.0 | Single block 8 interpolation weight (default: 1.0)     |
| `single_blocks.9.`  | FLOAT     | Yes      | 0.0 to 1.0 | Single block 9 interpolation weight (default: 1.0)     |
| `single_blocks.10.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 10 interpolation weight (default: 1.0)    |
| `single_blocks.11.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 11 interpolation weight (default: 1.0)    |
| `single_blocks.12.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 12 interpolation weight (default: 1.0)    |
| `single_blocks.13.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 13 interpolation weight (default: 1.0)    |
| `single_blocks.14.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 14 interpolation weight (default: 1.0)    |
| `single_blocks.15.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 15 interpolation weight (default: 1.0)    |
| `single_blocks.16.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 16 interpolation weight (default: 1.0)    |
| `single_blocks.17.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 17 interpolation weight (default: 1.0)    |
| `single_blocks.18.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 18 interpolation weight (default: 1.0)    |
| `single_blocks.19.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 19 interpolation weight (default: 1.0)    |
| `single_blocks.20.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 20 interpolation weight (default: 1.0)    |
| `single_blocks.21.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 21 interpolation weight (default: 1.0)    |
| `single_blocks.22.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 22 interpolation weight (default: 1.0)    |
| `single_blocks.23.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 23 interpolation weight (default: 1.0)    |
| `single_blocks.24.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 24 interpolation weight (default: 1.0)    |
| `single_blocks.25.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 25 interpolation weight (default: 1.0)    |
| `single_blocks.26.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 26 interpolation weight (default: 1.0)    |
| `single_blocks.27.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 27 interpolation weight (default: 1.0)    |
| `single_blocks.28.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 28 interpolation weight (default: 1.0)    |
| `single_blocks.29.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 29 interpolation weight (default: 1.0)    |
| `single_blocks.30.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 30 interpolation weight (default: 1.0)    |
| `single_blocks.31.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 31 interpolation weight (default: 1.0)    |
| `single_blocks.32.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 32 interpolation weight (default: 1.0)    |
| `single_blocks.33.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 33 interpolation weight (default: 1.0)    |
| `single_blocks.34.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 34 interpolation weight (default: 1.0)    |
| `single_blocks.35.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 35 interpolation weight (default: 1.0)    |
| `single_blocks.36.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 36 interpolation weight (default: 1.0)    |
| `single_blocks.37.` | FLOAT     | Yes      | 0.0 to 1.0 | Single block 37 interpolation weight (default: 1.0)    |
| `final_layer.`      | FLOAT     | Yes      | 0.0 to 1.0 | Final layer interpolation weight (default: 1.0)        |

## Outputs

| Output Name | Data Type | Description                                                       |
| ----------- | --------- | ----------------------------------------------------------------- |
| `model`     | MODEL     | The merged model combining characteristics from both input models |

***

**Source fingerprint (SHA-256):** `a632133b5d4bc7c5a4e1be5f6f779e424a491fffb8ef7702346adc4acf6f23bc`


# ModelNoiseScale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelNoiseScale

Complete documentation for the ModelNoiseScale node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelNoiseScale/en.md)

## Overview

This node adjusts the noise scale used during model sampling. It allows you to set a specific noise scale value, which controls the amount of noise applied to the model's sampling process.

## Inputs

| Parameter     | Data Type | Required | Range                    | Description                                                                               |
| ------------- | --------- | -------- | ------------------------ | ----------------------------------------------------------------------------------------- |
| `model`       | MODEL     | Yes      | -                        | The model to apply the noise scale adjustment to.                                         |
| `noise_scale` | FLOAT     | Yes      | 0.0 to 64.0 (step: 0.01) | Absolute training noise scale. For example HiDream-O1 base: 8.0, dev: 7.5. (default: 1.0) |

## Outputs

| Output Name | Data Type | Description                                          |
| ----------- | --------- | ---------------------------------------------------- |
| `MODEL`     | MODEL     | The modified model with the new noise scale applied. |

***

**Source fingerprint (SHA-256):** `37b77a5d65fb872f45be8ffa4efb65037bc7459bb001babaaf6b526a9a735190`


# ModelPatchLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelPatchLoader

Complete documentation for the ModelPatchLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelPatchLoader/en.md)

The ModelPatchLoader node loads specialized model patches from the model\_patches folder. It automatically detects the type of patch file and loads the appropriate model architecture, then wraps it in a ModelPatcher for use in the workflow. This node supports different patch types including controlnet blocks, feature embedder models, and other specialized architectures.

## Inputs

| Parameter | Data Type | Required | Range                                                      | Description                                                               |
| --------- | --------- | -------- | ---------------------------------------------------------- | ------------------------------------------------------------------------- |
| `name`    | STRING    | Yes      | All available model patch files from model\_patches folder | The filename of the model patch to load from the model\_patches directory |

## Outputs

| Output Name   | Data Type    | Description                                                              |
| ------------- | ------------ | ------------------------------------------------------------------------ |
| `MODEL_PATCH` | MODEL\_PATCH | The loaded model patch wrapped in a ModelPatcher for use in the workflow |

***

**Source fingerprint (SHA-256):** `e394e165cf416019ed53d9fde42d97c3c9b9f9afd843b12371a624467a4841bf`


# ModelSamplingAuraFlow - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingAuraFlow

Complete documentation for the ModelSamplingAuraFlow node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingAuraFlow/en.md)

The ModelSamplingAuraFlow node applies a specialized sampling configuration to diffusion models, specifically designed for AuraFlow model architectures. It modifies the model's sampling behavior by applying a shift parameter that adjusts the sampling distribution. This node inherits from the SD3 model sampling framework and provides fine control over the sampling process.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                                           |
| --------- | --------- | -------- | ----------- | --------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -           | The diffusion model to apply the AuraFlow sampling configuration to   |
| `shift`   | FLOAT     | Yes      | 0.0 - 100.0 | The shift value to apply to the sampling distribution (default: 1.73) |

## Outputs

| Output Name | Data Type | Description                                                     |
| ----------- | --------- | --------------------------------------------------------------- |
| `model`     | MODEL     | The modified model with AuraFlow sampling configuration applied |

***

**Source fingerprint (SHA-256):** `f49367534032fb2d697d16e8197c16dc761678a5e39990993bdc864bfccea314`


# ModelSamplingContinuousEDM - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingContinuousEDM

Complete documentation for the ModelSamplingContinuousEDM node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to enhance a model's sampling capabilities by integrating continuous EDM (Energy-based Diffusion Models) sampling techniques. It allows for the dynamic adjustment of the noise levels within the model's sampling process, offering a more refined control over the generation quality and diversity.

## Inputs

| Parameter   | Data Type      | Python dtype      | Description                                                                                                                                                                               |
| ----------- | -------------- | ----------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`     | `MODEL`        | `torch.nn.Module` | The model to be enhanced with continuous EDM sampling capabilities. It serves as the foundation for applying the advanced sampling techniques.                                            |
| `sampling`  | COMBO\[STRING] | `str`             | Specifies the type of sampling to be applied, either 'eps' for epsilon sampling or 'v\_prediction' for velocity prediction, influencing the model's behavior during the sampling process. |
| `sigma_max` | `FLOAT`        | `float`           | The maximum sigma value for noise level, allowing for upper bound control in the noise injection process during sampling.                                                                 |
| `sigma_min` | `FLOAT`        | `float`           | The minimum sigma value for noise level, setting the lower limit for noise injection, thus affecting the model's sampling precision.                                                      |

## Outputs

| Parameter | Data Type | Python dtype      | Description                                                                                                         |
| --------- | --------- | ----------------- | ------------------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | `torch.nn.Module` | The enhanced model with integrated continuous EDM sampling capabilities, ready for further use in generation tasks. |


# ModelSamplingContinuousV - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingContinuousV

Complete documentation for the ModelSamplingContinuousV node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingContinuousV/en.md)

The ModelSamplingContinuousV node modifies a model's sampling behavior by applying continuous V-prediction sampling parameters. It creates a clone of the input model and configures it with custom sigma range settings for advanced sampling control. This allows users to fine-tune the sampling process with specific minimum and maximum sigma values.

## Inputs

| Parameter   | Data Type | Required | Range            | Description                                                             |
| ----------- | --------- | -------- | ---------------- | ----------------------------------------------------------------------- |
| `model`     | MODEL     | Yes      | -                | The input model to be modified with continuous V-prediction sampling    |
| `sampling`  | STRING    | Yes      | `"v_prediction"` | The sampling method to apply (currently only V-prediction is supported) |
| `sigma_max` | FLOAT     | Yes      | 0.0 - 1000.0     | The maximum sigma value for sampling (default: 500.0)                   |
| `sigma_min` | FLOAT     | Yes      | 0.0 - 1000.0     | The minimum sigma value for sampling (default: 0.03)                    |

## Outputs

| Output Name | Data Type | Description                                                      |
| ----------- | --------- | ---------------------------------------------------------------- |
| `model`     | MODEL     | The modified model with continuous V-prediction sampling applied |

***

**Source fingerprint (SHA-256):** `8095b5024c0d33011f6a81ed496cf1711981701e0f35f9527646b150f5033d45`


# ModelSamplingDiscrete - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingDiscrete

Complete documentation for the ModelSamplingDiscrete node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to modify the sampling behavior of a model by applying a discrete sampling strategy. It allows for the selection of different sampling methods, such as epsilon, v\_prediction, lcm, or x0, and optionally adjusts the model's noise reduction strategy based on the zero-shot noise ratio (zsnr) setting.

## Inputs

| Parameter  | Data Type      | Python dtype      | Description                                                                                                                                                                                      |
| ---------- | -------------- | ----------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `model`    | MODEL          | `torch.nn.Module` | The model to which the discrete sampling strategy will be applied. This parameter is crucial as it defines the base model that will undergo modification.                                        |
| `sampling` | COMBO\[STRING] | `str`             | Specifies the discrete sampling method to be applied to the model. The choice of method affects how the model generates samples, offering different strategies for sampling.                     |
| `zsnr`     | `BOOLEAN`      | `bool`            | A boolean flag that, when enabled, adjusts the model's noise reduction strategy based on the zero-shot noise ratio. This can influence the quality and characteristics of the generated samples. |

## Outputs

| Parameter | Data Type | Python dtype      | Description                                                                                                                                                |
| --------- | --------- | ----------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | `torch.nn.Module` | The modified model with the applied discrete sampling strategy. This model is now equipped to generate samples using the specified method and adjustments. |


# ModelSamplingFlux - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingFlux

Complete documentation for the ModelSamplingFlux node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingFlux/en.md)

The ModelSamplingFlux node applies Flux model sampling to a given model by calculating a shift parameter based on image dimensions. It creates a specialized sampling configuration that adjusts the model's behavior according to the specified width, height, and shift parameters, then returns the modified model with the new sampling settings applied.

## Inputs

| Parameter    | Data Type | Required | Range                | Description                                                  |
| ------------ | --------- | -------- | -------------------- | ------------------------------------------------------------ |
| `model`      | MODEL     | Yes      | -                    | The model to apply Flux sampling to                          |
| `max_shift`  | FLOAT     | Yes      | 0.0 - 100.0          | Maximum shift value for sampling calculation (default: 1.15) |
| `base_shift` | FLOAT     | Yes      | 0.0 - 100.0          | Base shift value for sampling calculation (default: 0.5)     |
| `width`      | INT       | Yes      | 16 - MAX\_RESOLUTION | Width of the target image in pixels (default: 1024)          |
| `height`     | INT       | Yes      | 16 - MAX\_RESOLUTION | Height of the target image in pixels (default: 1024)         |

## Outputs

| Output Name | Data Type | Description                                                 |
| ----------- | --------- | ----------------------------------------------------------- |
| `model`     | MODEL     | The modified model with Flux sampling configuration applied |

***

**Source fingerprint (SHA-256):** `35733ab0cd032884ceada13715cf51e626586844e8e575471a5ba7cf8a1e5e49`


# ModelSamplingLTXV - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingLTXV

Complete documentation for the ModelSamplingLTXV node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingLTXV/en.md)

The ModelSamplingLTXV node applies advanced sampling parameters to a model based on token count. It calculates a shift value using a linear interpolation between base and maximum shift values, with the calculation depending on the number of tokens in the input latent. The node then creates a specialized model sampling configuration and applies it to the input model.

## Inputs

| Parameter    | Data Type | Required | Range        | Description                                                                                                                               |
| ------------ | --------- | -------- | ------------ | ----------------------------------------------------------------------------------------------------------------------------------------- |
| `model`      | MODEL     | Yes      | -            | The input model to apply sampling parameters to                                                                                           |
| `max_shift`  | FLOAT     | Yes      | 0.0 to 100.0 | The maximum shift value used in the linear interpolation calculation (default: 2.05)                                                      |
| `base_shift` | FLOAT     | Yes      | 0.0 to 100.0 | The base shift value used in the linear interpolation calculation (default: 0.95)                                                         |
| `latent`     | LATENT    | No       | -            | Optional latent input used to determine the token count for the shift calculation. If not provided, a default token count of 4096 is used |

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `model`     | MODEL     | The modified model with the applied sampling parameters |

***

**Source fingerprint (SHA-256):** `09c7628837c3961ad233bcd7e20b20cebb1f7558c0e7f5629d31964c16981a59`


# ModelSamplingSD3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingSD3

Complete documentation for the ModelSamplingSD3 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingSD3/en.md)

The ModelSamplingSD3 node applies Stable Diffusion 3 sampling parameters to a model. It modifies the model's sampling behavior by adjusting the shift parameter, which controls the sampling distribution characteristics. The node creates a modified copy of the input model with the specified sampling configuration applied.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                          |
| --------- | --------- | -------- | ----------- | ---------------------------------------------------- |
| `model`   | MODEL     | Yes      | -           | The input model to apply SD3 sampling parameters to  |
| `shift`   | FLOAT     | Yes      | 0.0 - 100.0 | Controls the sampling shift parameter (default: 3.0) |

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `model`     | MODEL     | The modified model with SD3 sampling parameters applied |

***

**Source fingerprint (SHA-256):** `410fbe0ce16c7e22733ff1e2124c24634a2c6752a882e1c97763b35666882e5f`


# ModelSamplingStableCascade - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSamplingStableCascade

Complete documentation for the ModelSamplingStableCascade node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSamplingStableCascade/en.md)

The ModelSamplingStableCascade node applies stable cascade sampling to a model by adjusting the sampling parameters with a shift value. It creates a modified version of the input model with custom sampling configuration for stable cascade generation.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                                        |
| --------- | --------- | -------- | ----------- | ------------------------------------------------------------------ |
| `model`   | MODEL     | Yes      | -           | The input model to apply stable cascade sampling to                |
| `shift`   | FLOAT     | Yes      | 0.0 - 100.0 | The shift value to apply to the sampling parameters (default: 2.0) |

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `model`     | MODEL     | The modified model with stable cascade sampling applied |

***

**Source fingerprint (SHA-256):** `2d0a342fff05434c8fe78999187bd31dbee7deb6f4447759a489102a8ce277de`


# NAGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/NAGuidance

Complete documentation for the NAGuidance node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/NAGuidance/en.md)

The NAGuidance node applies Normalized Attention Guidance to a model. This technique enables the use of negative prompts with distilled or schnell models by modifying the model's attention mechanism during the sampling process to steer the generation away from undesired concepts.

## Inputs

| Parameter   | Data Type | Required | Range      | Description                                                                                                                                     |
| ----------- | --------- | -------- | ---------- | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`     | MODEL     | Yes      | -          | The model to apply Normalized Attention Guidance to.                                                                                            |
| `nag_scale` | FLOAT     | Yes      | 0.0 - 50.0 | The guidance scale factor. Higher values push the generation further from the negative prompt. (default: 5.0)                                   |
| `nag_alpha` | FLOAT     | Yes      | 0.0 - 1.0  | The blending factor for the normalized attention. A value of 1.0 fully replaces the original attention, while 0.0 has no effect. (default: 0.5) |
| `nag_tau`   | FLOAT     | Yes      | 1.0 - 10.0 | A scaling factor used to limit the normalization ratio. (default: 1.5)                                                                          |

## Outputs

| Output Name | Data Type | Description                                                   |
| ----------- | --------- | ------------------------------------------------------------- |
| `model`     | MODEL     | The patched model with Normalized Attention Guidance enabled. |

***

**Source fingerprint (SHA-256):** `42b4d601312dcbb1c934c6a79bbb5e9fd6598fa5f32b18f5c0affcb596672cba`


# PairConditioningCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PairConditioningCombine

Complete documentation for the PairConditioningCombine node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PairConditioningCombine/en.md)

The PairConditioningCombine node merges two separate conditioning pairs (each consisting of a positive and negative conditioning) into a single combined pair. It takes the positive and negative conditioning from two different sources and combines them using ComfyUI's internal logic, outputting one final positive and one final negative conditioning. This node is experimental and designed for advanced conditioning manipulation workflows.

## Inputs

| Parameter    | Data Type    | Required | Range | Description                        |
| ------------ | ------------ | -------- | ----- | ---------------------------------- |
| `positive_A` | CONDITIONING | Yes      | -     | First positive conditioning input  |
| `negative_A` | CONDITIONING | Yes      | -     | First negative conditioning input  |
| `positive_B` | CONDITIONING | Yes      | -     | Second positive conditioning input |
| `negative_B` | CONDITIONING | Yes      | -     | Second negative conditioning input |

## Outputs

| Output Name | Data Type    | Description                           |
| ----------- | ------------ | ------------------------------------- |
| `positive`  | CONDITIONING | Combined positive conditioning output |
| `negative`  | CONDITIONING | Combined negative conditioning output |

***

**Source fingerprint (SHA-256):** `34c14207930ba31fea054b2e641e9666e738ed786aa117449c4a27667bde41b1`


# PairConditioningSetDefaultAndCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PairConditioningSetDefaultAndCombine

Complete documentation for the PairConditioningSetDefaultAndCombine node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PairConditioningSetDefaultAndCombine/en.md)

The **PairConditioningSetDefaultAndCombine** node sets default conditioning values and combines them with input conditioning data. It takes positive and negative conditioning inputs along with their default counterparts, then processes them through ComfyUI's hook system to produce final conditioning outputs that incorporate the default values.

## Inputs

| Parameter          | Data Type    | Required | Range | Description                                                     |
| ------------------ | ------------ | -------- | ----- | --------------------------------------------------------------- |
| `positive`         | CONDITIONING | Yes      | -     | The primary positive conditioning input to be processed         |
| `negative`         | CONDITIONING | Yes      | -     | The primary negative conditioning input to be processed         |
| `positive_DEFAULT` | CONDITIONING | Yes      | -     | The default positive conditioning values to be used as fallback |
| `negative_DEFAULT` | CONDITIONING | Yes      | -     | The default negative conditioning values to be used as fallback |
| `hooks`            | HOOKS        | No       | -     | Optional hook group for custom processing logic                 |

## Outputs

| Output Name | Data Type    | Description                                                          |
| ----------- | ------------ | -------------------------------------------------------------------- |
| `positive`  | CONDITIONING | The processed positive conditioning with default values incorporated |
| `negative`  | CONDITIONING | The processed negative conditioning with default values incorporated |

***

**Source fingerprint (SHA-256):** `dfa47d0fe02e81db8b68d20ae9b765c2518773f4f7fc8caf774cb870267dbb21`


# PairConditioningSetProperties - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PairConditioningSetProperties

Complete documentation for the PairConditioningSetProperties node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PairConditioningSetProperties/en.md)

The **PairConditioningSetProperties** node allows you to modify properties of both positive and negative conditioning pairs at the same time. It applies strength adjustments, conditioning area settings, and optional masking or timing controls to both conditioning inputs, returning the modified positive and negative conditioning data.

## Inputs

| Parameter       | Data Type        | Required | Range                        | Description                                                             |
| --------------- | ---------------- | -------- | ---------------------------- | ----------------------------------------------------------------------- |
| `positive_NEW`  | CONDITIONING     | Yes      | -                            | The positive conditioning input to modify                               |
| `negative_NEW`  | CONDITIONING     | Yes      | -                            | The negative conditioning input to modify                               |
| `strength`      | FLOAT            | Yes      | 0.0 to 10.0                  | The strength multiplier applied to the conditioning (default: 1.0)      |
| `set_cond_area` | STRING           | Yes      | "default"<br />"mask bounds" | Determines how the conditioning area is calculated (default: "default") |
| `mask`          | MASK             | No       | -                            | Optional mask to constrain the conditioning area                        |
| `hooks`         | HOOKS            | No       | -                            | Optional hook group for advanced conditioning modifications             |
| `timesteps`     | TIMESTEPS\_RANGE | No       | -                            | Optional timestep range to limit when conditioning is applied           |

## Outputs

| Output Name | Data Type    | Description                                                |
| ----------- | ------------ | ---------------------------------------------------------- |
| `positive`  | CONDITIONING | The modified positive conditioning with applied properties |
| `negative`  | CONDITIONING | The modified negative conditioning with applied properties |

***

**Source fingerprint (SHA-256):** `3f750c270665b4f3567790ab1ae0bdbfa176527d4f8d96cf10570a5c5deb9636`


# PairConditioningSetPropertiesAndCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PairConditioningSetPropertiesAndCombine

Complete documentation for the PairConditioningSetPropertiesAndCombine node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PairConditioningSetPropertiesAndCombine/en.md)

The PairConditioningSetPropertiesAndCombine node modifies and combines conditioning pairs by applying new conditioning data to existing positive and negative conditioning inputs. It allows you to adjust the strength of the applied conditioning and control how the conditioning area is set. This node is particularly useful for advanced conditioning manipulation workflows where you need to blend multiple conditioning sources together.

## Inputs

| Parameter       | Data Type        | Required | Range                        | Description                                                          |
| --------------- | ---------------- | -------- | ---------------------------- | -------------------------------------------------------------------- |
| `positive`      | CONDITIONING     | Yes      | -                            | The original positive conditioning input                             |
| `negative`      | CONDITIONING     | Yes      | -                            | The original negative conditioning input                             |
| `positive_NEW`  | CONDITIONING     | Yes      | -                            | The new positive conditioning to apply                               |
| `negative_NEW`  | CONDITIONING     | Yes      | -                            | The new negative conditioning to apply                               |
| `strength`      | FLOAT            | Yes      | 0.0 to 10.0                  | The strength factor for applying the new conditioning (default: 1.0) |
| `set_cond_area` | STRING           | Yes      | "default"<br />"mask bounds" | Controls how the conditioning area is applied (default: "default")   |
| `mask`          | MASK             | No       | -                            | Optional mask to constrain the conditioning application area         |
| `hooks`         | HOOKS            | No       | -                            | Optional hook group for advanced control                             |
| `timesteps`     | TIMESTEPS\_RANGE | No       | -                            | Optional timestep range specification                                |

## Outputs

| Output Name | Data Type    | Description                               |
| ----------- | ------------ | ----------------------------------------- |
| `positive`  | CONDITIONING | The combined positive conditioning output |
| `negative`  | CONDITIONING | The combined negative conditioning output |

***

**Source fingerprint (SHA-256):** `d434fdc1ccbe3ddee6293a6300cc55d30cb5bf357025b26777791746f51e755e`


# PiDConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PiDConditioning

Complete documentation for the PiDConditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PiDConditioning/en.md)

## Overview

Attaches a latent image and a degrade sigma value to a CONDITIONING data. This is used for PiD (Pixel-in-Detail) decoding or upscaling, allowing you to control how much the latent is degraded before processing.

## Inputs

| Parameter       | Data Type    | Required | Range                   | Description                                                                                                                                      |
| --------------- | ------------ | -------- | ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ |
| `positive`      | CONDITIONING | Yes      | -                       | The conditioning data to attach the latent and degrade sigma to.                                                                                 |
| `latent`        | LATENT       | Yes      | -                       | The latent image (from VAEEncode or a KSampler) to attach to the conditioning.                                                                   |
| `latent_format` | COMBO        | Yes      | `"flux"`<br />`"sd3"`   | The format of the latent. Flux1 and Flux2 latents are auto-detected from the channel dimension. SD3 must be selected manually (default: "flux"). |
| `degrade_sigma` | FLOAT        | Yes      | 0.0 to 1.0 (step: 0.01) | The amount of degradation to apply. 0 means a clean latent. Increase this value to denoise corrupted latent outputs (default: 0.0).              |

## Outputs

| Output Name    | Data Type    | Description                                                                       |
| -------------- | ------------ | --------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The original conditioning data with the latent and degrade sigma values attached. |

***

**Source fingerprint (SHA-256):** `7c8de543629c2299fc2c1e035e433dfc249af594773a77e65c69dde67eb104d7`


# Preview3D - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Preview3D

Complete documentation for the Preview3D node in ComfyUI. Learn its inputs, outputs, parameters and usage.

Preview3D node is mainly used to preview 3D model outputs. This node takes two inputs: one is the `camera_info` from the Load3D node, and the other is the path to the 3D model file. The model file path must be located in the `ComfyUI/output` folder.

**Supported Formats**
Currently, this node supports multiple 3D file formats, including `.gltf`, `.glb`, `.obj`, `.fbx`, and `.stl`.

**3D Node Preferences**
Some related preferences for 3D nodes can be configured in ComfyUI's settings menu. Please refer to the following documentation for corresponding settings:
[Settings Menu](https://docs.comfy.org/interface/settings/3d)

## Inputs

| Parameter Name | Type           | Description                             |
| -------------- | -------------- | --------------------------------------- |
| camera\_info   | LOAD3D\_CAMERA | Camera information                      |
| model\_file    | LOAD3D\_CAMERA | Model file path under `ComfyUI/output/` |

## Canvas Area Description

Currently, the 3D-related nodes in the ComfyUI frontend share the same canvas component, so their basic operations are mostly consistent except for some functional differences.

> The following content and interface are mainly based on the Load3D node. Please refer to the actual node interface for specific features.

The Canvas area includes various view operations, such as:

* Preview view settings (grid, background color, preview view)
* Camera control: FOV, camera type
* Global illumination intensity: adjust lighting
* Model export: supports `GLB`, `OBJ`, `STL` formats
* etc.

<img alt="Load 3D Node UI" />

1. Contains multiple menus and hidden menus of the Load 3D node
2. 3D view operation axis

### 1. View Operations

<video>
  <source type="video/mp4" />

  Your browser does not support video playback.
</video>

View control operations:

* Left-click + drag: Rotate the view
* Right-click + drag: Pan the view
* Middle wheel scroll or middle-click + drag: Zoom in/out
* Coordinate axis: Switch views

### 2. Left Menu Functions

![Menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu.webp)

In the preview area, some view operation menus are hidden in the menu. Click the menu button to expand different menus.

* 1. Scene: Contains preview window grid, background color, thumbnail settings
* 2. Model: Model rendering mode, texture material, up direction settings
* 3. Camera: Switch between orthographic and perspective views, set perspective angle
* 4. Light: Scene global illumination intensity
* 5. Export: Export model to other formats (GLB, OBJ, STL)

#### Scene

![scene menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_scene.webp)

The Scene menu provides some basic scene setting functions:

1. Show/Hide grid
2. Set background color
3. Click to upload a background image
4. Hide preview thumbnail

#### Model

![Menu\_Scene](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_model.webp)

The Model menu provides some model-related functions:

1. **Up direction**: Determine which axis is the up direction for the model
2. **Material mode**: Switch model rendering modes - Original, Normal, Wireframe, Lineart

#### Camera

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_camera.webp)

This menu provides switching between orthographic and perspective views, and perspective angle size settings:

1. **Camera**: Quickly switch between orthographic and perspective views
2. **FOV**: Adjust FOV angle

#### Light

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_light.webp)

Through this menu, you can quickly adjust the scene's global illumination intensity

#### Export

![menu\_export](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_export.webp)

This menu provides the ability to quickly convert and export model formats


# Preview3DAnimation - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Preview3DAnimation

Complete documentation for the Preview3DAnimation node in ComfyUI. Learn its inputs, outputs, parameters and usage.

Preview3DAnimation node is mainly used to preview 3D model outputs. This node takes two inputs: one is the `camera_info` from the Load3D node, and the other is the path to the 3D model file. The model file path must be located in the `ComfyUI/output` folder.

**Supported Formats**
Currently, this node supports multiple 3D file formats, including `.gltf`, `.glb`, `.obj`, `.fbx`, and `.stl`.

**3D Node Preferences**
Some related preferences for 3D nodes can be configured in ComfyUI's settings menu. Please refer to the following documentation for corresponding settings:
[Settings Menu](https://docs.comfy.org/interface/settings/3d)

## Inputs

| Parameter Name | Type           | Description                             |
| -------------- | -------------- | --------------------------------------- |
| camera\_info   | LOAD3D\_CAMERA | Camera information                      |
| model\_file    | STRING         | Model file path under `ComfyUI/output/` |

## Canvas Area Description

Currently, the 3D-related nodes in the ComfyUI frontend share the same canvas component, so their basic operations are mostly consistent except for some functional differences.

> The following content and interface are mainly based on the Load3D node. Please refer to the actual node interface for specific features.

The Canvas area includes various view operations, such as:

* Preview view settings (grid, background color, preview view)
* Camera control: FOV, camera type
* Global illumination intensity: adjust lighting
* Model export: supports `GLB`, `OBJ`, `STL` formats
* etc.

<img alt="Load 3D Node UI" />

1. Contains multiple menus and hidden menus of the Load 3D node
2. 3D view operation axis

### 1. View Operations

<video>
  <source type="video/mp4" />

  Your browser does not support video playback.
</video>

View control operations:

* Left-click + drag: Rotate the view
* Right-click + drag: Pan the view
* Middle wheel scroll or middle-click + drag: Zoom in/out
* Coordinate axis: Switch views

### 2. Left Menu Functions

![Menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu.webp)

In the preview area, some view operation menus are hidden in the menu. Click the menu button to expand different menus.

* 1. Scene: Contains preview window grid, background color, thumbnail settings
* 2. Model: Model rendering mode, texture material, up direction settings
* 3. Camera: Switch between orthographic and perspective views, set perspective angle
* 4. Light: Scene global illumination intensity
* 5. Export: Export model to other formats (GLB, OBJ, STL)

#### Scene

![scene menu](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_scene.webp)

The Scene menu provides some basic scene setting functions:

1. Show/Hide grid
2. Set background color
3. Click to upload a background image
4. Hide preview thumbnail

#### Model

![Menu\_Scene](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_model.webp)

The Model menu provides some model-related functions:

1. **Up direction**: Determine which axis is the up direction for the model
2. **Material mode**: Switch model rendering modes - Original, Normal, Wireframe, Lineart

#### Camera

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_camera.webp)

This menu provides switching between orthographic and perspective views, and perspective angle size settings:

1. **Camera**: Quickly switch between orthographic and perspective views
2. **FOV**: Adjust FOV angle

#### Light

![menu\_modelmenu\_camera](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_light.webp)

Through this menu, you can quickly adjust the scene's global illumination intensity

#### Export

![menu\_export](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/Load3d/asset/menu_export.webp)

This menu provides the ability to quickly convert and export model formats


# QuadrupleCLIPLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/QuadrupleCLIPLoader

Complete documentation for the QuadrupleCLIPLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The Quadruple CLIP Loader, QuadrupleCLIPLoader, is one of the core nodes of ComfyUI, first added to support the HiDream I1 version model. If you find this node missing, try updating ComfyUI to the latest version to ensure node support.

It requires 4 CLIP models, corresponding to the parameters `clip_name1`, `clip_name2`, `clip_name3`, and `clip_name4`, and will provide a CLIP model output for subsequent nodes.

This node will detect models located in the `ComfyUI/models/text_encoders` folder,
and it will also read models from additional paths configured in the extra\_model\_paths.yaml file.
Sometimes, after adding models, you may need to **reload the ComfyUI interface** to allow it to read the model files in the corresponding folder.


# QwenImageDiffsynthControlnet - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/QwenImageDiffsynthControlnet

Complete documentation for the QwenImageDiffsynthControlnet node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/QwenImageDiffsynthControlnet/en.md)

The QwenImageDiffsynthControlnet node applies a diffusion synthesis control network patch to modify a base model's behavior. It uses an image input and optional mask to guide the model's generation process with adjustable strength, creating a patched model that incorporates the control network's influence for more controlled image synthesis.

## Inputs

| Parameter     | Data Type    | Required | Range         | Description                                                                                        |
| ------------- | ------------ | -------- | ------------- | -------------------------------------------------------------------------------------------------- |
| `model`       | MODEL        | Yes      | -             | The base model to be patched with the control network                                              |
| `model_patch` | MODEL\_PATCH | Yes      | -             | The control network patch model to apply to the base model                                         |
| `vae`         | VAE          | Yes      | -             | The VAE (Variational Autoencoder) used in the diffusion process                                    |
| `image`       | IMAGE        | Yes      | -             | The input image used to guide the control network (only RGB channels are used)                     |
| `strength`    | FLOAT        | Yes      | -10.0 to 10.0 | The strength of the control network influence (default: 1.0)                                       |
| `mask`        | MASK         | No       | -             | Optional mask that defines areas where the control network should be applied (inverted internally) |

**Note:** When a mask is provided, it is automatically inverted (1.0 - mask) and reshaped to match the expected dimensions for the control network processing. The node uses different internal processing methods depending on whether the model patch is a ZImage Control type or a standard DiffSynth control network.

## Outputs

| Output Name | Data Type | Description                                                                   |
| ----------- | --------- | ----------------------------------------------------------------------------- |
| `model`     | MODEL     | The modified model with the diffusion synthesis control network patch applied |

***

**Source fingerprint (SHA-256):** `61833984d0b92be65fae72a894806572c0588dea74a295e8289d1194dee611bb`


# ReferenceLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReferenceLatent

Complete documentation for the ReferenceLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReferenceLatent/en.md)

This node sets the guiding latent for an edit model. It takes conditioning data and an optional latent input, then modifies the conditioning to include reference latent information. If the model supports it, you can chain multiple ReferenceLatent nodes to set multiple reference images.

## Inputs

| Parameter      | Data Type    | Required | Range | Description                                                            |
| -------------- | ------------ | -------- | ----- | ---------------------------------------------------------------------- |
| `conditioning` | CONDITIONING | Yes      | -     | The conditioning data to be modified with reference latent information |
| `latent`       | LATENT       | No       | -     | Optional latent data to use as reference for the edit model            |

## Outputs

| Output Name | Data Type    | Description                                                            |
| ----------- | ------------ | ---------------------------------------------------------------------- |
| `output`    | CONDITIONING | The modified conditioning data containing reference latent information |

***

**Source fingerprint (SHA-256):** `8465db01a0929ae27ac05419f93f0c206835924f1c0196b874fff9adb1834656`


# ReferenceTimbreAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReferenceTimbreAudio

Complete documentation for the ReferenceTimbreAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReferenceTimbreAudio/en.md)

This node sets a reference audio timbre for use in the "ace step 1.5" process. It works by taking a conditioning input and optionally a latent representation of audio, then attaches that latent data to the conditioning for use by subsequent nodes in the workflow.

## Inputs

| Parameter      | Data Type    | Required | Range | Description                                                                                                         |
| -------------- | ------------ | -------- | ----- | ------------------------------------------------------------------------------------------------------------------- |
| `conditioning` | CONDITIONING | Yes      |       | The conditioning data to which the reference audio information will be attached.                                    |
| `latent`       | LATENT       | No       |       | An optional latent representation of the reference audio. When provided, its samples are added to the conditioning. |

## Outputs

| Output Name    | Data Type    | Description                                                                                                                    |
| -------------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------ |
| `conditioning` | CONDITIONING | The modified conditioning data, now containing the reference audio timbre latents if the optional `latent` input was provided. |

***

**Source fingerprint (SHA-256):** `b4bd556add87f8da2cdb7d0d63da620b508de302ae1d674d2bcb7bc771e60a5d`


# RenormCFG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RenormCFG

Complete documentation for the RenormCFG node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RenormCFG/en.md)

The RenormCFG node modifies the classifier-free guidance (CFG) process in diffusion models by applying conditional scaling and normalization. It adjusts the denoising process based on specified timestep thresholds and renormalization factors to control the influence of conditional versus unconditional predictions during image generation.

## Inputs

| Parameter    | Data Type | Required | Range       | Description                                                                                                                                                                              |
| ------------ | --------- | -------- | ----------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`      | MODEL     | Yes      | -           | The diffusion model to apply renormalized CFG to                                                                                                                                         |
| `cfg_trunc`  | FLOAT     | No       | 0.0 - 100.0 | Timestep threshold for applying CFG scaling. When the current timestep is below this value, CFG scaling is applied; otherwise, only the conditional prediction is used (default: 100.0)  |
| `renorm_cfg` | FLOAT     | No       | 0.0 - 100.0 | Renormalization factor that limits the maximum norm of the CFG-scaled prediction relative to the original conditional prediction. A value of 0.0 disables renormalization (default: 1.0) |

## Outputs

| Output Name | Data Type | Description                                               |
| ----------- | --------- | --------------------------------------------------------- |
| `model`     | MODEL     | The modified model with renormalized CFG function applied |

***

**Source fingerprint (SHA-256):** `1fb74c816d82d39e030a25e372c01f251a42c7fe6314cc6cefbad984acb262d3`


# RescaleCFG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RescaleCFG

Complete documentation for the RescaleCFG node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The RescaleCFG node is designed to adjust the conditioning and unconditioning scales of a model's output based on a specified multiplier, aiming to achieve a more balanced and controlled generation process. It operates by rescaling the model's output to modify the influence of conditioned and unconditioned components, thereby potentially enhancing the model's performance or output quality.

## Inputs

| Parameter    | Data Type | Description                                                                                                                                                                                                    |
| ------------ | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`      | MODEL     | The model parameter represents the generative model to be adjusted. It is crucial as the node applies a rescaling function to the model's output, directly influencing the generation process.                 |
| `multiplier` | `FLOAT`   | The multiplier parameter controls the extent of rescaling applied to the model's output. It determines the balance between the original and rescaled components, affecting the final output's characteristics. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                                |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `model`   | MODEL     | The modified model with adjusted conditioning and unconditioning scales. This model is expected to produce outputs with potentially enhanced characteristics due to the applied rescaling. |


# SaveGLB - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveGLB

Complete documentation for the SaveGLB node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveGLB/en.md)

The SaveGLB node saves 3D mesh data or 3D files to the output directory. It accepts mesh data or various 3D file formats (GLB, GLTF, OBJ, FBX, STL, USDZ) and exports them with a specified filename prefix. When saving mesh data, it can handle multiple meshes and automatically adds workflow metadata to the files when metadata is enabled.

## Inputs

| Parameter         | Data Type      | Required | Range | Description                                                                                                |
| ----------------- | -------------- | -------- | ----- | ---------------------------------------------------------------------------------------------------------- |
| `mesh`            | MESH or FILE3D | Yes      | -     | Mesh or 3D file to save. Accepts mesh data or 3D file formats including GLB, GLTF, OBJ, FBX, STL, and USDZ |
| `filename_prefix` | STRING         | No       | -     | The prefix for the output filename (default: "3d/ComfyUI")                                                 |

## Outputs

| Output Name | Data Type | Description                                                                                      |
| ----------- | --------- | ------------------------------------------------------------------------------------------------ |
| `ui`        | UI        | Displays the saved 3D files in the user interface with filename, subfolder, and type information |

***

**Source fingerprint (SHA-256):** `ed56f61f60afea7dfbcae8b222aa7129608e3b10bc0daa27934b8c0cbeb1c0e8`


# SetClipHooks - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetClipHooks

Complete documentation for the SetClipHooks node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SetClipHooks/en.md)

The SetClipHooks node allows you to apply custom hooks to a CLIP model, enabling advanced modifications to its behavior. It can apply hooks to conditioning outputs and optionally enable clip scheduling functionality. This node creates a cloned copy of the input CLIP model with the specified hook configurations applied.

## Inputs

| Parameter        | Data Type | Required | Range | Description                                                    |
| ---------------- | --------- | -------- | ----- | -------------------------------------------------------------- |
| `clip`           | CLIP      | Yes      | -     | The CLIP model to apply hooks to                               |
| `apply_to_conds` | BOOLEAN   | Yes      | -     | Whether to apply hooks to conditioning outputs (default: True) |
| `schedule_clip`  | BOOLEAN   | Yes      | -     | Whether to enable clip scheduling (default: False)             |
| `hooks`          | HOOKS     | No       | -     | Optional hook group to apply to the CLIP model                 |

## Outputs

| Output Name | Data Type | Description                                          |
| ----------- | --------- | ---------------------------------------------------- |
| `clip`      | CLIP      | A cloned CLIP model with the specified hooks applied |

***

**Source fingerprint (SHA-256):** `904a878638c015bdce1983ae0c11a2b580b271090fca39edb304f6ed90c8c66d`


# SetHookKeyframes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetHookKeyframes

Complete documentation for the SetHookKeyframes node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SetHookKeyframes/en.md)

The Set Hook Keyframes node allows you to apply keyframe scheduling to existing hook groups. It takes a hook group and optionally applies keyframe timing information to control when different hooks are executed during the generation process. When keyframes are provided, the node clones the hook group and sets the keyframe timing on all hooks within the group.

## Inputs

| Parameter | Data Type       | Required | Range | Description                                                              |
| --------- | --------------- | -------- | ----- | ------------------------------------------------------------------------ |
| `hooks`   | HOOKS           | Yes      | -     | The hook group to which keyframe scheduling will be applied              |
| `hook_kf` | HOOK\_KEYFRAMES | No       | -     | Optional keyframe group containing timing information for hook execution |

## Outputs

| Output Name | Data Type | Description                                                                                  |
| ----------- | --------- | -------------------------------------------------------------------------------------------- |
| `hooks`     | HOOKS     | The modified hook group with keyframe scheduling applied (cloned if keyframes were provided) |

***

**Source fingerprint (SHA-256):** `48908e5247b18e5b7b1d894c2f1adcf6403e499125b0c3eb05978584b3d5759b`


# SetModelHooksOnCond - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetModelHooksOnCond

Complete documentation for the SetModelHooksOnCond node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SetModelHooksOnCond/en.md)

This node attaches custom hooks to conditioning data, allowing you to intercept and modify the conditioning process during model execution. It takes a set of hooks and applies them to the provided conditioning data, enabling advanced customization of the text-to-image generation workflow. The modified conditioning with attached hooks is then returned for use in subsequent processing steps.

## Inputs

| Parameter      | Data Type    | Required | Range | Description                                                        |
| -------------- | ------------ | -------- | ----- | ------------------------------------------------------------------ |
| `conditioning` | CONDITIONING | Yes      | -     | The conditioning data to which hooks will be attached              |
| `hooks`        | HOOKS        | Yes      | -     | The hook definitions that will be applied to the conditioning data |

## Outputs

| Output Name    | Data Type    | Description                                        |
| -------------- | ------------ | -------------------------------------------------- |
| `conditioning` | CONDITIONING | The modified conditioning data with hooks attached |

***

**Source fingerprint (SHA-256):** `a6e63a3a4d94d1b66a82d449af5ae001e1fc4a04f0f81d9fb5c4f8c13e5bdf8b`


# SkipLayerGuidanceDiT - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SkipLayerGuidanceDiT

Complete documentation for the SkipLayerGuidanceDiT node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SkipLayerGuidanceDiT/en.md)

Enhances guidance towards detailed structure by using another set of CFG negative with skipped layers. This generic version of SkipLayerGuidance can be used on every DiT model and is inspired by Perturbed Attention Guidance. The original experimental implementation was created for SD3.

## Inputs

| Parameter         | Data Type | Required | Range      | Description                                                                                |
| ----------------- | --------- | -------- | ---------- | ------------------------------------------------------------------------------------------ |
| `model`           | MODEL     | Yes      | -          | The model to apply skip layer guidance to                                                  |
| `double_layers`   | STRING    | Yes      | -          | Comma-separated layer numbers for double blocks to skip (default: "7, 8, 9")               |
| `single_layers`   | STRING    | Yes      | -          | Comma-separated layer numbers for single blocks to skip (default: "7, 8, 9")               |
| `scale`           | FLOAT     | Yes      | 0.0 - 10.0 | Guidance scale factor (default: 3.0)                                                       |
| `start_percent`   | FLOAT     | Yes      | 0.0 - 1.0  | Starting percentage for guidance application (default: 0.01)                               |
| `end_percent`     | FLOAT     | Yes      | 0.0 - 1.0  | Ending percentage for guidance application (default: 0.15)                                 |
| `rescaling_scale` | FLOAT     | Yes      | 0.0 - 10.0 | Rescaling scale factor to adjust the output magnitude (default: 0.0, meaning no rescaling) |

**Note:** If both `double_layers` and `single_layers` are empty (contain no layer numbers), the node returns the original model without applying any guidance.

## Outputs

| Output Name | Data Type | Description                                         |
| ----------- | --------- | --------------------------------------------------- |
| `model`     | MODEL     | The modified model with skip layer guidance applied |

***

**Source fingerprint (SHA-256):** `35ca97f87913d0efcbb502ca040a8f357da112b202184d8786f63acd76809808`


# SkipLayerGuidanceDiTSimple - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SkipLayerGuidanceDiTSimple

Complete documentation for the SkipLayerGuidanceDiTSimple node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SkipLayerGuidanceDiTSimple/en.md)

Simple version of the SkipLayerGuidanceDiT node that only modifies the unconditional pass during the denoising process. This node applies skip layer guidance to specific transformer layers in DiT (Diffusion Transformer) models by selectively skipping certain layers during the unconditional pass based on specified timing and layer parameters.

## Inputs

| Parameter       | Data Type | Required | Range     | Description                                                                                     |
| --------------- | --------- | -------- | --------- | ----------------------------------------------------------------------------------------------- |
| `model`         | MODEL     | Yes      | -         | The model to apply skip layer guidance to                                                       |
| `double_layers` | STRING    | No       | -         | Comma-separated list of double block layer indices to skip (default: "7, 8, 9")                 |
| `single_layers` | STRING    | No       | -         | Comma-separated list of single block layer indices to skip (default: "7, 8, 9")                 |
| `start_percent` | FLOAT     | No       | 0.0 - 1.0 | The starting percentage of the denoising process when skip layer guidance begins (default: 0.0) |
| `end_percent`   | FLOAT     | No       | 0.0 - 1.0 | The ending percentage of the denoising process when skip layer guidance stops (default: 1.0)    |

**Note:** Skip layer guidance is only applied when both `double_layers` and `single_layers` contain valid layer indices. If both are empty, the node returns the original model unchanged. The skip layer guidance is active only when the current denoising step's sigma value falls between `start_percent` and `end_percent` (converted to sigma values internally).

## Outputs

| Output Name | Data Type | Description                                                                 |
| ----------- | --------- | --------------------------------------------------------------------------- |
| `model`     | MODEL     | The modified model with skip layer guidance applied to the specified layers |

***

**Source fingerprint (SHA-256):** `f153348d75cf3b52d7d7d541f7467e51c797e1fe5844516591db7a191415cdb2`


# SkipLayerGuidanceSD3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SkipLayerGuidanceSD3

Complete documentation for the SkipLayerGuidanceSD3 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SkipLayerGuidanceSD3/en.md)

The SkipLayerGuidanceSD3 node enhances guidance towards detailed structure by applying an additional set of classifier-free guidance with skipped layers. This experimental implementation is inspired by Perturbed Attention Guidance and works by selectively bypassing certain layers during the negative conditioning process to improve structural details in the generated output.

## Inputs

| Parameter       | Data Type | Required | Range      | Description                                                                               |
| --------------- | --------- | -------- | ---------- | ----------------------------------------------------------------------------------------- |
| `model`         | MODEL     | Yes      | -          | The model to apply skip layer guidance to                                                 |
| `layers`        | STRING    | Yes      | -          | Comma-separated list of layer indices to skip (default: "7, 8, 9")                        |
| `scale`         | FLOAT     | Yes      | 0.0 - 10.0 | The strength of the skip layer guidance effect (default: 3.0)                             |
| `start_percent` | FLOAT     | Yes      | 0.0 - 1.0  | The starting point of guidance application as a percentage of total steps (default: 0.01) |
| `end_percent`   | FLOAT     | Yes      | 0.0 - 1.0  | The ending point of guidance application as a percentage of total steps (default: 0.15)   |

## Outputs

| Output Name | Data Type | Description                                         |
| ----------- | --------- | --------------------------------------------------- |
| `model`     | MODEL     | The modified model with skip layer guidance applied |

***

**Source fingerprint (SHA-256):** `8fba6e3037387e6beab64175099de1c96babdd492609099ba8ad3a49a6c34efe`


# TCFG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TCFG

Complete documentation for the TCFG node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TCFG/en.md)

TCFG (Tangential Damping CFG) refines the unconditional (negative) predictions to better align with the conditional (positive) predictions during the sampling process. This technique improves output quality by applying tangential damping to the unconditional guidance, based on the research paper 2503.18137. The node modifies the model's sampling behavior by adjusting how unconditional predictions are processed during classifier-free guidance.

## Inputs

| Parameter | Data Type | Required | Range | Description                                  |
| --------- | --------- | -------- | ----- | -------------------------------------------- |
| `model`   | MODEL     | Yes      | -     | The model to apply tangential damping CFG to |

## Outputs

| Output Name     | Data Type | Description                                            |
| --------------- | --------- | ------------------------------------------------------ |
| `patched_model` | MODEL     | The modified model with tangential damping CFG applied |

***

**Source fingerprint (SHA-256):** `6e0e1df09bdc29f14a4828ec54fd29f89926b9d8121bc8ba9f95ce066b899e95`


# TextEncodeHunyuanVideo_ImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeHunyuanVideo_ImageToVideo

Complete documentation for the TextEncodeHunyuanVideo_ImageToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeHunyuanVideo_ImageToVideo/en.md)

The TextEncodeHunyuanVideo\_ImageToVideo node creates conditioning data for video generation by combining text prompts with image embeddings. It uses a CLIP model to process both the text input and visual information from a CLIP vision output, then generates tokens that blend these two sources according to the specified image interleave setting.

## Inputs

| Parameter            | Data Type            | Required | Range | Description                                                                                                                                                                                                                                                                                                    |
| -------------------- | -------------------- | -------- | ----- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip`               | CLIP                 | Yes      | -     | The CLIP model used for tokenization and encoding                                                                                                                                                                                                                                                              |
| `clip_vision_output` | CLIP\_VISION\_OUTPUT | Yes      | -     | The visual embeddings from a CLIP vision model that provide image context                                                                                                                                                                                                                                      |
| `prompt`             | STRING               | Yes      | -     | The text description to guide the video generation. Supports multiline input and dynamic prompts. The prompt is formatted using a template that asks the model to describe the video based on the reference image, covering aspects like main content, object details, actions, background, and camera angles. |
| `image_interleave`   | INT                  | Yes      | 1-512 | How much the image influences things vs the text prompt. Higher number means more influence from the text prompt. (default: 2)                                                                                                                                                                                 |

## Outputs

| Output Name    | Data Type    | Description                                                                         |
| -------------- | ------------ | ----------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The conditioning data that combines text and image information for video generation |

***

**Source fingerprint (SHA-256):** `ecc190941e8d355bc6e6e4b5b7938d54a79e70a7ff0049157dab30b720605e6a`


# TextEncodeQwenImageEdit - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeQwenImageEdit

Complete documentation for the TextEncodeQwenImageEdit node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeQwenImageEdit/en.md)

The TextEncodeQwenImageEdit node processes text prompts and optional images to generate conditioning data for image generation or editing. It uses a CLIP model to tokenize the input and can optionally encode reference images using a VAE to create reference latents. When an image is provided, it automatically resizes the image to maintain consistent processing dimensions.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                           |
| --------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------- |
| `clip`    | CLIP      | Yes      | -     | The CLIP model used for text and image tokenization                                   |
| `prompt`  | STRING    | Yes      | -     | Text prompt for conditioning generation, supports multiline input and dynamic prompts |
| `vae`     | VAE       | No       | -     | Optional VAE model for encoding reference images into latents                         |
| `image`   | IMAGE     | No       | -     | Optional input image for reference or editing purposes                                |

**Note:** When both `image` and `vae` are provided, the node encodes the image into reference latents and attaches them to the conditioning output. The image is automatically resized to maintain a consistent processing scale of approximately 1024x1024 pixels.

## Outputs

| Output Name    | Data Type    | Description                                                                                  |
| -------------- | ------------ | -------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | Conditioning data containing text tokens and optional reference latents for image generation |

***

**Source fingerprint (SHA-256):** `7d1f82174d92ee86ca35e14a364e1a703fb9fc1ac9979611bd894a0a639c58a2`


# TextEncodeQwenImageEditPlus - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeQwenImageEditPlus

Complete documentation for the TextEncodeQwenImageEditPlus node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeQwenImageEditPlus/en.md)

The TextEncodeQwenImageEditPlus node processes text prompts and optional images to generate conditioning data for image generation or editing tasks. It uses a specialized template to analyze input images and understand how text instructions should modify them, then encodes this information for use in subsequent generation steps. The node can handle up to three input images and optionally generate reference latents when a VAE is provided.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                                               |
| --------- | --------- | -------- | ----- | --------------------------------------------------------------------------------------------------------- |
| `clip`    | CLIP      | Yes      | -     | The CLIP model used for tokenization and encoding                                                         |
| `prompt`  | STRING    | Yes      | -     | Text instruction describing the desired image modification (supports multiline input and dynamic prompts) |
| `vae`     | VAE       | No       | -     | Optional VAE model for generating reference latents from input images                                     |
| `image1`  | IMAGE     | No       | -     | First optional input image for analysis and modification                                                  |
| `image2`  | IMAGE     | No       | -     | Second optional input image for analysis and modification                                                 |
| `image3`  | IMAGE     | No       | -     | Third optional input image for analysis and modification                                                  |

**Note:** When a VAE is provided, the node generates reference latents from all input images. The node can process up to three images simultaneously. Images are automatically resized to 384x384 pixels for vision-language processing, and to dimensions divisible by 8 (with a target area of 1024x1024 pixels) for VAE encoding.

## Outputs

| Output Name    | Data Type    | Description                                                                                          |
| -------------- | ------------ | ---------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | Encoded conditioning data containing text tokens and optional reference latents for image generation |

***

**Source fingerprint (SHA-256):** `40e0104e1a5fd88afb889948bc43559f99049a91c03c3f9885455b6dbfde343e`


# TextEncodeZImageOmni - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeZImageOmni

Complete documentation for the TextEncodeZImageOmni node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeZImageOmni/en.md)

The TextEncodeZImageOmni node is an advanced conditioning node that encodes a text prompt along with optional reference images into a conditioning format suitable for image generation models. It can process up to three images, optionally encoding them with a vision encoder and/or a VAE to produce reference latents, and integrates these visual references with the text prompt using a specific template structure.

## Inputs

| Parameter            | Data Type  | Required | Range | Description                                                                                                                                                           |
| -------------------- | ---------- | -------- | ----- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip`               | CLIP       | Yes      |       | The CLIP model used for tokenizing and encoding the text prompt.                                                                                                      |
| `image_encoder`      | CLIPVision | No       |       | An optional vision encoder model. If provided, it will be used to encode the input images, and the resulting embeddings will be added to the conditioning.            |
| `prompt`             | STRING     | Yes      |       | The text prompt to be encoded. This field supports multiline input and dynamic prompts.                                                                               |
| `auto_resize_images` | BOOLEAN    | No       |       | When enabled (default: True), input images will be automatically resized based on their pixel area before being passed to the VAE for encoding.                       |
| `vae`                | VAE        | No       |       | An optional VAE model. If provided, it will be used to encode the input images into latent representations, which are added to the conditioning as reference latents. |
| `image1`             | IMAGE      | No       |       | The first optional reference image.                                                                                                                                   |
| `image2`             | IMAGE      | No       |       | The second optional reference image.                                                                                                                                  |
| `image3`             | IMAGE      | No       |       | The third optional reference image.                                                                                                                                   |

**Note:** The node can accept a maximum of three images (`image1`, `image2`, `image3`). The `image_encoder` and `vae` inputs are only utilized if at least one image is provided. When `auto_resize_images` is True and a `vae` is connected, images are resized to have a total pixel area close to 1024x1024 before encoding.

## Outputs

| Output Name    | Data Type    | Description                                                                                                                                                      |
| -------------- | ------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The final conditioning output, which contains the encoded text prompt and may include encoded image embeddings and/or reference latents if images were provided. |

***

**Source fingerprint (SHA-256):** `5edda1e70c2189c164fbde427999e74bfa21f4401feb7067e483802ca1c2df31`


# TripleCLIPLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripleCLIPLoader

Complete documentation for the TripleCLIPLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripleCLIPLoader/en.md)

The TripleCLIPLoader node loads three different text encoder models simultaneously and combines them into a single CLIP model. This is useful for advanced text encoding scenarios where multiple text encoders are needed, such as in SD3 workflows that require clip-l, clip-g, and t5 models working together.

## Inputs

| Parameter    | Data Type | Required | Range                      | Description                                                            |
| ------------ | --------- | -------- | -------------------------- | ---------------------------------------------------------------------- |
| `clip_name1` | STRING    | Yes      | Multiple options available | The first text encoder model to load from the available text encoders  |
| `clip_name2` | STRING    | Yes      | Multiple options available | The second text encoder model to load from the available text encoders |
| `clip_name3` | STRING    | Yes      | Multiple options available | The third text encoder model to load from the available text encoders  |

**Note:** All three text encoder parameters must be selected from the available text encoder models in your system. The node will load all three models and combine them into a single CLIP model for processing.

## Outputs

| Output Name | Data Type | Description                                                     |
| ----------- | --------- | --------------------------------------------------------------- |
| `CLIP`      | CLIP      | A combined CLIP model containing all three loaded text encoders |

***

**Source fingerprint (SHA-256):** `565ab519e46b9661705768b14f565f297002f4e6fe95c7725c4f742734e8d1c1`


# TripoImageToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoImageToModelNode

Complete documentation for the TripoImageToModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoImageToModelNode/en.md)

Generates 3D models synchronously based on a single image using Tripo's API. This node takes an input image and converts it into a 3D model with various customization options for texture, quality, and model properties.

## Inputs

| Parameter           | Data Type | Required | Range                                                                                              | Description                                                                   |
| ------------------- | --------- | -------- | -------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------- |
| `image`             | IMAGE     | Yes      | -                                                                                                  | Input image used to generate the 3D model                                     |
| `model_version`     | COMBO     | No       | `"v1.4"`<br />`"v3.0"`<br />`"v3.5"`<br />`"v3.6"`                                                 | The model version to use for generation                                       |
| `style`             | COMBO     | No       | `"None"`<br />`"realistic"`<br />`"cartoon"`<br />`"sculpture"`<br />`"low_poly"`                  | Style setting for the generated model (default: "None")                       |
| `texture`           | BOOLEAN   | No       | -                                                                                                  | Whether to generate textures for the model (default: True)                    |
| `pbr`               | BOOLEAN   | No       | -                                                                                                  | Whether to use Physically Based Rendering (default: True)                     |
| `model_seed`        | INT       | No       | -                                                                                                  | Random seed for model generation (default: 42)                                |
| `orientation`       | COMBO     | No       | `"default"`<br />`"front"`<br />`"back"`<br />`"left"`<br />`"right"`<br />`"top"`<br />`"bottom"` | Orientation setting for the generated model (default: "default")              |
| `texture_seed`      | INT       | No       | -                                                                                                  | Random seed for texture generation (default: 42)                              |
| `texture_quality`   | COMBO     | No       | `"standard"`<br />`"detailed"`                                                                     | Quality level for texture generation (default: "standard")                    |
| `texture_alignment` | COMBO     | No       | `"original_image"`<br />`"geometry"`                                                               | Alignment method for texture mapping (default: "original\_image")             |
| `face_limit`        | INT       | No       | -1 to 500000                                                                                       | Maximum number of faces in the generated model, -1 for no limit (default: -1) |
| `quad`              | BOOLEAN   | No       | -                                                                                                  | Whether to use quadrilateral faces instead of triangles (default: False)      |
| `geometry_quality`  | COMBO     | No       | `"standard"`<br />`"detailed"`                                                                     | Quality level for geometry generation (default: "standard")                   |

**Note:** The `image` parameter is required and must be provided for the node to function. If no image is provided, the node will raise a RuntimeError.

## Outputs

| Output Name     | Data Type       | Description                                                   |
| --------------- | --------------- | ------------------------------------------------------------- |
| `model_file`    | STRING          | The generated 3D model file (for backward compatibility only) |
| `model task_id` | MODEL\_TASK\_ID | The task ID for tracking the model generation process         |
| `GLB`           | FILE3DGLB       | The generated 3D model in GLB format                          |

***

**Source fingerprint (SHA-256):** `f12bae7cc766b7ac208243a10970da7719a13d6283d6b6c39444b577cafc7f04`


# TripoMultiviewToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoMultiviewToModelNode

Complete documentation for the TripoMultiviewToModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoMultiviewToModelNode/en.md)

This node generates 3D models synchronously using Tripo's API by processing up to four images showing different views of an object. It requires a front image and at least one additional view (left, back, or right) to create a complete 3D model with texture and material options.

## Inputs

| Parameter           | Data Type | Required | Range                                | Description                                                                          |
| ------------------- | --------- | -------- | ------------------------------------ | ------------------------------------------------------------------------------------ |
| `image`             | IMAGE     | Yes      | -                                    | Front view image of the object (required)                                            |
| `image_left`        | IMAGE     | No       | -                                    | Left view image of the object                                                        |
| `image_back`        | IMAGE     | No       | -                                    | Back view image of the object                                                        |
| `image_right`       | IMAGE     | No       | -                                    | Right view image of the object                                                       |
| `model_version`     | COMBO     | No       | Multiple options available           | The model version to use for generation                                              |
| `orientation`       | COMBO     | No       | Multiple options available           | Orientation setting for the 3D model (default: "default")                            |
| `texture`           | BOOLEAN   | No       | -                                    | Whether to generate textures for the model (default: True)                           |
| `pbr`               | BOOLEAN   | No       | -                                    | Whether to generate PBR (Physically Based Rendering) materials (default: True)       |
| `model_seed`        | INT       | No       | -                                    | Random seed for model generation (default: 42)                                       |
| `texture_seed`      | INT       | No       | -                                    | Random seed for texture generation (default: 42)                                     |
| `texture_quality`   | COMBO     | No       | `"standard"`<br />`"detailed"`       | Quality level for texture generation (default: "standard")                           |
| `texture_alignment` | COMBO     | No       | `"original_image"`<br />`"geometry"` | Method for aligning textures to the model (default: "original\_image")               |
| `face_limit`        | INT       | No       | -1 to 500000                         | Maximum number of faces in the generated model. Set to -1 for no limit (default: -1) |
| `quad`              | BOOLEAN   | No       | -                                    | This parameter is deprecated and does nothing (default: False)                       |
| `geometry_quality`  | COMBO     | No       | `"standard"`<br />`"detailed"`       | Quality level for geometry generation (default: "standard")                          |

**Note:** The front image (`image`) is always required. At least one additional view image (`image_left`, `image_back`, or `image_right`) must be provided for multiview processing.

## Outputs

| Output Name     | Data Type       | Description                                                                          |
| --------------- | --------------- | ------------------------------------------------------------------------------------ |
| `model_file`    | STRING          | File path or identifier for the generated 3D model (for backward compatibility only) |
| `model task_id` | MODEL\_TASK\_ID | Task identifier for tracking the model generation process                            |
| `GLB`           | FILE3DGLB       | The generated 3D model file in GLB format                                            |

***

**Source fingerprint (SHA-256):** `f44a39bd15dfd6111be191de81490136280491930ec0aa7159849f137479b089`


# TripoP1ImageToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoP1ImageToModelNode

Complete documentation for the TripoP1ImageToModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoP1ImageToModelNode/en.md)

## Overview

This node converts a single 2D image into a 3D model using the Tripo P1 API. It is optimized for generating low-polygon, game-ready meshes.

## Inputs

| Parameter              | Data Type | Required | Range           | Description                                                                                                                                                                                                                                                                                                                       |
| ---------------------- | --------- | -------- | --------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`                | IMAGE     | Yes      | -               | The input image to convert to a 3D model.                                                                                                                                                                                                                                                                                         |
| `output_mode`          | DICT      | Yes      | See description | A dictionary specifying the output mode and quality settings. This parameter controls the type of model generated and its texture quality. The available options are defined by the `_build_p1_output_mode` helper function and include settings for `texture_quality` (e.g., "standard", "high", "ultra") and `image_alignment`. |
| `enable_image_autofix` | BOOLEAN   | No       | True<br />False | Pre-process the input image for better generation quality. (default: False)                                                                                                                                                                                                                                                       |
| `face_limit`           | INT       | No       | -               | Limits the number of faces in the generated mesh. A value of -1 means no limit. (default: -1)                                                                                                                                                                                                                                     |
| `model_seed`           | INT       | No       | -               | A seed value for reproducible model generation. If not provided, a random seed is used. (default: None)                                                                                                                                                                                                                           |
| `auto_size`            | BOOLEAN   | No       | True<br />False | Automatically determine the optimal size for the generated model. (default: False)                                                                                                                                                                                                                                                |
| `export_uv`            | BOOLEAN   | No       | True<br />False | Export UV coordinates with the model. (default: True)                                                                                                                                                                                                                                                                             |
| `compress_geometry`    | BOOLEAN   | No       | True<br />False | Compress the geometry data to reduce file size. (default: False)                                                                                                                                                                                                                                                                  |

## Outputs

| Output Name     | Data Type       | Description                                                                                       |
| --------------- | --------------- | ------------------------------------------------------------------------------------------------- |
| `model_file`    | STRING          | The file path to the generated 3D model. This output is provided for backward compatibility only. |
| `model task_id` | MODEL\_TASK\_ID | The unique task ID for the model generation request.                                              |
| `GLB`           | FILE3DGLB       | The generated 3D model in GLB format.                                                             |

***

**Source fingerprint (SHA-256):** `2ac611603dd6eb88700a8105c19f97a8c4eefe5f4efb23d8854ccc27af590626`


# TripoP1MultiviewToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoP1MultiviewToModelNode

Complete documentation for the TripoP1MultiviewToModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoP1MultiviewToModelNode/en.md)

## Overview

This node generates a 3D model from 2 to 4 reference images of an object or character. You provide images from different angles (front, left, back, right), and the node creates a 3D mesh in GLB format. The front view is required, and you can optionally add any combination of the other three views for better results.

## Inputs

| Parameter           | Data Type | Required | Range                                            | Description                                                                                                                                                                                     |
| ------------------- | --------- | -------- | ------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`             | IMAGE     | Yes      | -                                                | Front view (0°). Required.                                                                                                                                                                      |
| `image_left`        | IMAGE     | No       | -                                                | Left view (90°), i.e. the subject's left side.                                                                                                                                                  |
| `image_back`        | IMAGE     | No       | -                                                | Back view (180°).                                                                                                                                                                               |
| `image_right`       | IMAGE     | No       | -                                                | Right view (270°), i.e. the subject's right side.                                                                                                                                               |
| `output_mode`       | COMBO     | Yes      | `"geometry"`<br />`"textured"`<br />`"detailed"` | The output mode for the generated model. `"geometry"` produces a raw mesh, `"textured"` adds a standard texture, and `"detailed"` creates a high-detail textured model (default: `"textured"`). |
| `face_limit`        | INT       | No       | -1 to 100000                                     | Maximum number of faces for the output mesh. Set to -1 for no limit (default: -1).                                                                                                              |
| `model_seed`        | INT       | No       | 0 to 2147483647                                  | Seed for reproducible model generation. Set to 0 for random (default: 0).                                                                                                                       |
| `auto_size`         | BOOLEAN   | No       | True / False                                     | Automatically size the model to fit within a standard bounding box (default: False).                                                                                                            |
| `export_uv`         | BOOLEAN   | No       | True / False                                     | Export UV coordinates with the model (default: True).                                                                                                                                           |
| `compress_geometry` | BOOLEAN   | No       | True / False                                     | Compress the geometry data to reduce file size (default: False).                                                                                                                                |

**Note:** You must provide at least 2 images: the front view (`image`) plus at least one of the other views (`image_left`, `image_back`, or `image_right`). If fewer than 2 images are provided, the node will raise an error.

## Outputs

| Output Name     | Data Type       | Description                                                                |
| --------------- | --------------- | -------------------------------------------------------------------------- |
| `model_file`    | STRING          | The filename of the generated GLB model (for backward compatibility only). |
| `model_task_id` | MODEL\_TASK\_ID | The unique task ID for this model generation request.                      |
| `GLB`           | FILE3DGLB       | The generated 3D model in GLB format.                                      |

***

**Source fingerprint (SHA-256):** `29bb87cdc5d3eef891a653c622e8876a37d6e6dc1a43e5c248b184060ead9029`


# TripoP1TextToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoP1TextToModelNode

Complete documentation for the TripoP1TextToModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoP1TextToModelNode/en.md)

## Overview

This node generates a 3D model from a text description using the Tripo P1 API. It is optimized for creating low-poly, game-ready meshes with stable topology, making it suitable for real-time applications.

## Inputs

| Parameter           | Data Type | Required | Range                 | Description                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      |
| ------------------- | --------- | -------- | --------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `prompt`            | STRING    | Yes      | Up to 1024 characters | The text description of the 3D model you want to generate.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
| `negative_prompt`   | STRING    | No       | Up to 255 characters  | A text description of what you do not want in the generated model.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
| `output_mode`       | DICT      | Yes      | See description       | Controls the output model's quality and texture settings. This parameter is a dictionary with the following keys:<br /><br />`texture_quality`: STRING, Range: `"standard"`<br />`pbr`: BOOLEAN, default: True<br />`texture`: BOOLEAN, default: True<br />`subdivision`: INT, default: 0, Range: 0 to 2<br />`texture_size`: INT, default: 2048, Range: 512 to 4096 (must be a power of 2)<br />`texture_format`: STRING, Range: `"png"`<br />`texture_clean`: BOOLEAN, default: False<br />`texture_seamless`: BOOLEAN, default: False<br /><br />Default: `{"texture_quality": "standard", "pbr": True, "texture": True, "subdivision": 0, "texture_size": 2048, "texture_format": "png", "texture_clean": False, "texture_seamless": False}` |
| `image_seed`        | INT       | No       |                       | A seed value for image generation, used to control randomness. Default: 42.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      |
| `face_limit`        | INT       | No       |                       | The maximum number of faces for the generated mesh. A value of -1 means no limit. Default: -1.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
| `model_seed`        | INT       | No       |                       | A seed value for model generation, used to control randomness.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
| `auto_size`         | BOOLEAN   | No       |                       | If enabled, the node will automatically determine the optimal model size. Default: False.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
| `export_uv`         | BOOLEAN   | No       |                       | If enabled, the model will include UV coordinates for texture mapping. Default: True.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| `compress_geometry` | BOOLEAN   | No       |                       | If enabled, the geometry will be compressed to reduce file size. Default: False.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |

## Outputs

| Output Name     | Data Type       | Description                                                                |
| --------------- | --------------- | -------------------------------------------------------------------------- |
| `model_file`    | STRING          | The file path to the generated 3D model (for backward compatibility only). |
| `model task_id` | MODEL\_TASK\_ID | The unique task ID for the model generation request.                       |
| `GLB`           | FILE3DGLB       | The generated 3D model in GLB format.                                      |

***

**Source fingerprint (SHA-256):** `154e75209d65c823d5681b74cd12fe7b2ed37d7b94bf51cac86f343c68f85722`


# TripoRefineNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoRefineNode

Complete documentation for the TripoRefineNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoRefineNode/en.md)

The TripoRefineNode refines draft 3D models created specifically by Tripo v1.4 models. It takes a model task ID and processes it through the Tripo API to generate an improved version of the model. This node is designed to work exclusively with draft models produced by Tripo v1.4 models.

## Inputs

| Parameter       | Data Type       | Required | Range | Description                |
| --------------- | --------------- | -------- | ----- | -------------------------- |
| `model_task_id` | MODEL\_TASK\_ID | Yes      | -     | Must be a v1.4 Tripo model |

**Note:** This node only accepts draft models created by Tripo v1.4 models. Using models from other versions may result in errors.

## Outputs

| Output Name     | Data Type       | Description                                                                       |
| --------------- | --------------- | --------------------------------------------------------------------------------- |
| `model_file`    | STRING          | The file path or reference to the refined model (for backward compatibility only) |
| `model task_id` | MODEL\_TASK\_ID | The task identifier for the refined model operation                               |
| `GLB`           | FILE3DGLB       | The refined 3D model in GLB format                                                |

***

**Source fingerprint (SHA-256):** `bb4b17652fd05c489e6151f23461fa79ae090f3b59491775768b32ca2b61d33c`


# TripoRetargetNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoRetargetNode

Complete documentation for the TripoRetargetNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoRetargetNode/en.md)

The TripoRetargetNode applies predefined animations to 3D character models by retargeting motion data. It takes a previously rigged 3D model and applies one of several preset animations, generating an animated 3D model file as output. The node communicates with the Tripo API to process the animation retargeting operation.

## Inputs

| Parameter                | Data Type               | Required | Range                                                                                                                                                                                                                                                                                                                                                       | Description                                                                                                                                                                                                                                                    |
| ------------------------ | ----------------------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `original_model_task_id` | RIG\_TASK\_ID           | Yes      | -                                                                                                                                                                                                                                                                                                                                                           | The task ID of the previously processed rigged 3D model to apply animation to                                                                                                                                                                                  |
| `animation`              | STRING                  | Yes      | "preset:idle"<br />"preset:walk"<br />"preset:run"<br />"preset:dive"<br />"preset:climb"<br />"preset:jump"<br />"preset:slash"<br />"preset:shoot"<br />"preset:hurt"<br />"preset:fall"<br />"preset:turn"<br />"preset:quadruped:walk"<br />"preset:hexapod:walk"<br />"preset:octopod:walk"<br />"preset:serpentine:march"<br />"preset:aquatic:march" | The animation preset to apply to the 3D model. Options include humanoid animations (idle, walk, run, dive, climb, jump, slash, shoot, hurt, fall, turn) and creature animations (quadruped walk, hexapod walk, octopod walk, serpentine march, aquatic march). |
| `auth_token_comfy_org`   | AUTH\_TOKEN\_COMFY\_ORG | No       | -                                                                                                                                                                                                                                                                                                                                                           | Authentication token for Comfy.org API access (hidden parameter)                                                                                                                                                                                               |
| `api_key_comfy_org`      | API\_KEY\_COMFY\_ORG    | No       | -                                                                                                                                                                                                                                                                                                                                                           | API key for Comfy.org service access (hidden parameter)                                                                                                                                                                                                        |
| `unique_id`              | UNIQUE\_ID              | No       | -                                                                                                                                                                                                                                                                                                                                                           | Unique identifier for tracking the operation (hidden parameter)                                                                                                                                                                                                |

## Outputs

| Output Name        | Data Type          | Description                                                            |
| ------------------ | ------------------ | ---------------------------------------------------------------------- |
| `model_file`       | STRING             | The generated animated 3D model file (for backward compatibility only) |
| `retarget task_id` | RETARGET\_TASK\_ID | The task ID for tracking the retargeting operation                     |
| `GLB`              | FILE3DGLB          | The animated 3D model in GLB format                                    |

***

**Source fingerprint (SHA-256):** `31d90c0a11a6a57fbc55f2c3b8e0e8e73943f048734e5f2d68711bf000730e0b`


# TripoRigNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoRigNode

Complete documentation for the TripoRigNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoRigNode/en.md)

The TripoRigNode generates a rigged 3D model from an original model task ID. It sends a request to the Tripo API to create an animated rig in GLB format using the Tripo specification, then polls the API until the rig generation task is complete.

## Inputs

| Parameter                | Data Type       | Required | Range | Description                                       |
| ------------------------ | --------------- | -------- | ----- | ------------------------------------------------- |
| `original_model_task_id` | MODEL\_TASK\_ID | Yes      | -     | The task ID of the original 3D model to be rigged |

## Outputs

| Output Name   | Data Type     | Description                                                          |
| ------------- | ------------- | -------------------------------------------------------------------- |
| `model_file`  | STRING        | The generated rigged 3D model file (kept for backward compatibility) |
| `rig task_id` | RIG\_TASK\_ID | The task ID for tracking the rig generation process                  |
| `GLB`         | FILE3DGLB     | The generated rigged 3D model in GLB format                          |

***

**Source fingerprint (SHA-256):** `c00053314112cf1a403d7bf1cf77dcb6cede6b4db83046d459069f2b57bb6de9`


# TripoTextToModelNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoTextToModelNode

Complete documentation for the TripoTextToModelNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoTextToModelNode/en.md)

Generates 3D models synchronously based on a text prompt using Tripo's API. This node takes a text description and creates a 3D model with optional texture and material properties.

## Inputs

| Parameter          | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                               | Description                                                                    |
| ------------------ | --------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------ |
| `prompt`           | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                                                   | Text description for generating the 3D model (multiline input)                 |
| `negative_prompt`  | STRING    | No       | -                                                                                                                                                                                                                                                                                                                                                   | Text description of what to avoid in the generated model (multiline input)     |
| `model_version`    | COMBO     | No       | `v1.4`<br />`v2.0`<br />`v2.5-20250123`<br />`v3.0`                                                                                                                                                                                                                                                                                                 | The version of the Tripo model to use for generation (default: v2.5-20250123)  |
| `style`            | COMBO     | No       | `None`<br />`sculpture`<br />`low-poly`<br />`voxel`<br />`brick`<br />`clay`<br />`marble`<br />`origami`<br />`papercraft`<br />`pixel-art`<br />`tile`<br />`cartoon`<br />`fantasy`<br />`hand-drawn`<br />`illustration`<br />`isometric`<br />`pixel-art`<br />`sketch`<br />`stained-glass`<br />`steampunk`<br />`vector`<br />`watercolor` | Style setting for the generated model (default: "None")                        |
| `texture`          | BOOLEAN   | No       | -                                                                                                                                                                                                                                                                                                                                                   | Whether to generate textures for the model (default: True)                     |
| `pbr`              | BOOLEAN   | No       | -                                                                                                                                                                                                                                                                                                                                                   | Whether to generate PBR (Physically Based Rendering) materials (default: True) |
| `image_seed`       | INT       | No       | -                                                                                                                                                                                                                                                                                                                                                   | Random seed for image generation (default: 42)                                 |
| `model_seed`       | INT       | No       | -                                                                                                                                                                                                                                                                                                                                                   | Random seed for model generation (default: 42)                                 |
| `texture_seed`     | INT       | No       | -                                                                                                                                                                                                                                                                                                                                                   | Random seed for texture generation (default: 42)                               |
| `texture_quality`  | COMBO     | No       | `standard`<br />`detailed`                                                                                                                                                                                                                                                                                                                          | Quality level for texture generation (default: "standard")                     |
| `face_limit`       | INT       | No       | -1 to 2000000                                                                                                                                                                                                                                                                                                                                       | Maximum number of faces in the generated model, -1 for no limit (default: -1)  |
| `quad`             | BOOLEAN   | No       | -                                                                                                                                                                                                                                                                                                                                                   | Whether to generate quad-based geometry instead of triangles (default: False)  |
| `geometry_quality` | COMBO     | No       | `standard`<br />`detailed`                                                                                                                                                                                                                                                                                                                          | Quality level for geometry generation (default: "standard")                    |

**Note:** The `prompt` parameter is required and cannot be empty. If no prompt is provided, the node will raise an error.

## Outputs

| Output Name     | Data Type       | Description                                                   |
| --------------- | --------------- | ------------------------------------------------------------- |
| `model_file`    | STRING          | The generated 3D model file (for backward compatibility only) |
| `model task_id` | MODEL\_TASK\_ID | The unique task identifier for the model generation process   |
| `GLB`           | FILE3DGLB       | The generated 3D model in GLB format                          |

***

**Source fingerprint (SHA-256):** `6cd6fefff0fbda14729b68383209eded6eb2e779ccf39dd2e03c0ddf04859372`


# TripoTextureNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TripoTextureNode

Complete documentation for the TripoTextureNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TripoTextureNode/en.md)

The TripoTextureNode generates textured 3D models using the Tripo API. It takes a model task ID and applies texture generation with various options including PBR materials, texture quality settings, and alignment methods. The node communicates with the Tripo API to process the texture generation request and returns the resulting model file and task ID.

## Inputs

| Parameter           | Data Type       | Required | Range                             | Description                                                                                                                                                                |
| ------------------- | --------------- | -------- | --------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model_task_id`     | MODEL\_TASK\_ID | Yes      | -                                 | The task ID of the model to apply textures to                                                                                                                              |
| `texture`           | BOOLEAN         | No       | -                                 | Whether to generate textures (default: True)                                                                                                                               |
| `pbr`               | BOOLEAN         | No       | -                                 | Whether to generate PBR (Physically Based Rendering) materials (default: True)                                                                                             |
| `texture_seed`      | INT             | No       | -                                 | Random seed for texture generation (default: 42)                                                                                                                           |
| `texture_quality`   | COMBO           | No       | "standard"<br />"detailed"        | Quality level for texture generation (default: "standard"). The "detailed" option costs $0.20 USD, while "standard" costs $0.10 USD.                                       |
| `texture_alignment` | COMBO           | No       | "original\_image"<br />"geometry" | Method for aligning textures (default: "original\_image"). "original\_image" aligns textures to the original input image, while "geometry" aligns them to the 3D geometry. |

*Note: This node requires authentication tokens and API keys which are automatically handled by the system.*

## Outputs

| Output Name     | Data Type       | Description                                                                      |
| --------------- | --------------- | -------------------------------------------------------------------------------- |
| `model_file`    | STRING          | The generated model file with applied textures (for backward compatibility only) |
| `model task_id` | MODEL\_TASK\_ID | The task ID for tracking the texture generation process                          |
| `GLB`           | FILE3DGLB       | The generated 3D model in GLB format with applied textures                       |

***

**Source fingerprint (SHA-256):** `dca49933b1b892df38004adc34ab0d95cdcb32d3e38db0e66b260ab7a58dcea5`


# UNETLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/UNETLoader

Complete documentation for the UNETLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The UNETLoader node is designed for loading U-Net models by name, facilitating the use of pre-trained U-Net architectures within the system.

This node will detect models located in the `ComfyUI/models/diffusion_models` folder.

## Inputs

| Parameter      | Data Type      | Description                                                                                                                                                                                |
| -------------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `unet_name`    | COMBO\[STRING] | Specifies the name of the U-Net model to be loaded. This name is used to locate the model within a predefined directory structure, enabling the dynamic loading of different U-Net models. |
| `weight_dtype` | ...            | 🚧  fp8\_e4m3fn fp9\_e5m2                                                                                                                                                                  |

## Outputs

| Parameter | Data Type | Description                                                                                                       |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | Returns the loaded U-Net model, allowing it to be utilized for further processing or inference within the system. |


# VoxelToMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VoxelToMesh

Complete documentation for the VoxelToMesh node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VoxelToMesh/en.md)

The VoxelToMesh node converts 3D voxel data into a mesh geometry by extracting a surface at a specified threshold value. It offers two algorithms for surface extraction: a basic method that creates simple box-like faces, and a surface net method that produces smoother, more detailed meshes. The node processes each voxel grid in the input and generates vertices and faces that form a 3D mesh representation.

## Inputs

| Parameter   | Data Type | Required | Range                          | Description                                                                                                                                             |
| ----------- | --------- | -------- | ------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `voxel`     | VOXEL     | Yes      | -                              | The input voxel data to convert to mesh geometry                                                                                                        |
| `algorithm` | COMBO     | Yes      | `"surface net"`<br />`"basic"` | The algorithm used for surface extraction. "surface net" produces smoother meshes, while "basic" creates simple box-like faces (default: "surface net") |
| `threshold` | FLOAT     | Yes      | -1.0 to 1.0                    | The threshold value for surface extraction. Voxels with values above this threshold are considered solid (default: 0.6)                                 |

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                                             |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `MESH`      | MESH      | The generated 3D mesh containing vertices and faces from all input voxel grids. If all voxel grids produce meshes with identical shapes, the output is a stacked tensor; otherwise, a variable-length batch is returned |

***

**Source fingerprint (SHA-256):** `b600be13f1a484d8c0cc1f9c3918630d00c15d35008bcac0f677b21ef64b5d98`


# VoxelToMeshBasic - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VoxelToMeshBasic

Complete documentation for the VoxelToMeshBasic node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VoxelToMeshBasic/en.md)

The VoxelToMeshBasic node converts 3D voxel data into mesh geometry. It processes voxel volumes by applying a threshold value to determine which parts of the volume become solid surfaces in the resulting mesh. The node outputs a complete mesh structure with vertices and faces that can be used for 3D rendering and modeling.

## Inputs

| Parameter   | Data Type | Required | Range       | Description                                                                                       |
| ----------- | --------- | -------- | ----------- | ------------------------------------------------------------------------------------------------- |
| `voxel`     | VOXEL     | Yes      | -           | The 3D voxel data to convert into a mesh                                                          |
| `threshold` | FLOAT     | Yes      | -1.0 to 1.0 | The threshold value used to determine which voxels become part of the mesh surface (default: 0.6) |

## Outputs

| Output Name | Data Type | Description                                         |
| ----------- | --------- | --------------------------------------------------- |
| `MESH`      | MESH      | The generated 3D mesh containing vertices and faces |

***

**Source fingerprint (SHA-256):** `95d729463e9d32fb0b8a82a397c6ed7fccaf190ec8a183d71a99fef170747fd1`


# ZImageFunControlnet - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ZImageFunControlnet

Complete documentation for the ZImageFunControlnet node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ZImageFunControlnet/en.md)

The ZImageFunControlnet node applies a specialized control network to influence the image generation or editing process. It uses a base model, a model patch, and a VAE, allowing you to adjust the strength of the control effect. This node can work with a base image, an inpainting image, and a mask for more targeted edits.

## Inputs

| Parameter       | Data Type    | Required | Range         | Description                                                                                                                            |
| --------------- | ------------ | -------- | ------------- | -------------------------------------------------------------------------------------------------------------------------------------- |
| `model`         | MODEL        | Yes      | -             | The base model used for the generation process.                                                                                        |
| `model_patch`   | MODEL\_PATCH | Yes      | -             | A specialized patch model that applies the control network's guidance.                                                                 |
| `vae`           | VAE          | Yes      | -             | The Variational Autoencoder used for encoding and decoding images.                                                                     |
| `strength`      | FLOAT        | Yes      | -10.0 to 10.0 | The strength of the control network's influence. Positive values apply the effect, while negative values can invert it (default: 1.0). |
| `image`         | IMAGE        | No       | -             | An optional base image to guide the generation process.                                                                                |
| `inpaint_image` | IMAGE        | No       | -             | An optional image used specifically for inpainting areas defined by a mask.                                                            |
| `mask`          | MASK         | No       | -             | An optional mask that defines which areas of an image should be edited or inpainted.                                                   |

**Note:** The `inpaint_image` parameter is typically used in conjunction with a `mask` to specify the content for inpainting. The node's behavior may change based on which optional inputs are provided (e.g., using `image` for guidance or using `image`, `mask`, and `inpaint_image` for inpainting).

## Outputs

| Output Name | Data Type    | Description                                                                             |
| ----------- | ------------ | --------------------------------------------------------------------------------------- |
| `model`     | MODEL        | The model with the control network patch applied, ready for use in a sampling pipeline. |
| `positive`  | CONDITIONING | The positive conditioning, potentially modified by the control network inputs.          |
| `negative`  | CONDITIONING | The negative conditioning, potentially modified by the control network inputs.          |

***

**Source fingerprint (SHA-256):** `465f9eb0dd60af23e6cdc2031579e404b4fed021738e592ee6acbb6ee57e83a0`


# ByteDanceImageEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceImageEditNode

Complete documentation for the ByteDanceImageEditNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceImageEditNode/en.md)

The ByteDance Image Edit node allows you to modify images using ByteDance's AI models through an API. You provide an input image and a text prompt describing the desired changes, and the node processes the image according to your instructions. The node handles the API communication automatically and returns the edited image.

## Inputs

| Parameter        | Data Type | Input Type | Default     | Range                        | Description                                                 |
| ---------------- | --------- | ---------- | ----------- | ---------------------------- | ----------------------------------------------------------- |
| `model`          | MODEL     | COMBO      | seededit\_3 | Image2ImageModelName options | Model name                                                  |
| `image`          | IMAGE     | IMAGE      | -           | -                            | The base image to edit                                      |
| `prompt`         | STRING    | STRING     | ""          | -                            | Instruction to edit image                                   |
| `seed`           | INT       | INT        | 0           | 0-2147483647                 | Seed to use for generation                                  |
| `guidance_scale` | FLOAT     | FLOAT      | 5.5         | 1.0-10.0                     | Higher value makes the image follow the prompt more closely |
| `watermark`      | BOOLEAN   | BOOLEAN    | True        | -                            | Whether to add an "AI generated" watermark to the image     |

## Outputs

| Output Name | Data Type | Description                                      |
| ----------- | --------- | ------------------------------------------------ |
| `IMAGE`     | IMAGE     | The edited image returned from the ByteDance API |

***

**Source fingerprint (SHA-256):** `9dc13d89f84756b545120efb5535e08ada163d4534975809f5056bdf7d8bfb73`


# CLIPMergeAdd - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPMergeAdd

Complete documentation for the CLIPMergeAdd node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPMergeAdd/en.md)

The CLIPMergeAdd node combines two CLIP models by adding patches from the second model to the first model. It creates a copy of the first CLIP model and selectively incorporates key patches from the second model, excluding position IDs and logit scale parameters. This allows you to merge CLIP model components while preserving the structure of the base model.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                      |
| --------- | --------- | -------- | ----- | -------------------------------------------------------------------------------- |
| `clip1`   | CLIP      | Yes      | -     | The base CLIP model that will be cloned and used as the foundation for merging   |
| `clip2`   | CLIP      | Yes      | -     | The secondary CLIP model that provides key patches to be added to the base model |

## Outputs

| Output Name | Data Type | Description                                                                                         |
| ----------- | --------- | --------------------------------------------------------------------------------------------------- |
| `CLIP`      | CLIP      | A merged CLIP model containing the base model structure with added patches from the secondary model |

***

**Source fingerprint (SHA-256):** `f212c2750f317ad51516a10a1a03a838b75bc878333381348d5eb388a2faf516`


# CLIPMergeSubtract - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPMergeSubtract

Complete documentation for the CLIPMergeSubtract node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPMergeSubtract/en.md)

The CLIPMergeSubtract node performs model merging by subtracting the weights of one CLIP model from another. It creates a new CLIP model by cloning the first model and then subtracting the key patches from the second model, with an adjustable multiplier to control the subtraction strength. This allows for fine-tuned model blending by removing specific characteristics from the base model.

## Inputs

| Parameter    | Data Type | Required | Range         | Description                                                             |
| ------------ | --------- | -------- | ------------- | ----------------------------------------------------------------------- |
| `clip1`      | CLIP      | Yes      | -             | The base CLIP model that will be cloned and modified                    |
| `clip2`      | CLIP      | Yes      | -             | The CLIP model whose key patches will be subtracted from the base model |
| `multiplier` | FLOAT     | Yes      | -10.0 to 10.0 | Controls the strength of the subtraction operation (default: 1.0)       |

**Note:** The node excludes `.position_ids` and `.logit_scale` parameters from the subtraction operation, regardless of the multiplier value.

## Outputs

| Output Name | Data Type | Description                                                                          |
| ----------- | --------- | ------------------------------------------------------------------------------------ |
| `clip`      | CLIP      | The resulting CLIP model after subtracting the second model's weights from the first |

***

**Source fingerprint (SHA-256):** `3136cf509fcbfa291af8f820928a6cc14de7a586f953af0ada9bea949b437d86`


# CheckpointSave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CheckpointSave

Complete documentation for the CheckpointSave node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `Save Checkpoint` node is designed to save a complete Stable Diffusion model (including UNet, CLIP, and VAE components) as a **.safetensors** format checkpoint file.

The Save Checkpoint is primarily used in model merging workflows. After creating a new merged model through nodes like `ModelMergeSimple`, `ModelMergeBlocks`, etc., you can use this node to save the result as a reusable checkpoint file.

## Inputs

| Parameter         | Data Type | Description                                                                                                                                                                   |
| ----------------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`           | MODEL     | The model parameter represents the primary model whose state is to be saved. It is essential for capturing the current state of the model for future restoration or analysis. |
| `clip`            | CLIP      | The clip parameter is intended for the CLIP model associated with the primary model, allowing its state to be saved alongside the main model.                                 |
| `vae`             | VAE       | The vae parameter is for the Variational Autoencoder (VAE) model, enabling its state to be saved for future use or analysis alongside the main model and CLIP.                |
| `filename_prefix` | STRING    | This parameter specifies the prefix for the filename under which the checkpoint will be saved.                                                                                |

Additionally, the node has two hidden inputs for metadata:

**prompt (PROMPT)**: Workflow prompt information
**extra\_pnginfo (EXTRA\_PNGINFO)**: Additional PNG information

## Outputs

This node will output a checkpoint file, and the corresponding output file path is `output/checkpoints/` directory

## Architecture Compatibility

* Currently fully supported: SDXL, SD3, SVD and other mainstream architectures, see [source code](https://github.com/comfyanonymous/ComfyUI/blob/master/comfy_extras/nodes_model_merging.py#L176-L189)
* Basic support: Other architectures can be saved but without standardized metadata information

## Related Links

Related source code: [nodes\_model\_merging.py#L227](https://github.com/comfyanonymous/ComfyUI/blob/master/comfy_extras/nodes_model_merging.py#L227)


# CLIPMergeSimple - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipMergeSimple

Complete documentation for the CLIPMergeSimple node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPMergeSimple/en.md)

`CLIPMergeSimple` is an advanced model merging node used to combine two CLIP text encoder models based on a specified ratio.

This node specializes in merging two CLIP models based on a specified ratio, effectively blending their characteristics. It selectively applies patches from one model to another, excluding specific components like position IDs and logit scale, to create a hybrid model that combines features from both source models.

## Inputs

| Parameter | Data Type | Input Type | Default | Range                  | Description                                                                                                                                                                                                    |
| --------- | --------- | ---------- | ------- | ---------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip1`   | CLIP      | REQUIRED   | -       | -                      | The first CLIP model to be merged. It serves as the base model for the merging process.                                                                                                                        |
| `clip2`   | CLIP      | REQUIRED   | -       | -                      | The second CLIP model to be merged. Its key patches, except for position IDs and logit scale, are applied to the first model based on the specified ratio.                                                     |
| `ratio`   | FLOAT     | REQUIRED   | 1.0     | 0.0 - 1.0 (step: 0.01) | Determines the proportion of features from the second model to blend into the first model. A ratio of 1.0 means fully adopting the second model's features, while 0.0 retains only the first model's features. |

## Outputs

| Output Name | Data Type | Description                                                                                                      |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------- |
| `clip`      | CLIP      | The resulting merged CLIP model, incorporating features from both input models according to the specified ratio. |

## Merging Mechanism Explained

### Merging Algorithm

The node uses weighted averaging to merge the two models:

1. **Clone Base Model**: First clones `clip1` as the base model
2. **Get Patches**: Obtains all key patches from `clip2`
3. **Filter Special Keys**: Skips keys ending with `.position_ids` and `.logit_scale`
4. **Apply Weighted Merge**: Uses the formula `(1.0 - ratio) * clip1 + ratio * clip2`

### Ratio Parameter Explained

* **ratio = 0.0**: Fully uses clip1, ignores clip2
* **ratio = 0.5**: 50% contribution from each model
* **ratio = 1.0**: Fully uses clip2, ignores clip1

## Use Cases

1. **Model Style Fusion**: Combine characteristics of CLIP models trained on different data
2. **Performance Optimization**: Balance strengths and weaknesses of different models
3. **Experimental Research**: Explore combinations of different CLIP encoders

***

**Source fingerprint (SHA-256):** `0d3c8388dbe88675ea7fb51161ab41ce898bcf63983b3d2817b16ec5bfa613e5`


# CLIPSave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipSave

Complete documentation for the CLIPSave node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPSave/en.md)

The `CLIPSave` node saves a CLIP text encoder model to disk in SafeTensors format. It is designed for advanced model merging workflows and automatically separates the CLIP model into its component parts (such as CLIP-L, CLIP-G, or T5XXL) based on the model's internal structure, saving each component as a separate file.

## Inputs

| Parameter         | Data Type      | Required | Range | Description                                                                                                                                                                                  |
| ----------------- | -------------- | -------- | ----- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip`            | CLIP           | Yes      | -     | The CLIP model to be saved.                                                                                                                                                                  |
| `filename_prefix` | STRING         | Yes      | -     | The prefix path and filename for the saved file(s). The node will append a component suffix (e.g., `_clip_l`, `_clip_g`) and a counter to create unique filenames (default: `clip/ComfyUI`). |
| `prompt`          | PROMPT         | No       | -     | The workflow prompt information, saved as metadata in the output file. This parameter is hidden in the UI.                                                                                   |
| `extra_pnginfo`   | EXTRA\_PNGINFO | No       | -     | Additional metadata, saved as key-value pairs in the output file. This parameter is hidden in the UI.                                                                                        |

## Outputs

This node has no output connections. It saves the processed files directly to the `ComfyUI/output/` directory.

### Saved File Details

The node analyzes the CLIP model's state dictionary and saves separate SafeTensors files for each detected component. The component is identified by the prefix of its parameter keys. The following prefixes are checked:

* `clip_l.` (CLIP-L text encoder)
* `clip_g.` (CLIP-G text encoder)
* `clip_h.` (CLIP-H text encoder)
* `t5xxl.` (T5-XXL text encoder)
* `pile_t5xl.` (Pile-T5-XL text encoder)
* `mt5xl.` (mT5-XL text encoder)
* `umt5xxl.` (UMT5-XXL text encoder)
* `t5base.` (T5-Base text encoder)
* `gemma2_2b.` (Gemma 2 2B text encoder)
* `llama.` (LLaMA text encoder)
* `hydit_clip.` (Hydit CLIP text encoder)
* Empty prefix (other CLIP components)

For each detected component, the node creates a file with the name `{filename_prefix}_{counter:05}_.safetensors`, where the component prefix is appended to the filename prefix (e.g., `clip/ComfyUI_clip_l_00001_.safetensors`). The `transformer.` prefix is removed from parameter keys during saving.

***

**Source fingerprint (SHA-256):** `65a5856b0cbf8765b380887741d52af8ad50d2d5d36145c994a8cbf93ebc9807`


# ElevenLabsAudioIsolation - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsAudioIsolation

Complete documentation for the ElevenLabsAudioIsolation node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsAudioIsolation/en.md)

The ElevenLabs Voice Isolation node removes background noise from an audio file, isolating the vocals or speech. It sends the audio to the ElevenLabs API for processing and returns the cleaned audio.

## Inputs

| Parameter | Data Type | Required | Range | Description                                    |
| --------- | --------- | -------- | ----- | ---------------------------------------------- |
| `audio`   | AUDIO     | Yes      |       | Audio to process for background noise removal. |

## Outputs

| Output Name | Data Type | Description                                        |
| ----------- | --------- | -------------------------------------------------- |
| `audio`     | AUDIO     | The processed audio with background noise removed. |

***

**Source fingerprint (SHA-256):** `84f1ea16911b9b1d1ab60dd75fade8cc524ac3e39d44f60a242214f14006ff1e`


# ElevenLabsInstantVoiceClone - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsInstantVoiceClone

Complete documentation for the ElevenLabsInstantVoiceClone node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsInstantVoiceClone/en.md)

The ElevenLabs Instant Voice Clone node creates a new, unique voice model by analyzing 1 to 8 audio recordings of a person's voice. It sends these samples to the ElevenLabs API, which processes them to generate a voice clone that can be used for text-to-speech synthesis.

## Inputs

| Parameter                 | Data Type | Required | Range        | Description                                                                        |
| ------------------------- | --------- | -------- | ------------ | ---------------------------------------------------------------------------------- |
| `audio_*`                 | AUDIO     | Yes      | 1 to 8 files | Audio recordings for voice cloning. You must provide between 1 and 8 audio files.  |
| `remove_background_noise` | BOOLEAN   | No       | True / False | Remove background noise from voice samples using audio isolation. (default: False) |

**Note:** You must provide at least one audio file, and you can provide up to eight. The node will automatically create input slots for the audio files you add.

## Outputs

| Output Name | Data Type         | Description                                                                                                                            |
| ----------- | ----------------- | -------------------------------------------------------------------------------------------------------------------------------------- |
| `voice`     | ELEVENLABS\_VOICE | The unique identifier for the newly created cloned voice model. This output can be connected to other ElevenLabs text-to-speech nodes. |

***

**Source fingerprint (SHA-256):** `760bd99ed8382eb875ab21739346d178130b02240526308b784332a59b048d78`


# ElevenLabsSpeechToSpeech - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsSpeechToSpeech

Complete documentation for the ElevenLabsSpeechToSpeech node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsSpeechToSpeech/en.md)

The ElevenLabs Speech to Speech node transforms an input audio file from one voice to another. It uses the ElevenLabs API to convert speech while preserving the original content and emotional tone of the audio.

## Inputs

| Parameter                 | Data Type    | Required | Range                                                     | Description                                                                                                                                                     |
| ------------------------- | ------------ | -------- | --------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `voice`                   | CUSTOM       | Yes      | -                                                         | Target voice for the transformation. Connect from Voice Selector or Instant Voice Clone.                                                                        |
| `audio`                   | AUDIO        | Yes      | -                                                         | Source audio to transform.                                                                                                                                      |
| `stability`               | FLOAT        | No       | 0.0 - 1.0                                                 | Voice stability. Lower values give broader emotional range, higher values produce more consistent but potentially monotonous speech (default: 0.5).             |
| `model`                   | DYNAMICCOMBO | No       | `eleven_multilingual_sts_v2`<br />`eleven_english_sts_v2` | Model to use for speech-to-speech transformation. Each option provides a specific set of voice settings (similarity\_boost, style, use\_speaker\_boost, speed). |
| `output_format`           | COMBO        | No       | `"mp3_44100_192"`<br />`"opus_48000_192"`                 | Audio output format (default: "mp3\_44100\_192").                                                                                                               |
| `seed`                    | INT          | No       | 0 - 4294967295                                            | Seed for reproducibility (default: 0).                                                                                                                          |
| `remove_background_noise` | BOOLEAN      | No       | -                                                         | Remove background noise from input audio using audio isolation (default: False).                                                                                |

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `audio`     | AUDIO     | The transformed audio file in the specified output format. |

***

**Source fingerprint (SHA-256):** `ef065ffa78a63398e746b52c6c8f2c336e6a4137722537c8026d292ed397a246`


# ElevenLabsSpeechToText - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsSpeechToText

Complete documentation for the ElevenLabsSpeechToText node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsSpeechToText/en.md)

The ElevenLabs Speech to Text node transcribes audio files into text. It uses ElevenLabs' API to convert spoken words into a written transcript, supporting features like automatic language detection, identifying different speakers, and tagging non-speech sounds like music or laughter.

## Inputs

| Parameter                | Data Type | Required | Range                                     | Description                                                                                                                                                                                       |
| ------------------------ | --------- | -------- | ----------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `audio`                  | AUDIO     | Yes      | -                                         | Audio to transcribe.                                                                                                                                                                              |
| `model`                  | COMBO     | Yes      | `"scribe_v2"`                             | Model to use for transcription. Selecting this model reveals additional parameters.                                                                                                               |
| `tag_audio_events`       | BOOLEAN   | No       | -                                         | Annotate sounds like (laughter), (music), etc. in transcript. This parameter is revealed when the `"scribe_v2"` model is selected. (default: False)                                               |
| `diarize`                | BOOLEAN   | No       | -                                         | Annotate which speaker is talking. This parameter is revealed when the `"scribe_v2"` model is selected. (default: False)                                                                          |
| `diarization_threshold`  | FLOAT     | No       | 0.1 - 0.4                                 | Speaker separation sensitivity. Lower values are more sensitive to speaker changes. This parameter is revealed when the `"scribe_v2"` model is selected and `diarize` is enabled. (default: 0.22) |
| `temperature`            | FLOAT     | No       | 0.0 - 2.0                                 | Randomness control. 0.0 uses model default. Higher values increase randomness. This parameter is revealed when the `"scribe_v2"` model is selected. (default: 0.0)                                |
| `timestamps_granularity` | COMBO     | No       | `"word"`<br />`"character"`<br />`"none"` | Timing precision for transcript words. This parameter is revealed when the `"scribe_v2"` model is selected. (default: "word")                                                                     |
| `language_code`          | STRING    | No       | -                                         | ISO-639-1 or ISO-639-3 language code (e.g., 'en', 'es', 'fra'). Leave empty for automatic detection. (default: "")                                                                                |
| `num_speakers`           | INT       | No       | 0 - 32                                    | Maximum number of speakers to predict. Set to 0 for automatic detection. (default: 0)                                                                                                             |
| `seed`                   | INT       | No       | 0 - 2147483647                            | Seed for reproducibility (determinism not guaranteed). (default: 1)                                                                                                                               |

**Note:** The `num_speakers` parameter cannot be set to a value greater than 0 when the `diarize` option is enabled. You must either disable `diarize` or set `num_speakers` to 0.

## Outputs

| Output Name     | Data Type | Description                                                                                                             |
| --------------- | --------- | ----------------------------------------------------------------------------------------------------------------------- |
| `text`          | STRING    | The transcribed text from the audio.                                                                                    |
| `language_code` | STRING    | The detected language code of the audio.                                                                                |
| `words_json`    | STRING    | A JSON-formatted string containing detailed word-level information, including timestamps and speaker labels if enabled. |

***

**Source fingerprint (SHA-256):** `1541ae5542b83d80cb96ab0c8694c25b2bd9d4f10c1030902064d05319b2a520`


# ElevenLabsTextToDialogue - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsTextToDialogue

Complete documentation for the ElevenLabsTextToDialogue node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsTextToDialogue/en.md)

The ElevenLabs Text to Dialogue node generates a multi-speaker audio dialogue from text. It allows you to create a conversation by specifying different text lines and distinct voices for each participant. The node sends the dialogue request to the ElevenLabs API and returns the generated audio.

## Inputs

| Parameter                  | Data Type    | Required | Range                                                                                                     | Description                                                                                                                                         |
| -------------------------- | ------------ | -------- | --------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- |
| `stability`                | FLOAT        | No       | 0.0 - 1.0                                                                                                 | Voice stability. Lower values give broader emotional range, higher values produce more consistent but potentially monotonous speech. (default: 0.5) |
| `apply_text_normalization` | COMBO        | No       | `"auto"`<br />`"on"`<br />`"off"`                                                                         | Text normalization mode. 'auto' lets the system decide, 'on' always applies normalization, 'off' skips it.                                          |
| `model`                    | COMBO        | No       | `"eleven_v3"`                                                                                             | Model to use for dialogue generation.                                                                                                               |
| `inputs`                   | DYNAMICCOMBO | Yes      | `"1"`<br />`"2"`<br />`"3"`<br />`"4"`<br />`"5"`<br />`"6"`<br />`"7"`<br />`"8"`<br />`"9"`<br />`"10"` | Number of dialogue entries. Selecting a number will generate that many text and voice input fields.                                                 |
| `language_code`            | STRING       | No       | -                                                                                                         | ISO-639-1 or ISO-639-3 language code (e.g., 'en', 'es', 'fra'). Leave empty for automatic detection. (default: empty)                               |
| `seed`                     | INT          | No       | 0 - 4294967295                                                                                            | Seed for reproducibility. (default: 1)                                                                                                              |
| `output_format`            | COMBO        | No       | `"mp3_44100_192"`<br />`"opus_48000_192"`                                                                 | Audio output format.                                                                                                                                |

**Note:** The `inputs` parameter is dynamic. When you select a number (e.g., "3"), the node will display three corresponding `text` and `voice` input fields (e.g., `text1`, `voice1`, `text2`, `voice2`, `text3`, `voice3`). Each `text` field must contain at least one character.

## Outputs

| Output Name | Data Type | Description                                                               |
| ----------- | --------- | ------------------------------------------------------------------------- |
| `audio`     | AUDIO     | The generated multi-speaker dialogue audio in the selected output format. |

***

**Source fingerprint (SHA-256):** `76eaa0ce55e1b542f4f2073405c707d686affd15202dc1adf1e1a81c542cbdb1`


# ElevenLabsTextToSoundEffects - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsTextToSoundEffects

Complete documentation for the ElevenLabsTextToSoundEffects node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsTextToSoundEffects/en.md)

The ElevenLabs Text to Sound Effects node generates audio sound effects from a text description. It uses the ElevenLabs API to create sound effects based on your prompt, allowing you to control the duration, looping behavior, and how closely the sound follows the text.

## Inputs

| Parameter       | Data Type | Required | Range                                     | Description                                                                                                                                                                                                                             |
| --------------- | --------- | -------- | ----------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `text`          | STRING    | Yes      | N/A                                       | Text description of the sound effect to generate. This is a required field.                                                                                                                                                             |
| `model`         | COMBO     | Yes      | `"eleven_sfx_v2"`                         | Model to use for sound effect generation. Selecting this model reveals additional parameters: `duration` (default: 5.0, range: 0.5 to 30.0 seconds), `loop` (default: False), and `prompt_influence` (default: 0.3, range: 0.0 to 1.0). |
| `output_format` | COMBO     | Yes      | `"mp3_44100_192"`<br />`"opus_48000_192"` | Audio output format.                                                                                                                                                                                                                    |

**Parameter Details:**

* **`model["duration"]`**: Duration of the generated sound in seconds. Default is 5.0, with a minimum of 0.5 and a maximum of 30.0.
* **`model["loop"]`**: When enabled, creates a smoothly looping sound effect. Default is False.
* **`model["prompt_influence"]`**: Controls how closely the generation follows the text prompt. Higher values make the sound follow the text more closely. Default is 0.3, with a range from 0.0 to 1.0.

## Outputs

| Output Name | Data Type | Description                            |
| ----------- | --------- | -------------------------------------- |
| `audio`     | AUDIO     | The generated sound effect audio file. |

***

**Source fingerprint (SHA-256):** `5868bfeb82c88b46587cbbce48266abd8b78ac05a24ae61a7c8dc978373c2c06`


# ElevenLabsTextToSpeech - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsTextToSpeech

Complete documentation for the ElevenLabsTextToSpeech node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsTextToSpeech/en.md)

The ElevenLabs Text to Speech node converts written text into spoken audio using the ElevenLabs API. It allows you to select a specific voice and fine-tune various speech characteristics like stability, speed, and style to generate a customized audio output.

## Inputs

| Parameter                  | Data Type    | Required | Range                                         | Description                                                                                                                                         |
| -------------------------- | ------------ | -------- | --------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- |
| `voice`                    | CUSTOM       | Yes      | N/A                                           | Voice to use for speech synthesis. Connect from Voice Selector or Instant Voice Clone.                                                              |
| `text`                     | STRING       | Yes      | N/A                                           | The text to convert to speech.                                                                                                                      |
| `stability`                | FLOAT        | No       | 0.0 - 1.0                                     | Voice stability. Lower values give broader emotional range, higher values produce more consistent but potentially monotonous speech (default: 0.5). |
| `apply_text_normalization` | COMBO        | No       | `"auto"`<br />`"on"`<br />`"off"`             | Text normalization mode. 'auto' lets the system decide, 'on' always applies normalization, 'off' skips it.                                          |
| `model`                    | DYNAMICCOMBO | No       | `"eleven_multilingual_v2"`<br />`"eleven_v3"` | Model to use for text-to-speech. Selecting a model reveals its specific parameters.                                                                 |
| `language_code`            | STRING       | No       | N/A                                           | ISO-639-1 or ISO-639-3 language code (e.g., 'en', 'es', 'fra'). Leave empty for automatic detection (default: "").                                  |
| `seed`                     | INT          | No       | 0 - 2147483647                                | Seed for reproducibility (determinism not guaranteed) (default: 1).                                                                                 |
| `output_format`            | COMBO        | No       | `"mp3_44100_192"`<br />`"opus_48000_192"`     | Audio output format.                                                                                                                                |

**Model-Specific Parameters:**
When the `model` parameter is set to `"eleven_multilingual_v2"`, the following additional parameters become available:

* `speed`: Speech speed. 1.0 is normal, \<1.0 slower, >1.0 faster (default: 1.0, range: 0.7 - 1.3).
* `similarity_boost`: Similarity boost. Higher values make the voice more similar to the original (default: 0.75, range: 0.0 - 1.0).
* `use_speaker_boost`: Boost similarity to the original speaker voice (default: False).
* `style`: Style exaggeration. Higher values increase stylistic expression but may reduce stability (default: 0.0, range: 0.0 - 0.2).

When the `model` parameter is set to `"eleven_v3"`, the following additional parameters become available:

* `speed`: Speech speed. 1.0 is normal, \<1.0 slower, >1.0 faster (default: 1.0, range: 0.7 - 1.3).
* `similarity_boost`: Similarity boost. Higher values make the voice more similar to the original (default: 0.75, range: 0.0 - 1.0).

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `audio`     | AUDIO     | The generated audio from the text-to-speech conversion. |

***

**Source fingerprint (SHA-256):** `0cd570fbb152e07ba028e96df56abc08dde8941d043386fd076f42a1e1dc6016`


# ElevenLabsVoiceSelector - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ElevenLabsVoiceSelector

Complete documentation for the ElevenLabsVoiceSelector node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ElevenLabsVoiceSelector/en.md)

The ElevenLabs Voice Selector node allows you to choose a specific voice from a predefined list of ElevenLabs text-to-speech voices. It takes a voice name as input and outputs the corresponding voice identifier needed for audio generation. This node simplifies the process of selecting a compatible voice for use with other ElevenLabs audio nodes.

## Inputs

| Parameter | Data Type | Required | Range                                                                                                                                                                                                                                                                                          | Description                                           |
| --------- | --------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------- |
| `voice`   | STRING    | Yes      | `"Adam (male, american)"`<br />`"Antoni (male, british)"`<br />`"Arnold (male, american)"`<br />`"Bella (female, american)"`<br />`"Domi (female, american)"`<br />`"Elli (female, american)"`<br />`"Josh (male, american)"`<br />`"Rachel (female, american)"`<br />`"Sam (male, american)"` | Choose a voice from the predefined ElevenLabs voices. |

## Outputs

| Output Name | Data Type | Description                                                                                                                |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------------------------- |
| `voice`     | STRING    | The unique identifier for the selected ElevenLabs voice, which can be passed to other nodes for text-to-speech generation. |

***

**Source fingerprint (SHA-256):** `47adf5da14e65749c16ada389331c380a1e3a18ecc6f366c32d84ffe7c34990a`


# FluxProCannyNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProCannyNode

Complete documentation for the FluxProCannyNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProCannyNode/en.md)

Generate image using a control image (canny). This node takes a control image and generates a new image based on the provided prompt while following the edge structure detected in the control image.

## Inputs

| Parameter              | Data Type | Required | Range                    | Description                                                                                                                                                                                                                     |
| ---------------------- | --------- | -------- | ------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `control_image`        | IMAGE     | Yes      | -                        | The input image used for canny edge detection control                                                                                                                                                                           |
| `prompt`               | STRING    | No       | -                        | Prompt for the image generation (default: empty string)                                                                                                                                                                         |
| `prompt_upsampling`    | BOOLEAN   | No       | -                        | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: False) |
| `canny_low_threshold`  | FLOAT     | No       | 0.01 - 0.99              | Low threshold for Canny edge detection; ignored if `skip_preprocessing` is True (default: 0.1)                                                                                                                                  |
| `canny_high_threshold` | FLOAT     | No       | 0.01 - 0.99              | High threshold for Canny edge detection; ignored if `skip_preprocessing` is True (default: 0.4)                                                                                                                                 |
| `skip_preprocessing`   | BOOLEAN   | No       | -                        | Whether to skip preprocessing; set to True if `control_image` already is canny-fied, False if it is a raw image. (default: False)                                                                                               |
| `guidance`             | FLOAT     | No       | 1 - 100                  | Guidance strength for the image generation process (default: 30)                                                                                                                                                                |
| `steps`                | INT       | No       | 15 - 50                  | Number of steps for the image generation process (default: 50)                                                                                                                                                                  |
| `seed`                 | INT       | No       | 0 - 18446744073709551615 | The random seed used for creating the noise. (default: 0)                                                                                                                                                                       |

**Note:** When `skip_preprocessing` is set to True, the `canny_low_threshold` and `canny_high_threshold` parameters are ignored since the control image is assumed to already be processed as a canny edge image. The `control_image` is then used directly as the preprocessed image.

## Outputs

| Output Name    | Data Type | Description                                               |
| -------------- | --------- | --------------------------------------------------------- |
| `output_image` | IMAGE     | The generated image based on the control image and prompt |

***

**Source fingerprint (SHA-256):** `dedf55a2b2c183519d7f5be0d9a96abbe40716a247f574fc0d50f10f715949a7`


# FluxProDepthNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProDepthNode

Complete documentation for the FluxProDepthNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProDepthNode/en.md)

This node generates images using a depth control image as guidance. It takes a control image and a text prompt, then creates a new image that follows both the depth information from the control image and the description in the prompt. The node connects to an external API to perform the image generation process.

## Inputs

| Parameter            | Data Type | Required | Range                  | Description                                                                                                                                                                                                                     |
| -------------------- | --------- | -------- | ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `control_image`      | IMAGE     | Yes      | -                      | The depth control image used to guide the image generation                                                                                                                                                                      |
| `prompt`             | STRING    | No       | -                      | Prompt for the image generation (default: empty string)                                                                                                                                                                         |
| `prompt_upsampling`  | BOOLEAN   | No       | -                      | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: False) |
| `skip_preprocessing` | BOOLEAN   | No       | -                      | Whether to skip preprocessing; set to True if `control_image` already is depth-ified, False if it is a raw image. (default: False)                                                                                              |
| `guidance`           | FLOAT     | No       | 1-100                  | Guidance strength for the image generation process (default: 15)                                                                                                                                                                |
| `steps`              | INT       | No       | 15-50                  | Number of steps for the image generation process (default: 50)                                                                                                                                                                  |
| `seed`               | INT       | No       | 0-18446744073709551615 | The random seed used for creating the noise. (default: 0)                                                                                                                                                                       |

## Outputs

| Output Name    | Data Type | Description                                                     |
| -------------- | --------- | --------------------------------------------------------------- |
| `output_image` | IMAGE     | The generated image based on the depth control image and prompt |

***

**Source fingerprint (SHA-256):** `34b80d7d63158b7dc4ad02da6b3a573b713d77efd0955d3477409f776f964462`


# FluxProImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProImageNode

Complete documentation for the FluxProImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProImageNode/en.md)

Generates images synchronously based on prompt and resolution. This node creates images using the Flux 1.1 Pro model by sending requests to an API endpoint and waiting for the complete response before returning the generated image.

## Inputs

| Parameter           | Data Type | Required | Range                  | Description                                                                                                                                                                                                                     |
| ------------------- | --------- | -------- | ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`            | STRING    | Yes      | -                      | Prompt for the image generation (default: empty string)                                                                                                                                                                         |
| `prompt_upsampling` | BOOLEAN   | Yes      | -                      | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: False) |
| `width`             | INT       | Yes      | 256-1440               | Image width in pixels (default: 1024, step: 32)                                                                                                                                                                                 |
| `height`            | INT       | Yes      | 256-1440               | Image height in pixels (default: 768, step: 32)                                                                                                                                                                                 |
| `seed`              | INT       | Yes      | 0-18446744073709551615 | The random seed used for creating the noise. (default: 0)                                                                                                                                                                       |
| `image_prompt`      | IMAGE     | No       | -                      | Optional reference image to guide the generation                                                                                                                                                                                |

## Outputs

| Output Name | Data Type | Description                               |
| ----------- | --------- | ----------------------------------------- |
| `output`    | IMAGE     | The generated image returned from the API |

***

**Source fingerprint (SHA-256):** `89316d84f364854541157b5b60bae3d4e25024bd4af61a47a1748c6671b463c1`


# ImageOnlyCheckpointSave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageOnlyCheckpointSave

Complete documentation for the ImageOnlyCheckpointSave node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageOnlyCheckpointSave/en.md)

The ImageOnlyCheckpointSave node saves a checkpoint file containing a model, CLIP vision encoder, and VAE. It creates a safetensors file with the specified filename prefix and stores it in the output directory. This node is specifically designed for saving image-related model components together in a single checkpoint file.

## Inputs

| Parameter         | Data Type      | Required | Range | Description                                                         |
| ----------------- | -------------- | -------- | ----- | ------------------------------------------------------------------- |
| `model`           | MODEL          | Yes      | -     | The model to be saved in the checkpoint                             |
| `clip_vision`     | CLIP\_VISION   | Yes      | -     | The CLIP vision encoder to be saved in the checkpoint               |
| `vae`             | VAE            | Yes      | -     | The VAE (Variational Autoencoder) to be saved in the checkpoint     |
| `filename_prefix` | STRING         | Yes      | -     | The prefix for the output filename (default: "checkpoints/ComfyUI") |
| `prompt`          | PROMPT         | No       | -     | Hidden parameter for workflow prompt data                           |
| `extra_pnginfo`   | EXTRA\_PNGINFO | No       | -     | Hidden parameter for additional PNG metadata                        |

## Outputs

| Output Name | Data Type | Description                           |
| ----------- | --------- | ------------------------------------- |
| -           | -         | This node does not return any outputs |

***

**Source fingerprint (SHA-256):** `d2a26933f0e2fcccf3c57f50038fb40ef5b23d00ccdd2e1d215b3cb78203b9fd`


# ModelMergeAdd - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeAdd

Complete documentation for the ModelMergeAdd node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The ModelMergeAdd node is designed for merging two models by adding key patches from one model to another. This process involves cloning the first model and then applying patches from the second model, allowing for the combination of features or behaviors from both models.

## Inputs

| Parameter | Data Type | Description                                                                                                                                              |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model1`  | `MODEL`   | The first model to be cloned and to which patches from the second model will be added. It serves as the base model for the merging process.              |
| `model2`  | `MODEL`   | The second model from which key patches are extracted and added to the first model. It contributes additional features or behaviors to the merged model. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                   |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | The result of merging two models by adding key patches from the second model to the first. This merged model combines features or behaviors from both models. |


# ModelMergeBlocks - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeBlocks

Complete documentation for the ModelMergeBlocks node in ComfyUI. Learn its inputs, outputs, parameters and usage.

ModelMergeBlocks is designed for advanced model merging operations, allowing for the integration of two models with customizable blending ratios for different parts of the models. This node facilitates the creation of hybrid models by selectively merging components from two source models based on specified parameters.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                     |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model1`  | `MODEL`   | The first model to be merged. It serves as the base model onto which patches from the second model are applied.                                                 |
| `model2`  | `MODEL`   | The second model from which patches are extracted and applied to the first model, based on the specified blending ratios.                                       |
| `input`   | `FLOAT`   | Specifies the blending ratio for the input layer of the models. It determines how much of the second model's input layer is merged into the first model.        |
| `middle`  | `FLOAT`   | Defines the blending ratio for the middle layers of the models. This parameter controls the integration level of the models' middle layers.                     |
| `out`     | `FLOAT`   | Determines the blending ratio for the output layer of the models. It affects the final output by adjusting the contribution of the second model's output layer. |

## Outputs

| Parameter | Data Type | Description                                                                                                                            |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | The resulting merged model, which is a hybrid of the two input models with patches applied according to the specified blending ratios. |


# ModelMergeLTXV - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeLTXV

Complete documentation for the ModelMergeLTXV node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeLTXV/en.md)

The ModelMergeLTXV node performs advanced model merging operations specifically designed for LTXV model architectures. It allows you to blend two different models together by adjusting interpolation weights for various model components including transformer blocks, projection layers, and other specialized modules.

## Inputs

| Parameter                | Data Type | Required | Range     | Description                                                                        |
| ------------------------ | --------- | -------- | --------- | ---------------------------------------------------------------------------------- |
| `model1`                 | MODEL     | Yes      | -         | The first model to merge                                                           |
| `model2`                 | MODEL     | Yes      | -         | The second model to merge                                                          |
| `patchify_proj.`         | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for patchify projection layers (default: 1.0)                 |
| `adaln_single.`          | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for adaptive layer normalization single layers (default: 1.0) |
| `caption_projection.`    | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for caption projection layers (default: 1.0)                  |
| `transformer_blocks.0.`  | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 0 (default: 1.0)                        |
| `transformer_blocks.1.`  | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 1 (default: 1.0)                        |
| `transformer_blocks.2.`  | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 2 (default: 1.0)                        |
| `transformer_blocks.3.`  | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 3 (default: 1.0)                        |
| `transformer_blocks.4.`  | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 4 (default: 1.0)                        |
| `transformer_blocks.5.`  | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 5 (default: 1.0)                        |
| `transformer_blocks.6.`  | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 6 (default: 1.0)                        |
| `transformer_blocks.7.`  | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 7 (default: 1.0)                        |
| `transformer_blocks.8.`  | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 8 (default: 1.0)                        |
| `transformer_blocks.9.`  | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 9 (default: 1.0)                        |
| `transformer_blocks.10.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 10 (default: 1.0)                       |
| `transformer_blocks.11.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 11 (default: 1.0)                       |
| `transformer_blocks.12.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 12 (default: 1.0)                       |
| `transformer_blocks.13.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 13 (default: 1.0)                       |
| `transformer_blocks.14.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 14 (default: 1.0)                       |
| `transformer_blocks.15.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 15 (default: 1.0)                       |
| `transformer_blocks.16.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 16 (default: 1.0)                       |
| `transformer_blocks.17.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 17 (default: 1.0)                       |
| `transformer_blocks.18.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 18 (default: 1.0)                       |
| `transformer_blocks.19.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 19 (default: 1.0)                       |
| `transformer_blocks.20.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 20 (default: 1.0)                       |
| `transformer_blocks.21.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 21 (default: 1.0)                       |
| `transformer_blocks.22.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 22 (default: 1.0)                       |
| `transformer_blocks.23.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 23 (default: 1.0)                       |
| `transformer_blocks.24.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 24 (default: 1.0)                       |
| `transformer_blocks.25.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 25 (default: 1.0)                       |
| `transformer_blocks.26.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 26 (default: 1.0)                       |
| `transformer_blocks.27.` | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for transformer block 27 (default: 1.0)                       |
| `scale_shift_table`      | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for scale shift table (default: 1.0)                          |
| `proj_out.`              | FLOAT     | Yes      | 0.0 - 1.0 | Interpolation weight for projection output layers (default: 1.0)                   |

## Outputs

| Output Name | Data Type | Description                                                                                                 |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------- |
| `model`     | MODEL     | The merged model combining features from both input models according to the specified interpolation weights |

***

**Source fingerprint (SHA-256):** `29ef8750b6e88f71abca10c8aaad5d75c9c32afec057af78842ca82441438922`


# ModelMergeMochiPreview - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeMochiPreview

Complete documentation for the ModelMergeMochiPreview node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeMochiPreview/en.md)

This node merges two AI models using a block-based approach with fine-grained control over different model components. It allows you to blend models by adjusting interpolation weights for specific sections including positional frequencies, embedding layers, and individual transformer blocks. The merging process combines the architectures and parameters from both input models according to the specified weight values.

## Inputs

| Parameter          | Data Type | Required | Range     | Description                                                    |
| ------------------ | --------- | -------- | --------- | -------------------------------------------------------------- |
| `model1`           | MODEL     | Yes      | -         | The first model to merge                                       |
| `model2`           | MODEL     | Yes      | -         | The second model to merge                                      |
| `pos_frequencies.` | FLOAT     | Yes      | 0.0 - 1.0 | Weight for positional frequencies interpolation (default: 1.0) |
| `t_embedder.`      | FLOAT     | Yes      | 0.0 - 1.0 | Weight for time embedder interpolation (default: 1.0)          |
| `t5_y_embedder.`   | FLOAT     | Yes      | 0.0 - 1.0 | Weight for T5-Y embedder interpolation (default: 1.0)          |
| `t5_yproj.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for T5-Y projection interpolation (default: 1.0)        |
| `blocks.0.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 0 interpolation (default: 1.0)                |
| `blocks.1.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 1 interpolation (default: 1.0)                |
| `blocks.2.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 2 interpolation (default: 1.0)                |
| `blocks.3.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 3 interpolation (default: 1.0)                |
| `blocks.4.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 4 interpolation (default: 1.0)                |
| `blocks.5.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 5 interpolation (default: 1.0)                |
| `blocks.6.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 6 interpolation (default: 1.0)                |
| `blocks.7.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 7 interpolation (default: 1.0)                |
| `blocks.8.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 8 interpolation (default: 1.0)                |
| `blocks.9.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 9 interpolation (default: 1.0)                |
| `blocks.10.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 10 interpolation (default: 1.0)               |
| `blocks.11.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 11 interpolation (default: 1.0)               |
| `blocks.12.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 12 interpolation (default: 1.0)               |
| `blocks.13.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 13 interpolation (default: 1.0)               |
| `blocks.14.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 14 interpolation (default: 1.0)               |
| `blocks.15.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 15 interpolation (default: 1.0)               |
| `blocks.16.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 16 interpolation (default: 1.0)               |
| `blocks.17.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 17 interpolation (default: 1.0)               |
| `blocks.18.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 18 interpolation (default: 1.0)               |
| `blocks.19.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 19 interpolation (default: 1.0)               |
| `blocks.20.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 20 interpolation (default: 1.0)               |
| `blocks.21.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 21 interpolation (default: 1.0)               |
| `blocks.22.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 22 interpolation (default: 1.0)               |
| `blocks.23.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 23 interpolation (default: 1.0)               |
| `blocks.24.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 24 interpolation (default: 1.0)               |
| `blocks.25.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 25 interpolation (default: 1.0)               |
| `blocks.26.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 26 interpolation (default: 1.0)               |
| `blocks.27.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 27 interpolation (default: 1.0)               |
| `blocks.28.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 28 interpolation (default: 1.0)               |
| `blocks.29.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 29 interpolation (default: 1.0)               |
| `blocks.30.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 30 interpolation (default: 1.0)               |
| `blocks.31.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 31 interpolation (default: 1.0)               |
| `blocks.32.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 32 interpolation (default: 1.0)               |
| `blocks.33.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 33 interpolation (default: 1.0)               |
| `blocks.34.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 34 interpolation (default: 1.0)               |
| `blocks.35.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 35 interpolation (default: 1.0)               |
| `blocks.36.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 36 interpolation (default: 1.0)               |
| `blocks.37.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 37 interpolation (default: 1.0)               |
| `blocks.38.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 38 interpolation (default: 1.0)               |
| `blocks.39.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 39 interpolation (default: 1.0)               |
| `blocks.40.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 40 interpolation (default: 1.0)               |
| `blocks.41.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 41 interpolation (default: 1.0)               |
| `blocks.42.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 42 interpolation (default: 1.0)               |
| `blocks.43.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 43 interpolation (default: 1.0)               |
| `blocks.44.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 44 interpolation (default: 1.0)               |
| `blocks.45.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 45 interpolation (default: 1.0)               |
| `blocks.46.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 46 interpolation (default: 1.0)               |
| `blocks.47.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 47 interpolation (default: 1.0)               |
| `final_layer.`     | FLOAT     | Yes      | 0.0 - 1.0 | Weight for final layer interpolation (default: 1.0)            |

## Outputs

| Output Name | Data Type | Description                                                                                   |
| ----------- | --------- | --------------------------------------------------------------------------------------------- |
| `model`     | MODEL     | The merged model combining features from both input models according to the specified weights |

***

**Source fingerprint (SHA-256):** `aebf536f3f89ca8c81141ac871b1b612082c3bd38a29984168b05eccf0cb57e3`


# ModelMergeQwenImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeQwenImage

Complete documentation for the ModelMergeQwenImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeQwenImage/en.md)

The ModelMergeQwenImage node merges two AI models by combining their components with adjustable weights. It allows you to blend specific parts of Qwen image models, including transformer blocks, positional embeddings, and text processing components. You can control how much influence each model has on different sections of the merged result.

## Inputs

| Parameter                                           | Data Type | Required | Range      | Description                                                |
| --------------------------------------------------- | --------- | -------- | ---------- | ---------------------------------------------------------- |
| `model1`                                            | MODEL     | Yes      | -          | The first model to merge (default: none)                   |
| `model2`                                            | MODEL     | Yes      | -          | The second model to merge (default: none)                  |
| `pos_embeds.`                                       | FLOAT     | Yes      | 0.0 to 1.0 | Weight for positional embeddings blending (default: 1.0)   |
| `img_in.`                                           | FLOAT     | Yes      | 0.0 to 1.0 | Weight for image input processing blending (default: 1.0)  |
| `txt_norm.`                                         | FLOAT     | Yes      | 0.0 to 1.0 | Weight for text normalization blending (default: 1.0)      |
| `txt_in.`                                           | FLOAT     | Yes      | 0.0 to 1.0 | Weight for text input processing blending (default: 1.0)   |
| `time_text_embed.`                                  | FLOAT     | Yes      | 0.0 to 1.0 | Weight for time and text embedding blending (default: 1.0) |
| `transformer_blocks.0.` to `transformer_blocks.59.` | FLOAT     | Yes      | 0.0 to 1.0 | Weight for each transformer block blending (default: 1.0)  |
| `proj_out.`                                         | FLOAT     | Yes      | 0.0 to 1.0 | Weight for output projection blending (default: 1.0)       |

## Outputs

| Output Name | Data Type | Description                                                                             |
| ----------- | --------- | --------------------------------------------------------------------------------------- |
| `model`     | MODEL     | The merged model combining components from both input models with the specified weights |

***

**Source fingerprint (SHA-256):** `a0424a3f4d4ffe170471ba463350d741f67ff1b1f5a8a016ad844c111033f97c`


# ModelMergeSD1 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSD1

Complete documentation for the ModelMergeSD1 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeSD1/en.md)

The ModelMergeSD1 node allows you to blend two Stable Diffusion 1.x models together by adjusting the influence of different model components. It provides individual control over time embedding, label embedding, and all input, middle, and output blocks, enabling fine-tuned model merging for specific use cases.

## Inputs

| Parameter           | Data Type | Required | Range     | Description                                          |
| ------------------- | --------- | -------- | --------- | ---------------------------------------------------- |
| `model1`            | MODEL     | Yes      | -         | The first model to merge                             |
| `model2`            | MODEL     | Yes      | -         | The second model to merge                            |
| `time_embed.`       | FLOAT     | Yes      | 0.0 - 1.0 | Time embedding layer blending weight (default: 1.0)  |
| `label_emb.`        | FLOAT     | Yes      | 0.0 - 1.0 | Label embedding layer blending weight (default: 1.0) |
| `input_blocks.0.`   | FLOAT     | Yes      | 0.0 - 1.0 | Input block 0 blending weight (default: 1.0)         |
| `input_blocks.1.`   | FLOAT     | Yes      | 0.0 - 1.0 | Input block 1 blending weight (default: 1.0)         |
| `input_blocks.2.`   | FLOAT     | Yes      | 0.0 - 1.0 | Input block 2 blending weight (default: 1.0)         |
| `input_blocks.3.`   | FLOAT     | Yes      | 0.0 - 1.0 | Input block 3 blending weight (default: 1.0)         |
| `input_blocks.4.`   | FLOAT     | Yes      | 0.0 - 1.0 | Input block 4 blending weight (default: 1.0)         |
| `input_blocks.5.`   | FLOAT     | Yes      | 0.0 - 1.0 | Input block 5 blending weight (default: 1.0)         |
| `input_blocks.6.`   | FLOAT     | Yes      | 0.0 - 1.0 | Input block 6 blending weight (default: 1.0)         |
| `input_blocks.7.`   | FLOAT     | Yes      | 0.0 - 1.0 | Input block 7 blending weight (default: 1.0)         |
| `input_blocks.8.`   | FLOAT     | Yes      | 0.0 - 1.0 | Input block 8 blending weight (default: 1.0)         |
| `input_blocks.9.`   | FLOAT     | Yes      | 0.0 - 1.0 | Input block 9 blending weight (default: 1.0)         |
| `input_blocks.10.`  | FLOAT     | Yes      | 0.0 - 1.0 | Input block 10 blending weight (default: 1.0)        |
| `input_blocks.11.`  | FLOAT     | Yes      | 0.0 - 1.0 | Input block 11 blending weight (default: 1.0)        |
| `middle_block.0.`   | FLOAT     | Yes      | 0.0 - 1.0 | Middle block 0 blending weight (default: 1.0)        |
| `middle_block.1.`   | FLOAT     | Yes      | 0.0 - 1.0 | Middle block 1 blending weight (default: 1.0)        |
| `middle_block.2.`   | FLOAT     | Yes      | 0.0 - 1.0 | Middle block 2 blending weight (default: 1.0)        |
| `output_blocks.0.`  | FLOAT     | Yes      | 0.0 - 1.0 | Output block 0 blending weight (default: 1.0)        |
| `output_blocks.1.`  | FLOAT     | Yes      | 0.0 - 1.0 | Output block 1 blending weight (default: 1.0)        |
| `output_blocks.2.`  | FLOAT     | Yes      | 0.0 - 1.0 | Output block 2 blending weight (default: 1.0)        |
| `output_blocks.3.`  | FLOAT     | Yes      | 0.0 - 1.0 | Output block 3 blending weight (default: 1.0)        |
| `output_blocks.4.`  | FLOAT     | Yes      | 0.0 - 1.0 | Output block 4 blending weight (default: 1.0)        |
| `output_blocks.5.`  | FLOAT     | Yes      | 0.0 - 1.0 | Output block 5 blending weight (default: 1.0)        |
| `output_blocks.6.`  | FLOAT     | Yes      | 0.0 - 1.0 | Output block 6 blending weight (default: 1.0)        |
| `output_blocks.7.`  | FLOAT     | Yes      | 0.0 - 1.0 | Output block 7 blending weight (default: 1.0)        |
| `output_blocks.8.`  | FLOAT     | Yes      | 0.0 - 1.0 | Output block 8 blending weight (default: 1.0)        |
| `output_blocks.9.`  | FLOAT     | Yes      | 0.0 - 1.0 | Output block 9 blending weight (default: 1.0)        |
| `output_blocks.10.` | FLOAT     | Yes      | 0.0 - 1.0 | Output block 10 blending weight (default: 1.0)       |
| `output_blocks.11.` | FLOAT     | Yes      | 0.0 - 1.0 | Output block 11 blending weight (default: 1.0)       |
| `out.`              | FLOAT     | Yes      | 0.0 - 1.0 | Output layer blending weight (default: 1.0)          |

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `MODEL`     | MODEL     | The merged model combining features from both input models |

***

**Source fingerprint (SHA-256):** `512c62fb5a4e1b7f90f5ad5b80de5818659a20c8f4b024cfa33ca13b823efad8`


# ModelMergeSD35_Large - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSD35_Large

Complete documentation for the ModelMergeSD35_Large node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeSD35_Large/en.md)

The ModelMergeSD35\_Large node allows you to blend two Stable Diffusion 3.5 Large models together by adjusting the influence of different model components. It provides precise control over how much each part of the second model contributes to the final merged model, from embedding layers to joint blocks and final layers.

## Inputs

| Parameter           | Data Type | Required | Range      | Description                                                                                             |
| ------------------- | --------- | -------- | ---------- | ------------------------------------------------------------------------------------------------------- |
| `model1`            | MODEL     | Yes      | -          | The base model that serves as the foundation for merging                                                |
| `model2`            | MODEL     | Yes      | -          | The secondary model whose components will be blended into the base model                                |
| `pos_embed.`        | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of the position embedding from model2 is blended into the merged model (default: 1.0) |
| `x_embedder.`       | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of the x embedder from model2 is blended into the merged model (default: 1.0)         |
| `context_embedder.` | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of the context embedder from model2 is blended into the merged model (default: 1.0)   |
| `y_embedder.`       | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of the y embedder from model2 is blended into the merged model (default: 1.0)         |
| `t_embedder.`       | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of the t embedder from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.0.`   | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 0 from model2 is blended into the merged model (default: 1.0)          |
| `joint_blocks.1.`   | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 1 from model2 is blended into the merged model (default: 1.0)          |
| `joint_blocks.2.`   | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 2 from model2 is blended into the merged model (default: 1.0)          |
| `joint_blocks.3.`   | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 3 from model2 is blended into the merged model (default: 1.0)          |
| `joint_blocks.4.`   | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 4 from model2 is blended into the merged model (default: 1.0)          |
| `joint_blocks.5.`   | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 5 from model2 is blended into the merged model (default: 1.0)          |
| `joint_blocks.6.`   | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 6 from model2 is blended into the merged model (default: 1.0)          |
| `joint_blocks.7.`   | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 7 from model2 is blended into the merged model (default: 1.0)          |
| `joint_blocks.8.`   | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 8 from model2 is blended into the merged model (default: 1.0)          |
| `joint_blocks.9.`   | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 9 from model2 is blended into the merged model (default: 1.0)          |
| `joint_blocks.10.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 10 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.11.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 11 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.12.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 12 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.13.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 13 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.14.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 14 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.15.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 15 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.16.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 16 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.17.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 17 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.18.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 18 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.19.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 19 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.20.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 20 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.21.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 21 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.22.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 22 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.23.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 23 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.24.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 24 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.25.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 25 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.26.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 26 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.27.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 27 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.28.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 28 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.29.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 29 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.30.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 30 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.31.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 31 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.32.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 32 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.33.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 33 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.34.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 34 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.35.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 35 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.36.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 36 from model2 is blended into the merged model (default: 1.0)         |
| `joint_blocks.37.`  | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of joint block 37 from model2 is blended into the merged model (default: 1.0)         |
| `final_layer.`      | FLOAT     | Yes      | 0.0 to 1.0 | Controls how much of the final layer from model2 is blended into the merged model (default: 1.0)        |

**Note:** All blend parameters accept values from 0.0 to 1.0, where 0.0 means no contribution from model2 and 1.0 means full contribution from model2 for that specific component.

## Outputs

| Output Name | Data Type | Description                                                                                                      |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------- |
| `model`     | MODEL     | The resulting merged model combining features from both input models according to the specified blend parameters |

***

**Source fingerprint (SHA-256):** `1b491bd96cc40c6098fd8194f66753bc0f7aa485ea5f97b67b4d864cc9615c9a`


# ModelMergeSD3_2B - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSD3_2B

Complete documentation for the ModelMergeSD3_2B node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeSD3_2B/en.md)

The ModelMergeSD3\_2B node allows you to merge two Stable Diffusion 3 2B models by blending their components with adjustable weights. It provides individual control over embedding layers and transformer blocks, enabling fine-tuned model combinations for specialized generation tasks.

## Inputs

| Parameter           | Data Type | Required | Range     | Description                                            |
| ------------------- | --------- | -------- | --------- | ------------------------------------------------------ |
| `model1`            | MODEL     | Yes      | -         | The first model to merge                               |
| `model2`            | MODEL     | Yes      | -         | The second model to merge                              |
| `pos_embed.`        | FLOAT     | Yes      | 0.0 - 1.0 | Position embedding interpolation weight (default: 1.0) |
| `x_embedder.`       | FLOAT     | Yes      | 0.0 - 1.0 | Input embedding interpolation weight (default: 1.0)    |
| `context_embedder.` | FLOAT     | Yes      | 0.0 - 1.0 | Context embedding interpolation weight (default: 1.0)  |
| `y_embedder.`       | FLOAT     | Yes      | 0.0 - 1.0 | Y embedding interpolation weight (default: 1.0)        |
| `t_embedder.`       | FLOAT     | Yes      | 0.0 - 1.0 | Time embedding interpolation weight (default: 1.0)     |
| `joint_blocks.0.`   | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 0 interpolation weight (default: 1.0)      |
| `joint_blocks.1.`   | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 1 interpolation weight (default: 1.0)      |
| `joint_blocks.2.`   | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 2 interpolation weight (default: 1.0)      |
| `joint_blocks.3.`   | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 3 interpolation weight (default: 1.0)      |
| `joint_blocks.4.`   | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 4 interpolation weight (default: 1.0)      |
| `joint_blocks.5.`   | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 5 interpolation weight (default: 1.0)      |
| `joint_blocks.6.`   | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 6 interpolation weight (default: 1.0)      |
| `joint_blocks.7.`   | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 7 interpolation weight (default: 1.0)      |
| `joint_blocks.8.`   | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 8 interpolation weight (default: 1.0)      |
| `joint_blocks.9.`   | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 9 interpolation weight (default: 1.0)      |
| `joint_blocks.10.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 10 interpolation weight (default: 1.0)     |
| `joint_blocks.11.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 11 interpolation weight (default: 1.0)     |
| `joint_blocks.12.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 12 interpolation weight (default: 1.0)     |
| `joint_blocks.13.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 13 interpolation weight (default: 1.0)     |
| `joint_blocks.14.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 14 interpolation weight (default: 1.0)     |
| `joint_blocks.15.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 15 interpolation weight (default: 1.0)     |
| `joint_blocks.16.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 16 interpolation weight (default: 1.0)     |
| `joint_blocks.17.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 17 interpolation weight (default: 1.0)     |
| `joint_blocks.18.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 18 interpolation weight (default: 1.0)     |
| `joint_blocks.19.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 19 interpolation weight (default: 1.0)     |
| `joint_blocks.20.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 20 interpolation weight (default: 1.0)     |
| `joint_blocks.21.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 21 interpolation weight (default: 1.0)     |
| `joint_blocks.22.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 22 interpolation weight (default: 1.0)     |
| `joint_blocks.23.`  | FLOAT     | Yes      | 0.0 - 1.0 | Joint block 23 interpolation weight (default: 1.0)     |
| `final_layer.`      | FLOAT     | Yes      | 0.0 - 1.0 | Final layer interpolation weight (default: 1.0)        |

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `model`     | MODEL     | The merged model combining features from both input models |

***

**Source fingerprint (SHA-256):** `5b0c28c66e1828742873191be424956a9006e59ea1167a5941069ba0b7bc390b`


# ModelMergeSDXL - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSDXL

Complete documentation for the ModelMergeSDXL node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeSDXL/en.md)

The ModelMergeSDXL node allows you to blend two SDXL models together by adjusting the influence of each model on different parts of the architecture. You can control how much each model contributes to time embeddings, label embeddings, and various blocks within the model structure. This creates a hybrid model that combines characteristics from both input models.

## Inputs

| Parameter         | Data Type | Required | Range     | Description                                               |
| ----------------- | --------- | -------- | --------- | --------------------------------------------------------- |
| `model1`          | MODEL     | Yes      | -         | The first SDXL model to merge                             |
| `model2`          | MODEL     | Yes      | -         | The second SDXL model to merge                            |
| `time_embed.`     | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for time embedding layers (default: 1.0)  |
| `label_emb.`      | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for label embedding layers (default: 1.0) |
| `input_blocks.0`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for input block 0 (default: 1.0)          |
| `input_blocks.1`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for input block 1 (default: 1.0)          |
| `input_blocks.2`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for input block 2 (default: 1.0)          |
| `input_blocks.3`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for input block 3 (default: 1.0)          |
| `input_blocks.4`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for input block 4 (default: 1.0)          |
| `input_blocks.5`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for input block 5 (default: 1.0)          |
| `input_blocks.6`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for input block 6 (default: 1.0)          |
| `input_blocks.7`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for input block 7 (default: 1.0)          |
| `input_blocks.8`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for input block 8 (default: 1.0)          |
| `middle_block.0`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for middle block 0 (default: 1.0)         |
| `middle_block.1`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for middle block 1 (default: 1.0)         |
| `middle_block.2`  | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for middle block 2 (default: 1.0)         |
| `output_blocks.0` | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for output block 0 (default: 1.0)         |
| `output_blocks.1` | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for output block 1 (default: 1.0)         |
| `output_blocks.2` | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for output block 2 (default: 1.0)         |
| `output_blocks.3` | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for output block 3 (default: 1.0)         |
| `output_blocks.4` | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for output block 4 (default: 1.0)         |
| `output_blocks.5` | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for output block 5 (default: 1.0)         |
| `output_blocks.6` | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for output block 6 (default: 1.0)         |
| `output_blocks.7` | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for output block 7 (default: 1.0)         |
| `output_blocks.8` | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for output block 8 (default: 1.0)         |
| `out.`            | FLOAT     | Yes      | 0.0 - 1.0 | Blending weight for output layers (default: 1.0)          |

## Outputs

| Output Name | Data Type | Description                                                            |
| ----------- | --------- | ---------------------------------------------------------------------- |
| `model`     | MODEL     | The merged SDXL model combining characteristics from both input models |

***

**Source fingerprint (SHA-256):** `6c7572a6ed50534f2d9ad6f499146763457da58f0c9dd4b85204e67f7d3e9660`


# ModelMergeSimple - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSimple

Complete documentation for the ModelMergeSimple node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The ModelMergeSimple node is designed for merging two models by blending their parameters based on a specified ratio. This node facilitates the creation of hybrid models that combine the strengths or characteristics of both input models.

The `ratio` parameter determines the blending ratio between the two models. When this value is 1, the output model is 100% `model1`, and when this value is 0, the output model is 100% `model2`.

## Inputs

| Parameter | Data Type | Description                                                                                                           |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------- |
| `model1`  | `MODEL`   | The first model to be merged. It serves as the base model onto which patches from the second model are applied.       |
| `model2`  | `MODEL`   | The second model whose patches are applied onto the first model, influenced by the specified ratio.                   |
| `ratio`   | `FLOAT`   | When this value is 1, the output model is 100% `model1`, and when this value is 0, the output model is 100% `model2`. |

## Outputs

| Parameter | Data Type | Description                                                                                                 |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | The resulting merged model, incorporating elements from both input models according to the specified ratio. |


# ModelMergeSubtract - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeSubtract

Complete documentation for the ModelMergeSubtract node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed for advanced model merging operations, specifically to subtract the parameters of one model from another based on a specified multiplier. It enables the customization of model behaviors by adjusting the influence of one model's parameters over another, facilitating the creation of new, hybrid models.

## Inputs

| Parameter    | Data Type | Description                                                                               |
| ------------ | --------- | ----------------------------------------------------------------------------------------- |
| `model1`     | `MODEL`   | The base model from which parameters will be subtracted.                                  |
| `model2`     | `MODEL`   | The model whose parameters will be subtracted from the base model.                        |
| `multiplier` | `FLOAT`   | A floating-point value that scales the subtraction effect on the base model's parameters. |

## Outputs

| Parameter | Data Type | Description                                                                                               |
| --------- | --------- | --------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | The resulting model after subtracting the parameters of one model from another, scaled by the multiplier. |


# ModelMergeWAN2_1 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelMergeWAN2_1

Complete documentation for the ModelMergeWAN2_1 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelMergeWAN2_1/en.md)

The ModelMergeWAN2\_1 node merges two WAN2.1 models by blending their components using weighted averages. It supports different model sizes including 1.3B models with 30 blocks and 14B models with 40 blocks, with special handling for image to video models that include an extra image embedding component. Each component of the models can be individually weighted to control the blending ratio between the two input models.

## Inputs

| Parameter          | Data Type | Required | Range     | Description                                                                        |
| ------------------ | --------- | -------- | --------- | ---------------------------------------------------------------------------------- |
| `model1`           | MODEL     | Yes      | -         | First model to merge                                                               |
| `model2`           | MODEL     | Yes      | -         | Second model to merge                                                              |
| `patch_embedding.` | FLOAT     | Yes      | 0.0 - 1.0 | Weight for patch embedding component (default: 1.0)                                |
| `time_embedding.`  | FLOAT     | Yes      | 0.0 - 1.0 | Weight for time embedding component (default: 1.0)                                 |
| `time_projection.` | FLOAT     | Yes      | 0.0 - 1.0 | Weight for time projection component (default: 1.0)                                |
| `text_embedding.`  | FLOAT     | Yes      | 0.0 - 1.0 | Weight for text embedding component (default: 1.0)                                 |
| `img_emb.`         | FLOAT     | Yes      | 0.0 - 1.0 | Weight for image embedding component, used in image to video models (default: 1.0) |
| `blocks.0.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 0 (default: 1.0)                                                  |
| `blocks.1.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 1 (default: 1.0)                                                  |
| `blocks.2.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 2 (default: 1.0)                                                  |
| `blocks.3.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 3 (default: 1.0)                                                  |
| `blocks.4.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 4 (default: 1.0)                                                  |
| `blocks.5.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 5 (default: 1.0)                                                  |
| `blocks.6.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 6 (default: 1.0)                                                  |
| `blocks.7.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 7 (default: 1.0)                                                  |
| `blocks.8.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 8 (default: 1.0)                                                  |
| `blocks.9.`        | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 9 (default: 1.0)                                                  |
| `blocks.10.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 10 (default: 1.0)                                                 |
| `blocks.11.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 11 (default: 1.0)                                                 |
| `blocks.12.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 12 (default: 1.0)                                                 |
| `blocks.13.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 13 (default: 1.0)                                                 |
| `blocks.14.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 14 (default: 1.0)                                                 |
| `blocks.15.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 15 (default: 1.0)                                                 |
| `blocks.16.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 16 (default: 1.0)                                                 |
| `blocks.17.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 17 (default: 1.0)                                                 |
| `blocks.18.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 18 (default: 1.0)                                                 |
| `blocks.19.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 19 (default: 1.0)                                                 |
| `blocks.20.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 20 (default: 1.0)                                                 |
| `blocks.21.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 21 (default: 1.0)                                                 |
| `blocks.22.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 22 (default: 1.0)                                                 |
| `blocks.23.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 23 (default: 1.0)                                                 |
| `blocks.24.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 24 (default: 1.0)                                                 |
| `blocks.25.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 25 (default: 1.0)                                                 |
| `blocks.26.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 26 (default: 1.0)                                                 |
| `blocks.27.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 27 (default: 1.0)                                                 |
| `blocks.28.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 28 (default: 1.0)                                                 |
| `blocks.29.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 29 (default: 1.0)                                                 |
| `blocks.30.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 30 (default: 1.0)                                                 |
| `blocks.31.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 31 (default: 1.0)                                                 |
| `blocks.32.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 32 (default: 1.0)                                                 |
| `blocks.33.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 33 (default: 1.0)                                                 |
| `blocks.34.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 34 (default: 1.0)                                                 |
| `blocks.35.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 35 (default: 1.0)                                                 |
| `blocks.36.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 36 (default: 1.0)                                                 |
| `blocks.37.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 37 (default: 1.0)                                                 |
| `blocks.38.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 38 (default: 1.0)                                                 |
| `blocks.39.`       | FLOAT     | Yes      | 0.0 - 1.0 | Weight for block 39 (default: 1.0)                                                 |
| `head.`            | FLOAT     | Yes      | 0.0 - 1.0 | Weight for head component (default: 1.0)                                           |

**Note:** All weight parameters use a range from 0.0 to 1.0 with 0.01 step increments. The node supports up to 40 blocks to accommodate different model sizes, where 1.3B models use 30 blocks and 14B models use 40 blocks. The `img_emb.` parameter is specifically for image to video models.

## Outputs

| Output Name | Data Type | Description                                                                                     |
| ----------- | --------- | ----------------------------------------------------------------------------------------------- |
| `model`     | MODEL     | The merged model combining components from both input models according to the specified weights |

***

**Source fingerprint (SHA-256):** `d550a2f62bbcb4b46ccdd8a04fab80e93f96ea63426d48acb3515d51175efc99`


# ModelSave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ModelSave

Complete documentation for the ModelSave node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ModelSave/en.md)

The ModelSave node saves trained or modified models to your computer's storage. It takes a model as input and writes it to a file with your specified filename. This allows you to preserve your work and reuse models in future projects.

## Inputs

| Parameter         | Data Type      | Required | Range | Description                                                                                  |
| ----------------- | -------------- | -------- | ----- | -------------------------------------------------------------------------------------------- |
| `model`           | MODEL          | Yes      | -     | The model to be saved to disk                                                                |
| `filename_prefix` | STRING         | Yes      | -     | The filename and path prefix for the saved model file (default: "diffusion\_models/ComfyUI") |
| `prompt`          | PROMPT         | No       | -     | Workflow prompt information (automatically provided)                                         |
| `extra_pnginfo`   | EXTRA\_PNGINFO | No       | -     | Additional workflow metadata (automatically provided)                                        |

## Outputs

| Output Name | Data Type | Description                                 |
| ----------- | --------- | ------------------------------------------- |
| *None*      | -         | This node does not return any output values |

***

**Source fingerprint (SHA-256):** `1dda8a6d85aa19b739c1fe3e6e7f816e05011044fc8b0b91b23fa303f71d8b19`


# MoonvalleyImg2VideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoonvalleyImg2VideoNode

Complete documentation for the MoonvalleyImg2VideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoonvalleyImg2VideoNode/en.md)

The Moonvalley Marey Image to Video node transforms a reference image into a video using the Moonvalley API. It takes an input image and a text prompt to generate a video with specified resolution, quality settings, and creative controls. The node handles the entire process from image upload to video generation and download.

## Inputs

| Parameter          | Data Type | Required | Range                                                                                                                     | Description                                                                                 |
| ------------------ | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------- |
| `image`            | IMAGE     | Yes      | -                                                                                                                         | The reference image used to generate the video                                              |
| `prompt`           | STRING    | Yes      | -                                                                                                                         | Text description for video generation (multiline input)                                     |
| `negative_prompt`  | STRING    | No       | -                                                                                                                         | Negative prompt text to exclude unwanted elements (default: extensive negative prompt list) |
| `resolution`       | COMBO     | No       | "16:9 (1920 x 1080)"<br />"9:16 (1080 x 1920)"<br />"1:1 (1152 x 1152)"<br />"4:3 (1536 x 1152)"<br />"3:4 (1152 x 1536)" | Resolution of the output video (default: "16:9 (1920 x 1080)")                              |
| `prompt_adherence` | FLOAT     | No       | 1.0 - 20.0                                                                                                                | Guidance scale for generation control (default: 4.5, step: 1.0)                             |
| `seed`             | INT       | No       | 0 - 4294967295                                                                                                            | Random seed value (default: 9, control after generate enabled)                              |
| `steps`            | INT       | No       | 1 - 100                                                                                                                   | Number of denoising steps (default: 33, step: 1)                                            |

**Constraints:**

* The input image must have dimensions between 300x300 pixels and the maximum allowed height/width
* Prompt and negative prompt text length is limited to the Moonvalley Marey maximum prompt length

## Outputs

| Output Name | Data Type | Description                |
| ----------- | --------- | -------------------------- |
| `output`    | VIDEO     | The generated video output |

***

**Source fingerprint (SHA-256):** `674e69a7f106f6f961f10c179008b7bb1147bf0e569c72d207a105f3fab2aaf5`


# MoonvalleyTxt2VideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoonvalleyTxt2VideoNode

Complete documentation for the MoonvalleyTxt2VideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoonvalleyTxt2VideoNode/en.md)

The Moonvalley Marey Text to Video node generates video content from text descriptions using the Moonvalley API. It takes a text prompt and converts it into a video with customizable settings for resolution, quality, and style. The node handles the entire process from sending the generation request to downloading the final video output.

## Inputs

| Parameter          | Data Type | Required | Range                                                                                                                                               | Description                                                                                                           |
| ------------------ | --------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------- |
| `prompt`           | STRING    | Yes      | -                                                                                                                                                   | Text description of the video content to generate                                                                     |
| `negative_prompt`  | STRING    | No       | -                                                                                                                                                   | Negative prompt text (default: extensive list of excluded elements like synthetic, scene cut, artifacts, noise, etc.) |
| `resolution`       | STRING    | No       | "16:9 (1920 x 1080)"<br />"9:16 (1080 x 1920)"<br />"1:1 (1152 x 1152)"<br />"4:3 (1536 x 1152)"<br />"3:4 (1152 x 1536)"<br />"21:9 (2560 x 1080)" | Resolution of the output video (default: "16:9 (1920 x 1080)")                                                        |
| `prompt_adherence` | FLOAT     | No       | 1.0-20.0                                                                                                                                            | Guidance scale for generation control (default: 4.0)                                                                  |
| `seed`             | INT       | No       | 0-4294967295                                                                                                                                        | Random seed value (default: 9)                                                                                        |
| `steps`            | INT       | No       | 1-100                                                                                                                                               | Inference steps (default: 33)                                                                                         |

## Outputs

| Output Name | Data Type | Description                                         |
| ----------- | --------- | --------------------------------------------------- |
| `video`     | VIDEO     | The generated video output based on the text prompt |

***

**Source fingerprint (SHA-256):** `3654043567d7aca3af741d706ee07a8d2e28dbeb4b5b8755514b790aa7c1bd41`


# MoonvalleyVideo2VideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoonvalleyVideo2VideoNode

Complete documentation for the MoonvalleyVideo2VideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoonvalleyVideo2VideoNode/en.md)

The Moonvalley Marey Video to Video node transforms an input video into a new video based on a text description. It uses the Moonvalley API to generate videos that match your prompt while preserving motion or pose characteristics from the original video. You can control the style and content of the output video through text prompts and various generation parameters.

## Inputs

| Parameter          | Data Type | Required | Range                                  | Description                                                                                                                                                             |
| ------------------ | --------- | -------- | -------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`           | STRING    | Yes      | -                                      | Describes the video to generate (multiline input)                                                                                                                       |
| `negative_prompt`  | STRING    | No       | -                                      | Negative prompt text (default: extensive list of negative descriptors)                                                                                                  |
| `seed`             | INT       | Yes      | 0 to 4294967295                        | Random seed value (default: 9)                                                                                                                                          |
| `video`            | VIDEO     | Yes      | -                                      | The reference video used to generate the output video. Must be at least 5 seconds long. Videos longer than 5s will be automatically trimmed. Only MP4 format supported. |
| `control_type`     | COMBO     | No       | "Motion Transfer"<br />"Pose Transfer" | Control type selection (default: "Motion Transfer")                                                                                                                     |
| `motion_intensity` | INT       | No       | 0 to 100                               | Only used if control\_type is "Motion Transfer" (default: 100)                                                                                                          |
| `steps`            | INT       | Yes      | 1 to 100                               | Number of inference steps (default: 33)                                                                                                                                 |

**Note:** The `motion_intensity` parameter is only applied when `control_type` is set to "Motion Transfer". When using "Pose Transfer", this parameter is ignored.

## Outputs

| Output Name | Data Type | Description                |
| ----------- | --------- | -------------------------- |
| `output`    | VIDEO     | The generated video output |

***

**Source fingerprint (SHA-256):** `8202a4be469afa16d77b9e0287c290b9c3f390347fc60f23878f50fd95a758e0`


# MultiGPU_Options - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MultiGPU_Options

Complete documentation for the MultiGPU_Options node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MultiGPU_Options/en.md)

## Overview

This node allows you to specify the relative performance of each GPU when using multiple graphics cards with different speeds. It creates a group of GPU options that can be used to distribute work across devices, though the actual speed-based workload distribution is not yet implemented in the current version.

## Inputs

| Parameter        | Data Type    | Required | Range            | Description                                                                                                  |
| ---------------- | ------------ | -------- | ---------------- | ------------------------------------------------------------------------------------------------------------ |
| `device_index`   | INT          | Yes      | 0 to 64          | The index number of the GPU device to configure (default: 0)                                                 |
| `relative_speed` | FLOAT        | Yes      | 0.0 to unlimited | The relative speed of this GPU compared to others, used for workload distribution (default: 1.0, step: 0.01) |
| `gpu_options`    | GPU\_OPTIONS | No       | -                | An existing GPU options group to add this device's options to. If not provided, a new group is created       |

## Outputs

| Output Name   | Data Type    | Description                                                                                                                   |
| ------------- | ------------ | ----------------------------------------------------------------------------------------------------------------------------- |
| `GPU_OPTIONS` | GPU\_OPTIONS | A group of GPU options containing the configured device settings, which can be passed to other nodes for multi-GPU operations |

**Note:** The `relative_speed` parameter is defined but not yet used by the internal scheduler for distributing work across GPUs. In the current implementation, work is distributed evenly across all devices regardless of their relative speeds.

***

**Source fingerprint (SHA-256):** `8010460560a69c57d4ee0d8c3728a7a5d999e56ef5316b557fba0c660c9f38b0`


# MultiGPU_WorkUnits - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MultiGPU_WorkUnits

Complete documentation for the MultiGPU_WorkUnits node in ComfyUI. Learn its inputs, outputs, parameters and usage.

# COMFYUI MultiGPU CFG Split Node

## Overview:

The MultiGPU CFG Split Node allows diffusion processing to occur using multiple GPUs installed in the same system. Performance results are workflow dependent, but speedups of up to 1.95x have been measured in common workflows.

## Key Details:

Mixing different GPU types is not supported, the installed GPUs must be the same (ie 2x 5090, or 2x 5080, etc.)

ComfyUI will automatically detect multiple installed GPUs at startup.

## Supported GPUs:

Any homogeneous dual GPU setups with Ampere+ architecture (e.g 2 x 3090 or 2 x RTX6000 Pro)

## Supported Models:

* LTX-2.3
* WAN 2.2
* FLUX.2 Klein - Base Versions
* Z-Image
* Stable Diffusion 3.5 Large
* Hunyuan Video
* Qwen-Image-Edit-2511
* Hunyuan-3D-v2.1
* SDXL

## Inputs

| Parameter  | Data Type | Required | Range                                   | Description                                                                                                                               |
| ---------- | --------- | -------- | --------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- |
| `model`    | MODEL     | Yes      | N/A                                     | The model to prepare for MultiGPU CFG splitting before sampling.                                                                          |
| `max_gpus` | INT       | Yes      | Minimum: 1<br />Step: 1<br />Default: 2 | The maximum number of identical GPUs to use for splitting the workload. Set this to the number of matching GPUs installed in your system. |

## Outputs

| Output Name | Data Type | Description                                                                    |
| ----------- | --------- | ------------------------------------------------------------------------------ |
| `MODEL`     | MODEL     | The model prepared for MultiGPU CFG splitting, ready for accelerated sampling. |

## Node:

<img alt="image1.png" />\
The max\_gpus field should be set to the maximum number of identical GPUs installed in the system.

**Node placement:**  The MultiGPU CFG Split needs to be placed between the Model Load node and Sampling node. If other nodes are connected to the model output of the model loader node, the MultiGPU CFG should be the last node in the chain before the Sampling node.

<img alt="image2.png" />

**Workflow Requirements:** The node works by splitting the diffusion workflow at the CFG level, due to this, the CFG in the workflow must be greater than CFG=1. Distilled workflows which require a CFG =1 will not show a performance benefit when using the MultiGPU CFG Split node to run on multiple GPUs.

## Verifying Multi-GPU Utilization

When running a workflow with MultiGPU CFG Split enabled, you can look at the Windows Task Manager and select the performance category\
<img alt="image3.png" />\
<img alt="image4.png" />\
You should see activity on both installed GPUs while the sampler is running in the workflow.

## Sample Multi-GPU Workflow: (Wan 2.2 FP8)

[Sample workflow (Wan 2.2 FP8)](https://raw.githubusercontent.com/Comfy-Org/embedded-docs/refs/heads/main/comfyui_embedded_docs/docs/MultiGPU_WorkUnits/asset/video_wan2_2_14B_t2v_mGPU.json)

***

**Source fingerprint (SHA-256):** `7293ee785e29aea9a1a70a10444b99e89fb23c866505628ec57c209a2b8aaee0`


# PikaImageToVideoNode2_2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PikaImageToVideoNode2_2

Complete documentation for the PikaImageToVideoNode2_2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PikaImageToVideoNode2_2/en.md)

The Pika Image to Video node sends an image and text prompt to the Pika API version 2.2 to generate a video. It converts your input image into video format based on the provided description and settings. The node handles the API communication and returns the generated video as output.

## Inputs

| Parameter         | Data Type | Required | Range | Description                                   |
| ----------------- | --------- | -------- | ----- | --------------------------------------------- |
| `image`           | IMAGE     | Yes      | -     | The image to convert to video                 |
| `prompt_text`     | STRING    | Yes      | -     | The text description guiding video generation |
| `negative_prompt` | STRING    | Yes      | -     | Text describing what to avoid in the video    |
| `seed`            | INT       | Yes      | -     | Random seed value for reproducible results    |
| `resolution`      | STRING    | Yes      | -     | Output video resolution setting               |
| `duration`        | INT       | Yes      | -     | Length of the generated video in seconds      |

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `output`    | VIDEO     | The generated video file |

***

**Source fingerprint (SHA-256):** `aaa8dc49b94f0fae2010a3b61a3fb41e212fa9d2946a934a1a7c651fdced81b3`


# PikaScenesV2_2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PikaScenesV2_2

Complete documentation for the PikaScenesV2_2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PikaScenesV2_2/en.md)

The PikaScenes v2.2 node combines multiple images to create a video that incorporates objects from all the input images. You can upload up to five different images as ingredients and generate a high-quality video that blends them together seamlessly.

## Inputs

| Parameter            | Data Type | Required | Range                     | Description                                             |
| -------------------- | --------- | -------- | ------------------------- | ------------------------------------------------------- |
| `prompt_text`        | STRING    | Yes      | -                         | Text description of what to generate                    |
| `negative_prompt`    | STRING    | Yes      | -                         | Text description of what to avoid in the generation     |
| `seed`               | INT       | Yes      | -                         | Random seed value for generation                        |
| `resolution`         | STRING    | Yes      | -                         | Output resolution for the video                         |
| `duration`           | INT       | Yes      | -                         | Duration of the generated video                         |
| `ingredients_mode`   | STRING    | No       | "creative"<br />"precise" | Mode for combining ingredients (default: "creative")    |
| `aspect_ratio`       | FLOAT     | No       | 0.4 - 2.5                 | Aspect ratio (width / height) (default: 1.778)          |
| `image_ingredient_1` | IMAGE     | No       | -                         | Image that will be used as ingredient to create a video |
| `image_ingredient_2` | IMAGE     | No       | -                         | Image that will be used as ingredient to create a video |
| `image_ingredient_3` | IMAGE     | No       | -                         | Image that will be used as ingredient to create a video |
| `image_ingredient_4` | IMAGE     | No       | -                         | Image that will be used as ingredient to create a video |
| `image_ingredient_5` | IMAGE     | No       | -                         | Image that will be used as ingredient to create a video |

**Note:** You can provide up to 5 image ingredients, but at least one image is required to generate a video. The node will use all provided images to create the final video composition.

## Outputs

| Output Name | Data Type | Description                                    |
| ----------- | --------- | ---------------------------------------------- |
| `output`    | VIDEO     | The generated video combining all input images |

***

**Source fingerprint (SHA-256):** `dda8f10a58527c2b9037744f59f30821cdde37ad23427b856ba5e699a05acafd`


# PikaStartEndFrameNode2_2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PikaStartEndFrameNode2_2

Complete documentation for the PikaStartEndFrameNode2_2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PikaStartEndFrameNode2_2/en.md)

The PikaFrames v2.2 Node generates a video by combining your first and last frame. You upload two images to define the start and end points, and the AI creates a smooth transition between them to produce a complete video.

## Inputs

| Parameter         | Data Type | Required | Range | Description                                       |
| ----------------- | --------- | -------- | ----- | ------------------------------------------------- |
| `image_start`     | IMAGE     | Yes      | -     | The first image to combine.                       |
| `image_end`       | IMAGE     | Yes      | -     | The last image to combine.                        |
| `prompt_text`     | STRING    | Yes      | -     | Text prompt describing the desired video content. |
| `negative_prompt` | STRING    | Yes      | -     | Text describing what to avoid in the video.       |
| `seed`            | INT       | Yes      | -     | Random seed value for generation consistency.     |
| `resolution`      | STRING    | Yes      | -     | Output video resolution.                          |
| `duration`        | INT       | Yes      | -     | Duration of the generated video.                  |

## Outputs

| Output Name | Data Type | Description                                                                 |
| ----------- | --------- | --------------------------------------------------------------------------- |
| `output`    | VIDEO     | The generated video combining the start and end frames with AI transitions. |

***

**Source fingerprint (SHA-256):** `0a26f6db754c61d1f35e3fd9faceb631a8103ce9ff38190a5dd637991914e238`


# PikaTextToVideoNode2_2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PikaTextToVideoNode2_2

Complete documentation for the PikaTextToVideoNode2_2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PikaTextToVideoNode2_2/en.md)

The Pika Text2Video v2.2 Node sends a text prompt to the Pika API version 2.2 to generate a video. It converts your text description into a video using Pika's AI video generation service. The node allows you to customize various aspects of the video generation process including aspect ratio, duration, and resolution.

## Inputs

| Parameter         | Data Type | Required | Range     | Description                                                                      |
| ----------------- | --------- | -------- | --------- | -------------------------------------------------------------------------------- |
| `prompt_text`     | STRING    | Yes      | -         | The main text description that describes what you want to generate in the video  |
| `negative_prompt` | STRING    | Yes      | -         | Text describing what you don't want to appear in the generated video             |
| `seed`            | INT       | Yes      | -         | A number that controls the randomness of the generation for reproducible results |
| `resolution`      | STRING    | Yes      | -         | The resolution setting for the output video                                      |
| `duration`        | INT       | Yes      | -         | The length of the video in seconds                                               |
| `aspect_ratio`    | FLOAT     | No       | 0.4 - 2.5 | Aspect ratio (width / height) (default: 1.7777777777777777)                      |

## Outputs

| Output Name | Data Type | Description                                         |
| ----------- | --------- | --------------------------------------------------- |
| `output`    | VIDEO     | The generated video file returned from the Pika API |

***

**Source fingerprint (SHA-256):** `b4287519f5d4cc4a1077a58fb13aa99697e3be038a0b382c4b4c9b0e53a0d8a8`


# Pikadditions - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Pikadditions

Complete documentation for the Pikadditions node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Pikadditions/en.md)

The Pikadditions node allows you to add any object or image into your video. You upload a video and specify what you'd like to add to create a seamlessly integrated result. This node uses the Pika API to insert images into videos with natural-looking integration.

## Inputs

| Parameter         | Data Type | Required | Range           | Description                                     |
| ----------------- | --------- | -------- | --------------- | ----------------------------------------------- |
| `video`           | VIDEO     | Yes      | -               | The video to add an image to.                   |
| `image`           | IMAGE     | Yes      | -               | The image to add to the video.                  |
| `prompt_text`     | STRING    | Yes      | -               | Text description of what to add to the video.   |
| `negative_prompt` | STRING    | Yes      | -               | Text description of what to avoid in the video. |
| `seed`            | INT       | Yes      | 0 to 4294967295 | Random seed value for reproducible results.     |

## Outputs

| Output Name | Data Type | Description                                  |
| ----------- | --------- | -------------------------------------------- |
| `output`    | VIDEO     | The processed video with the image inserted. |

***

**Source fingerprint (SHA-256):** `cf7bb4ee0a672e20c0ffc128fa95df43e05356aea03b2070f928a0263aff6234`


# Pikaffects - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Pikaffects

Complete documentation for the Pikaffects node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Pikaffects/en.md)

The Pikaffects node generates videos with various visual effects applied to an input image. It uses Pika's video generation API to transform static images into animated videos with specific effects like melting, exploding, or levitating. The node requires an API key and authentication token to access the Pika service.

## Inputs

| Parameter         | Data Type | Required | Range                                                                                                                                                                                                                           | Description                                                             |
| ----------------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------- |
| `image`           | IMAGE     | Yes      | -                                                                                                                                                                                                                               | The reference image to apply the Pikaffect to.                          |
| `pikaffect`       | COMBO     | Yes      | "Cake-ify"<br />"Crumble"<br />"Crush"<br />"Decapitate"<br />"Deflate"<br />"Dissolve"<br />"Explode"<br />"Eye-pop"<br />"Inflate"<br />"Levitate"<br />"Melt"<br />"Peel"<br />"Poke"<br />"Squish"<br />"Ta-da"<br />"Tear" | The specific visual effect to apply to the image (default: "Cake-ify"). |
| `prompt_text`     | STRING    | Yes      | -                                                                                                                                                                                                                               | Text description guiding the video generation.                          |
| `negative_prompt` | STRING    | Yes      | -                                                                                                                                                                                                                               | Text description of what to avoid in the generated video.               |
| `seed`            | INT       | Yes      | 0 to 4294967295                                                                                                                                                                                                                 | Random seed value for reproducible results.                             |

## Outputs

| Output Name | Data Type | Description                                     |
| ----------- | --------- | ----------------------------------------------- |
| `output`    | VIDEO     | The generated video with the applied Pikaffect. |

***

**Source fingerprint (SHA-256):** `68ebbee465763d463bf73678254eed38d37ebacb1c62d386bbe66961deffd5a8`


# Pikaswaps - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Pikaswaps

Complete documentation for the Pikaswaps node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Pikaswaps/en.md)

The Pika Swaps node replaces objects or regions in your video with a new image. You define the areas to replace using a mask, and the node seamlessly swaps the specified content throughout the video sequence.

## Inputs

| Parameter         | Data Type | Required | Range           | Description                                               |
| ----------------- | --------- | -------- | --------------- | --------------------------------------------------------- |
| `video`           | VIDEO     | Yes      | -               | The video to swap an object in.                           |
| `image`           | IMAGE     | Yes      | -               | The image used to replace the masked object in the video. |
| `mask`            | MASK      | Yes      | -               | Use the mask to define areas in the video to replace.     |
| `prompt_text`     | STRING    | Yes      | -               | Text prompt describing the desired replacement.           |
| `negative_prompt` | STRING    | Yes      | -               | Text prompt describing what to avoid in the replacement.  |
| `seed`            | INT       | Yes      | 0 to 4294967295 | Random seed value for consistent results.                 |

**Note:** This node requires all input parameters to be provided. The `video`, `image`, and `mask` work together to define the replacement operation, where the mask specifies which areas of the video will be replaced with the provided image.

## Outputs

| Output Name | Data Type | Description                                                       |
| ----------- | --------- | ----------------------------------------------------------------- |
| `output`    | VIDEO     | The processed video with the specified object or region replaced. |

***

**Source fingerprint (SHA-256):** `007b7bc429fdada2fb8910392b056ae3a98d482cce9e280bdcd162ede497eb03`


# SaveLoRA - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveLoRA

Complete documentation for the SaveLoRA node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveLoRA/en.md)

The SaveLoRA node saves a LoRA (Low-Rank Adaptation) model to a file. It takes a LoRA model as input and writes it to a `.safetensors` file in the output directory. You can specify a filename prefix and an optional step count to be included in the final filename.

## Inputs

| Parameter | Data Type   | Required | Range | Description                                                                               |
| --------- | ----------- | -------- | ----- | ----------------------------------------------------------------------------------------- |
| `lora`    | LORA\_MODEL | Yes      | N/A   | The LoRA model to save. Do not use the model with LoRA layers.                            |
| `prefix`  | STRING      | Yes      | N/A   | The prefix to use for the saved LoRA file (default: "loras/ComfyUI\_trained\_lora").      |
| `steps`   | INT         | No       | N/A   | Optional: The number of steps the LoRA has been trained for, used to name the saved file. |

**Note:** The `lora` input must be a pure LoRA model. Do not provide a base model that has LoRA layers applied to it.

## Outputs

| Output Name | Data Type | Description                                                                                         |
| ----------- | --------- | --------------------------------------------------------------------------------------------------- |
| *None*      | N/A       | This node does not output any data to the workflow. It is an output node that saves a file to disk. |

***

**Source fingerprint (SHA-256):** `0d9bb1adef75214e3ecf5a16f046761d547d21bea41488b0ce80cdc05ed2e81b`


# SaveLoRANode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveLoRANode

Complete documentation for the SaveLoRANode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveLoRANode/en.md)

The SaveLoRA node saves LoRA (Low-Rank Adaptation) models to your output directory. It takes a LoRA model as input and creates a safetensors file with an automatically generated filename. You can customize the filename prefix and optionally include the training step count in the filename for better organization.

## Inputs

| Parameter | Data Type   | Required | Range | Description                                                                               |
| --------- | ----------- | -------- | ----- | ----------------------------------------------------------------------------------------- |
| `lora`    | LORA\_MODEL | Yes      | -     | The LoRA model to save. Do not use the model with LoRA layers.                            |
| `prefix`  | STRING      | Yes      | -     | The prefix to use for the saved LoRA file (default: "loras/ComfyUI\_trained\_lora").      |
| `steps`   | INT         | No       | -     | Optional: The number of steps the LoRA has been trained for, used to name the saved file. |

## Outputs

| Output Name | Data Type | Description                                                                             |
| ----------- | --------- | --------------------------------------------------------------------------------------- |
| *None*      | -         | This node does not return any outputs but saves the LoRA model to the output directory. |

***

**Source fingerprint (SHA-256):** `06a1067433aa4b720b51050b09fbad4870caf12c5e92f788d44ea022a39efef4`


# SelectCLIPDevice - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SelectCLIPDevice

Complete documentation for the SelectCLIPDevice node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SelectCLIPDevice/en.md)

## Overview

The Select CLIP Device node lets you choose which device (CPU or a specific GPU) the CLIP text encoder runs on. By default, the device is assigned by the model loader, but you can override it to use the CPU or a particular GPU. If the requested device doesn't exist on your machine, the node simply passes the CLIP through unchanged and logs a message instead of causing an error.

## Inputs

| Parameter | Data Type | Required | Range                                                                                                                                            | Description                                                                                                                                                                                                                                 |
| --------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip`    | CLIP      | Yes      |                                                                                                                                                  | The CLIP text encoder to assign to a specific device.                                                                                                                                                                                       |
| `device`  | COMBO     | Yes      | `"default"`<br />`"cpu"`<br />`"gpu:0"`<br />`"gpu:1"`<br />`"gpu:2"`<br />`"gpu:3"`<br />`"gpu:4"`<br />`"gpu:5"`<br />`"gpu:6"`<br />`"gpu:7"` | The device to place the CLIP text encoder on. `"default"` restores the device assigned by the loader. `"cpu"` pins both the load and offload device to CPU. `"gpu:N"` pins the load device to the Nth available GPU (default: `"default"`). |

## Outputs

| Output Name | Data Type | Description                                                                                                                                    |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip`      | CLIP      | The CLIP text encoder assigned to the selected device, or the original CLIP passed through unchanged if the requested device is not available. |

***

**Source fingerprint (SHA-256):** `92af94d9f5eea27095cc008debdf7339d26888a0e2cc8bd71ae9c9ba8718eb01`


# SelectModelDevice - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SelectModelDevice

Complete documentation for the SelectModelDevice node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SelectModelDevice/en.md)

## Overview

The SelectModelDevice node allows you to manually choose which device (CPU or a specific GPU) a diffusion model runs on. It can move a model to a different device, and it handles conflicts with other multi-GPU nodes automatically.

## Inputs

| Parameter | Data Type | Required | Range                                                                                                                                            | Description                                                                                                      |
| --------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      |                                                                                                                                                  | The diffusion model to place on a specific device.                                                               |
| `device`  | COMBO     | Yes      | `"default"`<br />`"cpu"`<br />`"gpu:0"`<br />`"gpu:1"`<br />`"gpu:2"`<br />`"gpu:3"`<br />`"gpu:4"`<br />`"gpu:5"`<br />`"gpu:6"`<br />`"gpu:7"` | The target device for the model. Options are dynamically generated based on available GPUs. (default: "default") |

**Parameter Details:**

* `"default"`: Restores the device assigned by the model loader, even if a previous SelectModelDevice node changed it.
* `"cpu"`: Pins both the load and offload device to the CPU.
* `"gpu:N"`: Pins the load device to the Nth available GPU (e.g., `"gpu:0"` for the first GPU). The offload device is restored to the loader's original choice.

**Important Notes:**

* If the requested device does not exist on the current machine (e.g., a workflow created on a 2-GPU machine is opened on a 1-GPU machine), the node will pass the model through unchanged and log a message instead of failing.
* If the model is already on the requested device, the node takes a fast path and does not reload the model.
* Placing this node *after* a node that has already consumed the model (e.g., a KSampler) is not recommended, as any state changed by the prior node will be observed if the device matches the original.

## Outputs

| Output Name | Data Type | Description                                                                                                                              |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------- |
| `model`     | MODEL     | The diffusion model, now placed on the selected device. If the device was invalid or unavailable, the model is passed through unchanged. |

***

**Source fingerprint (SHA-256):** `02841975f123cc8ae8152ea86f1798e0e7e68255ecd11e04271da886b75eb0fd`


# SelectVAEDevice - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SelectVAEDevice

Complete documentation for the SelectVAEDevice node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SelectVAEDevice/en.md)

## Overview

This node allows you to manually select which GPU device the VAE model should be placed on. By default, the VAE is placed on the device assigned by the model loader, but you can pin it to a specific GPU (e.g., `gpu:0`, `gpu:1`). If the selected device is not available on your machine, the node will pass the VAE through unchanged and log a message instead of failing.

## Inputs

| Parameter | Data Type | Required | Range                                                                                                                               | Description                                                                                                                                                                                                                   |
| --------- | --------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `vae`     | VAE       | Yes      |                                                                                                                                     | The VAE model to assign to a specific device.                                                                                                                                                                                 |
| `device`  | COMBO     | Yes      | `"default"`<br />`"gpu:0"`<br />`"gpu:1"`<br />`"gpu:2"`<br />`"gpu:3"`<br />`"gpu:4"`<br />`"gpu:5"`<br />`"gpu:6"`<br />`"gpu:7"` | The target device for the VAE. `"default"` restores the device assigned by the loader. `"gpu:N"` pins the VAE to the Nth available GPU. CPU is not a supported choice and will be ignored if provided. (default: `"default"`) |

## Outputs

| Output Name | Data Type | Description                                                                                                                                 |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------- |
| `vae`       | VAE       | The VAE model, now assigned to the selected device. If the requested device is unavailable or invalid, the VAE is passed through unchanged. |

***

**Source fingerprint (SHA-256):** `011154043fc02f930b0074de656bb24baf4dfe74bcfd2e89ea76284f0a5b7d8e`


# SoniloTextToMusic - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SoniloTextToMusic

Complete documentation for the SoniloTextToMusic node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SoniloTextToMusic/en.md)

The Sonilo Text to Music node generates music from a text description using Sonilo's AI model. You provide a prompt describing the music you want, and the node sends a request to the Sonilo service to create an audio file. You can specify a target duration or let the model infer it from your prompt.

## Inputs

| Parameter  | Data Type | Required | Range                     | Description                                                                                                                             |
| ---------- | --------- | -------- | ------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`   | STRING    | Yes      | N/A                       | Text prompt describing the music to generate. This is a required field.                                                                 |
| `duration` | INT       | No       | 0 to 360                  | Target duration in seconds. Set to 0 to let the model infer the duration from the prompt. Maximum: 6 minutes (360 seconds). Default: 0. |
| `seed`     | INT       | No       | 0 to 18446744073709551615 | Seed for reproducibility. Currently ignored by the Sonilo service but kept for graph consistency. Default: 0.                           |

**Note:** The `seed` input is provided for workflow consistency but does not currently affect the output of the Sonilo service.

## Outputs

| Output Name | Data Type | Description                           |
| ----------- | --------- | ------------------------------------- |
| `audio`     | AUDIO     | The generated music as an audio file. |

***

**Source fingerprint (SHA-256):** `3c94a2f1004d01d410be089e5dbb926246cca38fdadadee0597c1843ba53883c`


# SoniloVideoToMusic - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SoniloVideoToMusic

Complete documentation for the SoniloVideoToMusic node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SoniloVideoToMusic/en.md)

Generate music from video using Sonilo's AI model. This node analyzes the content of an input video and creates a matching piece of music. It uses an external AI service to process the video and generate the audio.

## Inputs

| Parameter | Data Type | Required | Range                     | Description                                                                                                                                            |
| --------- | --------- | -------- | ------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `video`   | VIDEO     | Yes      | -                         | Input video to generate music from. Maximum duration: 6 minutes.                                                                                       |
| `prompt`  | STRING    | No       | -                         | Optional text prompt to guide music generation. Leave empty for best quality - the model will fully analyze the video content. (default: empty string) |
| `seed`    | INT       | No       | 0 to 18446744073709551615 | Seed for reproducibility. Currently ignored by the Sonilo service but kept for graph consistency. (default: 0)                                         |

## Outputs

| Output Name | Data Type | Description                           |
| ----------- | --------- | ------------------------------------- |
| `audio`     | AUDIO     | The generated music as an audio file. |

***

**Source fingerprint (SHA-256):** `6c7965a4cc31d9fce6711b57052fdfbff37ba9decd086b18587ff39cc4fc3a0b`


# StabilityAudioInpaint - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityAudioInpaint

Complete documentation for the StabilityAudioInpaint node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityAudioInpaint/en.md)

Transforms part of an existing audio sample using text instructions. This node allows you to modify specific sections of audio by providing descriptive prompts, effectively "inpainting" or regenerating selected portions while preserving the rest of the audio.

## Inputs

| Parameter    | Data Type | Required | Range                | Description                                                                                                         |
| ------------ | --------- | -------- | -------------------- | ------------------------------------------------------------------------------------------------------------------- |
| `model`      | STRING    | Yes      | `"stable-audio-2.5"` | The AI model to use for audio inpainting.                                                                           |
| `prompt`     | STRING    | Yes      |                      | Text description guiding how the audio should be transformed (default: empty). Maximum length is 10,000 characters. |
| `audio`      | AUDIO     | Yes      |                      | Input audio file to transform. Audio must be between 6 and 190 seconds long.                                        |
| `duration`   | INT       | No       | 1 to 190             | Controls the duration in seconds of the generated audio (default: 190).                                             |
| `seed`       | INT       | No       | 0 to 4294967294      | The random seed used for generation (default: 0).                                                                   |
| `steps`      | INT       | No       | 4 to 8               | Controls the number of sampling steps (default: 8).                                                                 |
| `mask_start` | INT       | No       | 0 to 190             | Starting position in seconds for the audio section to transform (default: 30).                                      |
| `mask_end`   | INT       | No       | 0 to 190             | Ending position in seconds for the audio section to transform (default: 190).                                       |

**Note:** The `mask_end` value must be greater than the `mask_start` value. The input audio must be between 6 and 190 seconds in duration.

## Outputs

| Output Name | Data Type | Description                                                                               |
| ----------- | --------- | ----------------------------------------------------------------------------------------- |
| `audio`     | AUDIO     | The transformed audio output with the specified section modified according to the prompt. |

***

**Source fingerprint (SHA-256):** `c00d84db73dfcd708495d7a04e21a2378880ca6ceb906473a45dcc1dae20bf79`


# StabilityAudioToAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityAudioToAudio

Complete documentation for the StabilityAudioToAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityAudioToAudio/en.md)

Transforms existing audio samples into new high-quality compositions using text instructions. This node takes an input audio file and modifies it based on your text prompt to create new audio content.

## Inputs

| Parameter  | Data Type | Required | Range              | Description                                                                                            |
| ---------- | --------- | -------- | ------------------ | ------------------------------------------------------------------------------------------------------ |
| `model`    | COMBO     | Yes      | "stable-audio-2.5" | The AI model to use for audio transformation                                                           |
| `prompt`   | STRING    | Yes      |                    | Text instructions describing how to transform the audio (default: empty, max length: 10000 characters) |
| `audio`    | AUDIO     | Yes      |                    | Audio must be between 6 and 190 seconds long                                                           |
| `duration` | INT       | No       | 1-190              | Controls the duration in seconds of the generated audio (default: 190)                                 |
| `seed`     | INT       | No       | 0-4294967294       | The random seed used for generation (default: 0)                                                       |
| `steps`    | INT       | No       | 4-8                | Controls the number of sampling steps (default: 8)                                                     |
| `strength` | FLOAT     | No       | 0.01-1.0           | Parameter controls how much influence the audio parameter has on the generated audio (default: 1.0)    |

**Note:** The input audio must be between 6 and 190 seconds in duration. The prompt text has a maximum length of 10,000 characters.

## Outputs

| Output Name | Data Type | Description                                                              |
| ----------- | --------- | ------------------------------------------------------------------------ |
| `audio`     | AUDIO     | The transformed audio generated based on the input audio and text prompt |

***

**Source fingerprint (SHA-256):** `4d320c851a58b58d1a744ca64295fe0cf3002455944ea1c5484b0c2df3ecd4d5`


# StabilityTextToAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityTextToAudio

Complete documentation for the StabilityTextToAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityTextToAudio/en.md)

Generates high-quality music and sound effects from text descriptions. This node uses Stability AI's audio generation technology to create audio content based on your text prompts.

## Inputs

| Parameter  | Data Type | Required | Range                | Description                                                                 |
| ---------- | --------- | -------- | -------------------- | --------------------------------------------------------------------------- |
| `model`    | COMBO     | Yes      | `"stable-audio-2.5"` | The audio generation model to use (default: "stable-audio-2.5")             |
| `prompt`   | STRING    | Yes      | -                    | The text description used to generate audio content (default: empty string) |
| `duration` | INT       | No       | 1-190                | Controls the duration in seconds of the generated audio (default: 190)      |
| `seed`     | INT       | No       | 0-4294967294         | The random seed used for generation (default: 0)                            |
| `steps`    | INT       | No       | 4-8                  | Controls the number of sampling steps (default: 8)                          |

## Outputs

| Output Name | Data Type | Description                                       |
| ----------- | --------- | ------------------------------------------------- |
| `audio`     | AUDIO     | The generated audio file based on the text prompt |

***

**Source fingerprint (SHA-256):** `123b166c3879b18854b8d3cf039576d76925664baac63a816a1639d764d869f7`


# VAESave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAESave

Complete documentation for the VAESave node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The VAESave node is designed for saving VAE models along with their metadata, including prompts and additional PNG information, to a specified output directory. It encapsulates the functionality to serialize the model state and associated information into a file, facilitating the preservation and sharing of trained models.

## Inputs

| Parameter         | Data Type | Description                                                                                                                                     |
| ----------------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| `vae`             | VAE       | The VAE model to be saved. This parameter is crucial as it represents the model whose state is to be serialized and stored.                     |
| `filename_prefix` | STRING    | A prefix for the filename under which the model and its metadata will be saved. This allows for organized storage and easy retrieval of models. |

## Outputs

The node doesn't have output types.


# Flux 1.1 [pro] Ultra Image - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/bfl/flux-1-1-pro-ultra-image

Create images using Black Forest Labs' high-resolution image generation API

<img alt="ComfyUI Native Flux 1.1 [pro] Ultra Image node" />

The Flux 1.1 \[pro] Ultra Image node allows you to generate ultra-high-resolution images through text prompts, directly connecting to Black Forest Labs' latest image generation API.

This node supports two main usage modes:

1. **Text-to-Image**: Generate high-quality images from text prompts (when no image input is used)
2. **Image-to-Image**: Combine existing images with prompts to create new images that blend features from both (Remix mode)

This node supports Ultra mode through API calls, capable of generating images at 4 times the resolution of standard Flux 1.1 \[pro] (up to 4MP), without sacrificing prompt adherence, and maintaining super-fast generation times of just 10 seconds. Compared to other high-resolution models, it's more than 2.5 times faster.

## Parameter Description

### Basic Parameters

| Parameter          | Type    | Default | Description                                                                                                                                                                                                                      |
| ------------------ | ------- | ------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| prompt             | String  | ""      | Text description for generating the image                                                                                                                                                                                        |
| prompt\_upsampling | Boolean | False   | Whether to use prompt upsampling technique to enhance details. When enabled, automatically modifies prompts for more creative generation, but results become non-deterministic (same seed won't produce exactly the same result) |
| seed               | Integer | 0       | Random seed value, controls generation randomness                                                                                                                                                                                |
| aspect\_ratio      | String  | "16:9"  | Width-to-height ratio of the image, must be between 1:4 and 4:1                                                                                                                                                                  |
| raw                | Boolean | False   | When set to True, generates less processed, more natural-looking images                                                                                                                                                          |

### Optional Parameters

| Parameter               | Type  | Default | Description                                                                                                                                               |
| ----------------------- | ----- | ------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- |
| image\_prompt           | Image | None    | Optional input, used for Image-to-Image (Remix) mode                                                                                                      |
| image\_prompt\_strength | Float | 0.1     | Active when `image_prompt` is input, adjusts the blend between prompt and image prompt. Higher values make output closer to input image, range is 0.0-1.0 |

### Output

| Output | Type  | Description                            |
| ------ | ----- | -------------------------------------- |
| IMAGE  | Image | Generated high-resolution image result |

## Usage Examples

Please visit the tutorial below to see corresponding usage examples

* [Flux 1.1 Pro Ultra Image Partner Nodes ComfyUI Official Example Workflow](/tutorials/partner-nodes/black-forest-labs/flux-1-1-pro-ultra-image)

## How It Works

Flux 1.1 \[pro] Ultra mode uses optimized deep learning architecture and efficient GPU acceleration technology to achieve high-resolution image generation without sacrificing speed. When a request is sent to the API, the system parses the prompt, applies appropriate parameters, then computes the image in parallel, finally generating and returning the high-resolution result.

Compared to regular models, Ultra mode particularly focuses on detail preservation and consistency at large scales, ensuring impressive quality even at 4MP high resolution.

## Source Code

\[Node Source Code (Updated on 2025-05-03)]

```python theme={null}
class FluxProUltraImageNode(ComfyNodeABC):
    """
    Generates images synchronously based on prompt and resolution.
    """

    MINIMUM_RATIO = 1 / 4
    MAXIMUM_RATIO = 4 / 1
    MINIMUM_RATIO_STR = "1:4"
    MAXIMUM_RATIO_STR = "4:1"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation",
                    },
                ),
                "prompt_upsampling": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                        "tooltip": "Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result).",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "The random seed used for creating the noise.",
                    },
                ),
                "aspect_ratio": (
                    IO.STRING,
                    {
                        "default": "16:9",
                        "tooltip": "Aspect ratio of image; must be between 1:4 and 4:1.",
                    },
                ),
                "raw": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                        "tooltip": "When True, generate less processed, more natural-looking images.",
                    },
                ),
            },
            "optional": {
                "image_prompt": (IO.IMAGE,),
                "image_prompt_strength": (
                    IO.FLOAT,
                    {
                        "default": 0.1,
                        "min": 0.0,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Blend between the prompt and the image prompt.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    @classmethod
    def VALIDATE_INPUTS(cls, aspect_ratio: str):
        try:
            validate_aspect_ratio(
                aspect_ratio,
                minimum_ratio=cls.MINIMUM_RATIO,
                maximum_ratio=cls.MAXIMUM_RATIO,
                minimum_ratio_str=cls.MINIMUM_RATIO_STR,
                maximum_ratio_str=cls.MAXIMUM_RATIO_STR,
            )
        except Exception as e:
            return str(e)
        return True

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/bfl"

    def api_call(
        self,
        prompt: str,
        aspect_ratio: str,
        prompt_upsampling=False,
        raw=False,
        seed=0,
        image_prompt=None,
        image_prompt_strength=0.1,
        auth_token=None,
        **kwargs,
    ):
        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/bfl/flux-pro-1.1-ultra/generate",
                method=HttpMethod.POST,
                request_model=BFLFluxProUltraGenerateRequest,
                response_model=BFLFluxProGenerateResponse,
            ),
            request=BFLFluxProUltraGenerateRequest(
                prompt=prompt,
                prompt_upsampling=prompt_upsampling,
                seed=seed,
                aspect_ratio=validate_aspect_ratio(
                    aspect_ratio,
                    minimum_ratio=self.MINIMUM_RATIO,
                    maximum_ratio=self.MAXIMUM_RATIO,
                    minimum_ratio_str=self.MINIMUM_RATIO_STR,
                    maximum_ratio_str=self.MAXIMUM_RATIO_STR,
                ),
                raw=raw,
                image_prompt=(
                    image_prompt
                    if image_prompt is None
                    else convert_image_to_base64(image_prompt)
                ),
                image_prompt_strength=(
                    None if image_prompt is None else round(image_prompt_strength, 2)
                ),
            ),
            auth_token=auth_token,
        )
        output_image = handle_bfl_synchronous_operation(operation)
        return (output_image,)
```


# Ideogram V1 - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/ideogram/ideogram-v1

Node for creating precise text rendering images using Ideogram API

<img alt="ComfyUI Native Ideogram V1 Node" />

The Ideogram V1 node allows you to generate images with high-quality text rendering capabilities using Ideogram's text-to-image API.

## Parameter Description

### Required Parameters

| Parameter             | Type    | Default | Description                                                                 |
| --------------------- | ------- | ------- | --------------------------------------------------------------------------- |
| prompt                | string  | ""      | Text prompt describing the content to generate                              |
| turbo                 | boolean | False   | Whether to use turbo mode (faster but possibly lower quality)               |
| aspect\_ratio         | select  | "1:1"   | Image aspect ratio                                                          |
| magic\_prompt\_option | select  | "AUTO"  | Determines whether to use MagicPrompt in generation, options: AUTO, ON, OFF |
| seed                  | integer | 0       | Random seed value (0-2147483647)                                            |
| negative\_prompt      | string  | ""      | Specifies elements you don't want in the image                              |
| num\_images           | integer | 1       | Number of images to generate (1-8)                                          |

### Output

| Output | Type  | Description            |
| ------ | ----- | ---------------------- |
| IMAGE  | image | Generated image result |

## Source Code

\[Node Source Code (Updated on 2025-05-03)]

```python theme={null}
class IdeogramV1(ComfyNodeABC):
    """
    Generates images synchronously using the Ideogram V1 model.

    Images links are available for a limited period of time; if you would like to keep the image, you must download it.
    """

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls) -> InputTypeDict:
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation",
                    },
                ),
                "turbo": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                        "tooltip": "Whether to use turbo mode (faster generation, potentially lower quality)",
                    }
                ),
            },
            "optional": {
                "aspect_ratio": (
                    IO.COMBO,
                    {
                        "options": list(V1_V2_RATIO_MAP.keys()),
                        "default": "1:1",
                        "tooltip": "The aspect ratio for image generation.",
                    },
                ),
                "magic_prompt_option": (
                    IO.COMBO,
                    {
                        "options": ["AUTO", "ON", "OFF"],
                        "default": "AUTO",
                        "tooltip": "Determine if MagicPrompt should be used in generation",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2147483647,
                        "step": 1,
                        "control_after_generate": True,
                        "display": "number",
                    },
                ),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Description of what to exclude from the image",
                    },
                ),
                "num_images": (
                    IO.INT,
                    {"default": 1, "min": 1, "max": 8, "step": 1, "display": "number"},
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = (IO.IMAGE,)
    FUNCTION = "api_call"
    CATEGORY = "api node/image/ideogram/v1"
    DESCRIPTION = cleandoc(__doc__ or "")
    API_NODE = True

    def api_call(
        self,
        prompt,
        turbo=False,
        aspect_ratio="1:1",
        magic_prompt_option="AUTO",
        seed=0,
        negative_prompt="",
        num_images=1,
        auth_token=None,
    ):
        # Determine the model based on turbo setting
        aspect_ratio = V1_V2_RATIO_MAP.get(aspect_ratio, None)
        model = "V_1_TURBO" if turbo else "V_1"

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/ideogram/generate",
                method=HttpMethod.POST,
                request_model=IdeogramGenerateRequest,
                response_model=IdeogramGenerateResponse,
            ),
            request=IdeogramGenerateRequest(
                image_request=ImageRequest(
                    prompt=prompt,
                    model=model,
                    num_images=num_images,
                    seed=seed,
                    aspect_ratio=aspect_ratio if aspect_ratio != "ASPECT_1_1" else None,
                    magic_prompt_option=(
                        magic_prompt_option if magic_prompt_option != "AUTO" else None
                    ),
                    negative_prompt=negative_prompt if negative_prompt else None,
                )
            ),
            auth_token=auth_token,
        )

        response = operation.execute()

        if not response.data or len(response.data) == 0:
            raise Exception("No images were generated in the response")

        image_urls = [image_data.url for image_data in response.data if image_data.url]

        if not image_urls:
            raise Exception("No image URLs were generated in the response")

        return (download_and_process_images(image_urls),)
```


# Ideogram V2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/ideogram/ideogram-v2

Node for creating high-quality images and text rendering using Ideogram V2 API

<img alt="ComfyUI Built-in Ideogram V2 Node" />

The Ideogram V2 node allows you to generate more refined images using Ideogram's second-generation AI model, with significant improvements in text rendering, image quality, and overall aesthetics.

## Parameters

### Required Parameters

| Parameter | Type    | Default | Description                                                           |
| --------- | ------- | ------- | --------------------------------------------------------------------- |
| prompt    | string  | ""      | Text prompt describing the content to generate                        |
| turbo     | boolean | False   | Whether to use turbo mode (faster generation, possibly lower quality) |

### Optional Parameters

| Parameter             | Type     | Default | Description                                                                                                     |
| --------------------- | -------- | ------- | --------------------------------------------------------------------------------------------------------------- |
| aspect\_ratio         | dropdown | "1:1"   | Image aspect ratio, effective when resolution is set to "Auto"                                                  |
| resolution            | dropdown | "Auto"  | Output image resolution, if not set to "Auto", it will override the aspect\_ratio setting                       |
| magic\_prompt\_option | dropdown | "AUTO"  | Determines whether to use MagicPrompt feature during generation, options are \["AUTO", "ON", "OFF"]             |
| seed                  | integer  | 0       | Random seed value, range 0-2147483647                                                                           |
| style\_type           | dropdown | "NONE"  | Generation style type (V2 only), options are \["AUTO", "GENERAL", "REALISTIC", "DESIGN", "RENDER\_3D", "ANIME"] |
| negative\_prompt      | string   | ""      | Specifies elements you don't want to appear in the image                                                        |
| num\_images           | integer  | 1       | Number of images to generate, range 1-8                                                                         |

### Output

| Output | Type  | Description        |
| ------ | ----- | ------------------ |
| IMAGE  | image | Generated image(s) |

## Source Code

\[Node Source Code (Updated on 2025-05-03)]

```python theme={null}

class IdeogramV2(ComfyNodeABC):
    """
    Generates images synchronously using the Ideogram V2 model.

    Images links are available for a limited period of time; if you would like to keep the image, you must download it.
    """

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls) -> InputTypeDict:
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation",
                    },
                ),
                "turbo": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                        "tooltip": "Whether to use turbo mode (faster generation, potentially lower quality)",
                    }
                ),
            },
            "optional": {
                "aspect_ratio": (
                    IO.COMBO,
                    {
                        "options": list(V1_V2_RATIO_MAP.keys()),
                        "default": "1:1",
                        "tooltip": "The aspect ratio for image generation. Ignored if resolution is not set to AUTO.",
                    },
                ),
                "resolution": (
                    IO.COMBO,
                    {
                        "options": list(V1_V1_RES_MAP.keys()),
                        "default": "Auto",
                        "tooltip": "The resolution for image generation. If not set to AUTO, this overrides the aspect_ratio setting.",
                    },
                ),
                "magic_prompt_option": (
                    IO.COMBO,
                    {
                        "options": ["AUTO", "ON", "OFF"],
                        "default": "AUTO",
                        "tooltip": "Determine if MagicPrompt should be used in generation",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2147483647,
                        "step": 1,
                        "control_after_generate": True,
                        "display": "number",
                    },
                ),
                "style_type": (
                    IO.COMBO,
                    {
                        "options": ["AUTO", "GENERAL", "REALISTIC", "DESIGN", "RENDER_3D", "ANIME"],
                        "default": "NONE",
                        "tooltip": "Style type for generation (V2 only)",
                    },
                ),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Description of what to exclude from the image",
                    },
                ),
                "num_images": (
                    IO.INT,
                    {"default": 1, "min": 1, "max": 8, "step": 1, "display": "number"},
                ),
                #"color_palette": (
                #    IO.STRING,
                #    {
                #        "multiline": False,
                #        "default": "",
                #        "tooltip": "Color palette preset name or hex colors with weights",
                #    },
                #),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = (IO.IMAGE,)
    FUNCTION = "api_call"
    CATEGORY = "api node/image/ideogram/v2"
    DESCRIPTION = cleandoc(__doc__ or "")
    API_NODE = True

    def api_call(
        self,
        prompt,
        turbo=False,
        aspect_ratio="1:1",
        resolution="Auto",
        magic_prompt_option="AUTO",
        seed=0,
        style_type="NONE",
        negative_prompt="",
        num_images=1,
        color_palette="",
        auth_token=None,
    ):
        aspect_ratio = V1_V2_RATIO_MAP.get(aspect_ratio, None)
        resolution = V1_V1_RES_MAP.get(resolution, None)
        # Determine the model based on turbo setting
        model = "V_2_TURBO" if turbo else "V_2"

        # Handle resolution vs aspect_ratio logic
        # If resolution is not AUTO, it overrides aspect_ratio
        final_resolution = None
        final_aspect_ratio = None

        if resolution != "AUTO":
            final_resolution = resolution
        else:
            final_aspect_ratio = aspect_ratio if aspect_ratio != "ASPECT_1_1" else None

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/ideogram/generate",
                method=HttpMethod.POST,
                request_model=IdeogramGenerateRequest,
                response_model=IdeogramGenerateResponse,
            ),
            request=IdeogramGenerateRequest(
                image_request=ImageRequest(
                    prompt=prompt,
                    model=model,
                    num_images=num_images,
                    seed=seed,
                    aspect_ratio=final_aspect_ratio,
                    resolution=final_resolution,
                    magic_prompt_option=(
                        magic_prompt_option if magic_prompt_option != "AUTO" else None
                    ),
                    style_type=style_type if style_type != "NONE" else None,
                    negative_prompt=negative_prompt if negative_prompt else None,
                    color_palette=color_palette if color_palette else None,
                )
            ),
            auth_token=auth_token,
        )

        response = operation.execute()

        if not response.data or len(response.data) == 0:
            raise Exception("No images were generated in the response")

        image_urls = [image_data.url for image_data in response.data if image_data.url]

        if not image_urls:
            raise Exception("No image URLs were generated in the response")

        return (download_and_process_images(image_urls),)

```


# Ideogram V3 - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/ideogram/ideogram-v3

Node for creating top-quality images and text rendering using Ideogram's latest V3 API

<img alt="ComfyUI Native Ideogram V3 Node" />

This node connects to the Ideogram V3 API to perform image generation tasks.

Currently, this node supports two image generation modes:

* **Text-to-Image Mode** - Generate new images from text prompts
* **Inpainting Mode** - Regenerate specific areas by providing an original image and mask

### Text-to-Image Mode

This is the default mode, activated when no image or mask inputs are provided. Simply provide a prompt and the desired parameters:

1. Describe the image you want in the prompt field
2. Select an appropriate aspect ratio or resolution
3. Adjust other parameters like magic prompt, seed, and rendering quality
4. Run the node to generate the image

### Inpainting Mode

**Important Note**: This mode requires both image and mask inputs. If only one is provided, the node will throw an error.

1. Connect the original image to the `image` input port
2. Create a mask with the same dimensions as the original image, where white areas represent parts to be regenerated
3. Connect the mask to the `mask` input port
4. Describe what you want to generate in the masked area in the prompt
5. Run the node to perform local editing

## Parameter Descriptions

### Basic Parameters

| Parameter             | Type   | Default    | Description                                       |
| --------------------- | ------ | ---------- | ------------------------------------------------- |
| prompt                | string | ""         | Text prompt describing the content to generate    |
| aspect\_ratio         | combo  | "1:1"      | Image aspect ratio (text-to-image mode only)      |
| resolution            | combo  | "Auto"     | Image resolution, overrides aspect ratio when set |
| magic\_prompt\_option | combo  | "AUTO"     | Magic prompt enhancement: AUTO, ON, or OFF        |
| seed                  | int    | 0          | Random seed value, 0 for random generation        |
| num\_images           | int    | 1          | Number of images to generate (1-8)                |
| rendering\_speed      | combo  | "BALANCED" | Rendering speed: BALANCED, TURBO, or QUALITY      |

### Optional Parameters

| Parameter | Type  | Description                                                                         |
| --------- | ----- | ----------------------------------------------------------------------------------- |
| image     | image | Input image for inpainting mode (**must be provided with mask**)                    |
| mask      | mask  | Mask for inpainting, white areas will be replaced (**must be provided with image**) |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| IMAGE  | image | Generated image |

## How It Works

The Ideogram V3 node uses state-of-the-art AI models to process user input, capable of understanding complex design intentions and text layout requirements. It supports two main modes:

1. **Generation Mode**: Creates new images from text prompts
2. **Edit Mode**: Uses original image + mask combination, replacing only the areas specified by the mask

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class IdeogramV3(ComfyNodeABC):
    """
    Generates images synchronously using the Ideogram V3 model.

    Supports both regular image generation from text prompts and image editing with mask.
    Images links are available for a limited period of time; if you would like to keep the image, you must download it.
    """

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls) -> InputTypeDict:
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation or editing",
                    },
                ),
            },
            "optional": {
                "image": (
                    IO.IMAGE,
                    {
                        "default": None,
                        "tooltip": "Optional reference image for image editing.",
                    },
                ),
                "mask": (
                    IO.MASK,
                    {
                        "default": None,
                        "tooltip": "Optional mask for inpainting (white areas will be replaced)",
                    },
                ),
                "aspect_ratio": (
                    IO.COMBO,
                    {
                        "options": list(V3_RATIO_MAP.keys()),
                        "default": "1:1",
                        "tooltip": "The aspect ratio for image generation. Ignored if resolution is not set to Auto.",
                    },
                ),
                "resolution": (
                    IO.COMBO,
                    {
                        "options": V3_RESOLUTIONS,
                        "default": "Auto",
                        "tooltip": "The resolution for image generation. If not set to Auto, this overrides the aspect_ratio setting.",
                    },
                ),
                "magic_prompt_option": (
                    IO.COMBO,
                    {
                        "options": ["AUTO", "ON", "OFF"],
                        "default": "AUTO",
                        "tooltip": "Determine if MagicPrompt should be used in generation",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2147483647,
                        "step": 1,
                        "control_after_generate": True,
                        "display": "number",
                    },
                ),
                "num_images": (
                    IO.INT,
                    {"default": 1, "min": 1, "max": 8, "step": 1, "display": "number"},
                ),
                "rendering_speed": (
                    IO.COMBO,
                    {
                        "options": ["BALANCED", "TURBO", "QUALITY"],
                        "default": "BALANCED",
                        "tooltip": "Controls the trade-off between generation speed and quality",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = (IO.IMAGE,)
    FUNCTION = "api_call"
    CATEGORY = "api node/image/ideogram/v3"
    DESCRIPTION = cleandoc(__doc__ or "")
    API_NODE = True

    def api_call(
        self,
        prompt,
        image=None,
        mask=None,
        resolution="Auto",
        aspect_ratio="1:1",
        magic_prompt_option="AUTO",
        seed=0,
        num_images=1,
        rendering_speed="BALANCED",
        auth_token=None,
    ):
        # Check if both image and mask are provided for editing mode
        if image is not None and mask is not None:
            # Edit mode
            path = "/proxy/ideogram/ideogram-v3/edit"

            # Process image and mask
            input_tensor = image.squeeze().cpu()

            # Validate mask dimensions match image
            if mask.shape[1:] != image.shape[1:-1]:
                raise Exception("Mask and Image must be the same size")

            # Process image
            img_np = (input_tensor.numpy() * 255).astype(np.uint8)
            img = Image.fromarray(img_np)
            img_byte_arr = io.BytesIO()
            img.save(img_byte_arr, format="PNG")
            img_byte_arr.seek(0)
            img_binary = img_byte_arr
            img_binary.name = "image.png"

            # Process mask - white areas will be replaced
            mask_np = (mask.squeeze().cpu().numpy() * 255).astype(np.uint8)
            mask_img = Image.fromarray(mask_np)
            mask_byte_arr = io.BytesIO()
            mask_img.save(mask_byte_arr, format="PNG")
            mask_byte_arr.seek(0)
            mask_binary = mask_byte_arr
            mask_binary.name = "mask.png"

            # Create edit request
            edit_request = IdeogramV3EditRequest(
                prompt=prompt,
                rendering_speed=rendering_speed,
            )

            # Add optional parameters
            if magic_prompt_option != "AUTO":
                edit_request.magic_prompt = magic_prompt_option
            if seed != 0:
                edit_request.seed = seed
            if num_images > 1:
                edit_request.num_images = num_images

            # Execute the operation for edit mode
            operation = SynchronousOperation(
                endpoint=ApiEndpoint(
                    path=path,
                    method=HttpMethod.POST,
                    request_model=IdeogramV3EditRequest,
                    response_model=IdeogramGenerateResponse,
                ),
                request=edit_request,
                files={
                    "image": img_binary,
                    "mask": mask_binary,
                },
                content_type="multipart/form-data",
                auth_token=auth_token,
            )

        elif image is not None or mask is not None:
            # If only one of image or mask is provided, raise an error
            raise Exception("Ideogram V3 image editing requires both an image AND a mask")
        else:
            # Generation mode
            path = "/proxy/ideogram/ideogram-v3/generate"

            # Create generation request
            gen_request = IdeogramV3Request(
                prompt=prompt,
                rendering_speed=rendering_speed,
            )

            # Handle resolution vs aspect ratio
            if resolution != "Auto":
                gen_request.resolution = resolution
            elif aspect_ratio != "1:1":
                v3_aspect = V3_RATIO_MAP.get(aspect_ratio)
                if v3_aspect:
                    gen_request.aspect_ratio = v3_aspect

            # Add optional parameters
            if magic_prompt_option != "AUTO":
                gen_request.magic_prompt = magic_prompt_option
            if seed != 0:
                gen_request.seed = seed
            if num_images > 1:
                gen_request.num_images = num_images

            # Execute the operation for generation mode
            operation = SynchronousOperation(
                endpoint=ApiEndpoint(
                    path=path,
                    method=HttpMethod.POST,
                    request_model=IdeogramV3Request,
                    response_model=IdeogramGenerateResponse,
                ),
                request=gen_request,
                auth_token=auth_token,
            )

        # Execute the operation and process response
        response = operation.execute()

        if not response.data or len(response.data) == 0:
            raise Exception("No images were generated in the response")

        image_urls = [image_data.url for image_data in response.data if image_data.url]

        if not image_urls:
            raise Exception("No image URLs were generated in the response")

        return (download_and_process_images(image_urls),)

```


# Luma Image to Image - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/luma/luma-image-to-image

Node for modifying images using Luma AI

<img alt="ComfyUI Built-in Luma Image to Image Node" />

The Luma Image to Image node allows you to modify existing images using Luma AI technology based on text prompts, while preserving certain features and structure of the original image.

## Node Function

This node connects to Luma AI's text-to-image API, enabling users to generate images through detailed text prompts. Luma AI is known for its excellent realism and detail, particularly excelling at generating photorealistic content and artistic style images.

## Parameters

### Basic Parameters

| Parameter            | Type    | Default | Description                                                                             |
| -------------------- | ------- | ------- | --------------------------------------------------------------------------------------- |
| prompt               | string  | ""      | Text prompt describing the content to generate                                          |
| model                | select  | -       | Select which generation model to use                                                    |
| aspect\_ratio        | select  | 16:9    | Set the aspect ratio of the output image                                                |
| seed                 | integer | 0       | Seed value to determine if node should rerun, but actual results don't depend on seed   |
| style\_image\_weight | float   | 1.0     | Weight of the style image, range 0.02-1.0, only effective when style\_image is provided |

### Optional Parameters

Without the following parameter inputs, the node functions in text-to-image mode

| Parameter        | Type      | Description                                                                                                               |
| ---------------- | --------- | ------------------------------------------------------------------------------------------------------------------------- |
| image\_luma\_ref | LUMA\_REF | Luma reference node connection, influences generation results through input images, can consider up to 4 images           |
| style\_image     | image     | Style reference image, uses only 1 image, influences the style of generated images, adjusted through `style_image_weight` |
| character\_image | image     | Adds character features to the generated results, can be a batch of multiple images, up to 4 images                       |

### Output

| Output | Type  | Description         |
| ------ | ----- | ------------------- |
| IMAGE  | image | The generated image |

## Usage Examples

## How It Works

The Luma Image to Image node analyzes the input image and combines it with text prompts to guide the modification process. It uses Luma AI's generation models to make creative changes to images based on prompts.

Node process:

1. First uploads the input image to ComfyAPI
2. Then sends the image URL with the prompt to Luma API
3. Waits for Luma AI to complete processing
4. Downloads and returns the generated image

The image\_weight parameter controls the degree of influence from the original image - values closer to 0 will preserve more of the original image features, while values closer to 1 allow for more substantial modifications.

## Source Code

\[Node Source Code (Updated on 2025-05-05)]

```python theme={null}

class LumaImageModifyNode(ComfyNodeABC):
    """
    Modifies images synchronously based on prompt and aspect ratio.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE,),
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation",
                    },
                ),
                "image_weight": (
                    IO.FLOAT,
                    {
                        "default": 1.0,
                        "min": 0.02,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Weight of the image; the closer to 0.0, the less the image will be modified.",
                    },
                ),
                "model": ([model.value for model in LumaImageModel],),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {},
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        model: str,
        image: torch.Tensor,
        image_weight: float,
        seed,
        auth_token=None,
        **kwargs,
    ):
        # first, upload image
        download_urls = upload_images_to_comfyapi(
            image, max_images=1, auth_token=auth_token
        )
        image_url = download_urls[0]
        # next, make Luma call with download url provided
        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/luma/generations/image",
                method=HttpMethod.POST,
                request_model=LumaImageGenerationRequest,
                response_model=LumaGeneration,
            ),
            request=LumaImageGenerationRequest(
                prompt=prompt,
                model=model,
                modify_image_ref=LumaModifyImageRef(
                    url=image_url, weight=round(image_weight, 2)
                ),
            ),
            auth_token=auth_token,
        )
        response_api: LumaGeneration = operation.execute()

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/luma/generations/{response_api.id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=LumaGeneration,
            ),
            completed_statuses=[LumaState.completed],
            failed_statuses=[LumaState.failed],
            status_extractor=lambda x: x.state,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        img_response = requests.get(response_poll.assets.image)
        img = process_image_response(img_response)
        return (img,)

```


# Luma Reference - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/luma/luma-reference

Helper node providing reference images for Luma image generation

<img alt="ComfyUI Built-in Luma Reference Node" />

The Luma Reference node allows you to set reference images and weights to guide the creation process of Luma image generation nodes, making the generated images closer to specific features of the reference images.

## Node Function

This node works as a helper tool for Luma generation nodes, allowing users to provide reference images to influence generation results. It enables users to set the weight of reference images to control how much they affect the final result.
Multiple Luma Reference nodes can be chained together, with a maximum of 4 working simultaneously according to API requirements.

## Parameters

### Basic Parameters

| Parameter | Type  | Default | Description                                                    |
| --------- | ----- | ------- | -------------------------------------------------------------- |
| image     | Image | -       | Input image used as reference                                  |
| weight    | Float | 1.0     | Controls the strength of the reference image's influence (0-1) |

### Output

| Output    | Type      | Description                                  |
| --------- | --------- | -------------------------------------------- |
| luma\_ref | LUMA\_REF | Reference object containing image and weight |

## Usage Example

<Card title="Luma Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/luma/luma-text-to-image">
  Luma Text to Image Workflow Example
</Card>

## How It Works

The Luma Reference node receives image input and allows setting a weight value. The node doesn't directly generate or modify images but creates a reference object containing image data and weight information, which is then passed to Luma generation nodes.

During the generation process, Luma AI analyzes the features of the reference image and incorporates these features into the generation results based on the set weight. Higher weight values mean the generated image will be closer to the reference image's features, while lower weight values indicate the reference image will only slightly influence the final result.

## Source Code

\[Node Source Code (Updated on 2025-05-03)]

```python theme={null}

class LumaReferenceNode(ComfyNodeABC):
    """
    Holds an image and weight for use with Luma Generate Image node.
    """

    RETURN_TYPES = (LumaIO.LUMA_REF,)
    RETURN_NAMES = ("luma_ref",)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "create_luma_reference"
    CATEGORY = "api node/image/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (
                    IO.IMAGE,
                    {
                        "tooltip": "Image to use as reference.",
                    },
                ),
                "weight": (
                    IO.FLOAT,
                    {
                        "default": 1.0,
                        "min": 0.0,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Weight of image reference.",
                    },
                ),
            },
            "optional": {"luma_ref": (LumaIO.LUMA_REF,)},
        }

    def create_luma_reference(
        self, image: torch.Tensor, weight: float, luma_ref: LumaReferenceChain = None
    ):
        if luma_ref is not None:
            luma_ref = luma_ref.clone()
        else:
            luma_ref = LumaReferenceChain()
        luma_ref.add(LumaReference(image=image, weight=round(weight, 2)))
        return (luma_ref,)

```


# Luma Text to Image - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/luma/luma-text-to-image

A node that converts text descriptions into high-quality images using Luma AI

<img alt="ComfyUI Native Luma Text to Image Node" />

The Luma Text to Image node allows you to create highly realistic and artistic images from text descriptions using Luma AI's advanced image generation capabilities.

## Node Function

This node connects to Luma AI's text-to-image API, enabling users to generate images through detailed text prompts. Luma AI is known for its excellent realism and detail representation, particularly excelling at producing photorealistic content and artistic style images.

## Parameters

### Basic Parameters

| Parameter            | Type    | Default | Description                                                                                                          |
| -------------------- | ------- | ------- | -------------------------------------------------------------------------------------------------------------------- |
| prompt               | String  | ""      | Text prompt describing the content to generate                                                                       |
| model                | Select  | -       | Choose which generation model to use                                                                                 |
| aspect\_ratio        | Select  | 16:9    | Set the output image's aspect ratio                                                                                  |
| seed                 | Integer | 0       | Seed value to determine if the node should re-run, but actual results are independent of the seed                    |
| style\_image\_weight | Float   | 1.0     | Style image weight, range 0.0-1.0, only applies when style\_image is provided, higher means stronger style reference |

### Optional Parameters

| Parameter        | Type      | Description                                                                              |
| ---------------- | --------- | ---------------------------------------------------------------------------------------- |
| image\_luma\_ref | LUMA\_REF | Luma reference node connection to influence generation with input images; up to 4 images |
| style\_image     | Image     | Style reference image; only 1 image will be used                                         |
| character\_image | Image     | Character reference images; can be a batch of multiple, up to 4 images                   |

### Output

| Output | Type  | Description            |
| ------ | ----- | ---------------------- |
| IMAGE  | Image | Generated image result |

## Usage Example

<Card title="Luma Text to Image Usage Example" icon="book" href="/tutorials/partner-nodes/luma/luma-text-to-image">
  Detailed guide for Luma Text to Image workflow
</Card>

## How It Works

The Luma Text to Image node analyzes the text prompt provided by the user and creates corresponding images through Luma AI's generation models. This process uses deep learning technology to understand text descriptions and convert them into visual representations. Users can fine-tune the generation process by adjusting various parameters, including resolution, guidance scale, and negative prompts.

Additionally, the node supports using reference images and concept guidance to further influence the generation results, allowing creators to more precisely achieve their creative vision.

## Source Code

\[Node Source Code (Updated on 2025-05-03)]

```python theme={null}

class LumaImageGenerationNode(ComfyNodeABC):
    """
    Generates images synchronously based on prompt and aspect ratio.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation",
                    },
                ),
                "model": ([model.value for model in LumaImageModel],),
                "aspect_ratio": (
                    [ratio.value for ratio in LumaAspectRatio],
                    {
                        "default": LumaAspectRatio.ratio_16_9,
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
                "style_image_weight": (
                    IO.FLOAT,
                    {
                        "default": 1.0,
                        "min": 0.0,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Weight of style image. Ignored if no style_image provided.",
                    },
                ),
            },
            "optional": {
                "image_luma_ref": (
                    LumaIO.LUMA_REF,
                    {
                        "tooltip": "Luma Reference node connection to influence generation with input images; up to 4 images can be considered."
                    },
                ),
                "style_image": (
                    IO.IMAGE,
                    {"tooltip": "Style reference image; only 1 image will be used."},
                ),
                "character_image": (
                    IO.IMAGE,
                    {
                        "tooltip": "Character reference images; can be a batch of multiple, up to 4 images can be considered."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        model: str,
        aspect_ratio: str,
        seed,
        style_image_weight: float,
        image_luma_ref: LumaReferenceChain = None,
        style_image: torch.Tensor = None,
        character_image: torch.Tensor = None,
        auth_token=None,
        **kwargs,
    ):
        # handle image_luma_ref
        api_image_ref = None
        if image_luma_ref is not None:
            api_image_ref = self._convert_luma_refs(
                image_luma_ref, max_refs=4, auth_token=auth_token
            )
        # handle style_luma_ref
        api_style_ref = None
        if style_image is not None:
            api_style_ref = self._convert_style_image(
                style_image, weight=style_image_weight, auth_token=auth_token
            )
        # handle character_ref images
        character_ref = None
        if character_image is not None:
            download_urls = upload_images_to_comfyapi(
                character_image, max_images=4, auth_token=auth_token
            )
            character_ref = LumaCharacterRef(
                identity0=LumaImageIdentity(images=download_urls)
            )

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/luma/generations/image",
                method=HttpMethod.POST,
                request_model=LumaImageGenerationRequest,
                response_model=LumaGeneration,
            ),
            request=LumaImageGenerationRequest(
                prompt=prompt,
                model=model,
                aspect_ratio=aspect_ratio,
                image_ref=api_image_ref,
                style_ref=api_style_ref,
                character_ref=character_ref,
            ),
            auth_token=auth_token,
        )
        response_api: LumaGeneration = operation.execute()

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/luma/generations/{response_api.id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=LumaGeneration,
            ),
            completed_statuses=[LumaState.completed],
            failed_statuses=[LumaState.failed],
            status_extractor=lambda x: x.state,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        img_response = requests.get(response_poll.assets.image)
        img = process_image_response(img_response)
        return (img,)

    def _convert_luma_refs(
        self, luma_ref: LumaReferenceChain, max_refs: int, auth_token=None
    ):
        luma_urls = []
        ref_count = 0
        for ref in luma_ref.refs:
            download_urls = upload_images_to_comfyapi(
                ref.image, max_images=1, auth_token=auth_token
            )
            luma_urls.append(download_urls[0])
            ref_count += 1
            if ref_count >= max_refs:
                break
        return luma_ref.create_api_model(download_urls=luma_urls, max_refs=max_refs)

    def _convert_style_image(
        self, style_image: torch.Tensor, weight: float, auth_token=None
    ):
        chain = LumaReferenceChain(
            first_ref=LumaReference(image=style_image, weight=weight)
        )
        return self._convert_luma_refs(chain, max_refs=1, auth_token=auth_token)

```


# OpenAI DALL·E 2 - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/openai/openai-dalle2

Node for generating images using OpenAI's DALL·E 2 model

<img alt="ComfyUI Native Stability AI Stable Image Ultra Node" />

The OpenAI DALL·E 2 node allows you to use OpenAI's DALL·E 2 API to generate creative images from text descriptions.

## Parameters

### Basic Parameters

| Parameter | Type    | Default     | Description                                                                                          |
| --------- | ------- | ----------- | ---------------------------------------------------------------------------------------------------- |
| prompt    | string  | ""          | Text prompt for DALL·E to generate images, supports multi-line input                                 |
| seed      | integer | 0           | The result is not actually related to the seed, this parameter only determines whether to re-execute |
| size      | select  | "1024x1024" | Output image size, options: 256x256, 512x512, 1024x1024                                              |
| n         | integer | 1           | Number of images to generate, range 1-8                                                              |

### Optional Parameters

| Parameter | Type  | Default | Description                                                 |
| --------- | ----- | ------- | ----------------------------------------------------------- |
| image     | image | None    | Optional reference image for image editing                  |
| mask      | mask  | None    | Optional mask for inpainting (white areas will be replaced) |

### Output

| Output | Type  | Description        |
| ------ | ----- | ------------------ |
| IMAGE  | image | Generated image(s) |

## Features

* Basic function: Generate images from text prompts
* Image editing: When both image and mask parameters are provided, performs image editing (white masked areas will be replaced)

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class OpenAIDalle2(ComfyNodeABC):
    """
    Generates images synchronously via OpenAI's DALL·E 2 endpoint.

    Uses the proxy at /proxy/openai/images/generations. Returned URLs are short‑lived,
    so download or cache results if you need to keep them.
    """

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls) -> InputTypeDict:
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text prompt for DALL·E",
                    },
                ),
            },
            "optional": {
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2**31 - 1,
                        "step": 1,
                        "display": "number",
                        "control_after_generate": True,
                        "tooltip": "not implemented yet in backend",
                    },
                ),
                "size": (
                    IO.COMBO,
                    {
                        "options": ["256x256", "512x512", "1024x1024"],
                        "default": "1024x1024",
                        "tooltip": "Image size",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 8,
                        "step": 1,
                        "display": "number",
                        "tooltip": "How many images to generate",
                    },
                ),
                "image": (
                    IO.IMAGE,
                    {
                        "default": None,
                        "tooltip": "Optional reference image for image editing.",
                    },
                ),
                "mask": (
                    IO.MASK,
                    {
                        "default": None,
                        "tooltip": "Optional mask for inpainting (white areas will be replaced)",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = (IO.IMAGE,)
    FUNCTION = "api_call"
    CATEGORY = "api node/image/openai"
    DESCRIPTION = cleandoc(__doc__ or "")
    API_NODE = True

    def api_call(
        self,
        prompt,
        seed=0,
        image=None,
        mask=None,
        n=1,
        size="1024x1024",
        auth_token=None,
    ):
        model = "dall-e-2"
        path = "/proxy/openai/images/generations"
        content_type = "application/json"
        request_class = OpenAIImageGenerationRequest
        img_binary = None

        if image is not None and mask is not None:
            path = "/proxy/openai/images/edits"
            content_type = "multipart/form-data"
            request_class = OpenAIImageEditRequest

            input_tensor = image.squeeze().cpu()
            height, width, channels = input_tensor.shape
            rgba_tensor = torch.ones(height, width, 4, device="cpu")
            rgba_tensor[:, :, :channels] = input_tensor

            if mask.shape[1:] != image.shape[1:-1]:
                raise Exception("Mask and Image must be the same size")
            rgba_tensor[:, :, 3] = 1 - mask.squeeze().cpu()

            rgba_tensor = downscale_image_tensor(rgba_tensor.unsqueeze(0)).squeeze()

            image_np = (rgba_tensor.numpy() * 255).astype(np.uint8)
            img = Image.fromarray(image_np)
            img_byte_arr = io.BytesIO()
            img.save(img_byte_arr, format="PNG")
            img_byte_arr.seek(0)
            img_binary = img_byte_arr  # .getvalue()
            img_binary.name = "image.png"
        elif image is not None or mask is not None:
            raise Exception("Dall-E 2 image editing requires an image AND a mask")

        # Build the operation
        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=path,
                method=HttpMethod.POST,
                request_model=request_class,
                response_model=OpenAIImageGenerationResponse,
            ),
            request=request_class(
                model=model,
                prompt=prompt,
                n=n,
                size=size,
                seed=seed,
            ),
            files=(
                {
                    "image": img_binary,
                }
                if img_binary
                else None
            ),
            content_type=content_type,
            auth_token=auth_token,
        )

        response = operation.execute()

        img_tensor = validate_and_cast_response(response)
        return (img_tensor,)
```


# OpenAI DALL·E 3 - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/openai/openai-dalle3

Node for generating high-quality images using OpenAI's DALL·E 3 model

<img alt="ComfyUI Native OpenAI DALL·E 3 Node" />

This node connects to OpenAI's DALL·E 3 API, allowing users to generate high-quality images through detailed text prompts. DALL·E 3 is OpenAI's image generation model that offers significantly improved image quality, more accurate prompt understanding, and better detail rendering compared to previous versions.

## Parameters

### Input Parameters

| Parameter | Type      | Default     | Description                                                                                                                                                                         |
| --------- | --------- | ----------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| prompt    | string    | ""          | Detailed text prompt describing what to generate                                                                                                                                    |
| seed      | integer   | 0           | Final result is not related to seed, this parameter only determines whether to re-execute                                                                                           |
| quality   | selection | "standard"  | Image quality, options: "standard" or "hd"                                                                                                                                          |
| style     | selection | "natural"   | Visual style, options: "natural" or "vivid". "Vivid" makes the model tend to create more surreal and dramatic images, while "natural" generates more realistic, less surreal images |
| size      | selection | "1024x1024" | Output image size, options: "1024x1024", "1024x1792", or "1792x1024"                                                                                                                |

### Output Parameters

| Output | Type  | Description                |
| ------ | ----- | -------------------------- |
| IMAGE  | image | The generated image result |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class OpenAIDalle3(ComfyNodeABC):
    """
    Generates images synchronously via OpenAI's DALL·E 3 endpoint.

    Uses the proxy at /proxy/openai/images/generations. Returned URLs are short‑lived,
    so download or cache results if you need to keep them.
    """

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls) -> InputTypeDict:
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text prompt for DALL·E",
                    },
                ),
            },
            "optional": {
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2**31 - 1,
                        "step": 1,
                        "display": "number",
                        "control_after_generate": True,
                        "tooltip": "not implemented yet in backend",
                    },
                ),
                "quality": (
                    IO.COMBO,
                    {
                        "options": ["standard", "hd"],
                        "default": "standard",
                        "tooltip": "Image quality",
                    },
                ),
                "style": (
                    IO.COMBO,
                    {
                        "options": ["natural", "vivid"],
                        "default": "natural",
                        "tooltip": "Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images.",
                    },
                ),
                "size": (
                    IO.COMBO,
                    {
                        "options": ["1024x1024", "1024x1792", "1792x1024"],
                        "default": "1024x1024",
                        "tooltip": "Image size",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = (IO.IMAGE,)
    FUNCTION = "api_call"
    CATEGORY = "api node/image/openai"
    DESCRIPTION = cleandoc(__doc__ or "")
    API_NODE = True

    def api_call(
        self,
        prompt,
        seed=0,
        style="natural",
        quality="standard",
        size="1024x1024",
        auth_token=None,
    ):
        model = "dall-e-3"

        # build the operation
        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/openai/images/generations",
                method=HttpMethod.POST,
                request_model=OpenAIImageGenerationRequest,
                response_model=OpenAIImageGenerationResponse,
            ),
            request=OpenAIImageGenerationRequest(
                model=model,
                prompt=prompt,
                quality=quality,
                size=size,
                style=style,
                seed=seed,
            ),
            auth_token=auth_token,
        )

        response = operation.execute()

        img_tensor = validate_and_cast_response(response)
        return (img_tensor,)
```


# OpenAI GPT Image 1 - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/openai/openai-gpt-image1

Node for generating images using OpenAI's GPT-4 Vision model

<img alt="ComfyUI Native OpenAI GPT Image 1 Node" />

This node connects to OpenAI's GPT Image 1 API, allowing users to generate images through detailed text prompts. Unlike traditional DALL·E models, GPT Image 1 leverages GPT-4's language understanding capabilities to handle more complex prompts and generate images that better match user intent.

## Parameters

### Basic Parameters

| Parameter | Type      | Default | Description                                                               |
| --------- | --------- | ------- | ------------------------------------------------------------------------- |
| prompt    | string    | ""      | Text prompt describing what to generate                                   |
| quality   | selection | "low"   | Image quality level, options: "low", "medium", "high"                     |
| size      | selection | "auto"  | Output image size, options: "auto", "1024x1024", "1024x1536", "1536x1024" |

### Image Editing Parameters

| Parameter | Type  | Description                                                  |
| --------- | ----- | ------------------------------------------------------------ |
| image     | image | Input image for editing, supports multiple images            |
| mask      | mask  | Optional mask to specify areas to modify (single image only) |

### Optional Parameters

| Parameter  | Type      | Description                                   |
| ---------- | --------- | --------------------------------------------- |
| background | selection | Background options: "opaque" or "transparent" |
| seed       | integer   | Random seed (not yet implemented in backend)  |
| n          | integer   | Number of images to generate, range 1-8       |

### Output

| Output | Type  | Description            |
| ------ | ----- | ---------------------- |
| IMAGE  | image | Generated image result |

## How It Works

The OpenAI GPT Image 1 node combines GPT-4's language understanding with image generation. It analyzes the text prompt to understand its meaning and intent, then generates matching images.

In image editing mode, the node can modify existing images. Using a mask allows precise control over which areas to change. Note that mask input only works with single image input.

Users can control the output by adjusting parameters like quality level, size, background handling, and number of generations.

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class OpenAIGPTImage1(ComfyNodeABC):
    """
    Generates images synchronously via OpenAI's GPT Image 1 endpoint.

    Uses the proxy at /proxy/openai/images/generations. Returned URLs are short‑lived,
    so download or cache results if you need to keep them.
    """

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls) -> InputTypeDict:
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text prompt for GPT Image 1",
                    },
                ),
            },
            "optional": {
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2**31 - 1,
                        "step": 1,
                        "display": "number",
                        "control_after_generate": True,
                        "tooltip": "not implemented yet in backend",
                    },
                ),
                "quality": (
                    IO.COMBO,
                    {
                        "options": ["low", "medium", "high"],
                        "default": "low",
                        "tooltip": "Image quality, affects cost and generation time.",
                    },
                ),
                "background": (
                    IO.COMBO,
                    {
                        "options": ["opaque", "transparent"],
                        "default": "opaque",
                        "tooltip": "Return image with or without background",
                    },
                ),
                "size": (
                    IO.COMBO,
                    {
                        "options": ["auto", "1024x1024", "1024x1536", "1536x1024"],
                        "default": "auto",
                        "tooltip": "Image size",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 8,
                        "step": 1,
                        "display": "number",
                        "tooltip": "How many images to generate",
                    },
                ),
                "image": (
                    IO.IMAGE,
                    {
                        "default": None,
                        "tooltip": "Optional reference image for image editing.",
                    },
                ),
                "mask": (
                    IO.MASK,
                    {
                        "default": None,
                        "tooltip": "Optional mask for inpainting (white areas will be replaced)",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = (IO.IMAGE,)
    FUNCTION = "api_call"
    CATEGORY = "api node/image/openai"
    DESCRIPTION = cleandoc(__doc__ or "")
    API_NODE = True

    def api_call(
        self,
        prompt,
        seed=0,
        quality="low",
        background="opaque",
        image=None,
        mask=None,
        n=1,
        size="1024x1024",
        auth_token=None,
    ):
        model = "gpt-image-1"
        path = "/proxy/openai/images/generations"
        content_type="application/json"
        request_class = OpenAIImageGenerationRequest
        img_binaries = []
        mask_binary = None
        files = []

        if image is not None:
            path = "/proxy/openai/images/edits"
            request_class = OpenAIImageEditRequest
            content_type ="multipart/form-data"

            batch_size = image.shape[0]

            for i in range(batch_size):
                single_image = image[i : i + 1]
                scaled_image = downscale_image_tensor(single_image).squeeze()

                image_np = (scaled_image.numpy() * 255).astype(np.uint8)
                img = Image.fromarray(image_np)
                img_byte_arr = io.BytesIO()
                img.save(img_byte_arr, format="PNG")
                img_byte_arr.seek(0)
                img_binary = img_byte_arr
                img_binary.name = f"image_{i}.png"

                img_binaries.append(img_binary)
                if batch_size == 1:
                    files.append(("image", img_binary))
                else:
                    files.append(("image[]", img_binary))

        if mask is not None:
            if image.shape[0] != 1:
                raise Exception("Cannot use a mask with multiple image")
            if image is None:
                raise Exception("Cannot use a mask without an input image")
            if mask.shape[1:] != image.shape[1:-1]:
                raise Exception("Mask and Image must be the same size")
            batch, height, width = mask.shape
            rgba_mask = torch.zeros(height, width, 4, device="cpu")
            rgba_mask[:, :, 3] = 1 - mask.squeeze().cpu()

            scaled_mask = downscale_image_tensor(rgba_mask.unsqueeze(0)).squeeze()

            mask_np = (scaled_mask.numpy() * 255).astype(np.uint8)
            mask_img = Image.fromarray(mask_np)
            mask_img_byte_arr = io.BytesIO()
            mask_img.save(mask_img_byte_arr, format="PNG")
            mask_img_byte_arr.seek(0)
            mask_binary = mask_img_byte_arr
            mask_binary.name = "mask.png"
            files.append(("mask", mask_binary))

        # Build the operation
        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=path,
                method=HttpMethod.POST,
                request_model=request_class,
                response_model=OpenAIImageGenerationResponse,
            ),
            request=request_class(
                model=model,
                prompt=prompt,
                quality=quality,
                background=background,
                n=n,
                seed=seed,
                size=size,
            ),
            files=files if files else None,
            content_type=content_type,
            auth_token=auth_token,
        )

        response = operation.execute()

        img_tensor = validate_and_cast_response(response)
        return (img_tensor,)
```


# Recraft Color RGB - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-color-rgb

Helper node for defining color controls in Recraft image generation

<img alt="ComfyUI Native Recraft Color RGB Node" />

The Recraft Color RGB node lets you define precise RGB color values to control colors in Recraft image generation.

## Node Function

This node creates a color configuration object that connects to the Recraft Controls node to specify colors used in generated images.

## Parameters

### Basic Parameters

| Parameter | Type    | Default | Description           |
| --------- | ------- | ------- | --------------------- |
| r         | integer | 0       | Red channel (0-255)   |
| g         | integer | 0       | Green channel (0-255) |
| b         | integer | 0       | Blue channel (0-255)  |

### Output

| Output         | Type          | Description                                        |
| -------------- | ------------- | -------------------------------------------------- |
| recraft\_color | Recraft Color | Color config object to connect to Recraft Controls |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftColorRGBNode:
    """
    Create Recraft Color by choosing specific RGB values.
    """

    RETURN_TYPES = (RecraftIO.COLOR,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    RETURN_NAMES = ("recraft_color",)
    FUNCTION = "create_color"
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "r": (IO.INT, {
                    "default": 0,
                    "min": 0,
                    "max": 255,
                    "tooltip": "Red value of color."
                }),
                "g": (IO.INT, {
                    "default": 0,
                    "min": 0,
                    "max": 255,
                    "tooltip": "Green value of color."
                }),
                "b": (IO.INT, {
                    "default": 0,
                    "min": 0,
                    "max": 255,
                    "tooltip": "Blue value of color."
                }),
            },
            "optional": {
                "recraft_color": (RecraftIO.COLOR,),
            }
        }

    def create_color(self, r: int, g: int, b: int, recraft_color: RecraftColorChain=None):
        recraft_color = recraft_color.clone() if recraft_color else RecraftColorChain()
        recraft_color.add(RecraftColor(r, g, b))
        return (recraft_color, )

```


# Recraft Controls - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-controls

Node providing advanced control parameters for Recraft image generation

<img alt="ComfyUI Native Recraft Controls Node" />

The Recraft Controls node lets you define control parameters (like colors and background colors) to guide Recraft's image generation process. This node combines multiple control inputs into a unified control object.

## Parameters

### Optional Parameters

| Parameter         | Type          | Description                         |
| ----------------- | ------------- | ----------------------------------- |
| colors            | Recraft Color | Color controls for image generation |
| background\_color | Recraft Color | Background color control            |

### Output

| Output            | Type             | Description                                        |
| ----------------- | ---------------- | -------------------------------------------------- |
| recraft\_controls | Recraft Controls | Control config object for Recraft generation nodes |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## How It Works

Node process:

1. Collects input control parameters (colors and background\_color)
2. Combines these parameters into a structured control object
3. Outputs this control object for connecting to Recraft generation nodes

When connected to Recraft generation nodes, these control parameters influence the AI generation process. The AI considers multiple factors beyond just the text prompt's semantic content. If color inputs are configured, the AI will try to use these colors appropriately in the generated image.

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftControlsNode:
    """
    Create Recraft Controls for customizing Recraft generation.
    """

    RETURN_TYPES = (RecraftIO.CONTROLS,)
    RETURN_NAMES = ("recraft_controls",)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "create_controls"
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
            },
            "optional": {
                "colors": (RecraftIO.COLOR,),
                "background_color": (RecraftIO.COLOR,),
            }
        }

    def create_controls(self, colors: RecraftColorChain=None, background_color: RecraftColorChain=None):
        return (RecraftControls(colors=colors, background_color=background_color), )

```


# Recraft Creative Upscale - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-creative-upscale

A Recraft Partner node that uses AI to creatively enhance image details and resolution

<img alt="ComfyUI Native Recraft Creative Upscale Node" />

The Recraft Creative Upscale node uses Recraft's API to increase image resolution while creatively enhancing and enriching image details.

## Parameters

### Basic Parameters

| Parameter | Type  | Default | Description                           |
| --------- | ----- | ------- | ------------------------------------- |
| image     | image | -       | Input image to be creatively upscaled |

### Output

| Output | Type  | Description                                    |
| ------ | ----- | ---------------------------------------------- |
| IMAGE  | image | High-resolution image after creative upscaling |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftCreativeUpscaleNode(RecraftCrispUpscaleNode):
    """
    Upscale image synchronously.
    Enhances a given raster image using ‘creative upscale’ tool, boosting resolution with a focus on refining small details and faces.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    RECRAFT_PATH = "/proxy/recraft/images/creativeUpscale"
```


# Recraft Crisp Upscale - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-crisp-upscale

A Recraft Partner node that enhances image clarity and resolution using AI

<img alt="ComfyUI Native Recraft Crisp Upscale Node" />

The Recraft Crisp Upscale node uses Recraft's API to improve image resolution and clarity.

## Parameters

### Basic Parameters

| Parameter | Type  | Default | Description                |
| --------- | ----- | ------- | -------------------------- |
| image     | image | -       | Input image to be upscaled |

### Output

| Output | Type  | Description                        |
| ------ | ----- | ---------------------------------- |
| IMAGE  | image | Upscaled and enhanced output image |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftCrispUpscaleNode:
    """
    Upscale image synchronously.
    Enhances a given raster image using ‘crisp upscale’ tool, increasing image resolution, making the image sharper and cleaner.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    RECRAFT_PATH = "/proxy/recraft/images/crispUpscale"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
            },
            "optional": {
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        auth_token=None,
        **kwargs,
    ):
        images = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                path=self.RECRAFT_PATH,
                auth_token=auth_token,
            )
            images.append(torch.cat([bytesio_to_image_tensor(x) for x in sub_bytes], dim=0))
            pbar.update(1)

        images_tensor = torch.cat(images, dim=0)
        return (images_tensor,)
```


# Recraft Image Inpainting - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-image-inpainting

Selectively modify image regions using Recraft API

<img alt="ComfyUI Native Recraft Image Inpainting Node" />

The Recraft Image Inpainting node lets you modify specific areas of an image while keeping the rest unchanged. By providing an image, mask and text prompt, you can generate new content to fill the selected areas.

## Parameters

### Basic Parameters

| Parameter | Type    | Default | Description                                     |
| --------- | ------- | ------- | ----------------------------------------------- |
| image     | image   | -       | Input image to modify                           |
| mask      | mask    | -       | Black and white mask defining areas to change   |
| prompt    | string  | ""      | Text describing what to generate in masked area |
| n         | integer | 1       | Number of results to generate (1-6)             |
| seed      | integer | 0       | Random seed value                               |

### Optional Parameters

| Parameter         | Type             | Description                            |
| ----------------- | ---------------- | -------------------------------------- |
| recraft\_style    | Recraft Style    | Style settings for generated content   |
| negative\_prompt  | string           | Elements to avoid in generated content |
| recraft\_controls | Recraft Controls | Additional controls like colors        |

### Output

| Output | Type  | Description           |
| ------ | ----- | --------------------- |
| IMAGE  | image | Modified image result |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftImageInpaintingNode:
    """
    Modify image based on prompt and mask.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
                "mask": (IO.MASK, ),
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation.",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 6,
                        "tooltip": "The number of images to generate.",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "recraft_style": (RecraftIO.STYLEV3,),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        mask: torch.Tensor,
        prompt: str,
        n: int,
        seed,
        auth_token=None,
        recraft_style: RecraftStyle = None,
        negative_prompt: str = None,
        **kwargs,
    ):
        default_style = RecraftStyle(RecraftStyleV3.realistic_image)
        if recraft_style is None:
            recraft_style = default_style

        if not negative_prompt:
            negative_prompt = None

        request = RecraftImageGenerationRequest(
            prompt=prompt,
            negative_prompt=negative_prompt,
            model=RecraftModel.recraftv3,
            n=n,
            style=recraft_style.style,
            substyle=recraft_style.substyle,
            style_id=recraft_style.style_id,
            random_seed=seed,
        )

        # prepare mask tensor
        _, H, W, _ = image.shape
        mask = mask.unsqueeze(-1)
        mask = mask.movedim(-1,1)
        mask = common_upscale(mask, width=W, height=H, upscale_method="nearest-exact", crop="disabled")
        mask = mask.movedim(1,-1)
        mask = (mask > 0.5).float()

        images = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                mask=mask[i:i+1],
                path="/proxy/recraft/images/inpaint",
                request=request,
                auth_token=auth_token,
            )
            images.append(torch.cat([bytesio_to_image_tensor(x) for x in sub_bytes], dim=0))
            pbar.update(1)

        images_tensor = torch.cat(images, dim=0)
        return (images_tensor, )
```


# Recraft Image to Image - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-image-to-image

A Recraft Partner node that generates new images based on text prompts and reference images

<img alt="ComfyUI Native Recraft Image to Image Node" />

The Recraft Image to Image node uses Recraft's API to generate new images based on a reference image and text prompts.

## Parameters

### Basic Parameters

| Parameter | Type    | Default | Description                              |
| --------- | ------- | ------- | ---------------------------------------- |
| image     | image   | -       | Reference image input                    |
| prompt    | string  | ""      | Text description for the generated image |
| n         | integer | 1       | Number of images to generate (1-6)       |
| seed      | integer | 0       | Random seed value                        |

### Optional Parameters

| Parameter         | Type             | Description                           |
| ----------------- | ---------------- | ------------------------------------- |
| recraft\_style    | Recraft Style    | Style settings for generated images   |
| negative\_prompt  | string           | Elements to avoid in generated images |
| recraft\_controls | Recraft Controls | Additional controls like colors       |

### Output

| Output | Type  | Description            |
| ------ | ----- | ---------------------- |
| IMAGE  | image | Generated image result |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class RecraftImageToImageNode:
    """
    Modify image based on prompt and strength.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation.",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 6,
                        "tooltip": "The number of images to generate.",
                    },
                ),
                "strength": (
                    IO.FLOAT,
                    {
                        "default": 0.5,
                        "min": 0.0,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Defines the difference with the original image, should lie in [0, 1], where 0 means almost identical, and 1 means miserable similarity."
                    }
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "recraft_style": (RecraftIO.STYLEV3,),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
                "recraft_controls": (
                    RecraftIO.CONTROLS,
                    {
                        "tooltip": "Optional additional controls over the generation via the Recraft Controls node."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        prompt: str,
        n: int,
        strength: float,
        seed,
        auth_token=None,
        recraft_style: RecraftStyle = None,
        negative_prompt: str = None,
        recraft_controls: RecraftControls = None,
        **kwargs,
    ):
        default_style = RecraftStyle(RecraftStyleV3.realistic_image)
        if recraft_style is None:
            recraft_style = default_style

        controls_api = None
        if recraft_controls:
            controls_api = recraft_controls.create_api_model()

        if not negative_prompt:
            negative_prompt = None

        request = RecraftImageGenerationRequest(
            prompt=prompt,
            negative_prompt=negative_prompt,
            model=RecraftModel.recraftv3,
            n=n,
            strength=round(strength, 2),
            style=recraft_style.style,
            substyle=recraft_style.substyle,
            style_id=recraft_style.style_id,
            controls=controls_api,
            random_seed=seed,
        )

        images = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                path="/proxy/recraft/images/imageToImage",
                request=request,
                auth_token=auth_token,
            )
            images.append(torch.cat([bytesio_to_image_tensor(x) for x in sub_bytes], dim=0))
            pbar.update(1)

        images_tensor = torch.cat(images, dim=0)
        return (images_tensor, )
```


# Recraft Remove Background - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-remove-background

A Recraft Partner node that automatically removes image backgrounds and creates transparent alpha channels

<img alt="ComfyUI Native Recraft Remove Background Node" />

The Recraft Remove Background node uses Recraft's API to intelligently detect and remove image backgrounds, creating images with transparent backgrounds and corresponding alpha masks.

## Parameters

### Basic Parameters

| Parameter | Type  | Default | Description                           |
| --------- | ----- | ------- | ------------------------------------- |
| image     | image | -       | Input image to remove background from |

### Output

| Output | Type  | Description                                          |
| ------ | ----- | ---------------------------------------------------- |
| IMAGE  | image | Image with background removed (with alpha channel)   |
| MASK   | mask  | Mask of the main subject (white areas are preserved) |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftRemoveBackgroundNode:
    """
    Remove background from image, and return processed image and mask.
    """

    RETURN_TYPES = (IO.IMAGE, IO.MASK)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
            },
            "optional": {
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        auth_token=None,
        **kwargs,
    ):
        images = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                path="/proxy/recraft/images/removeBackground",
                auth_token=auth_token,
            )
            images.append(torch.cat([bytesio_to_image_tensor(x) for x in sub_bytes], dim=0))
            pbar.update(1)

        images_tensor = torch.cat(images, dim=0)
        # use alpha channel as masks, in B,H,W format
        masks_tensor = images_tensor[:,:,:,-1:].squeeze(-1)
        return (images_tensor, masks_tensor)

```


# Recraft Replace Background - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-replace-background

A Recraft Partner node that automatically detects foreground subjects and replaces backgrounds

<img alt="ComfyUI Native Recraft Replace Background Node" />

The Recraft Replace Background node uses Recraft's API to intelligently detect subjects in images and generate new backgrounds based on text prompts.

## Parameters

### Basic Parameters

| Parameter | Type    | Default | Description                           |
| --------- | ------- | ------- | ------------------------------------- |
| image     | image   | -       | Input image with subject to preserve  |
| prompt    | string  | ""      | Text prompt for background generation |
| n         | integer | 1       | Number of images to generate (1-6)    |
| seed      | integer | 0       | Random seed value for node re-runs    |

### Optional Parameters

| Parameter        | Type          | Description                              |
| ---------------- | ------------- | ---------------------------------------- |
| recraft\_style   | Recraft Style | Style settings for background generation |
| negative\_prompt | string        | Text describing elements to avoid        |

### Output

| Output | Type  | Description                          |
| ------ | ----- | ------------------------------------ |
| IMAGE  | image | Final image with replaced background |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class RecraftReplaceBackgroundNode:
    """
    Replace background on image, based on provided prompt.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation.",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 6,
                        "tooltip": "The number of images to generate.",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "recraft_style": (RecraftIO.STYLEV3,),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        prompt: str,
        n: int,
        seed,
        auth_token=None,
        recraft_style: RecraftStyle = None,
        negative_prompt: str = None,
        **kwargs,
    ):
        default_style = RecraftStyle(RecraftStyleV3.realistic_image)
        if recraft_style is None:
            recraft_style = default_style

        if not negative_prompt:
            negative_prompt = None

        request = RecraftImageGenerationRequest(
            prompt=prompt,
            negative_prompt=negative_prompt,
            model=RecraftModel.recraftv3,
            n=n,
            style=recraft_style.style,
            substyle=recraft_style.substyle,
            style_id=recraft_style.style_id,
        )

        images = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                path="/proxy/recraft/images/replaceBackground",
                request=request,
                auth_token=auth_token,
            )
            images.append(torch.cat([bytesio_to_image_tensor(x) for x in sub_bytes], dim=0))
            pbar.update(1)

        images_tensor = torch.cat(images, dim=0)
        return (images_tensor, )

```


# Recraft Style - Digital Illustration - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-style-digital-illustration

A helper node for setting digital illustration style in Recraft image generation

<img alt="ComfyUI Native Recraft Style Digital Illustration Node" />

This node creates a style configuration object that guides Recraft's image generation process towards a digital illustration look.

## Parameters

### Basic Parameters

| Parameter | Type   | Default | Description                               |
| --------- | ------ | ------- | ----------------------------------------- |
| substyle  | select | None    | Specific substyle of digital illustration |

### Output

| Output         | Type          | Description                                                |
| -------------- | ------------- | ---------------------------------------------------------- |
| recraft\_style | Recraft Style | Style config object to connect to Recraft generation nodes |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftStyleV3DigitalIllustrationNode(RecraftStyleV3RealisticImageNode):
    """
    Select digital_illustration style and optional substyle.
    """

    RECRAFT_STYLE = RecraftStyleV3.digital_illustration

```


# Recraft Style - Logo Raster - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-style-logo-raster

Helper node for setting logo raster style in Recraft image generation

<img alt="ComfyUI Built-in Recraft Style - Logo Raster Node" />

This node creates a style configuration object that guides Recraft's image generation process toward professional logo design effects. By selecting different substyles, you can define the design style, complexity and use cases of the generated logo.

## Parameters

### Basic Parameters

| Parameter | Type      | Default | Description                                  |
| --------- | --------- | ------- | -------------------------------------------- |
| substyle  | Selection | -       | Specific substyle for logo raster (Required) |

### Output

| Output         | Type          | Description                                                     |
| -------------- | ------------- | --------------------------------------------------------------- |
| recraft\_style | Recraft Style | Style configuration object, connects to Recraft generation node |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}
class RecraftStyleV3LogoRasterNode(RecraftStyleV3RealisticImageNode):
    """
    Select vector_illustration style and optional substyle.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "substyle": (get_v3_substyles(s.RECRAFT_STYLE, include_none=False),),
            }
        }

    RECRAFT_STYLE = RecraftStyleV3.logo_raster
```


# Recraft Style - Realistic Image - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-style-realistic-image

A helper node for setting realistic photo style in Recraft image generation

<img alt="ComfyUI Native Recraft Style - Realistic Image Node" />

The Recraft Style - Realistic Image node helps set up realistic photo styles for Recraft image generation, with various substyle options to control the visual characteristics of generated images.

## Node Function

This node creates a style configuration object that guides Recraft's image generation process towards realistic photo effects.

## Parameters

### Basic Parameters

| Parameter | Type   | Default | Description                                     |
| --------- | ------ | ------- | ----------------------------------------------- |
| substyle  | select | None    | Specific substyle of realistic photo (Required) |

### Output

| Output         | Type          | Description                                                |
| -------------- | ------------- | ---------------------------------------------------------- |
| recraft\_style | Recraft Style | Style config object to connect to Recraft generation nodes |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class RecraftStyleV3RealisticImageNode:
    """
    Select realistic_image style and optional substyle.
    """

    RETURN_TYPES = (RecraftIO.STYLEV3,)
    RETURN_NAMES = ("recraft_style",)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "create_style"
    CATEGORY = "api node/image/Recraft"

    RECRAFT_STYLE = RecraftStyleV3.realistic_image

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "substyle": (get_v3_substyles(s.RECRAFT_STYLE),),
            }
        }

    def create_style(self, substyle: str):
        if substyle == "None":
            substyle = None
        return (RecraftStyle(self.RECRAFT_STYLE, substyle),)

```


# Recraft Text to Image - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-text-to-image

A Recraft Partner node that generates high-quality images from text descriptions

<img alt="ComfyUI Built-in Recraft Text to Image Node" />

The Recraft Text to Image node lets you generate high-quality images from text prompts by directly connecting to Recraft AI's image generation API to create images in various styles.

## Parameters

### Basic Parameters

| Parameter | Type   | Default   | Description                    |
| --------- | ------ | --------- | ------------------------------ |
| prompt    | string | ""        | Text description for the image |
| size      | select | 1024x1024 | Output image size              |
| n         | int    | 1         | Number of images (1-6)         |
| seed      | int    | 0         | Random seed value              |

### Optional Parameters

| Parameter         | Type             | Description                                       |
| ----------------- | ---------------- | ------------------------------------------------- |
| recraft\_style    | Recraft Style    | Image style setting, default is "realistic photo" |
| negative\_prompt  | string           | Elements to exclude from generation               |
| recraft\_controls | Recraft Controls | Additional control parameters (colors, etc.)      |

### Output

| Output | Type  | Description        |
| ------ | ----- | ------------------ |
| IMAGE  | image | Generated image(s) |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}
class RecraftTextToImageNode:
    """
    Generates images synchronously based on prompt and resolution.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation.",
                    },
                ),
                "size": (
                    [res.value for res in RecraftImageSize],
                    {
                        "default": RecraftImageSize.res_1024x1024,
                        "tooltip": "The size of the generated image.",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 6,
                        "tooltip": "The number of images to generate.",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "recraft_style": (RecraftIO.STYLEV3,),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
                "recraft_controls": (
                    RecraftIO.CONTROLS,
                    {
                        "tooltip": "Optional additional controls over the generation via the Recraft Controls node."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        size: str,
        n: int,
        seed,
        recraft_style: RecraftStyle = None,
        negative_prompt: str = None,
        recraft_controls: RecraftControls = None,
        auth_token=None,
        **kwargs,
    ):
        default_style = RecraftStyle(RecraftStyleV3.realistic_image)
        if recraft_style is None:
            recraft_style = default_style

        controls_api = None
        if recraft_controls:
            controls_api = recraft_controls.create_api_model()

        if not negative_prompt:
            negative_prompt = None

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/recraft/image_generation",
                method=HttpMethod.POST,
                request_model=RecraftImageGenerationRequest,
                response_model=RecraftImageGenerationResponse,
            ),
            request=RecraftImageGenerationRequest(
                prompt=prompt,
                negative_prompt=negative_prompt,
                model=RecraftModel.recraftv3,
                size=size,
                n=n,
                style=recraft_style.style,
                substyle=recraft_style.substyle,
                style_id=recraft_style.style_id,
                controls=controls_api,
            ),
            auth_token=auth_token,
        )
        response: RecraftImageGenerationResponse = operation.execute()
        images = []
        for data in response.data:
            image = bytesio_to_image_tensor(
                download_url_to_bytesio(data.url, timeout=1024)
            )
            if len(image.shape) < 4:
                image = image.unsqueeze(0)
            images.append(image)
        output_image = torch.cat(images, dim=0)

        return (output_image,)
```


# Recraft Text to Vector - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-text-to-vector

A Recraft Partner node that generates scalable vector graphics from text descriptions

<img alt="ComfyUI Native Recraft Text to Vector Node" />

The Recraft Text to Vector node lets you create high-quality vector graphics (SVG format) from text descriptions using Recraft's API. It's perfect for making logos, icons, and infinitely scalable illustrations.

## Parameters

### Basic Parameters

| Parameter | Type    | Default   | Description                                        |
| --------- | ------- | --------- | -------------------------------------------------- |
| prompt    | string  | ""        | Text description of the vector graphic to generate |
| substyle  | select  | -         | Vector style subtype                               |
| size      | select  | 1024x1024 | Canvas size for the vector output                  |
| n         | integer | 1         | Number of results to generate (1-6)                |
| seed      | integer | 0         | Random seed value                                  |

### Optional Parameters

| Parameter         | Type             | Description                                  |
| ----------------- | ---------------- | -------------------------------------------- |
| negative\_prompt  | string           | Elements to exclude from generation          |
| recraft\_controls | Recraft Controls | Additional control parameters (colors, etc.) |

### Output

| Output | Type   | Description                                                   |
| ------ | ------ | ------------------------------------------------------------- |
| SVG    | vector | Generated SVG vector graphic, connect to SaveSVG node to save |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class RecraftTextToVectorNode:
    """
    Generates SVG synchronously based on prompt and resolution.
    """

    RETURN_TYPES = (RecraftIO.SVG,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the image generation.",
                    },
                ),
                "substyle": (get_v3_substyles(RecraftStyleV3.vector_illustration),),
                "size": (
                    [res.value for res in RecraftImageSize],
                    {
                        "default": RecraftImageSize.res_1024x1024,
                        "tooltip": "The size of the generated image.",
                    },
                ),
                "n": (
                    IO.INT,
                    {
                        "default": 1,
                        "min": 1,
                        "max": 6,
                        "tooltip": "The number of images to generate.",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
                "recraft_controls": (
                    RecraftIO.CONTROLS,
                    {
                        "tooltip": "Optional additional controls over the generation via the Recraft Controls node."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        substyle: str,
        size: str,
        n: int,
        seed,
        negative_prompt: str = None,
        recraft_controls: RecraftControls = None,
        auth_token=None,
        **kwargs,
    ):
        # create RecraftStyle so strings will be formatted properly (i.e. "None" will become None)
        recraft_style = RecraftStyle(RecraftStyleV3.vector_illustration, substyle=substyle)

        controls_api = None
        if recraft_controls:
            controls_api = recraft_controls.create_api_model()

        if not negative_prompt:
            negative_prompt = None

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/recraft/image_generation",
                method=HttpMethod.POST,
                request_model=RecraftImageGenerationRequest,
                response_model=RecraftImageGenerationResponse,
            ),
            request=RecraftImageGenerationRequest(
                prompt=prompt,
                negative_prompt=negative_prompt,
                model=RecraftModel.recraftv3,
                size=size,
                n=n,
                style=recraft_style.style,
                substyle=recraft_style.substyle,
                controls=controls_api,
            ),
            auth_token=auth_token,
        )
        response: RecraftImageGenerationResponse = operation.execute()
        svg_data = []
        for data in response.data:
            svg_data.append(download_url_to_bytesio(data.url, timeout=1024))

        return (SVG(svg_data),)
```


# Recraft Vectorize Image - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/recraft-vectorize-image

A Recraft Partner node that converts raster images to vector SVG format

<img alt="ComfyUI Built-in Recraft Vectorize Image Node" />

The Recraft Vectorize Image node uses Recraft's API to convert raster images (like photos, PNGs or JPEGs) into vector SVG format.

## Parameters

### Basic Parameters

| Parameter | Type  | Default | Description                           |
| --------- | ----- | ------- | ------------------------------------- |
| image     | Image | -       | Input image to be converted to vector |

### Output

| Output | Type   | Description                                                                 |
| ------ | ------ | --------------------------------------------------------------------------- |
| SVG    | Vector | Converted SVG vector graphic, needs to be connected to SaveSVG node to save |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class RecraftVectorizeImageNode:
    """
    Generates SVG synchronously from an input image.
    """

    RETURN_TYPES = (RecraftIO.SVG,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Recraft"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (IO.IMAGE, ),
            },
            "optional": {
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        image: torch.Tensor,
        auth_token=None,
        **kwargs,
    ):
        svgs = []
        total = image.shape[0]
        pbar = ProgressBar(total)
        for i in range(total):
            sub_bytes = handle_recraft_file_request(
                image=image[i],
                path="/proxy/recraft/images/vectorize",
                auth_token=auth_token,
            )
            svgs.append(SVG(sub_bytes))
            pbar.update(1)

        return (SVG.combine_all(svgs), )

```


# Save SVG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/recraft/save-svg

A utility node for saving SVG vector graphics to files

<img alt="ComfyUI Built-in Save SVG Node" />

The Save SVG node allows you to save SVG data from Recraft vector generation nodes as usable files in the filesystem. This is an essential component for handling and exporting vector graphics.

## Node Function

This node receives SVG vector data and saves it as standard SVG files in the filesystem. It supports automatic file naming and save path specification, allowing vector graphics to be opened and edited in other software.

## Parameters

### Basic Parameters

| Parameter        | Type    | Default   | Description                                                                  |
| ---------------- | ------- | --------- | ---------------------------------------------------------------------------- |
| svg              | SVG     | -         | SVG vector data to save                                                      |
| filename\_prefix | string  | "recraft" | Prefix for the filename                                                      |
| output\_dir      | string  | -         | Output directory, defaults to ComfyUI output folder at `ComfyUI/output/svg/` |
| index            | integer | -1        | Save index, -1 means save all generated SVGs                                 |

### Output

| Output | Type | Description                       |
| ------ | ---- | --------------------------------- |
| SVG    | SVG  | Passes through the input SVG data |

## Usage Example

<Card title="Recraft Text to Image Workflow Example" icon="book" href="/tutorials/partner-nodes/recraft/recraft-text-to-image">
  Recraft Text to Image Workflow Example
</Card>

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}
class SaveSVGNode:
    """
    Save SVG files on disk.
    """

    def __init__(self):
        self.output_dir = folder_paths.get_output_directory()
        self.type = "output"
        self.prefix_append = ""

    RETURN_TYPES = ()
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "save_svg"
    CATEGORY = "api node/image/Recraft"
    OUTPUT_NODE = True

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "svg": (RecraftIO.SVG,),
                "filename_prefix": ("STRING", {"default": "svg/ComfyUI", "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes."})
            },
            "hidden": {
                "prompt": "PROMPT",
                "extra_pnginfo": "EXTRA_PNGINFO"
            }
        }

    def save_svg(self, svg: SVG, filename_prefix="svg/ComfyUI", prompt=None, extra_pnginfo=None):
        filename_prefix += self.prefix_append
        full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
        results = list()

        # Prepare metadata JSON
        metadata_dict = {}
        if prompt is not None:
            metadata_dict["prompt"] = prompt
        if extra_pnginfo is not None:
            metadata_dict.update(extra_pnginfo)

        # Convert metadata to JSON string
        metadata_json = json.dumps(metadata_dict, indent=2) if metadata_dict else None

        for batch_number, svg_bytes in enumerate(svg.data):
            filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
            file = f"{filename_with_batch_num}_{counter:05}_.svg"

            # Read SVG content
            svg_bytes.seek(0)
            svg_content = svg_bytes.read().decode('utf-8')

            # Inject metadata if available
            if metadata_json:
                # Create metadata element with CDATA section
                metadata_element = f"""  <metadata>
    <![CDATA[
{metadata_json}
    ]]>
  </metadata>
"""
                # Insert metadata after opening svg tag using regex
                import re
                svg_content = re.sub(r'(<svg[^>]*>)', r'\1\n' + metadata_element, svg_content)

            # Write the modified SVG to file
            with open(os.path.join(full_output_folder, file), 'wb') as svg_file:
                svg_file.write(svg_content.encode('utf-8'))

            results.append({
                "filename": file,
                "subfolder": subfolder,
                "type": self.type
            })
            counter += 1
        return { "ui": { "images": results } }

```


# Stability AI Stable Diffusion 3.5 - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/stability-ai/stability-ai-stable-diffusion-3-5-image

A node that generates high-quality images using Stability AI Stable Diffusion 3.5 model

<img alt="ComfyUI Native Stability AI Stable Diffusion 3.5 Node" />

The Stability AI Stable Diffusion 3.5 Image node uses Stability AI's Stable Diffusion 3.5 API to generate high-quality images. It supports both text-to-image and image-to-image generation, capable of creating detailed visual content from text prompts.

## Parameters

### Required Parameters

| Parameter     | Type    | Default | Description                                                                                                                                       |
| ------------- | ------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------- |
| prompt        | string  | ""      | What you want to see in the output image. Strong, descriptive prompts that clearly define elements, colors and themes will yield better results   |
| model         | select  | -       | Choose which Stability SD 3.5 model to use                                                                                                        |
| aspect\_ratio | select  | "1:1"   | Width to height ratio of generated image                                                                                                          |
| style\_preset | select  | "None"  | Optional preset style for the desired image                                                                                                       |
| cfg\_scale    | float   | 4.0     | How strictly the diffusion process adheres to the prompt text (higher values keep your image closer to your prompt). Range: 1.0 - 10.0, Step: 0.1 |
| seed          | integer | 0       | Random seed for noise generation (0-4294967294)                                                                                                   |

### Optional Parameters

| Parameter        | Type   | Default | Description                                                                                                                                                                             |
| ---------------- | ------ | ------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| image            | image  | -       | Input image. When provided, the node switches to image-to-image mode                                                                                                                    |
| negative\_prompt | string | ""      | Keywords of what you don't want to see in the output image. This is an advanced feature                                                                                                 |
| image\_denoise   | float  | 0.5     | Denoising strength for input image. 0.0 yields image identical to input, 1.0 is as if no image was provided at all. Range: 0.0 - 1.0, Step: 0.01. Only effective when image is provided |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| IMAGE  | image | Generated image |

## Usage Example

<Card title="Stability AI Stable Diffusion 3.5 Image Workflow Example" icon="book" href="/tutorials/partner-nodes/stability-ai/stable-diffusion-3-5-image">
  Stability AI Stable Diffusion 3.5 Image Workflow Example
</Card>

## Notes

* When an input image is provided, the node switches from text-to-image mode to image-to-image mode
* In image-to-image mode, aspect ratio parameters are ignored
* Mode selection automatically switches based on whether an image is provided:
  * No image provided: text-to-image mode
  * Image provided: image-to-image mode
* If style\_preset is set to "None", no preset style will be applied

## Source Code

\[Node source code (Updated on 2025-05-07)]

```python theme={null}
class StabilityStableImageSD_3_5Node:
    """
    Generates images synchronously based on prompt and resolution.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/Stability AI"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results."
                    },
                ),
                "model": ([x.value for x in Stability_SD3_5_Model],),
                "aspect_ratio": ([x.value for x in StabilityAspectRatio],
                    {
                        "default": StabilityAspectRatio.ratio_1_1,
                        "tooltip": "Aspect ratio of generated image.",
                    },
                ),
                "style_preset": (get_stability_style_presets(),
                    {
                        "tooltip": "Optional desired style of generated image.",
                    },
                ),
                "cfg_scale": (
                    IO.FLOAT,
                    {
                        "default": 4.0,
                        "min": 1.0,
                        "max": 10.0,
                        "step": 0.1,
                        "tooltip": "How strictly the diffusion process adheres to the prompt text (higher values keep your image closer to your prompt)",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 4294967294,
                        "control_after_generate": True,
                        "tooltip": "The random seed used for creating the noise.",
                    },
                ),
            },
            "optional": {
                "image": (IO.IMAGE,),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "Keywords of what you do not wish to see in the output image. This is an advanced feature."
                    },
                ),
                "image_denoise": (
                    IO.FLOAT,
                    {
                        "default": 0.5,
                        "min": 0.0,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Denoise of input image; 0.0 yields image identical to input, 1.0 is as if no image was provided at all.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(self, model: str, prompt: str, aspect_ratio: str, style_preset: str, seed: int, cfg_scale: float,
                 negative_prompt: str=None, image: torch.Tensor = None, image_denoise: float=None,
                 auth_token=None):
        validate_string(prompt, strip_whitespace=False)
        # prepare image binary if image present
        image_binary = None
        mode = Stability_SD3_5_GenerationMode.text_to_image
        if image is not None:
            image_binary = tensor_to_bytesio(image, total_pixels=1504*1504).read()
            mode = Stability_SD3_5_GenerationMode.image_to_image
            aspect_ratio = None
        else:
            image_denoise = None

        if not negative_prompt:
            negative_prompt = None
        if style_preset == "None":
            style_preset = None

        files = {
            "image": image_binary
        }

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/stability/v2beta/stable-image/generate/sd3",
                method=HttpMethod.POST,
                request_model=StabilityStable3_5Request,
                response_model=StabilityStableUltraResponse,
            ),
            request=StabilityStable3_5Request(
                prompt=prompt,
                negative_prompt=negative_prompt,
                aspect_ratio=aspect_ratio,
                seed=seed,
                strength=image_denoise,
                style_preset=style_preset,
                cfg_scale=cfg_scale,
                model=model,
                mode=mode,
            ),
            files=files,
            content_type="multipart/form-data",
            auth_token=auth_token,
        )
        response_api = operation.execute()

        if response_api.finish_reason != "SUCCESS":
            raise Exception(f"Stable Diffusion 3.5 Image generation failed: {response_api.finish_reason}.")

        image_data = base64.b64decode(response_api.image)
        returned_image = bytesio_to_image_tensor(BytesIO(image_data))

        return (returned_image,)
```


# Stability Stable Image Ultra - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/image/stability-ai/stability-ai-stable-image-ultra

A node that generates high-quality images using Stability AI's ultra stable diffusion model

<img alt="ComfyUI Native Stability Stable Image Ultra Node" />

The Stability Stable Image Ultra node uses Stability AI's Stable Diffusion Ultra API to generate high-quality images. It supports both text-to-image and image-to-image generation, creating detailed and artistic visuals from text prompts.

## Parameters

### Required Parameters

| Parameter     | Type    | Default | Description                                                                                                                                                                                                                                                                                                               |
| ------------- | ------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| prompt        | string  | ""      | Text description of what you want to generate. Better results come from clear, descriptive prompts that specify elements, colors and themes. You can control word importance using `(word:weight)` format, where weight is 0-1. For example: `The sky was (blue:0.3) and (green:0.8)` makes the sky more green than blue. |
| aspect\_ratio | select  | "1:1"   | Width to height ratio of output image                                                                                                                                                                                                                                                                                     |
| style\_preset | select  | "None"  | Optional preset style for generated image                                                                                                                                                                                                                                                                                 |
| seed          | integer | 0       | Random seed for noise generation (0-4294967294)                                                                                                                                                                                                                                                                           |

### Optional Parameters

| Parameter        | Type   | Default | Description                                                                                                      |
| ---------------- | ------ | ------- | ---------------------------------------------------------------------------------------------------------------- |
| image            | image  | -       | Input image for image-to-image generation                                                                        |
| negative\_prompt | string | ""      | Describes what you don't want in the output image. This is an advanced feature                                   |
| image\_denoise   | float  | 0.5     | Denoising strength for input image (0.0-1.0). 0.0 keeps input image unchanged, 1.0 is like having no input image |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| IMAGE  | image | Generated image |

## Notes

* image\_denoise has no effect when no input image is provided
* No preset style is applied when style\_preset is "None"
* For image-to-image, input images are converted to the proper format before API submission

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class StabilityStableImageUltraNode:
    """
    Generates images synchronously based on prompt and resolution.
    """

    RETURN_TYPES = (IO.IMAGE,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/image/stability"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "What you wish to see in the output image. A strong, descriptive prompt that clearly defines" +
                                    "What you wish to see in the output image. A strong, descriptive prompt that clearly defines" +
                                    "elements, colors, and subjects will lead to better results. " +
                                    "To control the weight of a given word use the format `(word:weight)`," +
                                    "where `word` is the word you'd like to control the weight of and `weight`" +
                                    "is a value between 0 and 1. For example: `The sky was a crisp (blue:0.3) and (green:0.8)`" +
                                    "would convey a sky that was blue and green, but more green than blue."
                    },
                ),
                "aspect_ratio": ([x.value for x in StabilityAspectRatio],
                    {
                        "default": StabilityAspectRatio.ratio_1_1,
                        "tooltip": "Aspect ratio of generated image.",
                    },
                ),
                "style_preset": (get_stability_style_presets(),
                    {
                        "tooltip": "Optional desired style of generated image.",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 4294967294,
                        "control_after_generate": True,
                        "tooltip": "The random seed used for creating the noise.",
                    },
                ),
            },
            "optional": {
                "image": (IO.IMAGE,),
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "A blurb of text describing what you do not wish to see in the output image. This is an advanced feature."
                    },
                ),
                "image_denoise": (
                    IO.FLOAT,
                    {
                        "default": 0.5,
                        "min": 0.0,
                        "max": 1.0,
                        "step": 0.01,
                        "tooltip": "Denoise of input image; 0.0 yields image identical to input, 1.0 is as if no image was provided at all.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(self, prompt: str, aspect_ratio: str, style_preset: str, seed: int,
                 negative_prompt: str=None, image: torch.Tensor = None, image_denoise: float=None,
                 auth_token=None):
        # prepare image binary if image present
        image_binary = None
        if image is not None:
            image_binary = tensor_to_bytesio(image, 1504 * 1504).read()
        else:
            image_denoise = None

        if not negative_prompt:
            negative_prompt = None
        if style_preset == "None":
            style_preset = None

        files = {
            "image": image_binary
        }

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/stability/v2beta/stable-image/generate/ultra",
                method=HttpMethod.POST,
                request_model=StabilityStableUltraRequest,
                response_model=StabilityStableUltraResponse,
            ),
            request=StabilityStableUltraRequest(
                prompt=prompt,
                negative_prompt=negative_prompt,
                aspect_ratio=aspect_ratio,
                seed=seed,
                strength=image_denoise,
                style_preset=style_preset,
            ),
            files=files,
            content_type="multipart/form-data",
            auth_token=auth_token,
        )
        response_api = operation.execute()

        if response_api.finish_reason != "SUCCESS":
            raise Exception(f"Stable Image Ultra generation failed: {response_api.finish_reason}.")

        image_data = base64.b64decode(response_api.image)
        returned_image = bytesio_to_image_tensor(BytesIO(image_data))

        return (returned_image,)


```


# Google Veo2 Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/google/google-veo2-video

A node that generates videos from text descriptions using Google's Veo2 technology

<img alt="ComfyUI Native Google Veo2 Video Node" />

The Google Veo2 Video node generates high-quality videos from text descriptions using Google's Veo2 API technology, converting text prompts into dynamic video content.

## Parameters

### Basic Parameters

| Parameter          | Type    | Default | Description                                          |
| ------------------ | ------- | ------- | ---------------------------------------------------- |
| prompt             | string  | ""      | Text description of the video content to generate    |
| aspect\_ratio      | select  | "16:9"  | Output video aspect ratio, "16:9" or "9:16"          |
| negative\_prompt   | string  | ""      | Text describing what to avoid in the video           |
| duration\_seconds  | integer | 5       | Video duration, 5-8 seconds                          |
| enhance\_prompt    | boolean | True    | Whether to use AI to enhance the prompt              |
| person\_generation | select  | "ALLOW" | Allow or block person generation, "ALLOW" or "BLOCK" |
| seed               | integer | 0       | Random seed, 0 means randomly generated              |

### Optional Parameters

| Parameter | Type  | Default | Description                                      |
| --------- | ----- | ------- | ------------------------------------------------ |
| image     | image | None    | Optional reference image to guide video creation |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class VeoVideoGenerationNode(ComfyNodeABC):
    """
    Generates videos from text prompts using Google's Veo API.

    This node can create videos from text descriptions and optional image inputs,
    with control over parameters like aspect ratio, duration, and more.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text description of the video",
                    },
                ),
                "aspect_ratio": (
                    IO.COMBO,
                    {
                        "options": ["16:9", "9:16"],
                        "default": "16:9",
                        "tooltip": "Aspect ratio of the output video",
                    },
                ),
            },
            "optional": {
                "negative_prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Negative text prompt to guide what to avoid in the video",
                    },
                ),
                "duration_seconds": (
                    IO.INT,
                    {
                        "default": 5,
                        "min": 5,
                        "max": 8,
                        "step": 1,
                        "display": "number",
                        "tooltip": "Duration of the output video in seconds",
                    },
                ),
                "enhance_prompt": (
                    IO.BOOLEAN,
                    {
                        "default": True,
                        "tooltip": "Whether to enhance the prompt with AI assistance",
                    }
                ),
                "person_generation": (
                    IO.COMBO,
                    {
                        "options": ["ALLOW", "BLOCK"],
                        "default": "ALLOW",
                        "tooltip": "Whether to allow generating people in the video",
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFF,
                        "step": 1,
                        "display": "number",
                        "control_after_generate": True,
                        "tooltip": "Seed for video generation (0 for random)",
                    },
                ),
                "image": (IO.IMAGE, {
                    "default": None,
                    "tooltip": "Optional reference image to guide video generation",
                }),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    RETURN_TYPES = (IO.VIDEO,)
    FUNCTION = "generate_video"
    CATEGORY = "api node/video/Veo"
    DESCRIPTION = "Generates videos from text prompts using Google's Veo API"
    API_NODE = True

    def generate_video(
        self,
        prompt,
        aspect_ratio="16:9",
        negative_prompt="",
        duration_seconds=5,
        enhance_prompt=True,
        person_generation="ALLOW",
        seed=0,
        image=None,
        auth_token=None,
    ):
        # Prepare the instances for the request
        instances = []

        instance = {
            "prompt": prompt
        }

        # Add image if provided
        if image is not None:
            image_base64 = convert_image_to_base64(image)
            if image_base64:
                instance["image"] = {
                    "bytesBase64Encoded": image_base64,
                    "mimeType": "image/png"
                }

        instances.append(instance)

        # Create parameters dictionary
        parameters = {
            "aspectRatio": aspect_ratio,
            "personGeneration": person_generation,
            "durationSeconds": duration_seconds,
            "enhancePrompt": enhance_prompt,
        }

        # Add optional parameters if provided
        if negative_prompt:
            parameters["negativePrompt"] = negative_prompt
        if seed > 0:
            parameters["seed"] = seed

        # Initial request to start video generation
        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/veo/generate",
                method=HttpMethod.POST,
                request_model=Veo2GenVidRequest,
                response_model=Veo2GenVidResponse
            ),
            request=Veo2GenVidRequest(
                instances=instances,
                parameters=parameters
            ),
            auth_token=auth_token
        )

        initial_response = initial_operation.execute()
        operation_name = initial_response.name

        logging.info(f"Veo generation started with operation name: {operation_name}")

        # Define status extractor function
        def status_extractor(response):
            # Only return "completed" if the operation is done, regardless of success or failure
            # We'll check for errors after polling completes
            return "completed" if response.done else "pending"

        # Define progress extractor function
        def progress_extractor(response):
            # Could be enhanced if the API provides progress information
            return None

        # Define the polling operation
        poll_operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path="/proxy/veo/poll",
                method=HttpMethod.POST,
                request_model=Veo2GenVidPollRequest,
                response_model=Veo2GenVidPollResponse
            ),
            completed_statuses=["completed"],
            failed_statuses=[],  # No failed statuses, we'll handle errors after polling
            status_extractor=status_extractor,
            progress_extractor=progress_extractor,
            request=Veo2GenVidPollRequest(
                operationName=operation_name
            ),
            auth_token=auth_token,
            poll_interval=5.0
        )

        # Execute the polling operation
        poll_response = poll_operation.execute()

        # Now check for errors in the final response
        # Check for error in poll response
        if hasattr(poll_response, 'error') and poll_response.error:
            error_message = f"Veo API error: {poll_response.error.message} (code: {poll_response.error.code})"
            logging.error(error_message)
            raise Exception(error_message)

        # Check for RAI filtered content
        if (hasattr(poll_response.response, 'raiMediaFilteredCount') and
            poll_response.response.raiMediaFilteredCount > 0):

            # Extract reason message if available
            if (hasattr(poll_response.response, 'raiMediaFilteredReasons') and
                poll_response.response.raiMediaFilteredReasons):
                reason = poll_response.response.raiMediaFilteredReasons[0]
                error_message = f"Content filtered by Google's Responsible AI practices: {reason} ({poll_response.response.raiMediaFilteredCount} videos filtered.)"
            else:
                error_message = f"Content filtered by Google's Responsible AI practices ({poll_response.response.raiMediaFilteredCount} videos filtered.)"

            logging.error(error_message)
            raise Exception(error_message)

        # Extract video data
        video_data = None
        if poll_response.response and hasattr(poll_response.response, 'videos') and poll_response.response.videos and len(poll_response.response.videos) > 0:
            video = poll_response.response.videos[0]

            # Check if video is provided as base64 or URL
            if hasattr(video, 'bytesBase64Encoded') and video.bytesBase64Encoded:
                # Decode base64 string to bytes
                video_data = base64.b64decode(video.bytesBase64Encoded)
            elif hasattr(video, 'gcsUri') and video.gcsUri:
                # Download from URL
                video_url = video.gcsUri
                video_response = requests.get(video_url)
                video_data = video_response.content
            else:
                raise Exception("Video returned but no data or URL was provided")
        else:
            raise Exception("Video generation completed but no video was returned")

        if not video_data:
            raise Exception("No video data was returned")

        logging.info("Video generation completed successfully")

        # Convert video data to BytesIO object
        video_io = io.BytesIO(video_data)

        # Return VideoFromFile object
        return (VideoFromFile(video_io),)

```


# Kling Image to Video (Camera Control) - ComfyUI Built-in Node
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-camera-control-i2v

Image to video conversion node with camera control features

<img alt="ComfyUI Built-in Kling Image to Video (Camera Control) Node" />

The Kling Image to Video (Camera Control) node converts static images into videos with professional camera movements. It supports camera controls like zoom, rotation, pan, tilt and first-person view while maintaining focus on the original image content.

## Parameters

### Basic Parameters

| Parameter        | Type   | Default | Description                                     |
| ---------------- | ------ | ------- | ----------------------------------------------- |
| start\_frame     | Image  | -       | Input image to convert to video                 |
| prompt           | String | ""      | Text prompt describing video action and content |
| negative\_prompt | String | ""      | Elements to avoid in the video                  |
| cfg\_scale       | Float  | 7.0     | Controls how closely to follow the prompt       |
| aspect\_ratio    | Select | 16:9    | Output video aspect ratio                       |

### Camera Control Parameters

| Parameter       | Type          | Description                                           |
| --------------- | ------------- | ----------------------------------------------------- |
| camera\_control | CameraControl | Camera control config from Kling Camera Controls node |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | Video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class KlingCameraControlI2VNode(KlingImage2VideoNode):
    """
    Kling Image to Video Camera Control Node. This node is a image to video node, but it supports controlling the camera.
    Duration, mode, and model_name request fields are hard-coded because camera control is only supported in pro mode with the kling-v1-5 model at 5s duration as of 2025-05-02.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "start_frame": model_field_to_node_input(
                    IO.IMAGE, KlingImage2VideoRequest, "image"
                ),
                "prompt": model_field_to_node_input(
                    IO.STRING, KlingImage2VideoRequest, "prompt", multiline=True
                ),
                "negative_prompt": model_field_to_node_input(
                    IO.STRING,
                    KlingImage2VideoRequest,
                    "negative_prompt",
                    multiline=True,
                ),
                "cfg_scale": model_field_to_node_input(
                    IO.FLOAT, KlingImage2VideoRequest, "cfg_scale"
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "aspect_ratio",
                    enum_type=AspectRatio,
                ),
                "camera_control": (
                    "CAMERA_CONTROL",
                    {
                        "tooltip": "Can be created using the Kling Camera Controls node. Controls the camera movement and motion during the video generation.",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    DESCRIPTION = "Transform still images into cinematic videos with professional camera movements that simulate real-world cinematography. Control virtual camera actions including zoom, rotation, pan, tilt, and first-person view, while maintaining focus on your original image."

    def api_call(
        self,
        start_frame: torch.Tensor,
        prompt: str,
        negative_prompt: str,
        cfg_scale: float,
        aspect_ratio: str,
        camera_control: CameraControl,
        auth_token: Optional[str] = None,
    ):
        return super().api_call(
            model_name="kling-v1-5",
            start_frame=start_frame,
            cfg_scale=cfg_scale,
            mode="pro",
            aspect_ratio=aspect_ratio,
            duration="5",
            prompt=prompt,
            negative_prompt=negative_prompt,
            camera_control=camera_control,
            auth_token=auth_token,
        )



```


# Kling Text to Video (Camera Control) - ComfyUI Built-in Node
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-camera-control-t2v

A text to video generation node with camera control features

<img alt="ComfyUI Built-in Kling Text to Video (Camera Control) Node" />

The Kling Text to Video (Camera Control) node converts text into videos with professional camera movements. It extends the standard Kling Text to Video node by adding camera control capabilities.

## Parameters

### Basic Parameters

| Parameter        | Type            | Default | Description                                     |
| ---------------- | --------------- | ------- | ----------------------------------------------- |
| prompt           | String          | ""      | Text prompt describing video content            |
| negative\_prompt | String          | ""      | Elements to avoid in the video                  |
| cfg\_scale       | Float           | 7.0     | Controls how closely to follow the prompt       |
| aspect\_ratio    | Select          | "16:9"  | Output video aspect ratio                       |
| camera\_control  | CAMERA\_CONTROL | -       | Camera settings from Kling Camera Controls node |

### Fixed Parameters

Note: The following parameters are fixed and cannot be changed:

* Model: kling-v1-5
* Mode: pro
* Duration: 5 seconds

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | Video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class KlingCameraControlT2VNode(KlingTextToVideoNode):
    """
    Kling Text to Video Camera Control Node. This node is a text to video node, but it supports controlling the camera.
    Duration, mode, and model_name request fields are hard-coded because camera control is only supported in pro mode with the kling-v1-5 model at 5s duration as of 2025-05-02.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": model_field_to_node_input(
                    IO.STRING, KlingText2VideoRequest, "prompt", multiline=True
                ),
                "negative_prompt": model_field_to_node_input(
                    IO.STRING,
                    KlingText2VideoRequest,
                    "negative_prompt",
                    multiline=True,
                ),
                "cfg_scale": model_field_to_node_input(
                    IO.FLOAT, KlingText2VideoRequest, "cfg_scale"
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.COMBO,
                    KlingText2VideoRequest,
                    "aspect_ratio",
                    enum_type=AspectRatio,
                ),
                "camera_control": (
                    "CAMERA_CONTROL",
                    {
                        "tooltip": "Can be created using the Kling Camera Controls node. Controls the camera movement and motion during the video generation.",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    DESCRIPTION = "Transform text into cinematic videos with professional camera movements that simulate real-world cinematography. Control virtual camera actions including zoom, rotation, pan, tilt, and first-person view, while maintaining focus on your original text."

    def api_call(
        self,
        prompt: str,
        negative_prompt: str,
        cfg_scale: float,
        aspect_ratio: str,
        camera_control: Optional[CameraControl] = None,
        auth_token: Optional[str] = None,
    ):
        return super().api_call(
            model_name="kling-v1-5",
            cfg_scale=cfg_scale,
            mode="pro",
            aspect_ratio=aspect_ratio,
            duration="5",
            prompt=prompt,
            negative_prompt=negative_prompt,
            camera_control=camera_control,
            auth_token=auth_token,
        )



```


# Kling Camera Controls - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-camera-controls

A node that provides camera control parameters for Kling video generation

<img alt="ComfyUI Built-in Kling Camera Controls Node" />

The Kling Camera Controls node defines virtual camera behavior parameters to control camera movement and view changes during Kling video generation.

## Parameters

| Parameter             | Type   | Default  | Description                                                                                                                                                                                                                                          |
| --------------------- | ------ | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| camera\_control\_type | Select | "simple" | Preset camera motion types. simple: Custom camera movement; down\_back: Camera moves down and back; forward\_up: Camera moves forward and up; right\_turn\_forward: Rotate right and move forward; left\_turn\_forward: Rotate left and move forward |
| horizontal\_movement  | Float  | 0        | Controls camera movement on horizontal axis (x-axis). Negative values move left, positive values move right                                                                                                                                          |
| vertical\_movement    | Float  | 0        | Controls camera movement on vertical axis (y-axis). Negative values move down, positive values move up                                                                                                                                               |
| pan                   | Float  | 0.5      | Controls camera rotation in vertical plane (x-axis). Negative values rotate down, positive values rotate up                                                                                                                                          |
| tilt                  | Float  | 0        | Controls camera rotation in horizontal plane (y-axis). Negative values rotate left, positive values rotate right                                                                                                                                     |
| roll                  | Float  | 0        | Controls camera roll amount (z-axis). Negative values rotate counterclockwise, positive values rotate clockwise                                                                                                                                      |
| zoom                  | Float  | 0        | Controls camera focal length. Negative values narrow field of view, positive values widen it                                                                                                                                                         |

**Note**: At least one non-zero camera control parameter is required for the effect to work.

### Output

| Output          | Type            | Description                               |
| --------------- | --------------- | ----------------------------------------- |
| camera\_control | CAMERA\_CONTROL | Configuration object with camera settings |

**Note**: Not all model and mode combinations support camera control. Please check the Kling API documentation for details.

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class KlingCameraControls(KlingNodeBase):
    """Kling Camera Controls Node"""

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "camera_control_type": (
                    IO.COMBO,
                    {
                        "options": [
                            camera_control_type.value
                            for camera_control_type in CameraType
                        ],
                        "default": "simple",
                        "tooltip": "Predefined camera movements type. simple: Customizable camera movement. down_back: Camera descends and moves backward. forward_up: Camera moves forward and tilts up. right_turn_forward: Rotate right and move forward. left_turn_forward: Rotate left and move forward.",
                    },
                ),
                "horizontal_movement": get_camera_control_input_config(
                    "Controls camera's movement along horizontal axis (x-axis). Negative indicates left, positive indicates right"
                ),
                "vertical_movement": get_camera_control_input_config(
                    "Controls camera's movement along vertical axis (y-axis). Negative indicates downward, positive indicates upward."
                ),
                "pan": get_camera_control_input_config(
                    "Controls camera's rotation in vertical plane (x-axis). Negative indicates downward rotation, positive indicates upward rotation.",
                    default=0.5,
                ),
                "tilt": get_camera_control_input_config(
                    "Controls camera's rotation in horizontal plane (y-axis). Negative indicates left rotation, positive indicates right rotation.",
                ),
                "roll": get_camera_control_input_config(
                    "Controls camera's rolling amount (z-axis). Negative indicates counterclockwise, positive indicates clockwise.",
                ),
                "zoom": get_camera_control_input_config(
                    "Controls change in camera's focal length. Negative indicates narrower field of view, positive indicates wider field of view.",
                ),
            }
        }

    DESCRIPTION = "Kling Camera Controls Node. Not all model and mode combinations support camera control. Please refer to the Kling API documentation for more information."
    RETURN_TYPES = ("CAMERA_CONTROL",)
    RETURN_NAMES = ("camera_control",)
    FUNCTION = "main"

    @classmethod
    def VALIDATE_INPUTS(
        cls,
        horizontal_movement: float,
        vertical_movement: float,
        pan: float,
        tilt: float,
        roll: float,
        zoom: float,
    ) -> bool | str:
        if not is_valid_camera_control_configs(
            [
                horizontal_movement,
                vertical_movement,
                pan,
                tilt,
                roll,
                zoom,
            ]
        ):
            return "Invalid camera control configs: at least one of the values must be non-zero"
        return True

    def main(
        self,
        camera_control_type: str,
        horizontal_movement: float,
        vertical_movement: float,
        pan: float,
        tilt: float,
        roll: float,
        zoom: float,
    ) -> tuple[CameraControl]:
        return (
            CameraControl(
                type=CameraType(camera_control_type),
                config=CameraConfig(
                    horizontal=horizontal_movement,
                    vertical=vertical_movement,
                    pan=pan,
                    roll=roll,
                    tilt=tilt,
                    zoom=zoom,
                ),
            ),
        )
```


# Kling Image to Video - ComfyUI Built-in Node
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-image-to-video

A node that converts static images to dynamic videos using Kling's AI technology

<img alt="ComfyUI Built-in Kling Image to Video Node" />

The Kling Image to Video node converts static images into dynamic video content using Kling's image-to-video API.

## Parameters

### Basic Parameters

All parameters below are required:

| Parameter        | Type   | Default      | Description                                     |
| ---------------- | ------ | ------------ | ----------------------------------------------- |
| start\_frame     | Image  | -            | Input source image                              |
| prompt           | String | ""           | Text prompt describing video action and content |
| negative\_prompt | String | ""           | Elements to avoid in the video                  |
| cfg\_scale       | Float  | 7.0          | Controls how closely to follow the prompt       |
| model\_name      | Select | "kling-v1-5" | Model type to use                               |
| aspect\_ratio    | Select | "16:9"       | Output video aspect ratio                       |
| duration         | Select | "5s"         | Generated video duration                        |
| mode             | Select | "pro"        | Video generation mode                           |

### Output

| Output    | Type   | Description             |
| --------- | ------ | ----------------------- |
| VIDEO     | Video  | Generated video         |
| video\_id | String | Unique video identifier |
| duration  | String | Actual video duration   |

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class KlingImage2VideoNode(KlingNodeBase):
    """Kling Image to Video Node"""

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "start_frame": model_field_to_node_input(
                    IO.IMAGE, KlingImage2VideoRequest, "image"
                ),
                "prompt": model_field_to_node_input(
                    IO.STRING, KlingImage2VideoRequest, "prompt", multiline=True
                ),
                "negative_prompt": model_field_to_node_input(
                    IO.STRING,
                    KlingImage2VideoRequest,
                    "negative_prompt",
                    multiline=True,
                ),
                "model_name": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "model_name",
                    enum_type=KlingVideoGenModelName,
                ),
                "cfg_scale": model_field_to_node_input(
                    IO.FLOAT, KlingImage2VideoRequest, "cfg_scale"
                ),
                "mode": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "mode",
                    enum_type=KlingVideoGenMode,
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "aspect_ratio",
                    enum_type=KlingVideoGenAspectRatio,
                ),
                "duration": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "duration",
                    enum_type=KlingVideoGenDuration,
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = ("VIDEO", "STRING", "STRING")
    RETURN_NAMES = ("VIDEO", "video_id", "duration")
    DESCRIPTION = "Kling Image to Video Node"

    def get_response(self, task_id: str, auth_token: str) -> KlingImage2VideoResponse:
        return poll_until_finished(
            auth_token,
            ApiEndpoint(
                path=f"{PATH_IMAGE_TO_VIDEO}/{task_id}",
                method=HttpMethod.GET,
                request_model=KlingImage2VideoRequest,
                response_model=KlingImage2VideoResponse,
            ),
        )

    def api_call(
        self,
        start_frame: torch.Tensor,
        prompt: str,
        negative_prompt: str,
        model_name: str,
        cfg_scale: float,
        mode: str,
        aspect_ratio: str,
        duration: str,
        camera_control: Optional[KlingCameraControl] = None,
        end_frame: Optional[torch.Tensor] = None,
        auth_token: Optional[str] = None,
    ) -> tuple[VideoFromFile]:
        validate_prompts(prompt, negative_prompt, MAX_PROMPT_LENGTH_I2V)
        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=PATH_IMAGE_TO_VIDEO,
                method=HttpMethod.POST,
                request_model=KlingImage2VideoRequest,
                response_model=KlingImage2VideoResponse,
            ),
            request=KlingImage2VideoRequest(
                model_name=KlingVideoGenModelName(model_name),
                image=tensor_to_base64_string(start_frame),
                image_tail=(
                    tensor_to_base64_string(end_frame)
                    if end_frame is not None
                    else None
                ),
                prompt=prompt,
                negative_prompt=negative_prompt if negative_prompt else None,
                cfg_scale=cfg_scale,
                mode=KlingVideoGenMode(mode),
                aspect_ratio=KlingVideoGenAspectRatio(aspect_ratio),
                duration=KlingVideoGenDuration(duration),
                camera_control=camera_control,
            ),
            auth_token=auth_token,
        )

        task_creation_response = initial_operation.execute()
        validate_task_creation_response(task_creation_response)
        task_id = task_creation_response.data.task_id

        final_response = self.get_response(task_id, auth_token)
        validate_video_result_response(final_response)

        video = get_video_from_response(final_response)
        return video_result_to_node_output(video)

```


# Kling Start-End Frame to Video - ComfyUI Built-in Node
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-start-end-frame-to-video

A node that creates smooth video transitions between start and end frames using Kling's AI technology

<img alt="ComfyUI Built-in Kling Start-End Frame to Video Node" />

The Kling Start-End Frame to Video node lets you create smooth video transitions between two images. It automatically generates all the intermediate frames to produce a fluid transformation.

## Parameters

### Required Parameters

| Parameter        | Type   | Description                                     |
| ---------------- | ------ | ----------------------------------------------- |
| start\_frame     | Image  | Starting image for the video                    |
| end\_frame       | Image  | Ending image for the video                      |
| prompt           | String | Text describing video content and transition    |
| negative\_prompt | String | Elements to avoid in the video                  |
| cfg\_scale       | Float  | Controls how closely to follow the prompt       |
| aspect\_ratio    | Select | Output video aspect ratio                       |
| mode             | Select | Video generation settings (mode/duration/model) |

### Mode Options

Available mode combinations:

* standard mode / 5s duration / kling-v1
* standard mode / 5s duration / kling-v1-5
* pro mode / 5s duration / kling-v1
* pro mode / 5s duration / kling-v1-5
* pro mode / 5s duration / kling-v1-6
* pro mode / 10s duration / kling-v1-5
* pro mode / 10s duration / kling-v1-6

Default: "pro mode / 5s duration / kling-v1"

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | Video | Generated video |

## How It Works

The node analyzes the start and end frames to create a smooth transition sequence between them. It sends the images and parameters to Kling's API server, which generates all necessary intermediate frames for a fluid transformation.

The transition style and content can be guided using prompts, while negative prompts help avoid unwanted elements.

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}


class KlingStartEndFrameNode(KlingImage2VideoNode):
    """
    Kling First Last Frame Node. This node allows creation of a video from a first and last frame. It calls the normal image to video endpoint, but only allows the subset of input options that support the `image_tail` request field.
    """

    @staticmethod
    def get_mode_string_mapping() -> dict[str, tuple[str, str, str]]:
        """
        Returns a mapping of mode strings to their corresponding (mode, duration, model_name) tuples.
        Only includes config combos that support the `image_tail` request field.
        """
        return {
            "standard mode / 5s duration / kling-v1": ("std", "5", "kling-v1"),
            "standard mode / 5s duration / kling-v1-5": ("std", "5", "kling-v1-5"),
            "pro mode / 5s duration / kling-v1": ("pro", "5", "kling-v1"),
            "pro mode / 5s duration / kling-v1-5": ("pro", "5", "kling-v1-5"),
            "pro mode / 5s duration / kling-v1-6": ("pro", "5", "kling-v1-6"),
            "pro mode / 10s duration / kling-v1-5": ("pro", "10", "kling-v1-5"),
            "pro mode / 10s duration / kling-v1-6": ("pro", "10", "kling-v1-6"),
        }

    @classmethod
    def INPUT_TYPES(s):
        modes = list(KlingStartEndFrameNode.get_mode_string_mapping().keys())
        return {
            "required": {
                "start_frame": model_field_to_node_input(
                    IO.IMAGE, KlingImage2VideoRequest, "image"
                ),
                "end_frame": model_field_to_node_input(
                    IO.IMAGE, KlingImage2VideoRequest, "image_tail"
                ),
                "prompt": model_field_to_node_input(
                    IO.STRING, KlingImage2VideoRequest, "prompt", multiline=True
                ),
                "negative_prompt": model_field_to_node_input(
                    IO.STRING,
                    KlingImage2VideoRequest,
                    "negative_prompt",
                    multiline=True,
                ),
                "cfg_scale": model_field_to_node_input(
                    IO.FLOAT, KlingImage2VideoRequest, "cfg_scale"
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.COMBO,
                    KlingImage2VideoRequest,
                    "aspect_ratio",
                    enum_type=AspectRatio,
                ),
                "mode": (
                    modes,
                    {
                        "default": modes[2],
                        "tooltip": "The configuration to use for the video generation following the format: mode / duration / model_name.",
                    },
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    DESCRIPTION = "Generate a video sequence that transitions between your provided start and end images. The node creates all frames in between, producing a smooth transformation from the first frame to the last."

    def parse_inputs_from_mode(self, mode: str) -> tuple[str, str, str]:
        """Parses the mode input into a tuple of (model_name, duration, mode)."""
        return KlingStartEndFrameNode.get_mode_string_mapping()[mode]

    def api_call(
        self,
        start_frame: torch.Tensor,
        end_frame: torch.Tensor,
        prompt: str,
        negative_prompt: str,
        cfg_scale: float,
        aspect_ratio: str,
        mode: str,
        auth_token: Optional[str] = None,
    ):
        mode, duration, model_name = self.parse_inputs_from_mode(mode)
        return super().api_call(
            prompt=prompt,
            negative_prompt=negative_prompt,
            model_name=model_name,
            start_frame=start_frame,
            cfg_scale=cfg_scale,
            mode=mode,
            aspect_ratio=aspect_ratio,
            duration=duration,
            end_frame=end_frame,
            auth_token=auth_token,
        )


```


# Kling Text to Video - ComfyUI Built-in Node
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/kwai_vgi/kling-text-to-video

A node that converts text descriptions into videos using Kling's AI technology

<img alt="ComfyUI Built-in Kling Text to Video Node" />

The Kling Text to Video node connects to Kling's API service to generate videos from text descriptions. Users simply provide descriptive text to create corresponding video content.

## Parameters

### Required Parameters

| Parameter        | Type   | Default           | Description                                  |
| ---------------- | ------ | ----------------- | -------------------------------------------- |
| prompt           | String | ""                | Text prompt describing desired video content |
| negative\_prompt | String | ""                | Elements to avoid in the video               |
| cfg\_scale       | Float  | 7.0               | Controls how closely to follow the prompt    |
| model\_name      | Select | "kling-v2-master" | Video generation model to use                |
| aspect\_ratio    | Select | AspectRatio enum  | Output video aspect ratio                    |
| duration         | Select | Duration enum     | Length of generated video                    |
| mode             | Select | Mode enum         | Video generation mode                        |

### Output

| Output         | Type   | Description             |
| -------------- | ------ | ----------------------- |
| VIDEO          | Video  | Generated video         |
| Kling ID       | String | Task identifier         |
| Duration (sec) | String | Video length in seconds |

## How It Works

The node sends text prompts to Kling's API server, which processes and returns the generated video. The process includes initial request and status polling. When complete, the node downloads and outputs the video.

Users can control the generation by adjusting parameters like negative prompts, configuration scale, and video properties. The system validates prompt length to ensure API compliance.

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class KlingTextToVideoNode(KlingNodeBase):
    """Kling Text to Video Node"""

    @staticmethod
    def poll_for_task_status(task_id: str, auth_token: str) -> KlingText2VideoResponse:
        """Polls the Kling API endpoint until the task reaches a terminal state."""
        polling_operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"{PATH_TEXT_TO_VIDEO}/{task_id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=KlingText2VideoResponse,
            ),
            completed_statuses=[
                TaskStatus.succeed.value,
            ],
            failed_statuses=[TaskStatus.failed.value],
            status_extractor=lambda response: (
                response.data.task_status.value
                if response.data and response.data.task_status
                else None
            ),
            auth_token=auth_token,
        )
        return polling_operation.execute()

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": model_field_to_node_input(
                    IO.STRING, KlingText2VideoRequest, "prompt", multiline=True
                ),
                "negative_prompt": model_field_to_node_input(
                    IO.STRING, KlingText2VideoRequest, "negative_prompt", multiline=True
                ),
                "model_name": model_field_to_node_input(
                    IO.COMBO,
                    KlingText2VideoRequest,
                    "model_name",
                    enum_type=ModelName,
                    default="kling-v2-master",
                ),
                "cfg_scale": model_field_to_node_input(
                    IO.FLOAT, KlingText2VideoRequest, "cfg_scale"
                ),
                "mode": model_field_to_node_input(
                    IO.COMBO, KlingText2VideoRequest, "mode", enum_type=Mode
                ),
                "duration": model_field_to_node_input(
                    IO.COMBO, KlingText2VideoRequest, "duration", enum_type=Duration
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.COMBO,
                    KlingText2VideoRequest,
                    "aspect_ratio",
                    enum_type=AspectRatio,
                ),
            },
            "hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
        }

    RETURN_TYPES = ("VIDEO", "STRING", "STRING")
    RETURN_NAMES = ("VIDEO", "Kling ID", "Duration (sec)")
    DESCRIPTION = "Kling Text to Video Node"

    def api_call(
        self,
        prompt: str,
        negative_prompt: str,
        model_name: str,
        cfg_scale: float,
        mode: str,
        duration: int,
        aspect_ratio: str,
        camera_control: Optional[CameraControl] = None,
        auth_token: Optional[str] = None,
    ) -> tuple[VideoFromFile, str, str]:
        validate_prompts(prompt, negative_prompt, MAX_PROMPT_LENGTH_T2V)
        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=PATH_TEXT_TO_VIDEO,
                method=HttpMethod.POST,
                request_model=KlingText2VideoRequest,
                response_model=KlingText2VideoResponse,
            ),
            request=KlingText2VideoRequest(
                prompt=prompt if prompt else None,
                negative_prompt=negative_prompt if negative_prompt else None,
                duration=Duration(duration),
                mode=Mode(mode),
                model_name=ModelName(model_name),
                cfg_scale=cfg_scale,
                aspect_ratio=AspectRatio(aspect_ratio),
                camera_control=camera_control,
            ),
            auth_token=auth_token,
        )

        initial_response = initial_operation.execute()
        if not is_valid_initial_response(initial_response):
            error_msg = f"Kling initial request failed. Code: {initial_response.code}, Message: {initial_response.message}, Data: {initial_response.data}"
            logging.error(error_msg)
            raise KlingApiError(error_msg)

        task_id = initial_response.data.task_id
        final_response = self.poll_for_task_status(task_id, auth_token)
        if not is_valid_video_response(final_response):
            error_msg = (
                f"Kling task {task_id} succeeded but no video data found in response."
            )
            logging.error(error_msg)
            raise KlingApiError(error_msg)

        video = final_response.data.task_result.videos[0]
        logging.debug("Kling task %s succeeded. Video URL: %s", task_id, video.url)
        return (
            download_url_to_video_output(video.url),
            str(video.id),
            str(video.duration),
        )

```


# Luma Concepts - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/luma/luma-concepts

A helper node that provides concept guidance for Luma image generation

<img alt="ComfyUI Native Luma Concepts Node" />

The Luma Concepts node allows you to apply predefined camera concepts to the Luma generation process, providing precise control over camera angles and perspectives without complex prompt descriptions.

## Node Function

This node serves as a helper tool for Luma generation nodes, enabling users to select and apply predefined camera concepts. These concepts include different shooting angles (like overhead or low angle), camera distances (like close-up or long shot), and movement styles (like push-in or follow). It simplifies the creative workflow by providing an intuitive way to control camera effects in the generated output.

## Parameters

### Basic Parameters

| Parameter | Type   | Description                                                       |
| --------- | ------ | ----------------------------------------------------------------- |
| concept1  | select | First camera concept choice, includes various presets and "none"  |
| concept2  | select | Second camera concept choice, includes various presets and "none" |
| concept3  | select | Third camera concept choice, includes various presets and "none"  |
| concept4  | select | Fourth camera concept choice, includes various presets and "none" |

### Optional Parameters

| Parameter      | Type           | Description                                              |
| -------------- | -------------- | -------------------------------------------------------- |
| luma\_concepts | LUMA\_CONCEPTS | Optional Camera Concepts to merge with selected concepts |

### Output

| Output         | Type          | Description                                      |
| -------------- | ------------- | ------------------------------------------------ |
| luma\_concepts | LUMA\_CONCEPT | Combined object containing all selected concepts |

## Usage Examples

<Card title="Luma Text to Video Workflow Example" icon="book" href="/tutorials/partner-nodes/luma/luma-text-to-video">
  Luma Text to Video Workflow Example
</Card>

<Card title="Luma Image to Video Workflow Example" icon="book" href="/tutorials/partner-nodes/luma/luma-image-to-video">
  Luma Image to Video Workflow Example
</Card>

## How It Works

The Luma Concepts node offers a variety of predefined camera concepts including:

* Camera distances (close-up, medium shot, long shot)
* View angles (eye level, overhead, low angle)
* Movement types (push-in, follow, orbit)
* Special effects (handheld, stabilized, floating)

Users can select up to 4 concepts to use together. The node creates an object containing the selected camera concepts, which is then passed to Luma generation nodes. During generation, Luma AI uses these camera concepts to influence the viewpoint and composition of the output, ensuring the results reflect the chosen photographic effects.

By combining multiple camera concepts, users can create complex camera guidance without writing detailed prompt descriptions. This is particularly useful when specific camera angles or compositions are needed.

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class LumaConceptsNode(ComfyNodeABC):
    """
    Holds one or more Camera Concepts for use with Luma Text to Video and Luma Image to Video nodes.
    """

    RETURN_TYPES = (LumaIO.LUMA_CONCEPTS,)
    RETURN_NAMES = ("luma_concepts",)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "create_concepts"
    CATEGORY = "api node/image/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "concept1": (get_luma_concepts(include_none=True),),
                "concept2": (get_luma_concepts(include_none=True),),
                "concept3": (get_luma_concepts(include_none=True),),
                "concept4": (get_luma_concepts(include_none=True),),
            },
            "optional": {
                "luma_concepts": (
                    LumaIO.LUMA_CONCEPTS,
                    {
                        "tooltip": "Optional Camera Concepts to add to the ones chosen here."
                    },
                ),
            },
        }

    def create_concepts(
        self,
        concept1: str,
        concept2: str,
        concept3: str,
        concept4: str,
        luma_concepts: LumaConceptChain = None,
    ):
        chain = LumaConceptChain(str_list=[concept1, concept2, concept3, concept4])
        if luma_concepts is not None:
            chain = luma_concepts.clone_and_merge(chain)
        return (chain,)


```


# Luma Image to Video - ComfyUI Native Partner Nodes Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/luma/luma-image-to-video

A node that converts static images to dynamic videos using Luma AI

<img alt="ComfyUI Native Luma Image to Video Node" />

The Luma Image to Video node uses Luma AI's technology to transform static images into smooth, dynamic videos, bringing your images to life.

## Node Function

This node connects to Luma AI's image-to-video API, allowing users to create dynamic videos from input images. It understands the image content and generates natural, coherent motion while maintaining the original visual style. Combined with text prompts, users can precisely control the video's dynamic effects.

## Parameters

### Basic Parameters

| Parameter  | Type    | Default | Description                                             |
| ---------- | ------- | ------- | ------------------------------------------------------- |
| prompt     | string  | ""      | Text prompt describing video motion and content         |
| model      | select  | -       | Video generation model to use                           |
| resolution | select  | "540p"  | Output video resolution                                 |
| duration   | select  | -       | Video length options                                    |
| loop       | boolean | False   | Whether to loop the video                               |
| seed       | integer | 0       | Seed value for node rerun, results are nondeterministic |

### Optional Parameters

| Parameter      | Type           | Description                                           |
| -------------- | -------------- | ----------------------------------------------------- |
| first\_image   | image          | First frame of video (required if no last\_image)     |
| last\_image    | image          | Last frame of video (required if no first\_image)     |
| luma\_concepts | LUMA\_CONCEPTS | Concepts for controlling camera motion and shot style |

### Requirements

* Either **first\_image** or **last\_image** must be provided
* Each image input (first\_image and last\_image) accepts only 1 image

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | video | Generated video |

## Usage Example

<Card title="Luma Image to Video Workflow Example" icon="book" href="/tutorials/partner-nodes/luma/luma-image-to-video">
  Luma Image to Video Workflow Tutorial
</Card>

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class LumaImageToVideoGenerationNode(ComfyNodeABC):
    """
    Generates videos synchronously based on prompt, input images, and output_size.
    """

    RETURN_TYPES = (IO.VIDEO,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/video/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the video generation",
                    },
                ),
                "model": ([model.value for model in LumaVideoModel],),
                # "aspect_ratio": ([ratio.value for ratio in LumaAspectRatio], {
                #     "default": LumaAspectRatio.ratio_16_9,
                # }),
                "resolution": (
                    [resolution.value for resolution in LumaVideoOutputResolution],
                    {
                        "default": LumaVideoOutputResolution.res_540p,
                    },
                ),
                "duration": ([dur.value for dur in LumaVideoModelOutputDuration],),
                "loop": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "first_image": (
                    IO.IMAGE,
                    {"tooltip": "First frame of generated video."},
                ),
                "last_image": (IO.IMAGE, {"tooltip": "Last frame of generated video."}),
                "luma_concepts": (
                    LumaIO.LUMA_CONCEPTS,
                    {
                        "tooltip": "Optional Camera Concepts to dictate camera motion via the Luma Concepts node."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        model: str,
        resolution: str,
        duration: str,
        loop: bool,
        seed,
        first_image: torch.Tensor = None,
        last_image: torch.Tensor = None,
        luma_concepts: LumaConceptChain = None,
        auth_token=None,
        **kwargs,
    ):
        if first_image is None and last_image is None:
            raise Exception(
                "At least one of first_image and last_image requires an input."
            )
        keyframes = self._convert_to_keyframes(first_image, last_image, auth_token)
        duration = duration if model != LumaVideoModel.ray_1_6 else None
        resolution = resolution if model != LumaVideoModel.ray_1_6 else None

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/luma/generations",
                method=HttpMethod.POST,
                request_model=LumaGenerationRequest,
                response_model=LumaGeneration,
            ),
            request=LumaGenerationRequest(
                prompt=prompt,
                model=model,
                aspect_ratio=LumaAspectRatio.ratio_16_9,  # ignored, but still needed by the API for some reason
                resolution=resolution,
                duration=duration,
                loop=loop,
                keyframes=keyframes,
                concepts=luma_concepts.create_api_model() if luma_concepts else None,
            ),
            auth_token=auth_token,
        )
        response_api: LumaGeneration = operation.execute()

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/luma/generations/{response_api.id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=LumaGeneration,
            ),
            completed_statuses=[LumaState.completed],
            failed_statuses=[LumaState.failed],
            status_extractor=lambda x: x.state,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        vid_response = requests.get(response_poll.assets.video)
        return (VideoFromFile(BytesIO(vid_response.content)),)

    def _convert_to_keyframes(
        self,
        first_image: torch.Tensor = None,
        last_image: torch.Tensor = None,
        auth_token=None,
    ):
        if first_image is None and last_image is None:
            return None
        frame0 = None
        frame1 = None
        if first_image is not None:
            download_urls = upload_images_to_comfyapi(
                first_image, max_images=1, auth_token=auth_token
            )
            frame0 = LumaImageReference(type="image", url=download_urls[0])
        if last_image is not None:
            download_urls = upload_images_to_comfyapi(
                last_image, max_images=1, auth_token=auth_token
            )
            frame1 = LumaImageReference(type="image", url=download_urls[0])
        return LumaKeyframes(frame0=frame0, frame1=frame1)

```


# Luma Text to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/luma/luma-text-to-video

A node that converts text descriptions to videos using Luma AI

<img alt="ComfyUI Native Luma Text to Video Node" />

The Luma Text to Video node lets you create high-quality, smooth videos from text descriptions using Luma AI's video generation technology.

## Node Function

This node connects to Luma AI's text-to-video API, allowing users to generate dynamic video content from detailed text prompts.

## Parameters

### Basic Parameters

| Parameter     | Type    | Default        | Description                                             |
| ------------- | ------- | -------------- | ------------------------------------------------------- |
| prompt        | string  | ""             | Text prompt describing the video content to generate    |
| model         | select  | -              | Video generation model to use                           |
| aspect\_ratio | select  | "ratio\_16\_9" | Video aspect ratio                                      |
| resolution    | select  | "res\_540p"    | Video resolution                                        |
| duration      | select  | -              | Video length options                                    |
| loop          | boolean | False          | Whether to loop the video                               |
| seed          | integer | 0              | Seed value for node rerun, results are nondeterministic |

<Note>
  When using Ray 1.6 model, duration and resolution parameters will not take effect.
</Note>

### Optional Parameters

| Parameter      | Type           | Description                                              |
| -------------- | -------------- | -------------------------------------------------------- |
| luma\_concepts | LUMA\_CONCEPTS | Camera concepts to control motion via Luma Concepts node |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | video | Generated video |

## Usage Example

<Card title="Luma Text to Video Workflow Example" icon="book" href="/tutorials/partner-nodes/luma/luma-text-to-video">
  Luma Text to Video Workflow Example
</Card>

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class LumaTextToVideoGenerationNode(ComfyNodeABC):
    """
    Generates videos synchronously based on prompt and output_size.
    """

    RETURN_TYPES = (IO.VIDEO,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/video/Luma"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the video generation",
                    },
                ),
                "model": ([model.value for model in LumaVideoModel],),
                "aspect_ratio": (
                    [ratio.value for ratio in LumaAspectRatio],
                    {
                        "default": LumaAspectRatio.ratio_16_9,
                    },
                ),
                "resolution": (
                    [resolution.value for resolution in LumaVideoOutputResolution],
                    {
                        "default": LumaVideoOutputResolution.res_540p,
                    },
                ),
                "duration": ([dur.value for dur in LumaVideoModelOutputDuration],),
                "loop": (
                    IO.BOOLEAN,
                    {
                        "default": False,
                    },
                ),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.",
                    },
                ),
            },
            "optional": {
                "luma_concepts": (
                    LumaIO.LUMA_CONCEPTS,
                    {
                        "tooltip": "Optional Camera Concepts to dictate camera motion via the Luma Concepts node."
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        model: str,
        aspect_ratio: str,
        resolution: str,
        duration: str,
        loop: bool,
        seed,
        luma_concepts: LumaConceptChain = None,
        auth_token=None,
        **kwargs,
    ):
        duration = duration if model != LumaVideoModel.ray_1_6 else None
        resolution = resolution if model != LumaVideoModel.ray_1_6 else None

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/luma/generations",
                method=HttpMethod.POST,
                request_model=LumaGenerationRequest,
                response_model=LumaGeneration,
            ),
            request=LumaGenerationRequest(
                prompt=prompt,
                model=model,
                resolution=resolution,
                aspect_ratio=aspect_ratio,
                duration=duration,
                loop=loop,
                concepts=luma_concepts.create_api_model() if luma_concepts else None,
            ),
            auth_token=auth_token,
        )
        response_api: LumaGeneration = operation.execute()

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/luma/generations/{response_api.id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=LumaGeneration,
            ),
            completed_statuses=[LumaState.completed],
            failed_statuses=[LumaState.failed],
            status_extractor=lambda x: x.state,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        vid_response = requests.get(response_poll.assets.video)
        return (VideoFromFile(BytesIO(vid_response.content)),)

```


# MiniMax Image to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/minimax/minimax-image-to-video

A node that converts static images to dynamic videos using MiniMax AI

<img alt="ComfyUI Native MiniMax Image to Video Node" />

The MiniMax Image to Video node uses MiniMax's API to generate videos from input images and text prompts.

## Parameters

### Required Parameters

| Parameter    | Type   | Default  | Description                                                  |
| ------------ | ------ | -------- | ------------------------------------------------------------ |
| image        | image  | -        | Input image used as the first frame of video                 |
| prompt\_text | string | ""       | Text prompt to guide video generation                        |
| model        | select | "I2V-01" | Available models: "I2V-01-Director", "I2V-01", "I2V-01-live" |

### Optional Parameters

| Parameter | Type    | Description                      |
| --------- | ------- | -------------------------------- |
| seed      | integer | Random seed for noise generation |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | video | Generated video |

## Source Code

\[Node source code (Updated on 2025-05-03)]

```python theme={null}

class MinimaxImageToVideoNode(MinimaxTextToVideoNode):
    """
    Generates videos synchronously based on an image and prompt, and optional parameters using Minimax's API.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": (
                    IO.IMAGE,
                    {
                        "tooltip": "Image to use as first frame of video generation"
                    },
                ),
                "prompt_text": (
                    "STRING",
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text prompt to guide the video generation",
                    },
                ),
                "model": (
                    [
                        "I2V-01-Director",
                        "I2V-01",
                        "I2V-01-live",
                    ],
                    {
                        "default": "I2V-01",
                        "tooltip": "Model to use for video generation",
                    },
                ),
            },
            "optional": {
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "The random seed used for creating the noise.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    RETURN_TYPES = ("VIDEO",)
    DESCRIPTION = "Generates videos from an image and prompts using Minimax's API"
    FUNCTION = "generate_video"
    CATEGORY = "api node/video/Minimax"
    API_NODE = True
    OUTPUT_NODE = True
```


# MiniMax Text to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/minimax/minimax-text-to-video

A node that converts text descriptions into videos using MiniMax AI

<img alt="ComfyUI Native MiniMax Text to Video Node" />

The MiniMax Text to Video node connects to MiniMax's API to generate high-quality, smooth videos from text prompts. It supports different video generation models to create short video clips in various styles.

## Parameters

### Required Parameters

| Parameter    | Type    | Default  | Description                                                    |
| ------------ | ------- | -------- | -------------------------------------------------------------- |
| prompt\_text | String  | ""       | Text prompt that guides the video generation                   |
| model        | Select  | "T2V-01" | Video model to use, options are "T2V-01" and "T2V-01-Director" |
| seed         | Integer | 0        | Random seed for noise generation, defaults to 0                |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | Video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-03)]

```python theme={null}

class MinimaxTextToVideoNode:
    """
    Generates videos synchronously based on a prompt, and optional parameters using Minimax's API.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt_text": (
                    "STRING",
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Text prompt to guide the video generation",
                    },
                ),
                "model": (
                    [
                        "T2V-01",
                        "T2V-01-Director",
                    ],
                    {
                        "default": "T2V-01",
                        "tooltip": "Model to use for video generation",
                    },
                ),
            },
            "optional": {
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 0xFFFFFFFFFFFFFFFF,
                        "control_after_generate": True,
                        "tooltip": "The random seed used for creating the noise.",
                    },
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    RETURN_TYPES = ("VIDEO",)
    DESCRIPTION = "Generates videos from prompts using Minimax's API"
    FUNCTION = "generate_video"
    CATEGORY = "api node/video/Minimax"
    API_NODE = True
    OUTPUT_NODE = True

    def generate_video(
        self,
        prompt_text,
        seed=0,
        model="T2V-01",
        image: torch.Tensor=None, # used for ImageToVideo
        subject: torch.Tensor=None, # used for SubjectToVideo
        auth_token=None,
    ):
        '''
        Function used between Minimax nodes - supports T2V, I2V, and S2V, based on provided arguments.
        '''
        # upload image, if passed in
        image_url = None
        if image is not None:
            image_url = upload_images_to_comfyapi(image, max_images=1, auth_token=auth_token)[0]

        # TODO: figure out how to deal with subject properly, API returns invalid params when using S2V-01 model
        subject_reference = None
        if subject is not None:
            subject_url = upload_images_to_comfyapi(subject, max_images=1, auth_token=auth_token)[0]
            subject_reference = [SubjectReferenceItem(image=subject_url)]


        video_generate_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/minimax/video_generation",
                method=HttpMethod.POST,
                request_model=MinimaxVideoGenerationRequest,
                response_model=MinimaxVideoGenerationResponse,
            ),
            request=MinimaxVideoGenerationRequest(
                model=Model(model),
                prompt=prompt_text,
                callback_url=None,
                first_frame_image=image_url,
                subject_reference=subject_reference,
                prompt_optimizer=None,
            ),
            auth_token=auth_token,
        )
        response = video_generate_operation.execute()

        task_id = response.task_id
        if not task_id:
            raise Exception(f"Minimax generation failed: {response.base_resp}")

        video_generate_operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path="/proxy/minimax/query/video_generation",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=MinimaxTaskResultResponse,
                query_params={"task_id": task_id},
            ),
            completed_statuses=["Success"],
            failed_statuses=["Fail"],
            status_extractor=lambda x: x.status.value,
            auth_token=auth_token,
        )
        task_result = video_generate_operation.execute()

        file_id = task_result.file_id
        if file_id is None:
            raise Exception("Request was not successful. Missing file ID.")
        file_retrieve_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/minimax/files/retrieve",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=MinimaxFileRetrieveResponse,
                query_params={"file_id": int(file_id)},
            ),
            request=EmptyRequest(),
            auth_token=auth_token,
        )
        file_result = file_retrieve_operation.execute()

        file_url = file_result.file.download_url
        if file_url is None:
            raise Exception(
                f"No video was found in the response. Full response: {file_result.model_dump()}"
            )
        logging.info(f"Generated video URL: {file_url}")

        video_io = download_url_to_bytesio(file_url)
        if video_io is None:
            error_msg = f"Failed to download video from {file_url}"
            logging.error(error_msg)
            raise Exception(error_msg)
        return (VideoFromFile(video_io),)
```


# Pika 2.2 Image to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pika/pika-image-to-video

A node that converts static images to dynamic videos using Pika AI

<img alt="ComfyUI Native Pika 2.2 Image to Video Node" />

The Pika 2.2 Image to Video node connects to Pika's latest 2.2 API to transform static images into dynamic videos. It preserves the visual features of the original image while adding natural motion based on text prompts.

## Parameters

### Required Parameters

| Parameter        | Type    | Default | Description                                     |
| ---------------- | ------- | ------- | ----------------------------------------------- |
| image            | Image   | -       | Input image to convert to video                 |
| prompt\_text     | String  | ""      | Text prompt describing video motion and content |
| negative\_prompt | String  | ""      | Elements to avoid in the video                  |
| seed             | Integer | 0       | Random seed for generation                      |
| resolution       | Select  | "1080p" | Output video resolution                         |
| duration         | Select  | "5s"    | Length of generated video                       |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | Video | Generated video |

## How It Works

The node sends the input image and parameters (prompts, resolution, duration, etc.) to Pika's API server as multipart form data. The API processes this and returns the generated video. Users can control the output by adjusting the prompts, negative prompts, random seed and other parameters.

## Source Code

\[Node Source Code (Updated 2025-05-05)]

```python theme={null}

class PikaImageToVideoV2_2(PikaNodeBase):
    """Pika 2.2 Image to Video Node."""

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "image": (
                    IO.IMAGE,
                    {"tooltip": "The image to convert to video"},
                ),
                **cls.get_base_inputs_types(PikaBodyGenerate22I2vGenerate22I2vPost),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    DESCRIPTION = "Sends an image and prompt to the Pika API v2.2 to generate a video."
    RETURN_TYPES = ("VIDEO",)

    def api_call(
        self,
        image: torch.Tensor,
        prompt_text: str,
        negative_prompt: str,
        seed: int,
        resolution: str,
        duration: int,
        auth_token: Optional[str] = None,
    ) -> tuple[VideoFromFile]:
        """API call for Pika 2.2 Image to Video."""
        # Convert image to BytesIO
        image_bytes_io = tensor_to_bytesio(image)
        image_bytes_io.seek(0)  # Reset stream position

        # Prepare file data for multipart upload
        pika_files = {"image": ("image.png", image_bytes_io, "image/png")}

        # Prepare non-file data using the Pydantic model
        pika_request_data = PikaBodyGenerate22I2vGenerate22I2vPost(
            promptText=prompt_text,
            negativePrompt=negative_prompt,
            seed=seed,
            resolution=resolution,
            duration=duration,
        )

        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=PATH_IMAGE_TO_VIDEO,
                method=HttpMethod.POST,
                request_model=PikaBodyGenerate22I2vGenerate22I2vPost,
                response_model=PikaGenerateResponse,
            ),
            request=pika_request_data,
            files=pika_files,
            content_type="multipart/form-data",
            auth_token=auth_token,
        )

        return self.execute_task(initial_operation, auth_token)

```


# Pika 2.2 Scenes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pika/pika-scenes

A node that creates coherent scene videos from multiple images using Pika AI

<img alt="ComfyUI Built-in Pika 2.2 Scenes Node" />

The Pika 2.2 Scenes node allows you to upload multiple images and generate a high-quality video incorporating these elements. It uses Pika's 2.2 API to create smooth scene transitions between the images.

## Parameters

### Required Parameters

| Parameter         | Type    | Default                   | Description                                     |
| ----------------- | ------- | ------------------------- | ----------------------------------------------- |
| prompt\_text      | string  | ""                        | Text prompt describing video content and scenes |
| negative\_prompt  | string  | ""                        | Elements to exclude from the video              |
| seed              | integer | 0                         | Random seed for generation                      |
| ingredients\_mode | select  | "creative"                | Image combination mode                          |
| resolution        | select  | API default               | Output video resolution                         |
| duration          | select  | API default               | Output video length                             |
| aspect\_ratio     | float   | 1.7777777777777777 (16:9) | Video aspect ratio, range 0.4-2.5               |

### Optional Parameters

| Parameter            | Type  | Description        |
| -------------------- | ----- | ------------------ |
| image\_ingredient\_1 | image | First scene image  |
| image\_ingredient\_2 | image | Second scene image |
| image\_ingredient\_3 | image | Third scene image  |
| image\_ingredient\_4 | image | Fourth scene image |
| image\_ingredient\_5 | image | Fifth scene image  |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | video | Generated video |

## How It Works

The Pika 2.2 Scenes node analyzes all input images and creates a video containing these image elements. The node sends the images and parameters to Pika's API server, which processes them and returns the generated video.

Users can guide the video style and content through prompts, and exclude unwanted elements using negative prompts. The node supports up to 5 input images as ingredients and generates the final video based on the specified combination mode, resolution, duration, and aspect ratio.

## Source Code

```python theme={null}

class PikaScenesV2_2(PikaNodeBase):
    """Pika 2.2 Scenes Node."""

    @classmethod
    def INPUT_TYPES(cls):
        image_ingredient_input = (
            IO.IMAGE,
            {"tooltip": "Image that will be used as ingredient to create a video."},
        )
        return {
            "required": {
                **cls.get_base_inputs_types(
                    PikaBodyGenerate22C2vGenerate22PikascenesPost,
                ),
                "ingredients_mode": model_field_to_node_input(
                    IO.COMBO,
                    PikaBodyGenerate22C2vGenerate22PikascenesPost,
                    "ingredientsMode",
                    enum_type=IngredientsMode,
                    default="creative",
                ),
                "aspect_ratio": model_field_to_node_input(
                    IO.FLOAT,
                    PikaBodyGenerate22C2vGenerate22PikascenesPost,
                    "aspectRatio",
                    step=0.001,
                    min=0.4,
                    max=2.5,
                    default=1.7777777777777777,
                ),
            },
            "optional": {
                "image_ingredient_1": image_ingredient_input,
                "image_ingredient_2": image_ingredient_input,
                "image_ingredient_3": image_ingredient_input,
                "image_ingredient_4": image_ingredient_input,
                "image_ingredient_5": image_ingredient_input,
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    DESCRIPTION = "Combine your images to create a video with the objects in them. Upload multiple images as ingredients and generate a high-quality video that incorporates all of them."
    RETURN_TYPES = ("VIDEO",)

    def api_call(
        self,
        prompt_text: str,
        negative_prompt: str,
        seed: int,
        resolution: str,
        duration: int,
        ingredients_mode: str,
        aspect_ratio: float,
        image_ingredient_1: Optional[torch.Tensor] = None,
        image_ingredient_2: Optional[torch.Tensor] = None,
        image_ingredient_3: Optional[torch.Tensor] = None,
        image_ingredient_4: Optional[torch.Tensor] = None,
        image_ingredient_5: Optional[torch.Tensor] = None,
        auth_token: Optional[str] = None,
    ) -> tuple[VideoFromFile]:
        """API call for Pika Scenes 2.2."""
        all_image_bytes_io = []
        for image in [
            image_ingredient_1,
            image_ingredient_2,
            image_ingredient_3,
            image_ingredient_4,
            image_ingredient_5,
        ]:
            if image is not None:
                image_bytes_io = tensor_to_bytesio(image)
                image_bytes_io.seek(0)
                all_image_bytes_io.append(image_bytes_io)

        # Prepare files data for multipart upload
        pika_files = [
            ("images", (f"image_{i}.png", image_bytes_io, "image/png"))
            for i, image_bytes_io in enumerate(all_image_bytes_io)
        ]

        # Prepare non-file data using the Pydantic model
        pika_request_data = PikaBodyGenerate22C2vGenerate22PikascenesPost(
            ingredientsMode=ingredients_mode,
            promptText=prompt_text,
            negativePrompt=negative_prompt,
            seed=seed,
            resolution=resolution,
            duration=duration,
            aspectRatio=aspect_ratio,
        )

        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=PATH_PIKASCENES,
                method=HttpMethod.POST,
                request_model=PikaBodyGenerate22C2vGenerate22PikascenesPost,
                response_model=PikaGenerateResponse,
            ),
            request=pika_request_data,
            files=pika_files,
            content_type="multipart/form-data",
            auth_token=auth_token,
        )

        return self.execute_task(initial_operation, auth_token)


```


# Pika 2.2 Text to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pika/pika-text-to-video

A node that converts text descriptions into videos using Pika AI

<img alt="ComfyUI Native Pika 2.2 Text to Video Node" />

The Pika 2.2 Text to Video node uses Pika's 2.2 API to create videos from text descriptions. It connects to Pika's text-to-video API, allowing users to generate videos using text prompts with various control parameters.

## Parameters

### Required Parameters

| Parameter        | Type    | Default            | Description                                   |
| ---------------- | ------- | ------------------ | --------------------------------------------- |
| prompt\_text     | String  | ""                 | Text prompt describing the video content      |
| negative\_prompt | String  | ""                 | Elements to exclude from the video            |
| seed             | Integer | 0                  | Random seed for generation                    |
| resolution       | Select  | "1080p"            | Output video resolution                       |
| duration         | Select  | "5s"               | Length of generated video                     |
| aspect\_ratio    | Float   | 1.7777777777777777 | Video aspect ratio, range 0.4-2.5, step 0.001 |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | Video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-05)]

```python theme={null}

class PikaTextToVideoNodeV2_2(PikaNodeBase):
    """Pika 2.2 Text to Video Node."""

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                **cls.get_base_inputs_types(PikaBodyGenerate22T2vGenerate22T2vPost),
                "aspect_ratio": model_field_to_node_input(
                    IO.FLOAT,
                    PikaBodyGenerate22T2vGenerate22T2vPost,
                    "aspectRatio",
                    step=0.001,
                    min=0.4,
                    max=2.5,
                    default=1.7777777777777777,
                ),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    RETURN_TYPES = ("VIDEO",)
    DESCRIPTION = "Sends a text prompt to the Pika API v2.2 to generate a video."

    def api_call(
        self,
        prompt_text: str,
        negative_prompt: str,
        seed: int,
        resolution: str,
        duration: int,
        aspect_ratio: float,
        auth_token: Optional[str] = None,
    ) -> tuple[VideoFromFile]:
        """API call for Pika 2.2 Text to Video."""
        initial_operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path=PATH_TEXT_TO_VIDEO,
                method=HttpMethod.POST,
                request_model=PikaBodyGenerate22T2vGenerate22T2vPost,
                response_model=PikaGenerateResponse,
            ),
            request=PikaBodyGenerate22T2vGenerate22T2vPost(
                promptText=prompt_text,
                negativePrompt=negative_prompt,
                seed=seed,
                resolution=resolution,
                duration=duration,
                aspectRatio=aspect_ratio,
            ),
            auth_token=auth_token,
            content_type="application/x-www-form-urlencoded",
        )

        return self.execute_task(initial_operation, auth_token)


```


# PixVerse Image to Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pixverse/pixverse-image-to-video

A node that converts static images to dynamic videos using PixVerse AI

<img alt="ComfyUI Native PixVerse Image to Video Node" />

The PixVerse Image to Video node uses PixVerse's API to transform static images into dynamic videos. It preserves the visual features of the original image while adding natural motion based on text prompts.

## Parameters

### Required Parameters

| Parameter        | Type    | Default      | Description                                 |
| ---------------- | ------- | ------------ | ------------------------------------------- |
| image            | Image   | -            | Input image to convert to video             |
| prompt           | String  | ""           | Text prompt describing video motion/content |
| negative\_prompt | String  | ""           | Elements to avoid in the video              |
| seed             | Integer | -1           | Random seed (-1 for random)                 |
| quality          | Select  | "high"       | Output video quality level                  |
| aspect\_ratio    | Select  | "r16\_9"     | Output video aspect ratio                   |
| duration         | Select  | "seconds\_4" | Length of generated video                   |
| motion\_mode     | Select  | "standard"   | Video motion style                          |

### Optional Parameters

| Parameter          | Type               | Default | Description                |
| ------------------ | ------------------ | ------- | -------------------------- |
| pixverse\_template | PIXVERSE\_TEMPLATE | None    | Optional PixVerse template |

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | Video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-05)]

```python theme={null}
class PixverseImageToVideoNode(ComfyNodeABC):
    """
    Pixverse Image to Video

    Generates videos from an image and prompts.
    """

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": ("IMAGE",),
                "prompt": ("STRING", {"multiline": True, "default": ""}),
                "negative_prompt": ("STRING", {"multiline": True, "default": ""}),
                "seed": ("INT", {"default": -1, "min": -1, "max": 0xffffffffffffffff}),
                "quality": (list(PixverseQuality.__members__.keys()), {"default": "high"}),
                "aspect_ratio": (list(PixverseAspectRatio.__members__.keys()), {"default": "r16_9"}),
                "duration": (list(PixverseDuration.__members__.keys()), {"default": "seconds_4"}),
                "motion_mode": (list(PixverseMotionMode.__members__.keys()), {"default": "standard"}),
            },
            "optional": {
                "pixverse_template": ("PIXVERSE_TEMPLATE",),
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    RETURN_TYPES = ("VIDEO",)
    DESCRIPTION = "Generates videos from an image and prompts using Pixverse's API"
    FUNCTION = "generate_video"
    CATEGORY = "api node/video/Pixverse"
    API_NODE = True
    OUTPUT_NODE = True
```


# PixVerse Template - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pixverse/pixverse-template

A helper node that provides preset templates for PixVerse video generation

<img alt="ComfyUI Native PixVerse Template Node" />

The PixVerse Template node lets you choose from predefined video generation templates to control the style and effects of PixVerse video generation nodes.
This helper node connects to PixVerse video generation nodes, allowing users to quickly apply preset video styles without manually adjusting complex parameter combinations.

## Parameters

### Required Parameters

| Parameter | Type   | Description                                    |
| --------- | ------ | ---------------------------------------------- |
| template  | Select | Choose a template from available video presets |

### Output

| Output             | Type                | Description                                              |
| ------------------ | ------------------- | -------------------------------------------------------- |
| pixverse\_template | PixverseIO.TEMPLATE | Configuration object containing the selected template ID |

## Source Code

\[Node Source Code (Updated 2025-05-05)]

```python theme={null}

class PixverseTemplateNode:
    """
    Select template for Pixverse Video generation.
    """

    RETURN_TYPES = (PixverseIO.TEMPLATE,)
    RETURN_NAMES = ("pixverse_template",)
    FUNCTION = "create_template"
    CATEGORY = "api node/video/Pixverse"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "template": (list(pixverse_templates.keys()), ),
            }
        }

    def create_template(self, template: str):
        template_id = pixverse_templates.get(template, None)
        if template_id is None:
            raise Exception(f"Template '{template}' is not recognized.")
        # just return the integer
        return (template_id,)

```


# PixVerse Text to Video - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pixverse/pixverse-text-to-video

A node that converts text descriptions into videos using PixVerse AI technology

<img alt="ComfyUI Built-in PixVerse Text to Video Node" />

The PixVerse Text to Video node connects to PixVerse's text-to-video API, allowing users to generate high-quality videos from text descriptions. Users can customize their creations by adjusting various parameters like video quality, duration, and motion mode.

## Parameters

### Required Parameters

| Parameter         | Type    | Default                   | Description                                   |
| ----------------- | ------- | ------------------------- | --------------------------------------------- |
| prompt            | string  | ""                        | Text prompt describing the video content      |
| aspect\_ratio     | select  | -                         | Output video aspect ratio                     |
| quality           | select  | PixverseQuality.res\_540p | Video quality level                           |
| duration\_seconds | select  | -                         | Video duration                                |
| motion\_mode      | select  | -                         | Video motion mode                             |
| seed              | integer | 0                         | Random seed for consistent generation results |

### Optional Parameters

| Parameter          | Type               | Default | Description                          |
| ------------------ | ------------------ | ------- | ------------------------------------ |
| negative\_prompt   | string             | ""      | Elements to exclude from the video   |
| pixverse\_template | PIXVERSE\_TEMPLATE | None    | Optional template for style settings |

### Limitations

* 1080p quality only supports normal motion mode with 5-second duration
* Non 5-second durations only support normal motion mode

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | video | Generated video |

## Source Code

\[Node Source Code (Updated 2025-05-05)]

```python theme={null}

class PixverseTextToVideoNode(ComfyNodeABC):
    """
    Generates videos synchronously based on prompt and output_size.
    """

    RETURN_TYPES = (IO.VIDEO,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/video/Pixverse"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the video generation",
                    },
                ),
                "aspect_ratio": (
                    [ratio.value for ratio in PixverseAspectRatio],
                ),
                "quality": (
                    [resolution.value for resolution in PixverseQuality],
                    {
                        "default": PixverseQuality.res_540p,
                    },
                ),
                "duration_seconds": ([dur.value for dur in PixverseDuration],),
                "motion_mode": ([mode.value for mode in PixverseMotionMode],),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2147483647,
                        "control_after_generate": True,
                        "tooltip": "Seed for video generation.",
                    },
                ),
            },
            "optional": {
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
                "pixverse_template": (
                    PixverseIO.TEMPLATE,
                    {
                        "tooltip": "An optional template to influence style of generation, created by the Pixverse Template node."
                    }
                )
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        prompt: str,
        aspect_ratio: str,
        quality: str,
        duration_seconds: int,
        motion_mode: str,
        seed,
        negative_prompt: str=None,
        pixverse_template: int=None,
        auth_token=None,
        **kwargs,
    ):
        # 1080p is limited to 5 seconds duration
        # only normal motion_mode supported for 1080p or for non-5 second duration
        if quality == PixverseQuality.res_1080p:
            motion_mode = PixverseMotionMode.normal
            duration_seconds = PixverseDuration.dur_5
        elif duration_seconds != PixverseDuration.dur_5:
            motion_mode = PixverseMotionMode.normal

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/pixverse/video/text/generate",
                method=HttpMethod.POST,
                request_model=PixverseTextVideoRequest,
                response_model=PixverseVideoResponse,
            ),
            request=PixverseTextVideoRequest(
                prompt=prompt,
                aspect_ratio=aspect_ratio,
                quality=quality,
                duration=duration_seconds,
                motion_mode=motion_mode,
                negative_prompt=negative_prompt if negative_prompt else None,
                template_id=pixverse_template,
                seed=seed,
            ),
            auth_token=auth_token,
        )
        response_api = operation.execute()

        if response_api.Resp is None:
            raise Exception(f"Pixverse request failed: '{response_api.ErrMsg}'")

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/pixverse/video/result/{response_api.Resp.video_id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=PixverseGenerationStatusResponse,
            ),
            completed_statuses=[PixverseStatus.successful],
            failed_statuses=[PixverseStatus.contents_moderation, PixverseStatus.failed, PixverseStatus.deleted],
            status_extractor=lambda x: x.Resp.status,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        vid_response = requests.get(response_poll.Resp.url)
        return (VideoFromFile(BytesIO(vid_response.content)),)

```


# PixVerse Transition Video - ComfyUI Native Node Documentation
Source: https://docs.comfy.org/built-in-nodes/partner-node/video/pixverse/pixverse-transition-video

Create smooth transition videos between start and end frames using PixVerse AI

<img alt="ComfyUI Native PixVerse Transition Video Node" />

The Pixverse Transition Video node connects to PixVerse's API to generate smooth video transitions between two images. It automatically creates all intermediate frames to produce fluid transformations, perfect for morphing effects, scene transitions, and object evolution.

## Parameters

### Required Parameters

| Parameter         | Type    | Default                     | Description                                 |
| ----------------- | ------- | --------------------------- | ------------------------------------------- |
| first\_frame      | Image   | -                           | Starting frame image                        |
| last\_frame       | Image   | -                           | Ending frame image                          |
| prompt            | String  | ""                          | Text prompt describing video and transition |
| quality           | Select  | "PixverseQuality.res\_540p" | Output video quality                        |
| duration\_seconds | Select  | -                           | Length of generated video                   |
| motion\_mode      | Select  | -                           | Video motion style                          |
| seed              | Integer | 0                           | Random seed (range: 0-2147483647)           |

### Optional Parameters

| Parameter          | Type               | Default | Description                |
| ------------------ | ------------------ | ------- | -------------------------- |
| negative\_prompt   | String             | ""      | Elements to avoid in video |
| pixverse\_template | PIXVERSE\_TEMPLATE | None    | Optional style preset      |

### Parameter Constraints

* When quality is set to 1080p, motion\_mode is forced to normal and duration\_seconds to 5 seconds
* When duration\_seconds is not 5 seconds, motion\_mode is forced to normal

### Output

| Output | Type  | Description     |
| ------ | ----- | --------------- |
| VIDEO  | Video | Generated video |

## Source Code

```python theme={null}

class PixverseTransitionVideoNode(ComfyNodeABC):
    """
    Generates videos synchronously based on prompt and output_size.
    """

    RETURN_TYPES = (IO.VIDEO,)
    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
    FUNCTION = "api_call"
    API_NODE = True
    CATEGORY = "api node/video/Pixverse"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "first_frame": (
                    IO.IMAGE,
                ),
                "last_frame": (
                    IO.IMAGE,
                ),
                "prompt": (
                    IO.STRING,
                    {
                        "multiline": True,
                        "default": "",
                        "tooltip": "Prompt for the video generation",
                    },
                ),
                "quality": (
                    [resolution.value for resolution in PixverseQuality],
                    {
                        "default": PixverseQuality.res_540p,
                    },
                ),
                "duration_seconds": ([dur.value for dur in PixverseDuration],),
                "motion_mode": ([mode.value for mode in PixverseMotionMode],),
                "seed": (
                    IO.INT,
                    {
                        "default": 0,
                        "min": 0,
                        "max": 2147483647,
                        "control_after_generate": True,
                        "tooltip": "Seed for video generation.",
                    },
                ),
            },
            "optional": {
                "negative_prompt": (
                    IO.STRING,
                    {
                        "default": "",
                        "forceInput": True,
                        "tooltip": "An optional text description of undesired elements on an image.",
                    },
                ),
                "pixverse_template": (
                    PixverseIO.TEMPLATE,
                    {
                        "tooltip": "An optional template to influence style of generation, created by the Pixverse Template node."
                    }
                )
            },
            "hidden": {
                "auth_token": "AUTH_TOKEN_COMFY_ORG",
            },
        }

    def api_call(
        self,
        first_frame: torch.Tensor,
        last_frame: torch.Tensor,
        prompt: str,
        quality: str,
        duration_seconds: int,
        motion_mode: str,
        seed,
        negative_prompt: str=None,
        pixverse_template: int=None,
        auth_token=None,
        **kwargs,
    ):
        first_frame_id = upload_image_to_pixverse(first_frame, auth_token=auth_token)
        last_frame_id = upload_image_to_pixverse(last_frame, auth_token=auth_token)

        # 1080p is limited to 5 seconds duration
        # only normal motion_mode supported for 1080p or for non-5 second duration
        if quality == PixverseQuality.res_1080p:
            motion_mode = PixverseMotionMode.normal
            duration_seconds = PixverseDuration.dur_5
        elif duration_seconds != PixverseDuration.dur_5:
            motion_mode = PixverseMotionMode.normal

        operation = SynchronousOperation(
            endpoint=ApiEndpoint(
                path="/proxy/pixverse/video/transition/generate",
                method=HttpMethod.POST,
                request_model=PixverseTransitionVideoRequest,
                response_model=PixverseVideoResponse,
            ),
            request=PixverseTransitionVideoRequest(
                first_frame_img=first_frame_id,
                last_frame_img=last_frame_id,
                prompt=prompt,
                quality=quality,
                duration=duration_seconds,
                motion_mode=motion_mode,
                negative_prompt=negative_prompt if negative_prompt else None,
                template_id=pixverse_template,
                seed=seed,
            ),
            auth_token=auth_token,
        )
        response_api = operation.execute()

        if response_api.Resp is None:
            raise Exception(f"Pixverse request failed: '{response_api.ErrMsg}'")

        operation = PollingOperation(
            poll_endpoint=ApiEndpoint(
                path=f"/proxy/pixverse/video/result/{response_api.Resp.video_id}",
                method=HttpMethod.GET,
                request_model=EmptyRequest,
                response_model=PixverseGenerationStatusResponse,
            ),
            completed_statuses=[PixverseStatus.successful],
            failed_statuses=[PixverseStatus.contents_moderation, PixverseStatus.failed, PixverseStatus.deleted],
            status_extractor=lambda x: x.Resp.status,
            auth_token=auth_token,
        )
        response_poll = operation.execute()

        vid_response = requests.get(response_poll.Resp.url)
        return (VideoFromFile(BytesIO(vid_response.content)),)
```


# AddNoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AddNoise

Complete documentation for the AddNoise node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AddNoise/en.md)

This node adds controlled noise to a latent image using a specified noise generator and sigma values. It processes the input through the model's sampling system to apply noise scaling appropriate for the given sigma range, returning a new latent representation with the noise applied.

## Inputs

| Parameter      | Data Type | Required | Range | Description                                                                                                                                                                                                                                                                                                                           |
| -------------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`        | MODEL     | Yes      | -     | The model containing sampling parameters and processing functions                                                                                                                                                                                                                                                                     |
| `noise`        | NOISE     | Yes      | -     | The noise generator that produces the base noise pattern                                                                                                                                                                                                                                                                              |
| `sigmas`       | SIGMAS    | Yes      | -     | Sigma values controlling the noise scaling intensity. If empty, the node returns the original latent image unchanged. When multiple sigmas are provided, the noise scale is calculated as the absolute difference between the first and last sigma values. When only one sigma is provided, that value is used directly as the scale. |
| `latent_image` | LATENT    | Yes      | -     | The input latent representation to which noise will be added. Empty latent images (containing only zeros) are not shifted during processing.                                                                                                                                                                                          |

## Outputs

| Output Name | Data Type | Description                                                                                                                         |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------- |
| `LATENT`    | LATENT    | The modified latent representation with added noise. Any NaN or infinite values in the output are converted to zeros for stability. |

***

**Source fingerprint (SHA-256):** `7e2b3e7f55c7c4380e831be5a558c506a6328ad2ec974f550ed30b40ddfab037`


# AdjustBrightness - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AdjustBrightness

Complete documentation for the AdjustBrightness node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AdjustBrightness/en.md)

The Adjust Brightness node modifies the brightness of an input image. It works by multiplying each pixel's value by a specified factor, then clamping the resulting values to stay within a valid range. A factor of 1.0 leaves the image unchanged, values below 1.0 make it darker, and values above 1.0 make it brighter.

## Inputs

| Parameter | Data Type | Required | Range     | Description                                                                         |
| --------- | --------- | -------- | --------- | ----------------------------------------------------------------------------------- |
| `image`   | IMAGE     | Yes      | -         | The input image to adjust.                                                          |
| `factor`  | FLOAT     | No       | 0.0 - 2.0 | Brightness factor. 1.0 = no change, \<1.0 = darker, >1.0 = brighter. (default: 1.0) |

## Outputs

| Output Name | Data Type | Description                                |
| ----------- | --------- | ------------------------------------------ |
| `image`     | IMAGE     | The output image with adjusted brightness. |

***

**Source fingerprint (SHA-256):** `dd1a35a4a133e6e15bb51788376e89c4e20e52ad395f889f4a4aa34fa614612e`


# AdjustContrast - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AdjustContrast

Complete documentation for the AdjustContrast node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AdjustContrast/en.md)

The Adjust Contrast node modifies the contrast level of an input image. It works by adjusting the difference between the light and dark areas of the image. A factor of 1.0 leaves the image unchanged, values below 1.0 reduce contrast, and values above 1.0 increase it.

## Inputs

| Parameter | Data Type | Required | Range     | Description                                                                                   |
| --------- | --------- | -------- | --------- | --------------------------------------------------------------------------------------------- |
| `image`   | IMAGE     | Yes      | -         | The input image to have its contrast adjusted.                                                |
| `factor`  | FLOAT     | No       | 0.0 - 2.0 | Contrast factor. 1.0 = no change, \<1.0 = less contrast, >1.0 = more contrast. (default: 1.0) |

## Outputs

| Output Name | Data Type | Description                                 |
| ----------- | --------- | ------------------------------------------- |
| `image`     | IMAGE     | The resulting image with adjusted contrast. |

***

**Source fingerprint (SHA-256):** `3debe91086d9818883dbe29b0cb2ae3ecaed44e4636b124d42a85d9906252330`


# AudioAdjustVolume - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioAdjustVolume

Complete documentation for the AudioAdjustVolume node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioAdjustVolume/en.md)

The AudioAdjustVolume node modifies the loudness of audio by applying volume adjustments in decibels (dB). It takes an audio input and applies a gain factor based on the specified volume level, where positive values increase volume and negative values decrease it. The node returns the modified audio with the same sample rate as the original.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                                                                 |
| --------- | --------- | -------- | ----------- | ------------------------------------------------------------------------------------------- |
| `audio`   | AUDIO     | Yes      | -           | The audio input to be processed                                                             |
| `volume`  | INT       | Yes      | -100 to 100 | Volume adjustment in decibels (dB). 0 = no change, +6 = double, -6 = half, etc (default: 1) |

## Outputs

| Output Name | Data Type | Description                                    |
| ----------- | --------- | ---------------------------------------------- |
| `audio`     | AUDIO     | The processed audio with adjusted volume level |

***

**Source fingerprint (SHA-256):** `8c19625104901a0c57021b1a775fdf287c8bd0fb1fd535809e1983b1949ca752`


# AudioConcat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioConcat

Complete documentation for the AudioConcat node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioConcat/en.md)

The AudioConcat node combines two audio inputs by joining them together. It takes two audio inputs and connects them in the order you specify, either placing the second audio before or after the first audio. The node automatically handles different audio formats by converting mono audio to stereo and matching sample rates between the two inputs.

## Inputs

| Parameter   | Data Type | Required | Range                     | Description                                                        |
| ----------- | --------- | -------- | ------------------------- | ------------------------------------------------------------------ |
| `audio1`    | AUDIO     | Yes      | -                         | The first audio input to be concatenated                           |
| `audio2`    | AUDIO     | Yes      | -                         | The second audio input to be concatenated                          |
| `direction` | COMBO     | Yes      | `"after"`<br />`"before"` | Whether to append audio2 after or before audio1 (default: "after") |

## Outputs

| Output Name | Data Type | Description                                                          |
| ----------- | --------- | -------------------------------------------------------------------- |
| `AUDIO`     | AUDIO     | The combined audio containing both input audio files joined together |

***

**Source fingerprint (SHA-256):** `faccc3d42e9c6927deadb7d5f7fe9e5bbbf08e4e9a3d636f42a2b9f995eec8c1`


# AudioEqualizer3Band - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioEqualizer3Band

Complete documentation for the AudioEqualizer3Band node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioEqualizer3Band/en.md)

The Audio Equalizer (3-Band) node allows you to adjust the bass, mid, and treble frequencies of an audio waveform. It applies three separate filters: a low shelf for bass, a peaking filter for mids, and a high shelf for treble. Each band can be independently controlled with gain, frequency, and bandwidth settings.

## Inputs

| Parameter      | Data Type | Required | Range         | Description                                                                                                                               |
| -------------- | --------- | -------- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------- |
| `audio`        | AUDIO     | Yes      | -             | The input audio data containing the waveform and sample rate.                                                                             |
| `low_gain_dB`  | FLOAT     | No       | -24.0 to 24.0 | Gain for Low frequencies (Bass). Positive values boost, negative values cut. (default: 0.0)                                               |
| `low_freq`     | INT       | No       | 20 to 500     | Cutoff frequency for Low shelf filter in Hertz (Hz). (default: 100)                                                                       |
| `mid_gain_dB`  | FLOAT     | No       | -24.0 to 24.0 | Gain for Mid frequencies. Positive values boost, negative values cut. (default: 0.0)                                                      |
| `mid_freq`     | INT       | No       | 200 to 4000   | Center frequency for the Mid peaking filter in Hertz (Hz). (default: 1000)                                                                |
| `mid_q`        | FLOAT     | No       | 0.1 to 10.0   | Q factor (bandwidth) for the Mid peaking filter. Lower values create a wider band, higher values create a narrower band. (default: 0.707) |
| `high_gain_dB` | FLOAT     | No       | -24.0 to 24.0 | Gain for High frequencies (Treble). Positive values boost, negative values cut. (default: 0.0)                                            |
| `high_freq`    | INT       | No       | 1000 to 15000 | Cutoff frequency for High shelf filter in Hertz (Hz). (default: 5000)                                                                     |

**Note:** The `low_gain_dB`, `mid_gain_dB`, and `high_gain_dB` parameters are only applied when their value is not zero. If a gain is set to 0.0, the corresponding filter stage is skipped.

## Outputs

| Output Name | Data Type | Description                                                                                                            |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------------- |
| `audio`     | AUDIO     | The processed audio data with the equalization applied, containing the modified waveform and the original sample rate. |

***

**Source fingerprint (SHA-256):** `be3a0981d8285885cb465e82717c3f56c9d301d55708962f9a9dd5b2c400ec81`


# AudioMerge - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioMerge

Complete documentation for the AudioMerge node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioMerge/en.md)

The AudioMerge node combines two audio tracks by overlaying their waveforms. It automatically matches the sample rates of both audio inputs and adjusts their lengths to be equal before merging. The node provides several mathematical methods for combining the audio signals and ensures the output remains within acceptable volume levels.

## Inputs

| Parameter      | Data Type | Required | Range                                                     | Description                                     |
| -------------- | --------- | -------- | --------------------------------------------------------- | ----------------------------------------------- |
| `audio1`       | AUDIO     | Yes      | -                                                         | First audio input to merge                      |
| `audio2`       | AUDIO     | Yes      | -                                                         | Second audio input to merge                     |
| `merge_method` | COMBO     | Yes      | `"add"`<br />`"mean"`<br />`"subtract"`<br />`"multiply"` | The method used to combine the audio waveforms. |

## Outputs

| Output Name | Data Type | Description                                                              |
| ----------- | --------- | ------------------------------------------------------------------------ |
| `AUDIO`     | AUDIO     | The merged audio output containing the combined waveform and sample rate |

***

**Source fingerprint (SHA-256):** `3bb8c223e9a5155b5e60f901e8653c6654336a10a56d25ba7a3c5e8f5382ad27`


# BatchMasksNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BatchMasksNode

Complete documentation for the BatchMasksNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BatchMasksNode/en.md)

The Batch Masks node combines multiple individual mask inputs into a single batch. It takes a variable number of mask inputs and outputs them as a single batched mask tensor, allowing for batch processing of masks in subsequent nodes. If the input masks have different sizes, they are automatically resized to match the dimensions of the first mask.

## Inputs

| Parameter | Data Type | Required | Range         | Description                                                                                                                                                                                                                                          |
| --------- | --------- | -------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `mask`    | MASK      | Yes      | 1 to 50 masks | The mask inputs to combine into a batch. At least one mask is required. You can add up to 50 masks total by clicking the "+" button on the node. If masks have different sizes, they are automatically resized to match the first mask's dimensions. |

**Note:** This node uses an autogrow input template. You must connect at least one mask. You can add up to 49 more mask inputs for a total of 50 masks. All connected masks will be combined into a single batch. If masks have different heights or widths, they are automatically resized to match the dimensions of the first mask using bilinear interpolation.

## Outputs

| Output Name | Data Type | Description                                                                                                    |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------------- |
| `output`    | MASK      | A single batched mask containing all the input masks stacked together. If no masks are provided, returns None. |

***

**Source fingerprint (SHA-256):** `7e9bc4be72c7fa8fceab2cf167c72b7e1ff858c0281d977f2ad3ab433d9d58d6`


# CLIPAttentionMultiply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPAttentionMultiply

Complete documentation for the CLIPAttentionMultiply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPAttentionMultiply/en.md)

The CLIPAttentionMultiply node allows you to adjust the attention mechanism in CLIP models by applying multiplication factors to different components of the self-attention layers. It works by modifying the query, key, value, and output projection weights and biases in the CLIP model's attention mechanism. This experimental node creates a modified copy of the input CLIP model with the specified scaling factors applied.

## Inputs

| Parameter | Data Type | Required | Range      | Description                                                                   |
| --------- | --------- | -------- | ---------- | ----------------------------------------------------------------------------- |
| `clip`    | CLIP      | Yes      | -          | The CLIP model to modify                                                      |
| `q`       | FLOAT     | Yes      | 0.0 - 10.0 | Multiplication factor for query projection weights and biases (default: 1.0)  |
| `k`       | FLOAT     | Yes      | 0.0 - 10.0 | Multiplication factor for key projection weights and biases (default: 1.0)    |
| `v`       | FLOAT     | Yes      | 0.0 - 10.0 | Multiplication factor for value projection weights and biases (default: 1.0)  |
| `out`     | FLOAT     | Yes      | 0.0 - 10.0 | Multiplication factor for output projection weights and biases (default: 1.0) |

## Outputs

| Output Name | Data Type | Description                                                                        |
| ----------- | --------- | ---------------------------------------------------------------------------------- |
| `CLIP`      | CLIP      | Returns a modified CLIP model with the specified attention scaling factors applied |

***

**Source fingerprint (SHA-256):** `1f5c437cb4a372dfd69ad3c10e2b8cfc68821e0fe82dcf37df5e6fd64aa0b436`


# CLIPTextEncodeControlnet - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodeControlnet

Complete documentation for the CLIPTextEncodeControlnet node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeControlnet/en.md)

The CLIPTextEncodeControlnet node processes text input using a CLIP model and combines it with existing conditioning data to create enhanced conditioning output for controlnet applications. It tokenizes the input text, encodes it through the CLIP model, and adds the resulting embeddings to the provided conditioning data as cross-attention controlnet parameters.

## Inputs

| Parameter      | Data Type    | Required | Range | Description                                                                               |
| -------------- | ------------ | -------- | ----- | ----------------------------------------------------------------------------------------- |
| `clip`         | CLIP         | Yes      | -     | The CLIP model used for text tokenization and encoding                                    |
| `conditioning` | CONDITIONING | Yes      | -     | Existing conditioning data to be enhanced with controlnet parameters                      |
| `text`         | STRING       | Yes      | -     | Text input to be processed by the CLIP model. Supports multiline text and dynamic prompts |

**Note:** This node requires all three inputs (`clip`, `conditioning`, and `text`) to function properly. The `text` input supports dynamic prompts and multiline text for flexible text processing.

## Outputs

| Output Name    | Data Type    | Description                                                                                                                                                              |
| -------------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `CONDITIONING` | CONDITIONING | Enhanced conditioning data with added controlnet cross-attention parameters (`cross_attn_controlnet` and `pooled_output_controlnet`) derived from the CLIP text encoding |

***

**Source fingerprint (SHA-256):** `36f0c9b7d3f3187bcf794c71e8a261d456972a41c079ddaca0cb5117912e9685`


# Canny - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Canny

Complete documentation for the Canny node in ComfyUI. Learn its inputs, outputs, parameters and usage.

Extract all edge lines from photos, like using a pen to outline a photo, drawing out the contours and detail boundaries of objects.

## Working Principle

Imagine you are an artist who needs to use a pen to outline a photo. The Canny node acts like an intelligent assistant, helping you decide where to draw lines (edges) and where not to.

This process is like a screening job:

* **High threshold** is the "must draw line standard": only very obvious and clear contour lines will be drawn, such as facial contours of people and building frames
* **Low threshold** is the "definitely don't draw line standard": edges that are too weak will be ignored to avoid drawing noise and meaningless lines
* **Middle area**: edges between the two standards will be drawn together if they connect to "must draw lines", but won't be drawn if they are isolated

The final output is a black and white image, where white parts are detected edge lines and black parts are areas without edges.

## Inputs

| Parameter Name   | Data Type | Input Type | Default | Range     | Function Description                                                                                            |
| ---------------- | --------- | ---------- | ------- | --------- | --------------------------------------------------------------------------------------------------------------- |
| `image`          | IMAGE     | Input      | -       | -         | Original photo that needs edge extraction                                                                       |
| `low_threshold`  | FLOAT     | Widget     | 0.4     | 0.01-0.99 | Low threshold, determines how weak edges to ignore. Lower values preserve more details but may produce noise    |
| `high_threshold` | FLOAT     | Widget     | 0.8     | 0.01-0.99 | High threshold, determines how strong edges to preserve. Higher values only keep the most obvious contour lines |

## Outputs

| Output Name | Data Type | Description                                                                                     |
| ----------- | --------- | ----------------------------------------------------------------------------------------------- |
| `image`     | IMAGE     | Black and white edge image, white lines are detected edges, black areas are parts without edges |

## Parameter Comparison

<img alt="Original Image" />

<img alt="Parameter Comparison" />

**Common Issues:**

* Broken edges: Try lowering high threshold
* Too much noise: Raise low threshold
* Missing important details: Lower low threshold
* Edges too rough: Check input image quality and resolution


# ColorTransfer - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ColorTransfer

Complete documentation for the ColorTransfer node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ColorTransfer/en.md)

The ColorTransfer node adjusts the color palette of a target image to match the colors of a reference image. It uses different mathematical algorithms to analyze and transfer the color characteristics, such as brightness, contrast, and hue distribution, from the reference to the target. This is useful for creating visual consistency across multiple images or applying a specific color grade.

## Inputs

| Parameter      | Data Type    | Required | Range                                                | Description                                                                                                                               |
| -------------- | ------------ | -------- | ---------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- |
| `image_target` | IMAGE        | Yes      | -                                                    | Image(s) to apply the color transform to.                                                                                                 |
| `image_ref`    | IMAGE        | Yes      | -                                                    | Reference image(s) to match colors to.                                                                                                    |
| `method`       | COMBO        | Yes      | `"reinhard_lab"`<br />`"mkl_lab"`<br />`"histogram"` | The color transfer algorithm to use.                                                                                                      |
| `source_stats` | DYNAMICCOMBO | Yes      | `"per_frame"`<br />`"uniform"`<br />`"target_frame"` | Determines how color statistics are calculated from the source (target) image(s).                                                         |
| `strength`     | FLOAT        | Yes      | 0.0 to 10.0                                          | The intensity of the color transfer effect. A value of 1.0 applies the full transform, while 0.0 returns the original image. Default: 1.0 |

**Parameter Details:**

* **`source_stats` Options:**
  * **`per_frame`**: Each frame in a batch is matched to the `image_ref` individually.
  * **`uniform`**: Color statistics are pooled across all source frames to create a single baseline, which is then matched to the `image_ref`.
  * **`target_frame`**: Uses one chosen frame from the target batch as the baseline for computing the transform to the `image_ref`. This transform is then applied uniformly to all frames, which preserves the relative color differences between them. When this option is selected, an additional `target_index` parameter becomes available.
* **`target_index`** (appears when `source_stats` is `"target_frame"`): The frame index (starting from 0) used as the source baseline for computing the transform. Default: 0. Must be between 0 and 10000.

**Constraints:**

* If `strength` is set to 0.0 or `image_ref` is `None`, the node returns the original `image_target` without processing.
* When `source_stats` is set to `"target_frame"`, the `target_index` must be a valid index within the batch of `image_target`. If it exceeds the number of frames, the last frame is used.
* For the `histogram` method with `source_stats` set to `"per_frame"`, if the batch size of `image_ref` is greater than 1, each target frame is matched to the corresponding reference frame by index. If the reference batch has only one frame, it is used for all target frames.

## Outputs

| Output Name | Data Type | Description                                                       |
| ----------- | --------- | ----------------------------------------------------------------- |
| `image`     | IMAGE     | The resulting image(s) after the color transfer has been applied. |

***

**Source fingerprint (SHA-256):** `f844af34ac6129c7751953c48e2d12aa0d2c556937e610f649f3eb2725955711`


# ConditioningAverage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningAverage

Complete documentation for the ConditioningAverage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `ConditioningAverage` node is used to blend two different sets of conditioning (such as text prompts) according to a specified weight, generating a new conditioning vector that lies between the two. By adjusting the weight parameter, you can flexibly control the influence of each conditioning on the final result. This is especially suitable for prompt interpolation, style fusion, and other advanced use cases.

As shown below, by adjusting the strength of `conditioning_to`, you can output a result between the two conditionings.

<img alt="example" />

## Inputs

| Parameter                  | Comfy dtype    | Description                                                                                          |
| -------------------------- | -------------- | ---------------------------------------------------------------------------------------------------- |
| `conditioning_to`          | `CONDITIONING` | The target conditioning vector, serving as the main base for the weighted average.                   |
| `conditioning_from`        | `CONDITIONING` | The source conditioning vector, which will be blended into the target according to a certain weight. |
| `conditioning_to_strength` | `FLOAT`        | The strength of the target conditioning, range 0.0-1.0, default 1.0, step 0.01.                      |

## Outputs

| Parameter      | Comfy dtype    | Description                                                                        |
| -------------- | -------------- | ---------------------------------------------------------------------------------- |
| `conditioning` | `CONDITIONING` | The resulting conditioning vector after blending, reflecting the weighted average. |

## Typical Use Cases

* **Prompt Interpolation:** Smoothly transition between two different text prompts, generating content with intermediate style or semantics.
* **Style Fusion:** Combine different artistic styles or semantic conditions to create novel effects.
* **Strength Adjustment:** Precisely control the influence of a particular conditioning on the result by adjusting the weight.
* **Creative Exploration:** Explore diverse generative effects by mixing different prompts.


# CropMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CropMask

Complete documentation for the CropMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The CropMask node is designed for cropping a specified area from a given mask. It allows users to define the region of interest by specifying coordinates and dimensions, effectively extracting a portion of the mask for further processing or analysis.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                      |
| --------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `mask`    | MASK      | The mask input represents the mask image to be cropped. It is essential for defining the area to be extracted based on the specified coordinates and dimensions. |
| `x`       | INT       | The x coordinate specifies the starting point on the horizontal axis from which the cropping should begin.                                                       |
| `y`       | INT       | The y coordinate determines the starting point on the vertical axis for the cropping operation.                                                                  |
| `width`   | INT       | Width defines the horizontal extent of the crop area from the starting point.                                                                                    |
| `height`  | INT       | Height specifies the vertical extent of the crop area from the starting point.                                                                                   |

## Outputs

| Parameter | Data Type | Description                                                                                                                |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------- |
| `mask`    | MASK      | The output is a cropped mask, which is a portion of the original mask defined by the specified coordinates and dimensions. |


# DifferentialDiffusion - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DifferentialDiffusion

Complete documentation for the DifferentialDiffusion node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DifferentialDiffusion/en.md)

The Differential Diffusion node modifies the denoising process by applying a binary mask based on timestep thresholds. It creates a mask that blends between the original denoise mask and a threshold-based binary mask, allowing controlled adjustment of the diffusion process strength.

## Inputs

| Parameter  | Data Type | Required | Range     | Description                                                                                                   |
| ---------- | --------- | -------- | --------- | ------------------------------------------------------------------------------------------------------------- |
| `model`    | MODEL     | Yes      | -         | The diffusion model to modify                                                                                 |
| `strength` | FLOAT     | No       | 0.0 - 1.0 | Controls the blending strength between the original denoise mask and the binary threshold mask (default: 1.0) |

## Outputs

| Output Name | Data Type | Description                                                     |
| ----------- | --------- | --------------------------------------------------------------- |
| `model`     | MODEL     | The modified diffusion model with updated denoise mask function |

***

**Source fingerprint (SHA-256):** `26387c3e6c7ead5415b36cfc9b9eef73448527e70646ab253984ff9627f69a25`


# DrawBBoxes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DrawBBoxes

Complete documentation for the DrawBBoxes node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DrawBBoxes/en.md)

The DrawBBoxes node visualizes object detection results by drawing bounding boxes, labels, and confidence scores onto an image. If no input image is provided, it creates a blank canvas large enough to contain all the drawn boxes. It supports batch processing, allowing you to draw different sets of detections for multiple images or repeat the same detections across a batch.

## Inputs

| Parameter | Data Type   | Required | Range | Description                                                                                                                                   |
| --------- | ----------- | -------- | ----- | --------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`   | IMAGE       | No       | -     | The input image(s) to draw the bounding boxes onto. If not provided, a blank canvas will be generated.                                        |
| `bboxes`  | BOUNDINGBOX | Yes      | -     | A list of bounding box dictionaries. Each dictionary should contain keys for `x`, `y`, `width`, `height`, and optionally `label` and `score`. |

**Input Constraints:**

* The `bboxes` input is required and must be provided.
* The node automatically handles different input formats for `bboxes`. A single dictionary will be applied to all images in the batch. A flat list of dictionaries will be treated as the same set of detections for every image. A list of lists allows you to specify different detections for each image in the batch.
* If an `image` is not provided, the node will create a blank image with dimensions large enough to fit all provided bounding boxes, with a default minimum size of 640x640.
* The `label` field in each bounding box dictionary is matched against the COCO dataset classes. If the label is not a recognized COCO class, it will be ignored and no text label will be drawn for that box.

## Outputs

| Output Name | Data Type | Description                                                                                |
| ----------- | --------- | ------------------------------------------------------------------------------------------ |
| `out_image` | IMAGE     | The output image(s) with the drawn bounding boxes, labels, and confidence scores overlaid. |

***

**Source fingerprint (SHA-256):** `ce5da10ec83e579515d70b7184fc78dfa04df4c514faccdcb75130212f56c84f`


# EmptyAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyAudio

Complete documentation for the EmptyAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyAudio/en.md)

The EmptyAudio node generates a silent audio clip with specified duration, sample rate, and channel configuration. It creates a waveform containing all zeros, producing complete silence for the given duration. This node is useful for creating placeholder audio or generating silent segments in audio workflows.

## Inputs

| Parameter     | Data Type | Required | Range                         | Description                                                      |
| ------------- | --------- | -------- | ----------------------------- | ---------------------------------------------------------------- |
| `duration`    | FLOAT     | Yes      | 0.0 to 1.8446744073709552e+19 | Duration of the empty audio clip in seconds (default: 60.0)      |
| `sample_rate` | INT       | Yes      | 1 to 192000                   | Sample rate of the empty audio clip (default: 44100)             |
| `channels`    | INT       | Yes      | 1 to 2                        | Number of audio channels (1 for mono, 2 for stereo) (default: 2) |

## Outputs

| Output Name | Data Type | Description                                                                          |
| ----------- | --------- | ------------------------------------------------------------------------------------ |
| `AUDIO`     | AUDIO     | The generated silent audio clip containing waveform data and sample rate information |

***

**Source fingerprint (SHA-256):** `687bfe02cb0192add9128ae9040fa5773be0d7a0a5df17618cf56050901c6dc5`


# FeatherMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FeatherMask

Complete documentation for the FeatherMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `FeatherMask` node applies a feathering effect to the edges of a given mask, smoothly transitioning the mask's edges by adjusting their opacity based on specified distances from each edge. This creates a softer, more blended edge effect.

## Inputs

| Parameter | Data Type | Description                                                                                                                           |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------- |
| `mask`    | MASK      | The mask to which the feathering effect will be applied. It determines the area of the image that will be affected by the feathering. |
| `left`    | INT       | Specifies the distance from the left edge within which the feathering effect will be applied.                                         |
| `top`     | INT       | Specifies the distance from the top edge within which the feathering effect will be applied.                                          |
| `right`   | INT       | Specifies the distance from the right edge within which the feathering effect will be applied.                                        |
| `bottom`  | INT       | Specifies the distance from the bottom edge within which the feathering effect will be applied.                                       |

## Outputs

| Parameter | Data Type | Description                                                                                       |
| --------- | --------- | ------------------------------------------------------------------------------------------------- |
| `mask`    | MASK      | The output is a modified version of the input mask with a feathering effect applied to its edges. |


# FluxKVCache - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxKVCache

Complete documentation for the FluxKVCache node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxKVCache/en.md)

The Flux KV Cache node enables a Key-Value (KV) Cache optimization for Flux family models. This optimization improves performance when using reference images by caching certain computations, which can speed up the generation process.

## Inputs

| Parameter | Data Type | Required | Range | Description                                  |
| --------- | --------- | -------- | ----- | -------------------------------------------- |
| `model`   | MODEL     | Yes      |       | The model to apply KV Cache optimization on. |

## Outputs

| Output Name | Data Type | Description                                           |
| ----------- | --------- | ----------------------------------------------------- |
| `model`     | MODEL     | The patched model with KV Cache optimization enabled. |

***

**Source fingerprint (SHA-256):** `bf2b19dd11336bec694a6eb586141fa850e3d0a5102c5d320455f7346738660c`


# FreSca - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FreSca

Complete documentation for the FreSca node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FreSca/en.md)

The FreSca node applies frequency-dependent scaling to the guidance during the sampling process. It separates the guidance signal into low-frequency and high-frequency components using Fourier filtering, then applies different scaling factors to each frequency range before recombining them. This allows for more nuanced control over how guidance affects different aspects of the generated output.

## Inputs

| Parameter     | Data Type | Required | Range     | Description                                                                          |
| ------------- | --------- | -------- | --------- | ------------------------------------------------------------------------------------ |
| `model`       | MODEL     | Yes      | -         | The model to apply frequency scaling to                                              |
| `scale_low`   | FLOAT     | No       | 0 - 10    | Scaling factor for low-frequency components (default: 1.0)                           |
| `scale_high`  | FLOAT     | No       | 0 - 10    | Scaling factor for high-frequency components (default: 1.25)                         |
| `freq_cutoff` | INT       | No       | 1 - 10000 | Number of frequency indices around center to consider as low-frequency (default: 20) |

## Outputs

| Output Name | Data Type | Description                                                                          |
| ----------- | --------- | ------------------------------------------------------------------------------------ |
| `model`     | MODEL     | The modified model with frequency-dependent scaling applied to its guidance function |

***

**Source fingerprint (SHA-256):** `2ff3517619d856db68a9091ae7c87af8c56a23420fa2176b089bf9700475a7a9`


# GrowMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrowMask

Complete documentation for the GrowMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `GrowMask` node is designed to modify the size of a given mask, either expanding or contracting it, while optionally applying a tapered effect to the corners. This functionality is crucial for dynamically adjusting mask boundaries in image processing tasks, allowing for more flexible and precise control over the area of interest.

## Inputs

| Parameter         | Data Type | Description                                                                                                                                                                                                          |
| ----------------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `mask`            | MASK      | The input mask to be modified. This parameter is central to the node's operation, serving as the base upon which the mask is either expanded or contracted.                                                          |
| `expand`          | INT       | Determines the magnitude and direction of the mask modification. Positive values cause the mask to expand, while negative values lead to contraction. This parameter directly influences the final size of the mask. |
| `tapered_corners` | BOOLEAN   | A boolean flag that, when set to True, applies a tapered effect to the corners of the mask during modification. This option allows for smoother transitions and visually appealing results.                          |

## Outputs

| Parameter | Data Type | Description                                                                                               |
| --------- | --------- | --------------------------------------------------------------------------------------------------------- |
| `mask`    | MASK      | The modified mask after applying the specified expansion/contraction and optional tapered corners effect. |


# ImageAddNoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageAddNoise

Complete documentation for the ImageAddNoise node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageAddNoise/en.md)

The ImageAddNoise node adds random noise to an input image. It uses a specified random seed to generate consistent noise patterns and allows controlling the intensity of the noise effect. The resulting image maintains the same dimensions as the input but with added visual texture.

## Inputs

| Parameter  | Data Type | Required | Range                     | Description                                                                                                               |
| ---------- | --------- | -------- | ------------------------- | ------------------------------------------------------------------------------------------------------------------------- |
| `image`    | IMAGE     | Yes      | -                         | The input image to which noise will be added                                                                              |
| `seed`     | INT       | Yes      | 0 to 18446744073709551615 | The random seed used for creating the noise (default: 0). This parameter supports "control after generate" functionality. |
| `strength` | FLOAT     | Yes      | 0.0 to 1.0                | Controls the intensity of the noise effect (default: 0.5, step: 0.01)                                                     |

## Outputs

| Output Name | Data Type | Description                               |
| ----------- | --------- | ----------------------------------------- |
| `image`     | IMAGE     | The output image with added noise applied |

***

**Source fingerprint (SHA-256):** `d35471d5402a322e175958c42a20c56a42199a129e8197030071a1495a9eab6a`


# ImageBlend - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageBlend

Complete documentation for the ImageBlend node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `ImageBlend` node is designed to blend two images together based on a specified blending mode and blend factor. It supports various blending modes such as normal, multiply, screen, overlay, soft light, and difference, allowing for versatile image manipulation and compositing techniques. This node is essential for creating composite images by adjusting the visual interaction between two image layers.

## Inputs

| Field          | Data Type      | Description                                                                                                                                                                |
| -------------- | -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image1`       | `IMAGE`        | The first image to be blended. It serves as the base layer for the blending operation.                                                                                     |
| `image2`       | `IMAGE`        | The second image to be blended. Depending on the blend mode, it modifies the appearance of the first image.                                                                |
| `blend_factor` | `FLOAT`        | Determines the weight of the second image in the blend. A higher blend factor gives more prominence to the second image in the resulting blend.                            |
| `blend_mode`   | COMBO\[STRING] | Specifies the method of blending the two images. Supports modes like normal, multiply, screen, overlay, soft light, and difference, each producing a unique visual effect. |

## Outputs

| Field   | Data Type | Description                                                                                               |
| ------- | --------- | --------------------------------------------------------------------------------------------------------- |
| `image` | `IMAGE`   | The resulting image after blending the two input images according to the specified blend mode and factor. |


# ImageBlur - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageBlur

Complete documentation for the ImageBlur node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `ImageBlur` node applies a Gaussian blur to an image, allowing for the softening of edges and reduction of detail and noise. It provides control over the intensity and spread of the blur through parameters.

## Inputs

| Field         | Data Type | Description                                                                                                      |
| ------------- | --------- | ---------------------------------------------------------------------------------------------------------------- |
| `image`       | `IMAGE`   | The input image to be blurred. This is the primary target for the blur effect.                                   |
| `blur_radius` | `INT`     | Determines the radius of the blur effect. A larger radius results in a more pronounced blur.                     |
| `sigma`       | `FLOAT`   | Controls the spread of the blur. A higher sigma value means the blur will affect a wider area around each pixel. |

## Outputs

| Field   | Data Type | Description                                                                                                       |
| ------- | --------- | ----------------------------------------------------------------------------------------------------------------- |
| `image` | `IMAGE`   | The output is the blurred version of the input image, with the degree of blur determined by the input parameters. |


# ImageColorToMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageColorToMask

Complete documentation for the ImageColorToMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `ImageColorToMask` node is designed to convert a specified color in an image to a mask. It processes an image and a target color, generating a mask where the specified color is highlighted, facilitating operations like color-based segmentation or object isolation.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                                     |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The 'image' parameter represents the input image to be processed. It is crucial for determining the areas of the image that match the specified color to be converted into a mask.              |
| `color`   | `INT`     | The 'color' parameter specifies the target color in the image to be converted into a mask. It plays a key role in identifying the specific color areas to be highlighted in the resulting mask. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                                        |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `mask`    | `MASK`    | The output is a mask highlighting the areas of the input image that match the specified color. This mask can be used for further image processing tasks, such as segmentation or object isolation. |


# ImageCompositeMasked - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageCompositeMasked

Complete documentation for the ImageCompositeMasked node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `ImageCompositeMasked` node is designed for compositing images, allowing for the overlay of a source image onto a destination image at specified coordinates, with optional resizing and masking.

## Inputs

| Parameter       | Data Type | Description                                                                                                                                                                                                 |
| --------------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `destination`   | `IMAGE`   | The destination image onto which the source image will be composited. It serves as the background for the composite operation.                                                                              |
| `source`        | `IMAGE`   | The source image to be composited onto the destination image. This image can optionally be resized to fit the destination image's dimensions.                                                               |
| `x`             | `INT`     | The x-coordinate in the destination image where the top-left corner of the source image will be placed.                                                                                                     |
| `y`             | `INT`     | The y-coordinate in the destination image where the top-left corner of the source image will be placed.                                                                                                     |
| `resize_source` | `BOOLEAN` | A boolean flag indicating whether the source image should be resized to match the destination image's dimensions.                                                                                           |
| `mask`          | `MASK`    | An optional mask that specifies which parts of the source image should be composited onto the destination image. This allows for more complex compositing operations, such as blending or partial overlays. |

## Outputs

| Parameter | Data Type | Description                                                                            |
| --------- | --------- | -------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The resulting image after the compositing operation, which combines elements of both t |


# ImageDeduplication - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageDeduplication

Complete documentation for the ImageDeduplication node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageDeduplication/en.md)

This node removes duplicate or very similar images from a batch. It works by creating a perceptual hash for each image—a simple numerical fingerprint based on its visual content—and then comparing them. Images whose hashes are more similar than a set threshold are considered duplicates and filtered out.

## Inputs

| Parameter              | Data Type | Required | Range     | Description                                                                                                                   |
| ---------------------- | --------- | -------- | --------- | ----------------------------------------------------------------------------------------------------------------------------- |
| `images`               | IMAGE     | Yes      | -         | The batch of images to process for deduplication.                                                                             |
| `similarity_threshold` | FLOAT     | No       | 0.0 - 1.0 | Similarity threshold (0-1). Higher means more similar. Images above this threshold are considered duplicates. (default: 0.95) |

## Outputs

| Output Name | Data Type | Description                                          |
| ----------- | --------- | ---------------------------------------------------- |
| `images`    | IMAGE     | The filtered list of images with duplicates removed. |

***

**Source fingerprint (SHA-256):** `d0c40694853c3dd0952d58b920bf735a4626cb2921928bb982ba479dc58fbe53`


# ImageFromBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageFromBatch

Complete documentation for the ImageFromBatch node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `ImageFromBatch` node is designed for extracting a specific segment of images from a batch based on the provided index and length. It allows for more granular control over the batched images, enabling operations on individual or subsets of images within a larger batch.

## Inputs

| Field         | Data Type | Description                                                                                                                                             |
| ------------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`       | `IMAGE`   | The batch of images from which a segment will be extracted. This parameter is crucial for specifying the source batch.                                  |
| `batch_index` | `INT`     | The starting index within the batch from which the extraction begins. It determines the initial position of the segment to be extracted from the batch. |
| `length`      | `INT`     | The number of images to extract from the batch starting from the batch\_index. This parameter defines the size of the segment to be extracted.          |

## Outputs

| Field   | Data Type | Description                                                                                                                                                            |
| ------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image` | `IMAGE`   | The extracted segment of images from the specified batch. This output represents a subset of the original batch, determined by the batch\_index and length parameters. |


# ImageGrid - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageGrid

Complete documentation for the ImageGrid node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageGrid/en.md)

The Image Grid node combines multiple images into a single, organized grid or collage. It takes a list of images and arranges them into a specified number of columns, resizing each image to fit a defined cell size and adding optional padding between them. The result is a single, new image containing all the input images in a grid layout.

## Inputs

| Parameter     | Data Type | Required | Range     | Description                                                                                      |
| ------------- | --------- | -------- | --------- | ------------------------------------------------------------------------------------------------ |
| `images`      | IMAGE     | Yes      | -         | A list of images to be arranged into the grid. The node requires at least one image to function. |
| `columns`     | INT       | No       | 1 - 20    | The number of columns in the grid (default: 4).                                                  |
| `cell_width`  | INT       | No       | 32 - 2048 | The width, in pixels, of each cell in the grid (default: 256).                                   |
| `cell_height` | INT       | No       | 32 - 2048 | The height, in pixels, of each cell in the grid (default: 256).                                  |
| `padding`     | INT       | No       | 0 - 50    | The amount of padding, in pixels, to place between images in the grid (default: 4).              |

## Outputs

| Output Name | Data Type | Description                                                                 |
| ----------- | --------- | --------------------------------------------------------------------------- |
| `image`     | IMAGE     | The single output image containing all the input images arranged in a grid. |

***

**Source fingerprint (SHA-256):** `87bc0af8af33a0fd703f13fec782075502c9562847fa3887a2273afa5b28c47e`


# ImageMergeTileList - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageMergeTileList

Complete documentation for the ImageMergeTileList node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageMergeTileList/en.md)

This node takes a list of image tiles and merges them back into a single, larger image. It is designed to reconstruct an image that was previously split into a grid of overlapping tiles, using a weighted blending technique to create a seamless final result.

## Inputs

| Parameter      | Data Type | Required | Range      | Description                                                                                                                                       |
| -------------- | --------- | -------- | ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image_list`   | IMAGE     | Yes      | N/A        | A list of image tiles to be merged. The first tile in the list is used to determine the tile dimensions and data type for the entire process.     |
| `final_width`  | INT       | Yes      | 64 - 32768 | The width of the final merged image in pixels (default: 1024).                                                                                    |
| `final_height` | INT       | Yes      | 64 - 32768 | The height of the final merged image in pixels (default: 1024).                                                                                   |
| `overlap`      | INT       | Yes      | 0 - 4096   | The amount of overlap between adjacent tiles in pixels. A value greater than 0 enables a smooth blending effect at the tile seams (default: 128). |

**Note:** The `image_list` is a dynamic input list. The node will process tiles in the order they are provided, up to the number required to fill the grid defined by the `final_width`, `final_height`, and the dimensions of the first tile. If the list contains more tiles than needed, the extra tiles are ignored.

## Outputs

| Output Name | Data Type | Description                                                 |
| ----------- | --------- | ----------------------------------------------------------- |
| `image`     | IMAGE     | The final merged image, reconstructed from the input tiles. |

***

**Source fingerprint (SHA-256):** `41b570bf758093f3693c015e7976b946b9d93ca56db2bf66617149f259ae8c06`


# ImageQuantize - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageQuantize

Complete documentation for the ImageQuantize node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The ImageQuantize node is designed to reduce the number of colors in an image to a specified number, optionally applying dithering techniques to maintain visual quality. This process is useful for creating palette-based images or reducing the color complexity for certain applications.

## Inputs

| Field    | Data Type      | Description                                                                                                                                   |
| -------- | -------------- | --------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`  | `IMAGE`        | The input image tensor to be quantized. It affects the node's execution by being the primary data upon which color reduction is performed.    |
| `colors` | `INT`          | Specifies the number of colors to reduce the image to. It directly influences the quantization process by determining the color palette size. |
| `dither` | COMBO\[STRING] | Determines the dithering technique to be applied during quantization, affecting the visual quality and appearance of the output image.        |

## Outputs

| Field   | Data Type | Description                                                                                                                 |
| ------- | --------- | --------------------------------------------------------------------------------------------------------------------------- |
| `image` | `IMAGE`   | The quantized version of the input image, with reduced color complexity and optionally dithered to maintain visual quality. |


# ImageRGBToYUV - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageRGBToYUV

Complete documentation for the ImageRGBToYUV node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageRGBToYUV/en.md)

The ImageRGBToYUV node converts an RGB image into the YUV color space. It separates the image into three channels: Y (luminance, or brightness), U (blue-difference), and V (red-difference), and returns each as a separate image.

## Inputs

| Parameter | Data Type | Required | Range | Description                                            |
| --------- | --------- | -------- | ----- | ------------------------------------------------------ |
| `image`   | IMAGE     | Yes      | -     | The input RGB image to be converted to YUV color space |

## Outputs

| Output Name | Data Type | Description                                                 |
| ----------- | --------- | ----------------------------------------------------------- |
| `Y`         | IMAGE     | The luminance (brightness) component of the YUV color space |
| `U`         | IMAGE     | The blue-difference chroma component of the YUV color space |
| `V`         | IMAGE     | The red-difference chroma component of the YUV color space  |

***

**Source fingerprint (SHA-256):** `727d9346a77f4efc015683a942b56e530deada1ff1f37dac0e67f96913ffd8ce`


# ImageSharpen - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageSharpen

Complete documentation for the ImageSharpen node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The ImageSharpen node enhances the clarity of an image by accentuating its edges and details. It applies a sharpening filter to the image, which can be adjusted in intensity and radius, thereby making the image appear more defined and crisp.

## Inputs

| Field            | Data Type | Description                                                                                                                                                                |
| ---------------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`          | `IMAGE`   | The input image to be sharpened. This parameter is crucial as it determines the base image on which the sharpening effect will be applied.                                 |
| `sharpen_radius` | `INT`     | Defines the radius of the sharpening effect. A larger radius means that more pixels around the edge will be affected, leading to a more pronounced sharpening effect.      |
| `sigma`          | `FLOAT`   | Controls the spread of the sharpening effect. A higher sigma value results in a smoother transition at the edges, while a lower sigma makes the sharpening more localized. |
| `alpha`          | `FLOAT`   | Adjusts the intensity of the sharpening effect. Higher alpha values result in a stronger sharpening effect.                                                                |

## Outputs

| Field   | Data Type | Description                                                                                    |
| ------- | --------- | ---------------------------------------------------------------------------------------------- |
| `image` | `IMAGE`   | The sharpened image, with enhanced edges and details, ready for further processing or display. |


# ImageToMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageToMask

Complete documentation for the ImageToMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The ImageToMask node is designed to convert an image into a mask based on a specified color channel. It allows for the extraction of mask layers corresponding to the red, green, blue, or alpha channels of an image, facilitating operations that require channel-specific masking or processing.

## Inputs

| Parameter | Data Type      | Description                                                                                                                                                                                                                                                  |
| --------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `image`   | `IMAGE`        | The 'image' parameter represents the input image from which a mask will be generated based on the specified color channel. It plays a crucial role in determining the content and characteristics of the resulting mask.                                     |
| `channel` | COMBO\[STRING] | The 'channel' parameter specifies which color channel (red, green, blue, or alpha) of the input image should be used to generate the mask. This choice directly influences the mask's appearance and which parts of the image are highlighted or masked out. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                               |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `mask`    | `MASK`    | The output 'mask' is a binary or grayscale representation of the specified color channel from the input image, useful for further image processing or masking operations. |


# ImageYUVToRGB - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageYUVToRGB

Complete documentation for the ImageYUVToRGB node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageYUVToRGB/en.md)

The ImageYUVToRGB node converts YUV color space images to RGB color space. It takes three separate input images representing the Y (luma), U (blue projection), and V (red projection) channels and combines them into a single RGB image using color space conversion.

## Inputs

| Parameter | Data Type | Required | Range | Description                                 |
| --------- | --------- | -------- | ----- | ------------------------------------------- |
| `Y`       | IMAGE     | Yes      | -     | The Y (luminance) channel input image       |
| `U`       | IMAGE     | Yes      | -     | The U (blue projection) channel input image |
| `V`       | IMAGE     | Yes      | -     | The V (red projection) channel input image  |

**Note:** All three input images (Y, U, and V) must be provided together and should have compatible dimensions for proper conversion.

## Outputs

| Output Name | Data Type | Description             |
| ----------- | --------- | ----------------------- |
| `output`    | IMAGE     | The converted RGB image |

***

**Source fingerprint (SHA-256):** `5aefb7b87ff76e03af9259f9dac06f027668d83618693e3c9dcfd17b95441070`


# InvertMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/InvertMask

Complete documentation for the InvertMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The InvertMask node is designed to invert the values of a given mask, effectively flipping the masked and unmasked areas. This operation is fundamental in image processing tasks where the focus of interest needs to be switched between the foreground and the background.

## Inputs

| Parameter | Data Type | Description                                                                                                                                    |
| --------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| `mask`    | MASK      | The 'mask' parameter represents the input mask to be inverted. It is crucial for determining the areas to be flipped in the inversion process. |

## Outputs

| Parameter | Data Type | Description                                                                                                         |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------- |
| `mask`    | MASK      | The output is an inverted version of the input mask, with previously masked areas becoming unmasked and vice versa. |


# JoinAudioChannels - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/JoinAudioChannels

Complete documentation for the JoinAudioChannels node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/JoinAudioChannels/en.md)

The Join Audio Channels node combines two separate mono audio inputs into a single stereo audio output. It takes a left channel and a right channel, ensures they have compatible sample rates and lengths, and merges them into a two-channel audio waveform.

## Inputs

| Parameter     | Data Type | Required | Range | Description                                                                        |
| ------------- | --------- | -------- | ----- | ---------------------------------------------------------------------------------- |
| `audio_left`  | AUDIO     | Yes      |       | The mono audio data to be used as the left channel in the resulting stereo audio.  |
| `audio_right` | AUDIO     | Yes      |       | The mono audio data to be used as the right channel in the resulting stereo audio. |

**Note:** Both input audio streams must be mono (single-channel). If they have different sample rates, the channel with the lower rate will be automatically resampled to match the higher rate. If the audio streams have different lengths, they will be trimmed to the length of the shorter one.

## Outputs

| Output Name | Data Type | Description                                                                |
| ----------- | --------- | -------------------------------------------------------------------------- |
| `audio`     | AUDIO     | The resulting stereo audio, containing the joined left and right channels. |

***

**Source fingerprint (SHA-256):** `8a68e59e0d037882e9dd87d93b38673a0de3072bab2c574c7a9750de93b50a68`


# JoinImageWithAlpha - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/JoinImageWithAlpha

Complete documentation for the JoinImageWithAlpha node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed for compositing operations, specifically to join an image with its corresponding alpha mask to produce a single output image. It effectively combines visual content with transparency information, enabling the creation of images where certain areas are transparent or semi-transparent.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                          |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The main visual content to be combined with an alpha mask. It represents the image without transparency information.                                                 |
| `alpha`   | `MASK`    | The alpha mask that defines the transparency of the corresponding image. It is used to determine which parts of the image should be transparent or semi-transparent. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                     |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The output is a single image that combines the input image with the alpha mask, incorporating transparency information into the visual content. |


# LatentBlend - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentBlend

Complete documentation for the LatentBlend node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentBlend/en.md)

The LatentBlend node combines two latent samples by blending them together using a specified blend factor. It takes two latent inputs and creates a new output where the first sample is weighted by the blend factor and the second sample is weighted by the inverse. If the input samples have different shapes, the second sample is automatically resized to match the first sample's dimensions.

## Inputs

| Parameter      | Data Type | Required | Range  | Description                                                        |
| -------------- | --------- | -------- | ------ | ------------------------------------------------------------------ |
| `samples1`     | LATENT    | Yes      | -      | The first latent sample to blend                                   |
| `samples2`     | LATENT    | Yes      | -      | The second latent sample to blend                                  |
| `blend_factor` | FLOAT     | Yes      | 0 to 1 | Controls the blending ratio between the two samples (default: 0.5) |

**Note:** If `samples1` and `samples2` have different shapes, `samples2` will be automatically resized to match the dimensions of `samples1` using bicubic interpolation with center cropping.

## Outputs

| Output Name | Data Type | Description                                            |
| ----------- | --------- | ------------------------------------------------------ |
| `latent`    | LATENT    | The blended latent sample combining both input samples |

***

**Source fingerprint (SHA-256):** `a19808c5b606a8c05f2685fcd78d9f08c1ba51613a4029b36cf0ce5305618c2f`


# LoadAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadAudio

Complete documentation for the LoadAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadAudio/en.md)

The LoadAudio node loads audio files from the input directory and converts them into a format that can be processed by other audio nodes in ComfyUI. It reads audio files and extracts both the waveform data and sample rate, making them available for downstream audio processing tasks.

## Inputs

| Parameter | Data Type | Required | Range                                                      | Description                                     |
| --------- | --------- | -------- | ---------------------------------------------------------- | ----------------------------------------------- |
| `audio`   | AUDIO     | Yes      | All supported audio and video files in the input directory | The audio file to load from the input directory |

**Note:** The node only accepts audio and video files that are present in ComfyUI's input directory. The file must exist and be accessible for successful loading.

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `AUDIO`     | AUDIO     | Audio data containing waveform and sample rate information |

***

**Source fingerprint (SHA-256):** `5631a5c50471e4612344c4bd0457e9824e9a7a8f8b75b22d06f13d5136c75258`


# LoadLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadLatent

Complete documentation for the LoadLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadLatent/en.md)

The LoadLatent node loads previously saved latent representations from .latent files in the input directory. It reads the latent tensor data from the file and applies any necessary scaling adjustments before returning the latent data for use in other nodes.

## Inputs

| Parameter | Data Type | Required | Range                                | Description                                                                        |
| --------- | --------- | -------- | ------------------------------------ | ---------------------------------------------------------------------------------- |
| `latent`  | STRING    | Yes      | All .latent files in input directory | Selects which .latent file to load from the available files in the input directory |

## Outputs

| Output Name | Data Type | Description                                                          |
| ----------- | --------- | -------------------------------------------------------------------- |
| `LATENT`    | LATENT    | Returns the loaded latent representation data from the selected file |

***

**Source fingerprint (SHA-256):** `020185a6066263b75b2417411f07af54d31a2a3a056d650eacfff188dc2cb87e`


# LoraSave - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraSave

Complete documentation for the LoraSave node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoraSave/en.md)

The LoraSave node extracts and saves LoRA (Low-Rank Adaptation) files from model differences. It can process diffusion model differences, text encoder differences, or both, converting them into LoRA format with specified rank and type. The resulting LoRA file is saved to the output directory for later use.

## Inputs

| Parameter           | Data Type | Required | Range                           | Description                                                                                                                                    |
| ------------------- | --------- | -------- | ------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| `filename_prefix`   | STRING    | Yes      | -                               | The prefix for the output filename (default: "loras/ComfyUI\_extracted\_lora")                                                                 |
| `rank`              | INT       | Yes      | 1-4096                          | The rank value for the LoRA, controlling the size and complexity (default: 8)                                                                  |
| `lora_type`         | COMBO     | Yes      | `"standard"`<br />`"full_diff"` | The type of LoRA to create. "standard" extracts low-rank matrices via SVD; "full\_diff" saves the full weight difference (default: "standard") |
| `bias_diff`         | BOOLEAN   | Yes      | -                               | Whether to include bias differences in the LoRA calculation (default: True)                                                                    |
| `model_diff`        | MODEL     | No       | -                               | The ModelSubtract output to be converted to a lora                                                                                             |
| `text_encoder_diff` | CLIP      | No       | -                               | The CLIPSubtract output to be converted to a lora                                                                                              |

**Note:** At least one of `model_diff` or `text_encoder_diff` must be provided for the node to function. If both are omitted, the node will produce no output.

## Outputs

| Output Name | Data Type | Description                                                                                           |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------- |
| -           | -         | This node saves a LoRA file to the output directory but does not return any data through the workflow |

***

**Source fingerprint (SHA-256):** `642510bfe083130cb2724d7ae38d30d4694c85a43c7ce27230690ddd9fe76b79`


# Mahiro - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Mahiro

Complete documentation for the Mahiro node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Mahiro/en.md)

The Mahiro node modifies the guidance function to focus more on the direction of the positive prompt rather than the difference between positive and negative prompts. It creates a patched model that applies a custom guidance scaling approach using cosine similarity between normalized conditional and unconditional denoised outputs. This experimental node helps steer the generation more strongly toward the positive prompt's intended direction.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                 |
| --------- | --------- | -------- | ----- | ----------------------------------------------------------- |
| `model`   | MODEL     | Yes      |       | The model to be patched with the modified guidance function |

## Outputs

| Output Name     | Data Type | Description                                                  |
| --------------- | --------- | ------------------------------------------------------------ |
| `patched_model` | MODEL     | The modified model with the Mahiro guidance function applied |

***

**Source fingerprint (SHA-256):** `56f13cd14ffde21ab980850b62e07bdd4db6733a545f9329bf908c6030147981`


# ManualSigmas - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ManualSigmas

Complete documentation for the ManualSigmas node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ManualSigmas/en.md)

The ManualSigmas node allows you to manually define a custom sequence of noise levels (sigmas) for the sampling process. You input a list of numbers as a string, and the node converts them into a tensor that can be used by other sampling nodes. This is useful for testing or creating specific noise schedules.

## Inputs

| Parameter | Data Type | Required | Range                                | Description                                                                                                                                                         |
| --------- | --------- | -------- | ------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `sigmas`  | STRING    | Yes      | Any comma or space-separated numbers | A string containing the sigma values. The node will extract all numbers from this string. For example, "1, 0.5, 0.1" or "1 0.5 0.1". The default value is "1, 0.5". |

## Outputs

| Output Name | Data Type | Description                                                                         |
| ----------- | --------- | ----------------------------------------------------------------------------------- |
| `sigmas`    | SIGMAS    | The tensor containing the sequence of sigma values extracted from the input string. |

***

**Source fingerprint (SHA-256):** `38fef43da8aa27a9b79584213c3b6cdd003bc47bcaddcf29d549b0b91880ae8d`


# MaskComposite - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MaskComposite

Complete documentation for the MaskComposite node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node specializes in combining two mask inputs through a variety of operations such as addition, subtraction, and logical operations, to produce a new, modified mask. It abstractly handles the manipulation of mask data to achieve complex masking effects, serving as a crucial component in mask-based image editing and processing workflows.

## Inputs

| Parameter     | Data Type      | Description                                                                                                                                                                          |
| ------------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `destination` | MASK           | The primary mask that will be modified based on the operation with the source mask. It plays a central role in the composite operation, acting as the base for modifications.        |
| `source`      | MASK           | The secondary mask that will be used in conjunction with the destination mask to perform the specified operation, influencing the final output mask.                                 |
| `x`           | INT            | The horizontal offset at which the source mask will be applied to the destination mask, affecting the positioning of the composite result.                                           |
| `y`           | INT            | The vertical offset at which the source mask will be applied to the destination mask, affecting the positioning of the composite result.                                             |
| `operation`   | COMBO\[STRING] | Specifies the type of operation to apply between the destination and source masks, such as 'add', 'subtract', or logical operations, determining the nature of the composite effect. |

## Outputs

| Parameter | Data Type | Description                                                                                                                             |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------- |
| `mask`    | MASK      | The resulting mask after applying the specified operation between the destination and source masks, representing the composite outcome. |


# MaskPreview - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MaskPreview

Complete documentation for the MaskPreview node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MaskPreview/en.md)

The MaskPreview node saves mask data as a preview image to your ComfyUI output directory, allowing you to visually inspect mask data during workflow execution. It converts the input mask into a format suitable for image display and saves it with a configurable filename prefix.

## Inputs

| Parameter         | Data Type      | Required | Range | Description                                                      |
| ----------------- | -------------- | -------- | ----- | ---------------------------------------------------------------- |
| `mask`            | MASK           | Yes      | -     | The mask data to be previewed and saved as an image              |
| `filename_prefix` | STRING         | No       | -     | Prefix for the output filename (default: "ComfyUI")              |
| `prompt`          | PROMPT         | No       | -     | Prompt information for metadata (automatically provided)         |
| `extra_pnginfo`   | EXTRA\_PNGINFO | No       | -     | Additional PNG information for metadata (automatically provided) |

## Outputs

| Output Name | Data Type | Description                                                               |
| ----------- | --------- | ------------------------------------------------------------------------- |
| `ui`        | DICT      | Contains the preview image information and metadata for display in the UI |

***

**Source fingerprint (SHA-256):** `c9d9dbc5720ac4c75518c758f2ec3e789b0d3c45431590fb0008573bb9159427`


# MediaPipeFaceLandmarker - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MediaPipeFaceLandmarker

Complete documentation for the MediaPipeFaceLandmarker node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MediaPipeFaceLandmarker/en.md)

## Overview

Detects faces in an image and identifies 468 facial landmarks (key points) on each face using MediaPipe's BlazeFace and FaceMesh models. It also calculates ARKit-52 blendshape coefficients for facial expression analysis. The node can process multiple images in a batch and outputs both the landmark data and bounding boxes for each detected face.

## Inputs

| Parameter                | Data Type              | Required | Range                                            | Description                                                                                                                                                                                                                                                                                                                   |
| ------------------------ | ---------------------- | -------- | ------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `face_detection_model`   | FACE\_DETECTION\_MODEL | Yes      |                                                  | The MediaPipe face detection model to use for landmark detection.                                                                                                                                                                                                                                                             |
| `image`                  | IMAGE                  | Yes      |                                                  | The input image or batch of images to detect faces in.                                                                                                                                                                                                                                                                        |
| `detector_variant`       | COMBO                  | Yes      | `"short"`<br />`"full"`<br />`"both"`            | Face detector range. `"short"` is tuned for close-up faces (within \~2 m of the camera); `"full"` covers farther/smaller faces (up to \~5 m) but is slower. `"both"` runs both detectors and keeps whichever found more faces per frame (\~2x detection cost). Default: `"short"`.                                            |
| `num_faces`              | INT                    | Yes      | 0 to 16                                          | Maximum number of faces to return per frame. 0 means no cap (return all detected). Default: 1.                                                                                                                                                                                                                                |
| `min_confidence`         | FLOAT                  | No       | 0.00 to 1.00                                     | BlazeFace score threshold. Lower values help catch small or occluded faces. Default: 0.5.                                                                                                                                                                                                                                     |
| `missing_frame_fallback` | COMBO                  | No       | `"empty"`<br />`"previous"`<br />`"interpolate"` | Per-frame behavior when detection fails in a batch. `"empty"` leaves the frame faceless. `"previous"` copies the most recent successful detection. `"interpolate"` lerps landmarks/bbox/blendshapes between bracketing successful frames. Multi-face: pairs faces across frames by greedy bbox-centre NN. Default: `"empty"`. |

## Outputs

| Output Name      | Data Type       | Description                                                                                                                                                                                             |
| ---------------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `face_landmarks` | FACE\_LANDMARKS | A structured output containing per-frame face detection results, including 468 facial landmarks, ARKit-52 blendshape coefficients, transformation matrices, and connection sets for mesh visualization. |
| `bboxes`         | BOUNDING\_BOX   | A list of bounding boxes for each detected face, with coordinates (x, y, width, height), label "face", and confidence score. One list per input frame.                                                  |

***

**Source fingerprint (SHA-256):** `f60ed6201288a59d65d62cc98c12f227a353870c36decea8da81a063cfdf2bba`


# MediaPipeFaceMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MediaPipeFaceMask

Complete documentation for the MediaPipeFaceMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MediaPipeFaceMask/en.md)

## Overview

This node creates a binary mask (a black and white image) based on face landmarks detected by MediaPipe. It draws filled polygon shapes for each detected face region, producing one mask per frame in a batch. When multiple faces are detected in the same frame, their masks are combined into a single mask.

## Inputs

| Parameter        | Data Type       | Required | Range                   | Description                                                                                                                                                                                                                |
| ---------------- | --------------- | -------- | ----------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `face_landmarks` | FACE\_LANDMARKS | Yes      | -                       | The face landmarks data from a MediaPipe face detection node.                                                                                                                                                              |
| `regions`        | COMBO           | Yes      | `"all"`<br />`"custom"` | Selects which facial regions to include in the mask. `"all"` creates a mask from the union of all face regions (face oval, lips, eyes, irises). `"custom"` allows you to toggle each region individually. Default: `"all"` |

When `regions` is set to `"custom"`, the following additional boolean parameters become available:

| Parameter   | Data Type | Required | Range      | Description                                             |
| ----------- | --------- | -------- | ---------- | ------------------------------------------------------- |
| `face_oval` | BOOLEAN   | No       | True/False | Include the face oval region in the mask. Default: True |
| `lips`      | BOOLEAN   | No       | True/False | Include the lips region in the mask. Default: True      |
| `eyes`      | BOOLEAN   | No       | True/False | Include the eyes region in the mask. Default: True      |
| `irises`    | BOOLEAN   | No       | True/False | Include the irises region in the mask. Default: True    |

**Note:** When using `"all"` mode, the mask includes all regions combined. Since the face oval encloses the other regions, selecting `"all"` effectively produces the same result as selecting only the face oval.

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                          |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `MASK`      | MASK      | A binary mask tensor where face regions are white (value 1.0) and background is black (value 0.0). The mask has the same dimensions as the input image and contains one mask per frame in the batch. |

***

**Source fingerprint (SHA-256):** `92270002a42ed59bc75e676a6881e1899186d3c8a1bb4dd4c0d39b3762b5bb66`


# MediaPipeFaceMeshVisualize - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MediaPipeFaceMeshVisualize

Complete documentation for the MediaPipeFaceMeshVisualize node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MediaPipeFaceMeshVisualize/en.md)

## Overview

Draws face landmark points and connection lines (a face mesh) on top of an input image. This node uses the landmark data produced by a face detection node to visualize the detected facial features, such as the eyes, nose, mouth, and face outline.

## Inputs

| Parameter        | Data Type       | Required | Range                                 | Description                                                                                                                                                                                                                                                       |
| ---------------- | --------------- | -------- | ------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `face_landmarks` | FACE\_LANDMARKS | Yes      |                                       | The face landmark data from a detection node.                                                                                                                                                                                                                     |
| `image`          | IMAGE           | No       |                                       | The image to draw the mesh on. If not connected, a black canvas of the same size as the detection result will be used.                                                                                                                                            |
| `connections`    | COMBO           | Yes      | `"all"`<br />`"fill"`<br />`"custom"` | Determines which parts of the face mesh to draw. `"all"` draws the full mesh (oval, eyes, brows, lips, irises, nose). `"fill"` draws a solid polygon of the face oval (silhouette mask). `"custom"` lets you toggle each feature individually. (default: `"all"`) |
| `color`          | COLOR           | Yes      |                                       | The color of the mesh lines and points. (default: `#00ff00`)                                                                                                                                                                                                      |
| `thickness`      | INT             | Yes      | 0 to 8                                | The thickness of the mesh lines in pixels. Setting this to 0 disables line drawing. (default: 1)                                                                                                                                                                  |
| `point_size`     | INT             | Yes      | 0 to 16                               | The radius of the landmark dots in pixels. Setting this to 0 disables dot drawing. (default: 2)                                                                                                                                                                   |

**Note on `connections` parameter:** When `"custom"` is selected, additional boolean inputs appear for each facial feature (e.g., `face_oval`, `lips`, `left_eye`, `right_eye`, `left_eyebrow`, `right_eyebrow`, `left_iris`, `right_iris`, `nose`, `tesselation`). Only the features you enable will be drawn.

## Outputs

| Output Name | Data Type | Description                                               |
| ----------- | --------- | --------------------------------------------------------- |
| `IMAGE`     | IMAGE     | The input image with the face landmarks mesh drawn on it. |

***

**Source fingerprint (SHA-256):** `fb5437d73378b0c8daa68669c2e19058ccb7133ed68fc51c8d4c5bab8662f243`


# MergeImageLists - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MergeImageLists

Complete documentation for the MergeImageLists node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MergeImageLists/en.md)

The Merge Image Lists node combines multiple separate lists of images into a single, continuous list. It works by taking all the images from each connected input and appending them together in the order they are received. This is useful for organizing or batching images from different sources for further processing.

**Note:** This node is deprecated and superseded by the Create List node.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                                                                                    |
| --------- | --------- | -------- | ----- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| `images`  | IMAGE     | Yes      | -     | A list of images to be merged. This input can accept multiple connections, and each connected list will be concatenated into the final output. |

**Note:** This node is designed to receive multiple inputs. You can connect several image lists to the single `images` input socket. The node will automatically concatenate all images from all connected lists into one output list.

## Outputs

| Output Name | Data Type | Description                                                                    |
| ----------- | --------- | ------------------------------------------------------------------------------ |
| `images`    | IMAGE     | The single, merged list containing all images from every connected input list. |

***

**Source fingerprint (SHA-256):** `0c9e302b02694a6a23fc7776c872856b1a629df3efe914a3e591a89d5a28914a`


# MoGeInference - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoGeInference

Complete documentation for the MoGeInference node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoGeInference/en.md)

## Overview

Run MoGe on a single image to estimate depth and geometry. This node processes an input image through the MoGe model to generate a 3D point cloud, depth map, camera intrinsics, a mask, and surface normals.

## Inputs

| Parameter          | Data Type   | Required | Range        | Description                                                                                                                                                                                                                                                   |
| ------------------ | ----------- | -------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `moge_model`       | MOGE\_MODEL | Yes      | N/A          | The MoGe model to use for inference.                                                                                                                                                                                                                          |
| `image`            | IMAGE       | Yes      | N/A          | The input image for depth and geometry estimation.                                                                                                                                                                                                            |
| `resolution_level` | INT         | Yes      | 0 to 9       | Controls the processing resolution. 0 is fastest, 9 provides the most detail. (default: 9)                                                                                                                                                                    |
| `fov_x_degrees`    | FLOAT       | Yes      | 0.0 to 170.0 | Horizontal field of view of the source camera in degrees. Sets the focal length used to unproject the depth map into 3D. Set to 0.0 to automatically recover the field of view from the predicted points. (default: 0.0)                                      |
| `batch_size`       | INT         | Yes      | 1 to 64      | Number of images processed per inference call. Lower this value if you run out of memory when processing long videos or large image sets. (default: 4)                                                                                                        |
| `force_projection` | BOOLEAN     | Yes      | True/False   | (Advanced) Forces projection of the predicted points. (default: True)                                                                                                                                                                                         |
| `apply_mask`       | BOOLEAN     | Yes      | True/False   | When enabled, sets masked-out (sky or invalid) pixels to infinity in the points and depth outputs. This helps meshing tools ignore these areas. Disable to keep the raw predicted geometry everywhere; the mask is still returned separately. (default: True) |

## Outputs

| Output Name     | Data Type      | Description                                                                                                                                                                                                                                                        |
| --------------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `moge_geometry` | MOGE\_GEOMETRY | A dictionary containing the estimated geometry. It includes the original `image`, and may contain `points` (3D point cloud), `depth` (depth map), `intrinsics` (camera intrinsics matrix), `mask` (mask identifying valid pixels), and `normal` (surface normals). |

***

**Source fingerprint (SHA-256):** `5213b280513850eeef2e22ae723ebb015789109435e28ddd79f91f9a4b4a1e79`


# MoGePanoramaInference - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoGePanoramaInference

Complete documentation for the MoGePanoramaInference node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoGePanoramaInference/en.md)

## Overview

This node performs depth estimation on equirectangular panorama images. It works by splitting the panorama into 12 perspective views, running the MoGe depth estimation model on each view, and then merging the results back into a single, complete depth map for the original panorama.

## Inputs

| Parameter          | Data Type   | Required | Range       | Description                                                                                                   |
| ------------------ | ----------- | -------- | ----------- | ------------------------------------------------------------------------------------------------------------- |
| `moge_model`       | MOGE\_MODEL | Yes      |             | The MoGe model to use for inference.                                                                          |
| `image`            | IMAGE       | Yes      |             | Equirectangular panorama image (any aspect ratio).                                                            |
| `resolution_level` | INT         | Yes      | 0 to 9      | Per-view detail level. Higher values produce more detailed depth maps (default: 9).                           |
| `split_resolution` | INT         | Yes      | 256 to 1024 | Resolution of each perspective view after splitting the panorama (default: 512).                              |
| `merge_resolution` | INT         | Yes      | 256 to 8192 | Long-side resolution of the final merged equirectangular depth map (default: 1920).                           |
| `batch_size`       | INT         | Yes      | 1 to 12     | Number of perspective views to process in each inference batch. The total number of views is 12 (default: 4). |

## Outputs

| Output Name     | Data Type      | Description                                                                                                                                              |
| --------------- | -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `moge_geometry` | MOGE\_GEOMETRY | A dictionary containing the estimated geometry: `points` (3D point cloud), `depth` (depth map), `mask` (valid area mask), and `image` (the input image). |

***

**Source fingerprint (SHA-256):** `3a701e3679bc35cd5fddc54868ac9c4bc9b4e23a5b97bbf61e46b7309e43600b`


# MoGePointMapToMesh - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoGePointMapToMesh

Complete documentation for the MoGePointMapToMesh node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoGePointMapToMesh/en.md)

## Overview

This node converts a MoGe point map into a 3D mesh. It takes the geometry data produced by a MoGe depth estimation node and triangulates it into a mesh with UV coordinates and an optional texture.

## Inputs

| Parameter                 | Data Type      | Required | Range      | Description                                                                                                                                  |
| ------------------------- | -------------- | -------- | ---------- | -------------------------------------------------------------------------------------------------------------------------------------------- |
| `moge_geometry`           | MOGE\_GEOMETRY | Yes      | N/A        | The MoGe geometry data containing point maps, depth, and optionally the source image.                                                        |
| `batch_index`             | INT            | Yes      | 0 to 4096  | Which image of a batched MoGe geometry to mesh. Per-image vertex counts differ, so batches can't be stacked into a single MESH (default: 0). |
| `decimation`              | INT            | Yes      | 1 to 8     | Vertex stride; 1 = full resolution (default: 1).                                                                                             |
| `discontinuity_threshold` | FLOAT          | Yes      | 0.0 to 1.0 | Drop pixels whose 3x3 depth span exceeds this fraction. 0 = off (default: 0.04).                                                             |
| `texture`                 | BOOLEAN        | Yes      | True/False | Carry the source image through as the baseColor texture (default: True).                                                                     |

## Outputs

| Output Name | Data Type | Description                                                                                    |
| ----------- | --------- | ---------------------------------------------------------------------------------------------- |
| `MESH`      | MESH      | A 3D mesh with vertices, faces, UV coordinates, and an optional texture from the source image. |

***

**Source fingerprint (SHA-256):** `65c43d64050d1c63d9efbb6c2bb96123f94c6d356d6341f2975537ac24ace29f`


# MoGeRender - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MoGeRender

Complete documentation for the MoGeRender node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MoGeRender/en.md)

## Overview

This node takes a MOGE\_GEOMETRY packet (produced by a MoGe depth/normal estimation node) and renders it into a standard image format. You can choose to output a depth map, a colored depth map, a normal map, or a mask.

## Inputs

| Parameter       | Data Type      | Required | Range                                                                                         | Description                                                                                                                                                                                                                            |
| --------------- | -------------- | -------- | --------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `moge_geometry` | MOGE\_GEOMETRY | Yes      | N/A                                                                                           | The geometry data packet from a MoGe estimation node.                                                                                                                                                                                  |
| `output`        | COMBO          | Yes      | `"depth"`<br />`"depth_colored"`<br />`"normal_opengl"`<br />`"normal_directx"`<br />`"mask"` | The type of image to render from the geometry data. DirectX vs OpenGL controls the normal-map green-channel convention. DirectX: green = -Y down (Unreal). OpenGL: green = +Y up (Blender, Substance, Unity, glTF). (default: "depth") |

## Outputs

| Output Name | Data Type | Description                                                                                                                                                  |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `IMAGE`     | IMAGE     | The rendered image as a batch of RGB tensors. The content depends on the `output` mode: a grayscale depth map, a colored depth map, a normal map, or a mask. |

***

**Source fingerprint (SHA-256):** `45ba499e746ce46f9b6f7773e3218bcf80ad2e8d65940b38e248cc2f20c8b2fe`


# Morphology - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Morphology

Complete documentation for the Morphology node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Morphology/en.md)

The Morphology node applies various morphological operations to images, which are mathematical operations used to process and analyze shapes in images. It can perform operations like erosion, dilation, opening, closing, and more using a customizable kernel size to control the effect strength.

## Inputs

| Parameter     | Data Type | Required | Range                                                                                                         | Description                                                                     |
| ------------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------- |
| `image`       | IMAGE     | Yes      | -                                                                                                             | The input image to process                                                      |
| `operation`   | STRING    | Yes      | `"erode"`<br />`"dilate"`<br />`"open"`<br />`"close"`<br />`"gradient"`<br />`"bottom_hat"`<br />`"top_hat"` | The morphological operation to apply (default: "erode")                         |
| `kernel_size` | INT       | Yes      | 3-999                                                                                                         | The size of the structuring element kernel (default: 3). Must be an odd number. |

## Outputs

| Output Name | Data Type | Description                                                    |
| ----------- | --------- | -------------------------------------------------------------- |
| `image`     | IMAGE     | The processed image after applying the morphological operation |

***

**Source fingerprint (SHA-256):** `ea596f8d30975f153fccbc5651eec0fbbf308ef1c616313d996c200cddf748e3`


# NormalizeImages - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/NormalizeImages

Complete documentation for the NormalizeImages node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/NormalizeImages/en.md)

This node adjusts the pixel values of an input image using a mathematical normalization process. It subtracts a specified mean value from each pixel and then divides the result by a specified standard deviation. This is a common preprocessing step to prepare image data for other machine learning models.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                          |
| --------- | --------- | -------- | ----------- | ---------------------------------------------------- |
| `image`   | IMAGE     | Yes      | -           | The input image to be normalized.                    |
| `mean`    | FLOAT     | No       | 0.0 - 1.0   | Mean value for normalization (default: 0.5).         |
| `std`     | FLOAT     | No       | 0.001 - 1.0 | Standard deviation for normalization (default: 0.5). |

## Outputs

| Output Name | Data Type | Description                                                           |
| ----------- | --------- | --------------------------------------------------------------------- |
| `image`     | IMAGE     | The resulting image after the normalization process has been applied. |

***

**Source fingerprint (SHA-256):** `881e14dbbd8d380960a72b828609861a01a88a397f296dcb134955928afff039`


# PerpNeg - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PerpNeg

Complete documentation for the PerpNeg node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PerpNeg/en.md)

The PerpNeg node applies perpendicular negative guidance to a model's sampling process. This node modifies the model's configuration function to adjust noise predictions using negative conditioning and scaling factors. It has been deprecated and replaced by the PerpNegGuider node for improved functionality.

## Inputs

| Parameter            | Data Type    | Required | Range       | Description                                                |
| -------------------- | ------------ | -------- | ----------- | ---------------------------------------------------------- |
| `model`              | MODEL        | Yes      | -           | The model to apply perpendicular negative guidance to      |
| `empty_conditioning` | CONDITIONING | Yes      | -           | Empty conditioning used for negative guidance calculations |
| `neg_scale`          | FLOAT        | No       | 0.0 - 100.0 | Scaling factor for negative guidance (default: 1.0)        |

## Outputs

| Output Name | Data Type | Description                                                     |
| ----------- | --------- | --------------------------------------------------------------- |
| `model`     | MODEL     | The modified model with perpendicular negative guidance applied |

**Note**: This node is deprecated and has been replaced by PerpNegGuider. It is marked as experimental and should not be used in production workflows.

***

**Source fingerprint (SHA-256):** `016bd9a9a9ee42855c15b3e582ada03557297df9a786d977439edd9d3363a5ba`


# PerpNegGuider - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PerpNegGuider

Complete documentation for the PerpNegGuider node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PerpNegGuider/en.md)

The PerpNegGuider node creates a guidance system for controlling image generation using perpendicular negative conditioning. It takes positive, negative, and empty conditioning inputs and applies a specialized guidance algorithm that computes all three noise predictions in a single batch for efficiency. This node is designed for experimental testing and provides fine control over the guidance strength and negative scaling.

## Inputs

| Parameter            | Data Type    | Required | Range       | Description                                                                                                             |
| -------------------- | ------------ | -------- | ----------- | ----------------------------------------------------------------------------------------------------------------------- |
| `model`              | MODEL        | Yes      | -           | The model to use for guidance generation                                                                                |
| `positive`           | CONDITIONING | Yes      | -           | The positive conditioning that guides the generation toward desired content                                             |
| `negative`           | CONDITIONING | Yes      | -           | The negative conditioning that guides the generation away from unwanted content                                         |
| `empty_conditioning` | CONDITIONING | Yes      | -           | The empty or neutral conditioning used as a baseline reference for perpendicular negative guidance                      |
| `cfg`                | FLOAT        | Yes      | 0.0 - 100.0 | The classifier-free guidance scale that controls how strongly the conditioning influences the generation (default: 8.0) |
| `neg_scale`          | FLOAT        | Yes      | 0.0 - 100.0 | The negative scaling factor that adjusts the strength of the perpendicular negative effect (default: 1.0)               |

## Outputs

| Output Name | Data Type | Description                                                           |
| ----------- | --------- | --------------------------------------------------------------------- |
| `guider`    | GUIDER    | A configured guidance system ready for use in the generation pipeline |

***

**Source fingerprint (SHA-256):** `02e4b4e0ea413da31c280cb1e510bdf5caa7b5187eb6de94632e45a91e881820`


# PhotoMakerEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PhotoMakerEncode

Complete documentation for the PhotoMakerEncode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PhotoMakerEncode/en.md)

The PhotoMakerEncode node processes a reference image and a text prompt to generate conditioning data for AI image generation. It uses the PhotoMaker model to combine visual characteristics from the image with text embeddings, specifically looking for the "photomaker" token in the text to determine where to apply the image-based conditioning.

## Inputs

| Parameter    | Data Type  | Required | Range | Description                                                                              |
| ------------ | ---------- | -------- | ----- | ---------------------------------------------------------------------------------------- |
| `photomaker` | PHOTOMAKER | Yes      | -     | The PhotoMaker model used for processing the image and generating image-based embeddings |
| `image`      | IMAGE      | Yes      | -     | The reference image that provides visual characteristics for conditioning                |
| `clip`       | CLIP       | Yes      | -     | The CLIP model used for text tokenization and encoding                                   |
| `text`       | STRING     | Yes      | -     | The text prompt for conditioning generation (default: "photograph of photomaker")        |

**Note:** When the text contains the word "photomaker", the node applies image-based conditioning at that position in the prompt. If "photomaker" is not found in the text, the node generates standard text conditioning without image influence.

## Outputs

| Output Name    | Data Type    | Description                                                                                                                                  |
| -------------- | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The conditioning data containing image and text embeddings for guiding image generation, along with pooled output from the CLIP text encoder |

***

**Source fingerprint (SHA-256):** `d3b669f4a1aee8add8262c19c7ea24852ea7308c4310dafd9d3bbe96920fb991`


# PhotoMakerLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PhotoMakerLoader

Complete documentation for the PhotoMakerLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PhotoMakerLoader/en.md)

The PhotoMakerLoader node loads a PhotoMaker model from the available model files. It reads the specified model file and prepares the PhotoMaker ID encoder for use in identity-based image generation tasks. This node is marked as experimental and is intended for testing purposes.

## Inputs

| Parameter               | Data Type | Required | Range                      | Description                                                                                                                                |
| ----------------------- | --------- | -------- | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
| `photomaker_model_name` | STRING    | Yes      | Multiple options available | The name of the PhotoMaker model file to load. The available options are determined by the model files present in the `photomaker` folder. |

## Outputs

| Output Name        | Data Type  | Description                                                                                           |
| ------------------ | ---------- | ----------------------------------------------------------------------------------------------------- |
| `photomaker_model` | PHOTOMAKER | The loaded PhotoMaker model containing the ID encoder, ready for use in identity encoding operations. |

***

**Source fingerprint (SHA-256):** `43824e1afc147e8d85117eebce5cb47b9c0091a3a5b70f3e1ee0134a1482c6f3`


# PorterDuffImageComposite - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PorterDuffImageComposite

Complete documentation for the PorterDuffImageComposite node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The PorterDuffImageComposite node is designed to perform image compositing using the Porter-Duff compositing operators. It allows for the combination of source and destination images according to various blending modes, enabling the creation of complex visual effects by manipulating image transparency and overlaying images in creative ways.

## Inputs

| Parameter           | Data Type      | Description                                                                                                                                                                   |
| ------------------- | -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `source`            | `IMAGE`        | The source image tensor to be composited over the destination image. It plays a crucial role in determining the final visual outcome based on the selected compositing mode.  |
| `source_alpha`      | `MASK`         | The alpha channel of the source image, which specifies the transparency of each pixel in the source image. It affects how the source image blends with the destination image. |
| `destination`       | `IMAGE`        | The destination image tensor that serves as the backdrop over which the source image is composited. It contributes to the final composited image based on the blending mode.  |
| `destination_alpha` | `MASK`         | The alpha channel of the destination image, defining the transparency of the destination image's pixels. It influences the blending of the source and destination images.     |
| `mode`              | COMBO\[STRING] | The Porter-Duff compositing mode to apply, which determines how the source and destination images are blended together. Each mode creates different visual effects.           |

## Outputs

| Parameter | Data Type | Description                                                                            |
| --------- | --------- | -------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The composited image resulting from the application of the specified Porter-Duff mode. |
| `mask`    | `MASK`    | The alpha channel of the composited image, indicating the transparency of each pixel.  |


# PreviewAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PreviewAudio

Complete documentation for the PreviewAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PreviewAudio/en.md)

The PreviewAudio node creates a temporary audio preview that can be played directly in the interface. It takes audio data as input and generates a preview widget, allowing users to listen to audio outputs without saving permanent files.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                                                                                     |
| --------- | --------- | -------- | ----- | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| `audio`   | AUDIO     | Yes      | -     | The audio data to preview. This node will raise an error if the input audio is None, which can happen when the source video has no audio track. |

## Outputs

| Output Name | Data Type | Description                                                               |
| ----------- | --------- | ------------------------------------------------------------------------- |
| `ui`        | UI        | Displays an audio player widget in the interface for previewing the audio |

***

**Source fingerprint (SHA-256):** `d914d634c063cc97e3cd24b813250d1e5b0e4bce23dfe97d475259a53b3212d2`


# RTDETR_detect - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RTDETR_detect

Complete documentation for the RTDETR_detect node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RTDETR_detect/en.md)

The RT-DETR Detect node performs object detection on input images using an RT-DETR model. It identifies objects, draws bounding boxes around them, and labels them according to the COCO dataset classes. You can filter the results by confidence score, object class, and limit the total number of detections.

## Inputs

| Parameter        | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                | Description                                                                                               |
| ---------------- | --------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- |
| `model`          | MODEL     | Yes      | N/A                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | The RT-DETR model used for object detection.                                                              |
| `image`          | IMAGE     | Yes      | N/A                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | The input image(s) to detect objects in. The node processes images in batches of up to 32.                |
| `threshold`      | FLOAT     | No       | N/A                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | The minimum confidence score a detection must have to be included in the results (default: 0.5).          |
| `class_name`     | COMBO     | No       | `"all"`<br />`"person"`<br />`"bicycle"`<br />`"car"`<br />`"motorcycle"`<br />`"airplane"`<br />`"bus"`<br />`"train"`<br />`"truck"`<br />`"boat"`<br />`"traffic light"`<br />`"fire hydrant"`<br />`"stop sign"`<br />`"parking meter"`<br />`"bench"`<br />`"bird"`<br />`"cat"`<br />`"dog"`<br />`"horse"`<br />`"sheep"`<br />`"cow"`<br />`"elephant"`<br />`"bear"`<br />`"zebra"`<br />`"giraffe"`<br />`"backpack"`<br />`"umbrella"`<br />`"handbag"`<br />`"tie"`<br />`"suitcase"`<br />`"frisbee"`<br />`"skis"`<br />`"snowboard"`<br />`"sports ball"`<br />`"kite"`<br />`"baseball bat"`<br />`"baseball glove"`<br />`"skateboard"`<br />`"surfboard"`<br />`"tennis racket"`<br />`"bottle"`<br />`"wine glass"`<br />`"cup"`<br />`"fork"`<br />`"knife"`<br />`"spoon"`<br />`"bowl"`<br />`"banana"`<br />`"apple"`<br />`"sandwich"`<br />`"orange"`<br />`"broccoli"`<br />`"carrot"`<br />`"hot dog"`<br />`"pizza"`<br />`"donut"`<br />`"cake"`<br />`"chair"`<br />`"couch"`<br />`"potted plant"`<br />`"bed"`<br />`"dining table"`<br />`"toilet"`<br />`"tv"`<br />`"laptop"`<br />`"mouse"`<br />`"remote"`<br />`"keyboard"`<br />`"cell phone"`<br />`"microwave"`<br />`"oven"`<br />`"toaster"`<br />`"sink"`<br />`"refrigerator"`<br />`"book"`<br />`"clock"`<br />`"vase"`<br />`"scissors"`<br />`"teddy bear"`<br />`"hair drier"`<br />`"toothbrush"` | Filter detections by class. Set to 'all' to disable filtering (default: "all").                           |
| `max_detections` | INT       | No       | N/A                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | Maximum number of detections to return per image. In order of descending confidence score (default: 100). |

## Outputs

| Output Name | Data Type   | Description                                                                                                                                |
| ----------- | ----------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
| `bboxes`    | BOUNDINGBOX | A list of bounding boxes for each input image. Each box contains coordinates (x, y, width, height), a class label, and a confidence score. |

***

**Source fingerprint (SHA-256):** `2abc841cc439138bbd944a2e0f9dc5f76e373b158b3b5caed0d9dd405b7f3538`


# RebatchImages - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RebatchImages

Complete documentation for the RebatchImages node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The RebatchImages node is designed to reorganize a batch of images into a new batch configuration, adjusting the batch size as specified. This process is essential for managing and optimizing the processing of image data in batch operations, ensuring that images are grouped according to the desired batch size for efficient handling.

## Inputs

| Field        | Data Type | Description                                                                                                                                                                 |
| ------------ | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `images`     | `IMAGE`   | A list of images to be rebatched. This parameter is crucial for determining the input data that will undergo the rebatching process.                                        |
| `batch_size` | `INT`     | Specifies the desired size of the output batches. This parameter directly influences how the input images are grouped and processed, impacting the structure of the output. |

## Outputs

| Field   | Data Type | Description                                                                                                                                                                             |
| ------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image` | `IMAGE`   | The output consists of a list of image batches, reorganized according to the specified batch size. This allows for flexible and efficient processing of image data in batch operations. |


# RecordAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecordAudio

Complete documentation for the RecordAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecordAudio/en.md)

The RecordAudio node loads audio files that have been recorded or selected through the audio recording interface. It processes the audio file and converts it into a waveform format that can be used by other audio processing nodes in the workflow. The node automatically detects the sample rate and prepares the audio data for further manipulation.

## Inputs

| Parameter | Data Type     | Required | Range | Description                                                  |
| --------- | ------------- | -------- | ----- | ------------------------------------------------------------ |
| `audio`   | AUDIO\_RECORD | Yes      | N/A   | The audio recording input from the audio recording interface |

## Outputs

| Output Name | Data Type | Description                                                              |
| ----------- | --------- | ------------------------------------------------------------------------ |
| `AUDIO`     | AUDIO     | The processed audio data containing waveform and sample rate information |

***

**Source fingerprint (SHA-256):** `ca4dde492ecc4f57fcf87b022162692e3123ee90cce51186433ff8f14f606b70`


# RemoveBackground - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RemoveBackground

Complete documentation for the RemoveBackground node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RemoveBackground/en.md)

## Overview

The Remove Background node generates a foreground mask that separates the main subject from the background of an input image. It uses a background removal model to analyze the image and produce a mask highlighting the foreground elements.

## Inputs

| Parameter          | Data Type                  | Required | Range | Description                                        |
| ------------------ | -------------------------- | -------- | ----- | -------------------------------------------------- |
| `image`            | IMAGE                      | Yes      | N/A   | Input image to remove the background from          |
| `bg_removal_model` | BACKGROUND\_REMOVAL\_MODEL | Yes      | N/A   | Background removal model used to generate the mask |

## Outputs

| Output Name | Data Type | Description                                                                   |
| ----------- | --------- | ----------------------------------------------------------------------------- |
| `mask`      | MASK      | Generated foreground mask that highlights the main subject of the input image |

***

**Source fingerprint (SHA-256):** `6b0e31792dc8a5c949944680129e91790ca396336a43ac67b7816b9d6c5b9049`


# RepeatImageBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RepeatImageBatch

Complete documentation for the RepeatImageBatch node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The RepeatImageBatch node is designed to replicate a given image a specified number of times, creating a batch of identical images. This functionality is useful for operations that require multiple instances of the same image, such as batch processing or data augmentation.

## Inputs

| Field    | Data Type | Description                                                                                                                                                                           |
| -------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`  | `IMAGE`   | The 'image' parameter represents the image to be replicated. It is crucial for defining the content that will be duplicated across the batch.                                         |
| `amount` | `INT`     | The 'amount' parameter specifies the number of times the input image should be replicated. It directly influences the size of the output batch, allowing for flexible batch creation. |

## Outputs

| Field   | Data Type | Description                                                                                                         |
| ------- | --------- | ------------------------------------------------------------------------------------------------------------------- |
| `image` | `IMAGE`   | The output is a batch of images, each identical to the input image, replicated according to the specified 'amount'. |


# SAM3_Detect - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3_Detect

Complete documentation for the SAM3_Detect node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3_Detect/en.md)

# SAM3 Detect Node

## Overview

The SAM3 Detect node performs open-vocabulary detection and segmentation using text descriptions, bounding boxes, or point prompts. It can identify and segment objects in an image based on what you describe in text, where you draw boxes, or where you click points.

## Inputs

| Parameter           | Data Type     | Required | Range      | Description                                                                                                                                                                                                                              |
| ------------------- | ------------- | -------- | ---------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`             | MODEL         | Yes      | -          | The SAM3 model to use for detection and segmentation                                                                                                                                                                                     |
| `image`             | IMAGE         | Yes      | -          | The input image to process                                                                                                                                                                                                               |
| `conditioning`      | CONDITIONING  | No       | -          | Text conditioning from CLIPTextEncode. Required when using text prompts for detection                                                                                                                                                    |
| `bboxes`            | BOUNDING\_BOX | No       | -          | Bounding boxes to segment within. Can be a single box (applied to all frames), a list of boxes (applied to all frames), or a list of lists (per-frame boxes). When provided without text conditioning, the node segments inside each box |
| `positive_coords`   | STRING        | No       | -          | Positive point prompts as JSON format `[{"x": int, "y": int}, ...]` using pixel coordinates. These are points you want to include in the segmentation                                                                                    |
| `negative_coords`   | STRING        | No       | -          | Negative point prompts as JSON format `[{"x": int, "y": int}, ...]` using pixel coordinates. These are points you want to exclude from the segmentation                                                                                  |
| `threshold`         | FLOAT         | No       | 0.0 to 1.0 | Confidence threshold for text-based detections. Only detections with scores above this value are kept (default: 0.5)                                                                                                                     |
| `refine_iterations` | INT           | No       | 0 to 5     | Number of SAM decoder refinement passes. Higher values can improve mask quality. Set to 0 to use raw detector masks without refinement (default: 2)                                                                                      |
| `individual_masks`  | BOOLEAN       | No       | True/False | When enabled, outputs separate masks for each detected object instead of combining them into a single mask (default: False)                                                                                                              |

### Parameter Constraints and Notes

* **Text prompts**: To use text-based detection, you must provide `conditioning` input. When text conditioning is provided, the node runs text-guided detection on the image.
* **Box prompts**: When `bboxes` are provided without text conditioning, the node segments the area inside each bounding box.
* **Point prompts**: When `positive_coords` or `negative_coords` are provided, the node uses point-based segmentation. Points are scaled to the model's internal resolution automatically.
* **Multiple prompt types**: You can combine different prompt types. For example, you can provide both text conditioning and bounding boxes to restrict text detection to specific areas.
* **Batch processing**: The node supports batched images. When processing multiple frames, bounding boxes can be provided per-frame using a list of lists format.
* **JSON format for points**: Point coordinates must be provided as valid JSON strings in the format `[{"x": 100, "y": 200}, {"x": 150, "y": 250}]`.

## Outputs

| Output Name | Data Type     | Description                                                                                                                                                            |
| ----------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `masks`     | MASK          | Segmentation masks. When `individual_masks` is False (default), returns a single combined mask per frame. When True, returns individual masks for each detected object |
| `bboxes`    | BOUNDING\_BOX | Detected bounding boxes with coordinates and confidence scores. Each box includes `x`, `y`, `width`, `height`, and `score` values                                      |

***

**Source fingerprint (SHA-256):** `3f61343c284c249476f2010831863c6094260b11d0a348003b270a126c67d399`


# SAM3_TrackPreview - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3_TrackPreview

Complete documentation for the SAM3_TrackPreview node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3_TrackPreview/en.md)

## Overview

This node creates a video preview of tracked objects, drawing each tracked object with a distinct color overlay and a number label. It does not output any image or video tensors — instead, it saves the resulting preview video directly to a temporary file.

## Inputs

| Parameter    | Data Type   | Required | Range                    | Description                                                                                                  |
| ------------ | ----------- | -------- | ------------------------ | ------------------------------------------------------------------------------------------------------------ |
| `track_data` | TRACK\_DATA | Yes      | -                        | The tracking data containing packed masks and object information from a SAM3 tracking node.                  |
| `images`     | IMAGE       | No       | -                        | Optional input images to use as the background for the preview. If not provided, a black background is used. |
| `opacity`    | FLOAT       | No       | 0.0 to 1.0 (step: 0.05)  | The opacity of the color overlay applied to tracked objects (default: 0.5).                                  |
| `fps`        | FLOAT       | No       | 1.0 to 120.0 (step: 1.0) | The frame rate of the output video (default: 24.0).                                                          |

## Outputs

| Output Name | Data Type      | Description                                                                         |
| ----------- | -------------- | ----------------------------------------------------------------------------------- |
| `ui`        | PREVIEW\_VIDEO | A UI element that displays the generated preview video. No tensor data is returned. |

***

**Source fingerprint (SHA-256):** `76389f354c8acdf249137d966765069d530034a0f8eeb39d769bde3c0f7a1bd0`


# SAM3_TrackToMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3_TrackToMask

Complete documentation for the SAM3_TrackToMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3_TrackToMask/en.md)

## Overview

Selects specific tracked objects from a SAM3 tracking session by their index numbers and combines them into a single output mask. This allows you to choose which objects to keep and which to ignore from the tracking results.

## Inputs

| Parameter        | Data Type     | Required | Range                                | Description                                                                                                                    |
| ---------------- | ------------- | -------- | ------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------ |
| `track_data`     | SAM3TRACKDATA | Yes      | N/A                                  | The tracking data output from a SAM3 tracker node, containing the packed masks and original image size.                        |
| `object_indices` | STRING        | No       | Any comma-separated list of integers | Comma-separated object indices to include in the output mask (e.g., '0,2,3'). If left empty, all tracked objects are included. |

## Outputs

| Output Name | Data Type | Description                                                                                                                                                         |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `masks`     | MASK      | A single binary mask for each frame, where selected objects are combined into one mask. If no objects are selected or no tracking data exists, returns a zero mask. |

***

**Source fingerprint (SHA-256):** `77c9f5142f2078fabb81e58979df01ad9ec41d3de953939570bebb4f2687f8ad`


# SAM3_VideoTrack - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SAM3_VideoTrack

Complete documentation for the SAM3_VideoTrack node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SAM3_VideoTrack/en.md)

## Overview

Track objects across video frames using SAM3's memory-based tracker. This node processes a sequence of video frames and maintains object identities across frames, using either initial masks or text prompts to define what to track.

## Inputs

| Parameter             | Data Type    | Required | Range                       | Description                                                                                              |
| --------------------- | ------------ | -------- | --------------------------- | -------------------------------------------------------------------------------------------------------- |
| `images`              | IMAGE        | Yes      | Batched video frames        | Video frames as batched images                                                                           |
| `model`               | MODEL        | Yes      | SAM3 model                  | The SAM3 model to use for tracking                                                                       |
| `initial_mask`        | MASK         | No       | One mask per object         | Mask(s) for the first frame to track (one per object). Required if `conditioning` is not provided.       |
| `conditioning`        | CONDITIONING | No       | Text conditioning           | Text conditioning for detecting new objects during tracking. Required if `initial_mask` is not provided. |
| `detection_threshold` | FLOAT        | No       | 0.0 to 1.0 (default: 0.5)   | Score threshold for text-prompted detection                                                              |
| `max_objects`         | INT          | No       | 0 to 64 (default: 0)        | Max tracked objects. Initial masks count toward this limit. 0 uses the internal cap of 64.               |
| `detect_interval`     | INT          | No       | 1 to unlimited (default: 1) | Run detection every N frames (1=every frame). Higher values save compute.                                |

**Note:** Either `initial_mask` or `conditioning` must be provided. If both are omitted, the node will raise an error.

## Outputs

| Output Name  | Data Type     | Description                                                                |
| ------------ | ------------- | -------------------------------------------------------------------------- |
| `track_data` | SAM3TrackData | Tracking data containing object masks and metadata across all video frames |

***

**Source fingerprint (SHA-256):** `36ee256c46ea3816be4d06b64d945b79af530032f29e5e4c8741971c7ebf9fae`


# SDPoseDrawKeypoints - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SDPoseDrawKeypoints

Complete documentation for the SDPoseDrawKeypoints node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SDPoseDrawKeypoints/en.md)

The SDPoseDrawKeypoints node takes pose estimation data (keypoints) and draws them as a visual skeleton on a blank canvas. It allows you to selectively draw different parts of the pose, such as the body, hands, face, and feet, with customizable line widths and point sizes. The resulting image can be used for visualization or as input for other nodes that require a pose image.

## Inputs

| Parameter         | Data Type      | Required | Range      | Description                                                                                                                       |
| ----------------- | -------------- | -------- | ---------- | --------------------------------------------------------------------------------------------------------------------------------- |
| `keypoints`       | POSE\_KEYPOINT | Yes      | -          | The pose keypoint data to be drawn. This data typically comes from a pose detection node.                                         |
| `draw_body`       | BOOLEAN        | No       | -          | Controls whether the main body skeleton is drawn (default: True).                                                                 |
| `draw_hands`      | BOOLEAN        | No       | -          | Controls whether the hand keypoints are drawn (default: True).                                                                    |
| `draw_face`       | BOOLEAN        | No       | -          | Controls whether the face keypoints are drawn (default: True).                                                                    |
| `draw_feet`       | BOOLEAN        | No       | -          | Controls whether the foot keypoints are drawn (default: False).                                                                   |
| `stick_width`     | INT            | No       | 1 to 10    | The width of the lines used to draw the body skeleton (default: 4).                                                               |
| `face_point_size` | INT            | No       | 1 to 10    | The size of the points used to draw the face keypoints (default: 3).                                                              |
| `score_threshold` | FLOAT          | No       | 0.0 to 1.0 | The minimum confidence score a keypoint must have to be drawn. Keypoints with scores below this value are ignored (default: 0.3). |

**Note:** If the `keypoints` input is empty or `None`, the node will output a blank 64x64 image.

## Outputs

| Output Name | Data Type | Description                                                                                                                                     |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| `output`    | IMAGE     | An image with the drawn pose keypoints. The image dimensions match the `canvas_height` and `canvas_width` specified in the input keypoint data. |

***

**Source fingerprint (SHA-256):** `09b91930bd88c64aefe32b2b742562537408a13882ad59398fb2e8bcd12fa4eb`


# SDPoseFaceBBoxes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SDPoseFaceBBoxes

Complete documentation for the SDPoseFaceBBoxes node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SDPoseFaceBBoxes/en.md)

The SDPoseFaceBBoxes node processes pose keypoint data to detect and generate bounding boxes around human faces. It analyzes the 2D face keypoints for each person in a frame, calculates a bounding box based on those points, and can adjust the box's size and shape. The resulting bounding boxes are formatted to be compatible with other nodes in the SDPose workflow, such as the SDPoseKeypointExtractor.

## Inputs

| Parameter      | Data Type      | Required | Range      | Description                                                                                                         |
| -------------- | -------------- | -------- | ---------- | ------------------------------------------------------------------------------------------------------------------- |
| `keypoints`    | POSE\_KEYPOINT | Yes      | -          | The pose keypoint data containing information about detected people and their body/face landmarks per frame.        |
| `scale`        | FLOAT          | No       | 1.0 - 10.0 | Multiplier for the bounding box area around each detected face. A larger value creates a larger box. (default: 1.5) |
| `force_square` | BOOLEAN        | No       | -          | Expand the shorter bbox axis so the crop region is always square. (default: True)                                   |

**Note:** The `keypoints` input must be in the specific format produced by nodes like SDPoseKeypointExtractor, containing `canvas_height`, `canvas_width`, and `people` data with `face_keypoints_2d` for each person.

## Outputs

| Output Name | Data Type   | Description                                                                                                                                                                                                                      |
| ----------- | ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `bboxes`    | BOUNDINGBOX | A list of face bounding boxes for each frame. Each bounding box is defined by its top-left coordinates (`x`, `y`), `width`, and `height`. This output is compatible with the `bboxes` input of the SDPoseKeypointExtractor node. |

***

**Source fingerprint (SHA-256):** `dc68640f46afcba4c10a907fd9467671d508cd5bac7670b35a038d159f9d8f50`


# SDPoseKeypointExtractor - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SDPoseKeypointExtractor

Complete documentation for the SDPoseKeypointExtractor node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SDPoseKeypointExtractor/en.md)

The SDPoseKeypointExtractor node detects human pose keypoints from input images using the SDPose model. It can process full images or specific regions defined by bounding boxes and outputs the detected keypoints in the OpenPose format, which includes the coordinates for each person and a confidence score for each keypoint.

## Inputs

| Parameter    | Data Type   | Required | Range      | Description                                                                                                                                                         |
| ------------ | ----------- | -------- | ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`      | MODEL       | Yes      | -          | The SDPose model used for keypoint detection. Must be a model with a `heatmap_head` attribute, specifically from the SDPose repository.                             |
| `vae`        | VAE         | Yes      | -          | The VAE model used to encode the input images into the latent space for processing.                                                                                 |
| `image`      | IMAGE       | Yes      | -          | The input image or batch of images from which to extract pose keypoints.                                                                                            |
| `batch_size` | INT         | No       | 1 to 10000 | The number of images to process at once when running in full-image mode (i.e., when `bboxes` is not provided). This can speed up processing. (default: 16)          |
| `bboxes`     | BOUNDINGBOX | No       | -          | Optional bounding boxes for more accurate detections. Required for multi-person detection. If provided, the node will extract keypoints from each specified region. |

**Parameter Constraints:**

* The `model` input must be a specific SDPose model. If the provided model does not have a `heatmap_head` attribute, the node will raise an error.
* The node operates in two distinct modes based on the `bboxes` input:
  1. **Bounding Box Mode:** When `bboxes` is provided, it processes each specified region individually. This is required for detecting multiple people in a single image.
  2. **Full-Image Mode:** When `bboxes` is not provided, it processes the entire image as a batch. The `batch_size` parameter only applies in this mode.
* When `bboxes` is provided, it must be a list of bounding boxes. If there are fewer bounding box lists than images, the last list is reused for remaining images.
* Bounding boxes with zero width or height (e.g., `x2 <= x1` or `y2 <= y1`) are skipped.

## Outputs

| Output Name | Data Type      | Description                                                                                                                                                                                                        |
| ----------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `keypoints` | POSE\_KEYPOINT | Keypoints in OpenPose frame format (canvas\_width, canvas\_height, people). The output contains the detected persons, each with an array of keypoint coordinates (x, y) and their corresponding confidence scores. |

***

**Source fingerprint (SHA-256):** `5e199e9d08a46d934c6d1f4b1a411f0ca95eb5e7f85ec39f59a058c9be598e9f`


# SVD_img2vid_Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SVD_img2vid_Conditioning

Complete documentation for the SVD_img2vid_Conditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SVD_img2vid_Conditioning/en.md)

The SVD\_img2vid\_Conditioning node prepares conditioning data for video generation using Stable Video Diffusion. It takes an initial image and processes it through CLIP vision and VAE encoders to create positive and negative conditioning pairs, along with an empty latent space for video generation. This node sets up the necessary parameters for controlling motion, frame rate, and augmentation levels in the generated video.

## Inputs

| Parameter            | Data Type    | Required | Range                 | Description                                                                        |
| -------------------- | ------------ | -------- | --------------------- | ---------------------------------------------------------------------------------- |
| `clip_vision`        | CLIP\_VISION | Yes      | -                     | CLIP vision model for encoding the input image                                     |
| `init_image`         | IMAGE        | Yes      | -                     | Initial image to use as the starting point for video generation                    |
| `vae`                | VAE          | Yes      | -                     | VAE model for encoding the image into latent space                                 |
| `width`              | INT          | Yes      | 16 to MAX\_RESOLUTION | Output video width (default: 1024, step: 8)                                        |
| `height`             | INT          | Yes      | 16 to MAX\_RESOLUTION | Output video height (default: 576, step: 8)                                        |
| `video_frames`       | INT          | Yes      | 1 to 4096             | Number of frames to generate in the video (default: 14)                            |
| `motion_bucket_id`   | INT          | Yes      | 1 to 1023             | Controls the amount of motion in the generated video (default: 127)                |
| `fps`                | INT          | Yes      | 1 to 1024             | Frames per second for the generated video (default: 6)                             |
| `augmentation_level` | FLOAT        | Yes      | 0.0 to 10.0           | Level of noise augmentation to apply to the input image (default: 0.0, step: 0.01) |

## Outputs

| Output Name | Data Type    | Description                                                                 |
| ----------- | ------------ | --------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Positive conditioning data containing image embeddings and video parameters |
| `negative`  | CONDITIONING | Negative conditioning data with zeroed embeddings and video parameters      |
| `latent`    | LATENT       | Empty latent space tensor ready for video generation                        |

***

**Source fingerprint (SHA-256):** `33b295b6f2e459852aaa95d9dca26c724aa2e9ad0f884a1c7760766530a00a09`


# SamplerEulerCFGpp - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerEulerCFGpp

Complete documentation for the SamplerEulerCFGpp node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerEulerCFGpp/en.md)

The SamplerEulerCFGpp node provides an Euler CFG++ sampling method for generating outputs. This node offers two different implementation versions of the Euler CFG++ sampler that can be selected based on user preference.

## Inputs

| Parameter | Data Type | Required | Range                            | Description                                                                       |
| --------- | --------- | -------- | -------------------------------- | --------------------------------------------------------------------------------- |
| `version` | STRING    | Yes      | `"regular"`<br />`"alternative"` | The implementation version of the Euler CFG++ sampler to use (default: "regular") |

## Outputs

| Output Name | Data Type | Description                                       |
| ----------- | --------- | ------------------------------------------------- |
| `sampler`   | SAMPLER   | Returns a configured Euler CFG++ sampler instance |

***

**Source fingerprint (SHA-256):** `ff80ae845259b6fd415f11f20bb224617c7a6134b8e02799fef4549d42d44b83`


# SaveAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveAudio

Complete documentation for the SaveAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveAudio/en.md)

The SaveAudio node saves audio data to a file in FLAC format. It takes audio input and writes it to the specified output directory with the given filename prefix. The node automatically handles file naming and ensures the audio is properly saved for later use.

## Inputs

| Parameter         | Data Type | Required | Range | Description                                                   |
| ----------------- | --------- | -------- | ----- | ------------------------------------------------------------- |
| `audio`           | AUDIO     | Yes      | -     | The audio data to be saved                                    |
| `filename_prefix` | STRING    | No       | -     | The prefix for the output filename (default: "audio/ComfyUI") |

*Note: The `prompt` and `extra_pnginfo` parameters are hidden and automatically handled by the system.*

## Outputs

| Output Name | Data Type | Description                                                                                |
| ----------- | --------- | ------------------------------------------------------------------------------------------ |
| *None*      | -         | This node does not return any output data but saves the audio file to the output directory |

***

**Source fingerprint (SHA-256):** `fddb5b1b2e103efa18cd367969193b25753a08e9a56420c39df4645894006ac2`


# SaveAudioMP3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveAudioMP3

Complete documentation for the SaveAudioMP3 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveAudioMP3/en.md)

The SaveAudioMP3 node saves audio data as an MP3 file. It takes audio input and exports it to the specified output directory with customizable filename and quality settings. The node automatically handles file naming and format conversion to create a playable MP3 file.

## Inputs

| Parameter         | Data Type      | Required | Range                        | Description                                                       |
| ----------------- | -------------- | -------- | ---------------------------- | ----------------------------------------------------------------- |
| `audio`           | AUDIO          | Yes      | -                            | The audio data to be saved as an MP3 file                         |
| `filename_prefix` | STRING         | No       | -                            | The prefix for the output filename (default: "audio/ComfyUI")     |
| `quality`         | STRING         | No       | "V0"<br />"128k"<br />"320k" | The audio quality setting for the MP3 file (default: "V0")        |
| `prompt`          | PROMPT         | No       | -                            | Internal prompt data (automatically provided by the system)       |
| `extra_pnginfo`   | EXTRA\_PNGINFO | No       | -                            | Additional PNG information (automatically provided by the system) |

## Outputs

| Output Name | Data Type | Description                                                                                 |
| ----------- | --------- | ------------------------------------------------------------------------------------------- |
| *None*      | -         | This node does not return any output data, but saves the audio file to the output directory |

***

**Source fingerprint (SHA-256):** `b238008410f7e8d65b07d79f12cad2cf2ead1fd105bc881a3bef87ab4e71f484`


# SaveAudioOpus - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveAudioOpus

Complete documentation for the SaveAudioOpus node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveAudioOpus/en.md)

The SaveAudioOpus node saves audio data to an Opus format file. It takes audio input and exports it as a compressed Opus file with configurable quality settings. The node automatically handles file naming and saves the output to the designated output directory.

## Inputs

| Parameter         | Data Type | Required | Range                                                | Description                                                   |
| ----------------- | --------- | -------- | ---------------------------------------------------- | ------------------------------------------------------------- |
| `audio`           | AUDIO     | Yes      | -                                                    | The audio data to be saved as an Opus file                    |
| `filename_prefix` | STRING    | No       | -                                                    | The prefix for the output filename (default: "audio/ComfyUI") |
| `quality`         | COMBO     | No       | "64k"<br />"96k"<br />"128k"<br />"192k"<br />"320k" | The audio quality setting for the Opus file (default: "128k") |

## Outputs

| Output Name | Data Type | Description                                                                                           |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------- |
| -           | -         | This node does not return any output values. It saves the audio file to disk as its primary function. |

***

**Source fingerprint (SHA-256):** `d793d9ef7da6bd3f9257ad16ab9dc5b31a16354a2dff1449afcb6980b9e1dc63`


# SaveLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveLatent

Complete documentation for the SaveLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveLatent/en.md)

The SaveLatent node saves latent tensors to disk as files for later use or sharing. It takes latent samples and saves them to the output directory with optional metadata including prompt information. The node automatically handles file naming and organization while preserving the latent data structure.

## Inputs

| Parameter         | Data Type      | Required | Range | Description                                                          |
| ----------------- | -------------- | -------- | ----- | -------------------------------------------------------------------- |
| `samples`         | LATENT         | Yes      | -     | The latent samples to be saved to disk                               |
| `filename_prefix` | STRING         | No       | -     | The prefix for the output filename (default: "latents/ComfyUI")      |
| `prompt`          | PROMPT         | No       | -     | Prompt information to include in metadata (hidden parameter)         |
| `extra_pnginfo`   | EXTRA\_PNGINFO | No       | -     | Additional PNG information to include in metadata (hidden parameter) |

## Outputs

| Output Name | Data Type | Description                                                                      |
| ----------- | --------- | -------------------------------------------------------------------------------- |
| `ui`        | UI        | Provides file location information for the saved latent in the ComfyUI interface |

***

**Source fingerprint (SHA-256):** `dc7fd101c8dd93e2bcc39de64e0c39abe8e056c9e5932587fc6ce80e2fd143e8`


# Sd4xupscaleConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Sd4xupscaleConditioning

Complete documentation for the Sd4xupscaleConditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node specializes in enhancing the resolution of images through a 4x upscale process, incorporating conditioning elements to refine the output. It leverages diffusion techniques to upscale images while allowing for the adjustment of scale ratio and noise augmentation to fine-tune the enhancement process.

## Inputs

| Parameter            | Comfy dtype    | Description                                                                                                                                                             |
| -------------------- | -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `images`             | `IMAGE`        | The input images to be upscaled. This parameter is crucial as it directly influences the quality and resolution of the output images.                                   |
| `positive`           | `CONDITIONING` | Positive conditioning elements that guide the upscale process towards desired attributes or features in the output images.                                              |
| `negative`           | `CONDITIONING` | Negative conditioning elements that the upscale process should avoid, helping to steer the output away from undesired attributes or features.                           |
| `scale_ratio`        | `FLOAT`        | Determines the factor by which the image resolution is increased. A higher scale ratio results in a larger output image, allowing for greater detail and clarity.       |
| `noise_augmentation` | `FLOAT`        | Controls the level of noise augmentation applied during the upscale process. This can be used to introduce variability and improve the robustness of the output images. |

## Outputs

| Parameter  | Data Type      | Description                                                                                                                  |
| ---------- | -------------- | ---------------------------------------------------------------------------------------------------------------------------- |
| `positive` | `CONDITIONING` | The refined positive conditioning elements resulting from the upscale process.                                               |
| `negative` | `CONDITIONING` | The refined negative conditioning elements resulting from the upscale process.                                               |
| `latent`   | `LATENT`       | A latent representation generated during the upscale process, which can be utilized in further processing or model training. |


# SelfAttentionGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SelfAttentionGuidance

Complete documentation for the SelfAttentionGuidance node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SelfAttentionGuidance/en.md)

The Self-Attention Guidance node applies guidance to diffusion models by modifying the attention mechanism during the sampling process. It captures attention scores from unconditional denoising steps and uses them to create blurred guidance maps that influence the final output. This technique helps guide the generation process by leveraging the model's own attention patterns.

## Inputs

| Parameter    | Data Type | Required | Range       | Description                                                          |
| ------------ | --------- | -------- | ----------- | -------------------------------------------------------------------- |
| `model`      | MODEL     | Yes      | -           | The diffusion model to apply self-attention guidance to              |
| `scale`      | FLOAT     | No       | -2.0 to 5.0 | The strength of the self-attention guidance effect (default: 0.5)    |
| `blur_sigma` | FLOAT     | No       | 0.0 to 10.0 | The amount of blur applied to create the guidance map (default: 2.0) |

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `model`     | MODEL     | The modified model with self-attention guidance applied |

**Note:** This node is currently experimental and has limitations with chunked batches. It can only save attention scores from one UNet call and may not work properly with larger batch sizes.

***

**Source fingerprint (SHA-256):** `ab8f7a0cf19c85f8e77b2d6b380c0224a407a900a42341de7503f5394a3216fb`


# ShuffleDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ShuffleDataset

Complete documentation for the ShuffleDataset node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ShuffleDataset/en.md)

The Shuffle Dataset node takes a list of images and randomly changes their order. It uses a seed value to control the randomness, ensuring the same shuffle order can be reproduced. This is useful for randomizing the sequence of images in a dataset before processing.

## Inputs

| Parameter | Data Type | Required | Range                     | Description                        |
| --------- | --------- | -------- | ------------------------- | ---------------------------------- |
| `images`  | IMAGE     | Yes      | -                         | The list of images to be shuffled. |
| `seed`    | INT       | No       | 0 to 18446744073709551615 | Random seed. (default: 0)          |

## Outputs

| Output Name | Data Type | Description                                                     |
| ----------- | --------- | --------------------------------------------------------------- |
| `images`    | IMAGE     | The same list of images, but in a new, randomly shuffled order. |

***

**Source fingerprint (SHA-256):** `6cde5dcf15817ab98f35f7b2e40fe79a5451c86dba93c0e3cd2622d1cec76c36`


# ShuffleImageTextDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ShuffleImageTextDataset

Complete documentation for the ShuffleImageTextDataset node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ShuffleImageTextDataset/en.md)

This node shuffles a list of images and a list of texts together, keeping their pairings intact. It uses a random seed to determine the shuffle order, ensuring the same input lists will be shuffled in the same way each time the seed is reused.

## Inputs

| Parameter | Data Type | Required | Range                     | Description                                                              |
| --------- | --------- | -------- | ------------------------- | ------------------------------------------------------------------------ |
| `images`  | IMAGE     | Yes      | -                         | List of images to shuffle.                                               |
| `texts`   | STRING    | Yes      | -                         | List of texts to shuffle.                                                |
| `seed`    | INT       | No       | 0 to 18446744073709551615 | Random seed. The shuffle order is determined by this value (default: 0). |

**Note:** The `images` and `texts` inputs must be lists of the same length. The node will pair the first image with the first text, the second image with the second text, and so on, before shuffling these pairs together.

## Outputs

| Output Name | Data Type | Description                                                                      |
| ----------- | --------- | -------------------------------------------------------------------------------- |
| `images`    | IMAGE     | The shuffled list of images.                                                     |
| `texts`     | STRING    | The shuffled list of texts, maintaining their original pairings with the images. |

***

**Source fingerprint (SHA-256):** `77050e9f7255e64b07bd394908b679acef399d78ec9be7c1346d6f297c109968`


# SplitAudioChannels - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplitAudioChannels

Complete documentation for the SplitAudioChannels node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SplitAudioChannels/en.md)

The SplitAudioChannels node separates stereo audio into individual left and right channels. It takes a stereo audio input with two channels and outputs two separate audio streams, one for the left channel and one for the right channel.

## Inputs

| Parameter | Data Type | Required | Range | Description                                          |
| --------- | --------- | -------- | ----- | ---------------------------------------------------- |
| `audio`   | AUDIO     | Yes      | -     | The stereo audio input to be separated into channels |

**Note:** The input audio must have exactly two channels (stereo). The node will raise an error if the input audio has only one channel.

## Outputs

| Output Name | Data Type | Description                       |
| ----------- | --------- | --------------------------------- |
| `left`      | AUDIO     | The separated left channel audio  |
| `right`     | AUDIO     | The separated right channel audio |

***

**Source fingerprint (SHA-256):** `c6e6ecb219e0cb47b003ec9c28fdc060ef83bf1c8bd77d9fb29a088d55a9ab3f`


# SplitImageToTileList - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplitImageToTileList

Complete documentation for the SplitImageToTileList node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SplitImageToTileList/en.md)

The Split Image into List of Tiles node divides a single input image into a series of smaller, overlapping rectangular sections called tiles. It creates a batched list of these tiles, which can be processed individually by other nodes. The size of each tile and the amount of overlap between them can be specified.

## Inputs

| Parameter     | Data Type | Required | Range         | Description                                                           |
| ------------- | --------- | -------- | ------------- | --------------------------------------------------------------------- |
| `image`       | IMAGE     | Yes      | -             | The input image to be split into tiles.                               |
| `tile_width`  | INT       | Yes      | 64 to 1048576 | The width of each output tile in pixels (default: 1024).              |
| `tile_height` | INT       | Yes      | 64 to 1048576 | The height of each output tile in pixels (default: 1024).             |
| `overlap`     | INT       | Yes      | 0 to 4096     | The number of pixels that adjacent tiles will overlap (default: 128). |

## Outputs

| Output Name | Data Type | Description                                               |
| ----------- | --------- | --------------------------------------------------------- |
| `image`     | IMAGE     | A batched list containing all the individual image tiles. |

***

**Source fingerprint (SHA-256):** `4a04e7042446c2368091ffd051c781f9f0ec8496ab681ee9e0741bb269bb54af`


# SplitImageWithAlpha - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplitImageWithAlpha

Complete documentation for the SplitImageWithAlpha node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The SplitImageWithAlpha node is designed to separate the color and alpha components of an image. It processes an input image tensor, extracting the RGB channels as the color component and the alpha channel as the transparency component, facilitating operations that require manipulation of these distinct image aspects.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                                      |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `image`   | `IMAGE`   | The 'image' parameter represents the input image tensor from which the RGB and alpha channels are to be separated. It is crucial for the operation as it provides the source data for the split. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                      |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------ |
| `image`   | `IMAGE`   | The 'image' output represents the separated RGB channels of the input image, providing the color component without the transparency information. |
| `mask`    | `MASK`    | The 'mask' output represents the separated alpha channel of the input image, providing the transparency information.                             |


# StableCascade_SuperResolutionControlnet - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableCascade_SuperResolutionControlnet

Complete documentation for the StableCascade_SuperResolutionControlnet node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableCascade_SuperResolutionControlnet/en.md)

The StableCascade\_SuperResolutionControlnet node prepares inputs for Stable Cascade super-resolution processing. It takes an input image and encodes it using a VAE to create controlnet input, while also generating placeholder latent representations for stage C and stage B of the Stable Cascade pipeline.

## Inputs

| Parameter | Data Type | Required | Range | Description                                          |
| --------- | --------- | -------- | ----- | ---------------------------------------------------- |
| `image`   | IMAGE     | Yes      | -     | The input image to be processed for super-resolution |
| `vae`     | VAE       | Yes      | -     | The VAE model used to encode the input image         |

## Outputs

| Output Name        | Data Type | Description                                                                                                                             |
| ------------------ | --------- | --------------------------------------------------------------------------------------------------------------------------------------- |
| `controlnet_input` | IMAGE     | The encoded image representation suitable for controlnet input                                                                          |
| `stage_c`          | LATENT    | Placeholder latent representation for stage C of Stable Cascade processing, with dimensions based on the input image size divided by 16 |
| `stage_b`          | LATENT    | Placeholder latent representation for stage B of Stable Cascade processing, with dimensions based on the input image size divided by 2  |

***

**Source fingerprint (SHA-256):** `6872eb8610355871ec05c3dacc63ac86d2dc393819f283d256650878a54b7522`


# Stablezero123Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Stablezero123Conditioning

Complete documentation for the Stablezero123Conditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to process and condition data for use in StableZero123 models, focusing on preparing the input in a specific format that is compatible and optimized for these models.

## Inputs

| Parameter     | Comfy dtype   | Description                                                                                                          |
| ------------- | ------------- | -------------------------------------------------------------------------------------------------------------------- |
| `clip_vision` | `CLIP_VISION` | Processes visual data to align with the model's requirements, enhancing the model's understanding of visual context. |
| `init_image`  | `IMAGE`       | Serves as the initial image input for the model, setting the baseline for further image-based operations.            |
| `vae`         | `VAE`         | Integrates variational autoencoder outputs, facilitating the model's ability to generate or modify images.           |
| `width`       | `INT`         | Specifies the width of the output image, allowing for dynamic resizing according to model needs.                     |
| `height`      | `INT`         | Determines the height of the output image, enabling customization of the output dimensions.                          |
| `batch_size`  | `INT`         | Controls the number of images processed in a single batch, optimizing computational efficiency.                      |
| `elevation`   | `FLOAT`       | Adjusts the elevation angle for 3D model rendering, enhancing the model's spatial understanding.                     |
| `azimuth`     | `FLOAT`       | Modifies the azimuth angle for 3D model visualization, improving the model's perception of orientation.              |

## Outputs

| Parameter  | Data Type      | Description                                                                                     |
| ---------- | -------------- | ----------------------------------------------------------------------------------------------- |
| `positive` | `CONDITIONING` | Generates positive conditioning vectors, aiding in the model's positive feature reinforcement.  |
| `negative` | `CONDITIONING` | Produces negative conditioning vectors, assisting in the model's avoidance of certain features. |
| `latent`   | `LATENT`       | Creates latent representations, facilitating deeper model insights into the data.               |


# Stablezero123ConditioningBatched - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Stablezero123ConditioningBatched

Complete documentation for the Stablezero123ConditioningBatched node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to process conditioning information in a batched manner specifically tailored for the StableZero123 model. It focuses on efficiently handling multiple sets of conditioning data simultaneously, optimizing the workflow for scenarios where batch processing is crucial.

## Inputs

| Parameter                   | Data Type     | Description                                                                                       |
| --------------------------- | ------------- | ------------------------------------------------------------------------------------------------- |
| `clip_vision`               | `CLIP_VISION` | The CLIP vision embeddings that provide visual context for the conditioning process.              |
| `init_image`                | `IMAGE`       | The initial image to be conditioned upon, serving as a starting point for the generation process. |
| `vae`                       | `VAE`         | The variational autoencoder used for encoding and decoding images in the conditioning process.    |
| `width`                     | `INT`         | The width of the output image.                                                                    |
| `height`                    | `INT`         | The height of the output image.                                                                   |
| `batch_size`                | `INT`         | The number of conditioning sets to be processed in a single batch.                                |
| `elevation`                 | `FLOAT`       | The elevation angle for 3D model conditioning, affecting the perspective of the generated image.  |
| `azimuth`                   | `FLOAT`       | The azimuth angle for 3D model conditioning, affecting the orientation of the generated image.    |
| `elevation_batch_increment` | `FLOAT`       | The incremental change in elevation angle across the batch, allowing for varied perspectives.     |
| `azimuth_batch_increment`   | `FLOAT`       | The incremental change in azimuth angle across the batch, allowing for varied orientations.       |

## Outputs

| Parameter  | Data Type      | Description                                                                                                        |
| ---------- | -------------- | ------------------------------------------------------------------------------------------------------------------ |
| `positive` | `CONDITIONING` | The positive conditioning output, tailored for promoting certain features or aspects in the generated content.     |
| `negative` | `CONDITIONING` | The negative conditioning output, tailored for demoting certain features or aspects in the generated content.      |
| `latent`   | `LATENT`       | The latent representation derived from the conditioning process, ready for further processing or generation steps. |


# SvdImg2vidConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SvdImg2vidConditioning

Complete documentation for the SvdImg2vidConditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed for generating conditioning data for video generation tasks, specifically tailored for use with SVD\_img2vid models. It takes various inputs including initial images, video parameters, and a VAE model to produce conditioning data that can be used to guide the generation of video frames.

## Inputs

| Parameter            | Comfy dtype   | Description                                                                                                                                                                                   |
| -------------------- | ------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip_vision`        | `CLIP_VISION` | Represents the CLIP vision model used for encoding visual features from the initial image, playing a crucial role in understanding the content and context of the image for video generation. |
| `init_image`         | `IMAGE`       | The initial image from which the video will be generated, serving as the starting point for the video generation process.                                                                     |
| `vae`                | `VAE`         | A Variational Autoencoder (VAE) model used for encoding the initial image into a latent space, facilitating the generation of coherent and continuous video frames.                           |
| `width`              | `INT`         | The desired width of the video frames to be generated, allowing for customization of the video's resolution.                                                                                  |
| `height`             | `INT`         | The desired height of the video frames, enabling control over the video's aspect ratio and resolution.                                                                                        |
| `video_frames`       | `INT`         | Specifies the number of frames to be generated for the video, determining the video's length.                                                                                                 |
| `motion_bucket_id`   | `INT`         | An identifier for categorizing the type of motion to be applied in the video generation, aiding in the creation of dynamic and engaging videos.                                               |
| `fps`                | `INT`         | The frames per second (fps) rate for the video, influencing the smoothness and realism of the generated video.                                                                                |
| `augmentation_level` | `FLOAT`       | A parameter controlling the level of augmentation applied to the initial image, affecting the diversity and variability of the generated video frames.                                        |

## Outputs

| Parameter  | Comfy dtype    | Description                                                                                                                                                        |
| ---------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `positive` | `CONDITIONING` | The positive conditioning data, consisting of encoded features and parameters for guiding the video generation process in a desired direction.                     |
| `negative` | `CONDITIONING` | The negative conditioning data, providing a contrast to the positive conditioning, which can be used to avoid certain patterns or features in the generated video. |
| `latent`   | `LATENT`       | Latent representations generated for each frame of the video, serving as a foundational component for the video generation process.                                |


# T5TokenizerOptions - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/T5TokenizerOptions

Complete documentation for the T5TokenizerOptions node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/T5TokenizerOptions/en.md)

The T5TokenizerOptions node allows you to configure tokenizer settings for various T5 model types. It sets minimum padding and minimum length parameters for multiple T5 model variants including t5xxl, pile\_t5xl, t5base, mt5xl, and umt5xxl. The node takes a CLIP input and returns a modified CLIP with the specified tokenizer options applied.

## Inputs

| Parameter     | Data Type | Required | Range      | Description                                                      |
| ------------- | --------- | -------- | ---------- | ---------------------------------------------------------------- |
| `clip`        | CLIP      | Yes      | -          | The CLIP model to configure tokenizer options for                |
| `min_padding` | INT       | No       | 0 to 10000 | Minimum padding value to set for all T5 model types (default: 0) |
| `min_length`  | INT       | No       | 0 to 10000 | Minimum length value to set for all T5 model types (default: 0)  |

## Outputs

| Output Name | Data Type | Description                                                                       |
| ----------- | --------- | --------------------------------------------------------------------------------- |
| `output`    | CLIP      | The modified CLIP model with updated tokenizer options applied to all T5 variants |

***

**Source fingerprint (SHA-256):** `8fbc016680d83d0b10b07362656296f10ce0c43b20c1d93ab0cfd44dcae284fe`


# TorchCompileModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TorchCompileModel

Complete documentation for the TorchCompileModel node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TorchCompileModel/en.md)

The TorchCompileModel node applies PyTorch compilation to a model to optimize its performance. It creates a copy of the input model and wraps it with PyTorch's compilation functionality using the specified backend. This can improve the model's execution speed during inference.

## Inputs

| Parameter | Data Type | Required | Range                        | Description                                                                   |
| --------- | --------- | -------- | ---------------------------- | ----------------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -                            | The model to be compiled and optimized                                        |
| `backend` | STRING    | Yes      | "inductor"<br />"cudagraphs" | The PyTorch compilation backend to use for optimization (default: "inductor") |

## Outputs

| Output Name | Data Type | Description                                         |
| ----------- | --------- | --------------------------------------------------- |
| `model`     | MODEL     | The compiled model with PyTorch compilation applied |

***

**Source fingerprint (SHA-256):** `240c6eb84ce2b93fe4d7c04fcf69df571e662f17893a4fd8e721241ea082edc8`


# TrimAudioDuration - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TrimAudioDuration

Complete documentation for the TrimAudioDuration node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TrimAudioDuration/en.md)

The TrimAudioDuration node allows you to cut a specific time segment from an audio file. You can specify when to start the trim and how long the resulting audio clip should be. The node works by converting time values to audio frame positions and extracting the corresponding portion of the audio waveform.

## Inputs

| Parameter     | Data Type | Required | Range                                     | Description                                                                                       |
| ------------- | --------- | -------- | ----------------------------------------- | ------------------------------------------------------------------------------------------------- |
| `audio`       | AUDIO     | Yes      | -                                         | The audio input to be trimmed                                                                     |
| `start_index` | FLOAT     | Yes      | -0xffffffffffffffff to 0xffffffffffffffff | Start time in seconds, can be negative to count from the end (supports sub-seconds). Default: 0.0 |
| `duration`    | FLOAT     | Yes      | 0.0 to 0xffffffffffffffff                 | Duration in seconds. Default: 60.0                                                                |

**Note:** The start time must be less than the end time and within the audio length. Negative start values count backwards from the end of the audio. If the start time is negative, it is converted to a frame position counting from the end of the audio. The start and end frames are clamped to the audio boundaries. If the start time equals or exceeds the end time, the node will raise an error.

## Outputs

| Output Name | Data Type | Description                                                          |
| ----------- | --------- | -------------------------------------------------------------------- |
| `audio`     | AUDIO     | The trimmed audio segment with the specified start time and duration |

***

**Source fingerprint (SHA-256):** `4f8c9f966fec8c1d1a1a2bb531014fe7460d61abbafdc367adb667a5044752ef`


# UNetCrossAttentionMultiply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/UNetCrossAttentionMultiply

Complete documentation for the UNetCrossAttentionMultiply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/UNetCrossAttentionMultiply/en.md)

The UNetCrossAttentionMultiply node applies multiplication factors to the cross-attention mechanism in a UNet model. It allows you to scale the query, key, value, and output components of the cross-attention layers to experiment with different attention behaviors and effects.

## Inputs

| Parameter | Data Type | Required | Range      | Description                                                            |
| --------- | --------- | -------- | ---------- | ---------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -          | The UNet model to modify with attention scaling factors                |
| `q`       | FLOAT     | No       | 0.0 - 10.0 | Scaling factor for query components in cross-attention (default: 1.0)  |
| `k`       | FLOAT     | No       | 0.0 - 10.0 | Scaling factor for key components in cross-attention (default: 1.0)    |
| `v`       | FLOAT     | No       | 0.0 - 10.0 | Scaling factor for value components in cross-attention (default: 1.0)  |
| `out`     | FLOAT     | No       | 0.0 - 10.0 | Scaling factor for output components in cross-attention (default: 1.0) |

## Outputs

| Output Name | Data Type | Description                                                    |
| ----------- | --------- | -------------------------------------------------------------- |
| `model`     | MODEL     | The modified UNet model with scaled cross-attention components |

***

**Source fingerprint (SHA-256):** `f55a6809be88bfb32fa2c70fabd0e5bb7360be78670c9473d4a79517b811454e`


# UNetSelfAttentionMultiply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/UNetSelfAttentionMultiply

Complete documentation for the UNetSelfAttentionMultiply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/UNetSelfAttentionMultiply/en.md)

The UNetSelfAttentionMultiply node applies multiplication factors to the query, key, value, and output components of the self-attention mechanism in a UNet model. It allows you to scale different parts of the attention computation to experiment with how attention weights affect the model's behavior.

## Inputs

| Parameter | Data Type | Required | Range      | Description                                               |
| --------- | --------- | -------- | ---------- | --------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -          | The UNet model to modify with attention scaling factors   |
| `q`       | FLOAT     | No       | 0.0 - 10.0 | Multiplication factor for query component (default: 1.0)  |
| `k`       | FLOAT     | No       | 0.0 - 10.0 | Multiplication factor for key component (default: 1.0)    |
| `v`       | FLOAT     | No       | 0.0 - 10.0 | Multiplication factor for value component (default: 1.0)  |
| `out`     | FLOAT     | No       | 0.0 - 10.0 | Multiplication factor for output component (default: 1.0) |

## Outputs

| Output Name | Data Type | Description                                              |
| ----------- | --------- | -------------------------------------------------------- |
| `MODEL`     | MODEL     | The modified UNet model with scaled attention components |

***

**Source fingerprint (SHA-256):** `7a6039eb2faae56437a5eb6fe01be6d38e53c0632175a3405a1e24a476d4da82`


# UNetTemporalAttentionMultiply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/UNetTemporalAttentionMultiply

Complete documentation for the UNetTemporalAttentionMultiply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/UNetTemporalAttentionMultiply/en.md)

The UNetTemporalAttentionMultiply node applies multiplication factors to different types of attention mechanisms in a temporal UNet model. It modifies the model by adjusting the weights of self-attention and cross-attention layers, distinguishing between structural and temporal components. This allows fine-tuning of how much influence each attention type has on the model's output.

## Inputs

| Parameter          | Data Type | Required | Range      | Description                                                         |
| ------------------ | --------- | -------- | ---------- | ------------------------------------------------------------------- |
| `model`            | MODEL     | Yes      | -          | The input model to modify with attention multipliers                |
| `self_structural`  | FLOAT     | No       | 0.0 - 10.0 | Multiplier for self-attention structural components (default: 1.0)  |
| `self_temporal`    | FLOAT     | No       | 0.0 - 10.0 | Multiplier for self-attention temporal components (default: 1.0)    |
| `cross_structural` | FLOAT     | No       | 0.0 - 10.0 | Multiplier for cross-attention structural components (default: 1.0) |
| `cross_temporal`   | FLOAT     | No       | 0.0 - 10.0 | Multiplier for cross-attention temporal components (default: 1.0)   |

## Outputs

| Output Name | Data Type | Description                                        |
| ----------- | --------- | -------------------------------------------------- |
| `model`     | MODEL     | The modified model with adjusted attention weights |

***

**Source fingerprint (SHA-256):** `b43c7c51cbc71349dd267c4abe1704899a394e205a60a13b45869f690d83a0f0`


# VAEDecodeTiled - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEDecodeTiled

Complete documentation for the VAEDecodeTiled node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEDecodeTiled/en.md)

The VAEDecodeTiled node decodes latent representations into images using a tiled approach to handle large images efficiently. It processes the input in smaller tiles to manage memory usage while maintaining image quality. The node also supports video VAEs by processing temporal frames in chunks with overlap for smooth transitions.

## Inputs

| Parameter          | Data Type | Required | Range              | Description                                                                  |
| ------------------ | --------- | -------- | ------------------ | ---------------------------------------------------------------------------- |
| `samples`          | LATENT    | Yes      | -                  | The latent representation to be decoded into images                          |
| `vae`              | VAE       | Yes      | -                  | The VAE model used for decoding the latent samples                           |
| `tile_size`        | INT       | Yes      | 64-4096 (step: 32) | The size of each tile for processing (default: 512)                          |
| `overlap`          | INT       | Yes      | 0-4096 (step: 32)  | The amount of overlap between adjacent tiles (default: 64)                   |
| `temporal_size`    | INT       | Yes      | 8-4096 (step: 4)   | Only used for video VAEs: Amount of frames to decode at a time (default: 64) |
| `temporal_overlap` | INT       | Yes      | 4-4096 (step: 4)   | Only used for video VAEs: Amount of frames to overlap (default: 8)           |

**Note:** The node automatically adjusts overlap values if they exceed practical limits. If `tile_size` is less than 4 times the `overlap`, the overlap is reduced to one quarter of the tile size. Similarly, if `temporal_size` is less than twice the `temporal_overlap`, the temporal overlap is halved. The node also accounts for the VAE's internal compression ratios when calculating tile and overlap sizes for both spatial and temporal dimensions.

## Outputs

| Output Name | Data Type | Description                                                          |
| ----------- | --------- | -------------------------------------------------------------------- |
| `IMAGE`     | IMAGE     | The decoded image or images generated from the latent representation |

***

**Source fingerprint (SHA-256):** `193d5cb219d66855ae581d3e4488b7b6ae3a45b735fb0f9f784fea1f5d466e46`


# VAEEncodeTiled - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEEncodeTiled

Complete documentation for the VAEEncodeTiled node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEEncodeTiled/en.md)

The VAEEncodeTiled node processes images by breaking them into smaller tiles and encoding them using a Variational Autoencoder. This tiled approach allows handling of large images that might otherwise exceed memory limitations. The node supports both image and video VAEs, with separate tiling controls for spatial and temporal dimensions.

## Inputs

| Parameter          | Data Type | Required | Range              | Description                                                                  |
| ------------------ | --------- | -------- | ------------------ | ---------------------------------------------------------------------------- |
| `pixels`           | IMAGE     | Yes      | -                  | The input image data to be encoded                                           |
| `vae`              | VAE       | Yes      | -                  | The Variational Autoencoder model used for encoding                          |
| `tile_size`        | INT       | Yes      | 64-4096 (step: 64) | The size of each tile for spatial processing (default: 512)                  |
| `overlap`          | INT       | Yes      | 0-4096 (step: 32)  | The amount of overlap between adjacent tiles (default: 64)                   |
| `temporal_size`    | INT       | Yes      | 8-4096 (step: 4)   | Only used for video VAEs: Amount of frames to encode at a time (default: 64) |
| `temporal_overlap` | INT       | Yes      | 4-4096 (step: 4)   | Only used for video VAEs: Amount of frames to overlap (default: 8)           |

**Note:** The `temporal_size` and `temporal_overlap` parameters are only relevant when using video VAEs and have no effect on standard image VAEs.

## Outputs

| Output Name | Data Type | Description                                          |
| ----------- | --------- | ---------------------------------------------------- |
| `LATENT`    | LATENT    | The encoded latent representation of the input image |

***

**Source fingerprint (SHA-256):** `87420b96ef9b2d5ef18ecb0339a62b6955151e2a9d2c4390758048c00432939a`


# Wan Vace To Video - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/conditioning/video-models/wan-vace-to-video

Create videos using Alibaba Tongyi Wanxiang's high-resolution video generation API

<img alt="Wan Vace To Video" />

The Wan Vace To Video node allows you to generate videos through text prompts and supports multiple input methods, including text, images, videos, masks, and control signals.

This node combines input conditions (prompts), control videos, and masks to generate high-quality videos. It first preprocesses and encodes the inputs, then applies the conditional information to generate the final video latent representation.
When a reference image is provided, it serves as the initial reference for the video. Control videos and masks can be used to guide the generation process, making the generated video more aligned with expectations.

## Parameter Description

### Required Parameters

| Parameter   | Type         | Default | Range              | Description                         |
| ----------- | ------------ | ------- | ------------------ | ----------------------------------- |
| positive    | CONDITIONING | -       | -                  | Positive prompt condition           |
| negative    | CONDITIONING | -       | -                  | Negative prompt condition           |
| vae         | VAE          | -       | -                  | VAE model for encoding/decoding     |
| width       | INT          | 832     | 16-MAX\_RESOLUTION | Video width, step size 16           |
| height      | INT          | 480     | 16-MAX\_RESOLUTION | Video height, step size 16          |
| length      | INT          | 81      | 1-MAX\_RESOLUTION  | Number of video frames, step size 4 |
| batch\_size | INT          | 1       | 1-4096             | Batch size                          |
| strength    | FLOAT        | 1.0     | 0.0-1000.0         | Condition strength, step size 0.01  |

### Optional Parameters

| Parameter        | Type  | Description                                                   |
| ---------------- | ----- | ------------------------------------------------------------- |
| control\_video   | IMAGE | Control video for guiding the generation process              |
| control\_masks   | MASK  | Control masks defining which areas should be controlled       |
| reference\_image | IMAGE | Reference image as starting point or reference (single image) |

### Output Parameters

| Parameter    | Type         | Description                                                                                                                                                                                                                                                                                                                                                                                           |
| ------------ | ------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| positive     | CONDITIONING | Processed positive prompt condition                                                                                                                                                                                                                                                                                                                                                                   |
| negative     | CONDITIONING | Processed negative prompt condition                                                                                                                                                                                                                                                                                                                                                                   |
| latent       | LATENT       | Generated video latent representation                                                                                                                                                                                                                                                                                                                                                                 |
| trim\_latent | INT          | Parameter for trimming latent representation, default value is 0. When a reference image is provided, this value is set to the shape size of the reference image in latent space. It indicates how much content from the reference image downstream nodes should trim from the generated latent representation to ensure proper control of the reference image's influence in the final video output. |

## Source Code

\[Source code update time: 2025-05-15]

```Python theme={null}
class WanVaceToVideo:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": {"positive": ("CONDITIONING", ),
                             "negative": ("CONDITIONING", ),
                             "vae": ("VAE", ),
                             "width": ("INT", {"default": 832, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
                             "height": ("INT", {"default": 480, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
                             "length": ("INT", {"default": 81, "min": 1, "max": nodes.MAX_RESOLUTION, "step": 4}),
                             "batch_size": ("INT", {"default": 1, "min": 1, "max": 4096}),
                             "strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1000.0, "step": 0.01}),
                },
                "optional": {"control_video": ("IMAGE", ),
                             "control_masks": ("MASK", ),
                             "reference_image": ("IMAGE", ),
                }}

    RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "LATENT", "INT")
    RETURN_NAMES = ("positive", "negative", "latent", "trim_latent")
    FUNCTION = "encode"

    CATEGORY = "conditioning/video_models"

    EXPERIMENTAL = True

    def encode(self, positive, negative, vae, width, height, length, batch_size, strength, control_video=None, control_masks=None, reference_image=None):
        latent_length = ((length - 1) // 4) + 1
        if control_video is not None:
            control_video = comfy.utils.common_upscale(control_video[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
            if control_video.shape[0] < length:
                control_video = torch.nn.functional.pad(control_video, (0, 0, 0, 0, 0, 0, 0, length - control_video.shape[0]), value=0.5)
        else:
            control_video = torch.ones((length, height, width, 3)) * 0.5

        if reference_image is not None:
            reference_image = comfy.utils.common_upscale(reference_image[:1].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
            reference_image = vae.encode(reference_image[:, :, :, :3])
            reference_image = torch.cat([reference_image, comfy.latent_formats.Wan21().process_out(torch.zeros_like(reference_image))], dim=1)

        if control_masks is None:
            mask = torch.ones((length, height, width, 1))
        else:
            mask = control_masks
            if mask.ndim == 3:
                mask = mask.unsqueeze(1)
            mask = comfy.utils.common_upscale(mask[:length], width, height, "bilinear", "center").movedim(1, -1)
            if mask.shape[0] < length:
                mask = torch.nn.functional.pad(mask, (0, 0, 0, 0, 0, 0, 0, length - mask.shape[0]), value=1.0)

        control_video = control_video - 0.5
        inactive = (control_video * (1 - mask)) + 0.5
        reactive = (control_video * mask) + 0.5

        inactive = vae.encode(inactive[:, :, :, :3])
        reactive = vae.encode(reactive[:, :, :, :3])
        control_video_latent = torch.cat((inactive, reactive), dim=1)
        if reference_image is not None:
            control_video_latent = torch.cat((reference_image, control_video_latent), dim=2)

        vae_stride = 8
        height_mask = height // vae_stride
        width_mask = width // vae_stride
        mask = mask.view(length, height_mask, vae_stride, width_mask, vae_stride)
        mask = mask.permute(2, 4, 0, 1, 3)
        mask = mask.reshape(vae_stride * vae_stride, length, height_mask, width_mask)
        mask = torch.nn.functional.interpolate(mask.unsqueeze(0), size=(latent_length, height_mask, width_mask), mode='nearest-exact').squeeze(0)

        trim_latent = 0
        if reference_image is not None:
            mask_pad = torch.zeros_like(mask[:, :reference_image.shape[2], :, :])
            mask = torch.cat((mask_pad, mask), dim=1)
            latent_length += reference_image.shape[2]
            trim_latent = reference_image.shape[2]

        mask = mask.unsqueeze(0)
        positive = node_helpers.conditioning_set_values(positive, {"vace_frames": control_video_latent, "vace_mask": mask, "vace_strength": strength})
        negative = node_helpers.conditioning_set_values(negative, {"vace_frames": control_video_latent, "vace_mask": mask, "vace_strength": strength})

        latent = torch.zeros([batch_size, 16, latent_length, height // 8, width // 8], device=comfy.model_management.intermediate_device())
        out_latent = {}
        out_latent["samples"] = latent
        return (positive, negative, out_latent, trim_latent)

```


# BatchImagesNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BatchImagesNode

Complete documentation for the BatchImagesNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BatchImagesNode/en.md)

The Batch Images node combines multiple individual images into a single batch. It takes a variable number of image inputs and outputs them as one batched image tensor, allowing them to be processed together in subsequent nodes.

## Inputs

| Parameter | Data Type | Required | Range          | Description                                                                                                                                                             |
| --------- | --------- | -------- | -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `images`  | IMAGE     | Yes      | 2 to 50 inputs | A dynamic list of image inputs. You can add between 2 and 50 images to be combined into a batch. The node interface allows you to add more image input slots as needed. |

**Note:** You must connect at least two images for the node to function. The first input slot is always required, and you can add more using the "+" button that appears in the node interface.

## Outputs

| Output Name | Data Type | Description                                                                     |
| ----------- | --------- | ------------------------------------------------------------------------------- |
| `output`    | IMAGE     | A single batched image tensor containing all the input images stacked together. |

***

**Source fingerprint (SHA-256):** `f756fb15760cd2518da9c3f88281d3ab3361b4c2b4820fe2be152e4db1cf102c`


# BeebleSwitchXImageEdit - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BeebleSwitchXImageEdit

Complete documentation for the BeebleSwitchXImageEdit node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BeebleSwitchXImageEdit/en.md)

## Overview

Edit a single image with Beeble SwitchX. This node can switch anything in the scene (background, lighting, costume) while preserving the original subject's pixels. Provide a reference image and/or text prompt to describe the new look. Maximum resolution is approximately 2.77 megapixels.

## Inputs

| Parameter         | Data Type | Required | Range                                    | Description                                                                                                                                                                   |
| ----------------- | --------- | -------- | ---------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`           | IMAGE     | Yes      | -                                        | The source image to edit.                                                                                                                                                     |
| `prompt`          | STRING    | Yes      | -                                        | A text description of the desired new look (e.g., "a knight in shining armor").                                                                                               |
| `alpha_mode`      | COMBO     | Yes      | `"select"`<br />`"fill"`<br />`"custom"` | How to handle the alpha matte. "select" uses a keyframe to select the subject, "fill" replaces the entire image without a separate matte, "custom" uses a user-provided mask. |
| `max_resolution`  | COMBO     | Yes      | `"1080p"`<br />`"720p"`                  | The maximum resolution for the output image. Higher resolution costs more credits.                                                                                            |
| `seed`            | INT       | Yes      | -                                        | A seed value for reproducibility.                                                                                                                                             |
| `reference_image` | IMAGE     | No       | -                                        | An optional reference image to guide the style or appearance of the new scene elements.                                                                                       |

**Note on `alpha_mode`:** When `alpha_mode` is set to `"select"`, you must also provide an `alpha_keyframe` (a keyframe image used to select the subject). When set to `"custom"`, you must provide an `alpha_mask` (a user-created mask). When set to `"fill"`, no alpha input is needed.

## Outputs

| Output Name | Data Type | Description                                                                         |
| ----------- | --------- | ----------------------------------------------------------------------------------- |
| `image`     | IMAGE     | The edited image with the scene elements switched.                                  |
| `alpha`     | MASK      | The alpha matte used by Beeble. Empty for "fill" mode, which has no separate matte. |

***

**Source fingerprint (SHA-256):** `41f23435686626e3ade28708fcb1da192ded347b210080ee9b17834ea8b727fb`


# BriaImageEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaImageEditNode

Complete documentation for the BriaImageEditNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaImageEditNode/en.md)

The Bria FIBO Image Edit node allows you to modify an existing image using a text instruction. It sends the image and your prompt to the Bria API, which uses the FIBO model to generate a new, edited version of the image based on your request. You can also provide a mask to limit the edits to a specific area.

## Inputs

| Parameter           | Data Type    | Required | Range                   | Description                                                                                                                                             |
| ------------------- | ------------ | -------- | ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`             | COMBO        | Yes      | `"FIBO"`                | The model version to use for image editing.                                                                                                             |
| `image`             | IMAGE        | Yes      | -                       | The input image you want to edit.                                                                                                                       |
| `prompt`            | STRING       | No       | -                       | The text instruction describing how to edit the image (default: empty).                                                                                 |
| `negative_prompt`   | STRING       | No       | -                       | Text describing what you do not want to appear in the edited image (default: empty).                                                                    |
| `structured_prompt` | STRING       | No       | -                       | A string containing the structured edit prompt in JSON format. Use this instead of the usual prompt for precise, programmatic control (default: empty). |
| `seed`              | INT          | Yes      | 1 to 2147483647         | A number used to initialize the random generation, ensuring reproducible results (default: 1).                                                          |
| `guidance_scale`    | FLOAT        | Yes      | 3.0 to 5.0              | Controls how closely the generated image follows the prompt. A higher value results in stronger adherence (default: 3.0).                               |
| `steps`             | INT          | Yes      | 20 to 50                | The number of denoising steps the model will perform (default: 50).                                                                                     |
| `moderation`        | DYNAMICCOMBO | Yes      | `"false"`<br />`"true"` | Enables or disables content moderation. Selecting `"true"` reveals additional moderation options for prompt content, visual input, and visual output.   |
| `mask`              | MASK         | No       | -                       | An optional mask image. If provided, edits will only be applied to the masked areas of the image.                                                       |

**Important Constraints:**

* You must provide at least one of the `prompt` or `structured_prompt` inputs. They cannot both be empty.
* Exactly one input `image` is required.
* When the `moderation` parameter is set to `"true"`, three additional boolean inputs become available: `prompt_content_moderation` (default: false), `visual_input_moderation` (default: false), and `visual_output_moderation` (default: true).

## Outputs

| Output Name         | Data Type | Description                                                                  |
| ------------------- | --------- | ---------------------------------------------------------------------------- |
| `IMAGE`             | IMAGE     | The edited image returned by the Bria API.                                   |
| `structured_prompt` | STRING    | The structured prompt that was used or generated during the editing process. |

***

**Source fingerprint (SHA-256):** `60a5f42392ba803380695f036f78d4b88436b3d216aea381b2e3c13eeb5c5456`


# BriaRemoveImageBackground - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaRemoveImageBackground

Complete documentation for the BriaRemoveImageBackground node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaRemoveImageBackground/en.md)

This node removes the background from an image using the Bria RMBG 2.0 service. It sends the image to an external API for processing and returns the result with the background removed.

## Inputs

| Parameter                  | Data Type | Required | Range                   | Description                                                                                                                                    |
| -------------------------- | --------- | -------- | ----------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`                    | IMAGE     | Yes      | -                       | The input image from which the background will be removed.                                                                                     |
| `moderation`               | COMBO     | No       | `"false"`<br />`"true"` | Moderation settings. When set to `"true"`, additional moderation options become available.                                                     |
| `visual_input_moderation`  | BOOLEAN   | No       | -                       | Enables visual content moderation on the input image. This parameter is only available when `moderation` is set to `"true"`. Default: `False`. |
| `visual_output_moderation` | BOOLEAN   | No       | -                       | Enables visual content moderation on the output image. This parameter is only available when `moderation` is set to `"true"`. Default: `True`. |
| `seed`                     | INT       | No       | 0 to 2147483647         | A seed value that controls whether the node should re-run. The results are non-deterministic regardless of the seed value. Default: `0`.       |

**Note:** The `visual_input_moderation` and `visual_output_moderation` parameters are dependent on the `moderation` parameter. They are only active and required if `moderation` is set to `"true"`.

## Outputs

| Output Name | Data Type | Description                                      |
| ----------- | --------- | ------------------------------------------------ |
| `image`     | IMAGE     | The processed image with its background removed. |

***

**Source fingerprint (SHA-256):** `ba1626cbe1a98eb0b20d10a2857307b7589e05ea9f39564273dbb6ceeb8b2d41`


# ByteDanceCreateImageAsset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceCreateImageAsset

Complete documentation for the ByteDanceCreateImageAsset node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceCreateImageAsset/en.md)

This node creates a personal image asset for ByteDance's Seedance 2.0 service. It uploads an input image and registers it within a specified asset group. If no group ID is provided, it will initiate a real-person authentication process in your browser to create a new group before adding the asset.

## Inputs

| Parameter  | Data Type | Required | Range | Description                                                                                                                                                                                              |
| ---------- | --------- | -------- | ----- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`    | IMAGE     | Yes      |       | The image to be registered as a personal asset.                                                                                                                                                          |
| `group_id` | STRING    | No       |       | Reuse an existing Seedance asset group ID to skip repeated human verification for the same person. Leave empty to run real-person authentication in the browser and create a new group (default: empty). |

**Image Constraints:**

* The image width must be between 300 and 6000 pixels.
* The image height must be between 300 and 6000 pixels.
* The image aspect ratio must be between 0.4:1 and 2.5:1.

## Outputs

| Output Name | Data Type | Description                                                                                      |
| ----------- | --------- | ------------------------------------------------------------------------------------------------ |
| `asset_id`  | STRING    | The unique identifier for the newly created image asset.                                         |
| `group_id`  | STRING    | The identifier for the asset group. This will be the provided `group_id` or a newly created one. |

***

**Source fingerprint (SHA-256):** `16e55191af67306bf995c8508f56b64491d2a107e168a3dddb4a05f3468cf103`


# ByteDanceImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceImageNode

Complete documentation for the ByteDanceImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceImageNode/en.md)

The ByteDance Image node generates images using ByteDance models through an API based on text prompts. It allows you to select a model, specify image dimensions, and control various generation parameters like seed and guidance scale. The node connects to ByteDance's image generation service and returns the created image.

## Inputs

| Parameter        | Data Type | Required | Range                       | Description                                                                                                                                |
| ---------------- | --------- | -------- | --------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
| `model`          | STRING    | Yes      | `"seedream-3-0-t2i-250415"` | The ByteDance model to use for image generation. Currently only one model option is available.                                             |
| `prompt`         | STRING    | Yes      | -                           | The text prompt used to generate the image. Must be at least 1 character long after stripping whitespace.                                  |
| `size_preset`    | STRING    | Yes      | See description             | Pick a recommended size. Select Custom to use the width and height below. Available presets are defined by the `RECOMMENDED_PRESETS` list. |
| `width`          | INT       | Yes      | 512 to 2048 (step 64)       | Custom width for the image. This value is only used when `size_preset` is set to `Custom`. Default: 1024.                                  |
| `height`         | INT       | Yes      | 512 to 2048 (step 64)       | Custom height for the image. This value is only used when `size_preset` is set to `Custom`. Default: 1024.                                 |
| `seed`           | INT       | No       | 0 to 2147483647 (step 1)    | Seed to use for generation. Default: 0.                                                                                                    |
| `guidance_scale` | FLOAT     | No       | 1.0 to 10.0 (step 0.01)     | Higher value makes the image follow the prompt more closely. Default: 2.5.                                                                 |
| `watermark`      | BOOLEAN   | No       | True / False                | Whether to add an "AI generated" watermark to the image. Default: False. This is an advanced parameter.                                    |

**Note on size parameters:** The `width` and `height` parameters are only used when `size_preset` is set to `Custom`. If a preset size is selected, the preset's dimensions override the custom width and height values. Both width and height must be between 512 and 2048 pixels when using custom dimensions.

## Outputs

| Output Name | Data Type | Description                                                      |
| ----------- | --------- | ---------------------------------------------------------------- |
| `IMAGE`     | IMAGE     | The generated image returned from the ByteDance API as a tensor. |

***

**Source fingerprint (SHA-256):** `69c1f6fd24e6e184b1a1d785b541c8962f3751d2bbd121d6a3b105d66d58d4b1`


# ByteDanceSeedreamNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceSeedreamNode

Complete documentation for the ByteDanceSeedreamNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceSeedreamNode/en.md)

The ByteDance Seedream 4.5 & 5.0 node provides unified text-to-image generation and precise single-sentence editing capabilities at up to 4K resolution. It can create new images from text prompts or edit existing images using text instructions. The node supports both single image generation and sequential generation of multiple related images.

## Inputs

| Parameter                     | Data Type | Required | Range                                                                     | Description                                                                                                                                                                                                 |
| ----------------------------- | --------- | -------- | ------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`                       | STRING    | Yes      | "seedream 5.0 lite"<br />"seedream-4-5-251128"<br />"seedream-4-0-250828" | The Seedream model to use for generation.                                                                                                                                                                   |
| `prompt`                      | STRING    | Yes      | -                                                                         | Text prompt for creating or editing an image. Must be at least 1 character long.                                                                                                                            |
| `image`                       | IMAGE     | No       | -                                                                         | Input image(s) for image-to-image generation. Reference image(s) for single or multi-reference generation. Maximum of 14 reference images for seedream-5-0-260128, or 10 for other models.                  |
| `size_preset`                 | STRING    | No       | Multiple options available                                                | Pick a recommended size. Select Custom to use the width and height below. Default: first preset from RECOMMENDED\_PRESETS\_SEEDREAM\_4.                                                                     |
| `width`                       | INT       | No       | 1024 to 6240 (step 2)                                                     | Custom width for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048.                                                                                                           |
| `height`                      | INT       | No       | 1024 to 4992 (step 2)                                                     | Custom height for image. Value is working only if `size_preset` is set to `Custom`. Default: 2048.                                                                                                          |
| `sequential_image_generation` | STRING    | No       | "disabled"<br />"auto"                                                    | Group image generation mode. "disabled" generates a single image. "auto" lets the model decide whether to generate multiple related images (e.g., story scenes, character variations). Default: "disabled". |
| `max_images`                  | INT       | No       | 1 to 15 (step 1)                                                          | Maximum number of images to generate when sequential\_image\_generation='auto'. Total images (input + generated) cannot exceed 15. Default: 1.                                                              |
| `seed`                        | INT       | No       | 0 to 2147483647 (step 1)                                                  | Seed to use for generation. Default: 0.                                                                                                                                                                     |
| `watermark`                   | BOOLEAN   | No       | -                                                                         | Whether to add an "AI generated" watermark to the image. Default: False.                                                                                                                                    |
| `fail_on_partial`             | BOOLEAN   | No       | -                                                                         | If enabled, abort execution if any requested images are missing or return an error. Default: True.                                                                                                          |

**Notes on parameter constraints:**

* The minimum image resolution depends on the selected model: 3.68MP for seedream-4-5 and seedream-5-0 models, 0.92MP for seedream-4-0 models.
* The maximum image resolution is 10.4MP for seedream-5-0 models and 16.78MP for other models.
* Reference images must have an aspect ratio between 1:3 and 3:1.
* When `sequential_image_generation` is set to "auto", the total number of input images plus `max_images` cannot exceed 15.
* The `width` and `height` parameters are only used when `size_preset` is set to "Custom".

## Outputs

| Output Name | Data Type | Description                                                                                                                                              |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `IMAGE`     | IMAGE     | Generated image(s) based on the input parameters and prompt. Returns a single image tensor or a batch of image tensors if multiple images are generated. |

***

**Source fingerprint (SHA-256):** `daddffc265ab7b24746337825239c25b633a923804b6e5ad11149aea15772a7f`


# ByteDanceSeedreamNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceSeedreamNodeV2

Complete documentation for the ByteDanceSeedreamNodeV2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceSeedreamNodeV2/en.md)

## Overview

This node generates or edits images using ByteDance's Seedream models (versions 4.0, 4.5, and 5.0 Lite). It can create new images from a text prompt or edit existing images by providing reference images, supporting resolutions up to 4K.

## Inputs

| Parameter   | Data Type | Required | Range                                                                           | Description                                                                                          |
| ----------- | --------- | -------- | ------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------- |
| `prompt`    | STRING    | Yes      | N/A                                                                             | Text prompt for creating or editing an image.                                                        |
| `model`     | COMBO     | Yes      | `"seedream 5.0 lite"`<br />`"seedream-4-5-251128"`<br />`"seedream-4-0-250828"` | The Seedream model version to use for generation. Each model has different capabilities and pricing. |
| `seed`      | INT       | No       | 0 to 2147483647                                                                 | Seed to use for generation (default: 0).                                                             |
| `watermark` | BOOLEAN   | No       | True / False                                                                    | Whether to add an "AI generated" watermark to the image (default: False).                            |

### Model-Specific Parameters

When you select a model, additional parameters become available:

* **Size Preset**: A dropdown to select a predefined image resolution. The available presets depend on the selected model.
* **Width**: The width of the generated image in pixels (default: 2048).
* **Height**: The height of the generated image in pixels (default: 2048).
* **Max Images**: The maximum number of images to generate (default: 1). When set to 1, sequential image generation is disabled.
* **Reference Images**: Up to 10 (for Seedream 4.0 and 4.5) or 14 (for Seedream 5.0 Lite) reference images for editing. Images must have an aspect ratio between 1:3 and 3:1.
* **Fail on Partial**: If enabled, the node will raise an error if not all requested images are generated successfully (default: False).

### Resolution Constraints

* **Seedream 5.0 Lite and 4.5**: Minimum resolution is 3.68 megapixels (e.g., 1920x1920).
* **Seedream 4.0**: Minimum resolution is 0.92 megapixels (e.g., 960x960).
* **All models**: Maximum resolution is 16.78 megapixels (e.g., 4096x4096).

### Image Count Constraints

* The total number of reference images plus generated images cannot exceed 15.
* For Seedream 5.0 Lite, a maximum of 14 reference images are supported.
* For Seedream 4.0 and 4.5, a maximum of 10 reference images are supported.

## Outputs

| Output Name | Data Type | Description                                                                                                              |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------ |
| `image`     | IMAGE     | The generated or edited image as a tensor. If multiple images were requested, they are concatenated into a single batch. |

***

**Source fingerprint (SHA-256):** `6a98d2c1f1e73e304970115bc6dd3ea24ca3cdf440803eed862b7a1ea8d394ce`


# CenterCropImages - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CenterCropImages

Complete documentation for the CenterCropImages node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CenterCropImages/en.md)

The Center Crop Images node crops an image from its center to a specified width and height. It calculates the central region of the input image and extracts a rectangular area of the defined dimensions. If the requested crop size is larger than the image, the crop will be constrained to the image's boundaries.

## Inputs

| Parameter | Data Type | Required | Range     | Description                                 |
| --------- | --------- | -------- | --------- | ------------------------------------------- |
| `image`   | IMAGE     | Yes      | -         | The input image to be cropped.              |
| `width`   | INT       | Yes      | 1 to 8192 | The width of the crop area (default: 512).  |
| `height`  | INT       | Yes      | 1 to 8192 | The height of the crop area (default: 512). |

## Outputs

| Output Name | Data Type | Description                                          |
| ----------- | --------- | ---------------------------------------------------- |
| `image`     | IMAGE     | The resulting image after the center crop operation. |

***

**Source fingerprint (SHA-256):** `1b22529602e3aca816b583158c4bb5aa51de3478ac8068c2a69a3392fb12746f`


# CropByBBoxes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CropByBBoxes

Complete documentation for the CropByBBoxes node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CropByBBoxes/en.md)

The CropByBBoxes node extracts and resizes specific rectangular regions from an input image batch. It uses provided bounding box coordinates to define the area to crop from each image. The cropped regions are then resized to a specified output dimension, with options to either stretch the crop or pad it to preserve its original aspect ratio.

## Inputs

| Parameter       | Data Type   | Required | Range                    | Description                                                                                                                     |
| --------------- | ----------- | -------- | ------------------------ | ------------------------------------------------------------------------------------------------------------------------------- |
| `image`         | IMAGE       | Yes      | -                        | The input batch of images to crop.                                                                                              |
| `bboxes`        | BOUNDINGBOX | Yes      | -                        | The list of bounding boxes defining the regions to crop. This input is forced, meaning it must be connected.                    |
| `output_width`  | INT         | No       | 64 - 4096                | The width each crop is resized to (default: 512).                                                                               |
| `output_height` | INT         | No       | 64 - 4096                | The height each crop is resized to (default: 512).                                                                              |
| `padding`       | INT         | No       | 0 - 1024                 | Extra padding in pixels added on each side of the bounding box before cropping (default: 0).                                    |
| `keep_aspect`   | COMBO       | No       | `"stretch"`<br />`"pad"` | Whether to stretch the crop to fit the output size, or pad with black pixels to preserve its aspect ratio (default: "stretch"). |

**Note:** The node processes one image frame at a time. If multiple bounding boxes are provided for a single frame, it calculates a single crop region that is the union (the smallest rectangle containing all boxes) of all provided boxes. If a calculated crop region is invalid (e.g., zero width or height), the node will create a fallback crop from the center-top of the image.

## Outputs

| Output Name | Data Type | Description                                                         |
| ----------- | --------- | ------------------------------------------------------------------- |
| `image`     | IMAGE     | All cropped and resized regions, stacked into a single image batch. |

***

**Source fingerprint (SHA-256):** `7524d629e61f5af2475f819bc9431d4f4173feb5ad59f9bcf81d822330fb3e22`


# Flux2ImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Flux2ImageNode

Complete documentation for the Flux2ImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Flux2ImageNode/en.md)

## Overview

Generate images using the Flux.2 \[pro] or Flux.2 \[max] model from a text prompt and optional reference images. This node sends your request to the BFL API, polls for the result, and returns the generated image as a tensor.

## Inputs

| Parameter | Data Type | Required | Range                                  | Description                                                                                                                        |
| --------- | --------- | -------- | -------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`  | STRING    | Yes      | N/A                                    | Prompt for the image generation or edit (default: empty string).                                                                   |
| `model`   | COMBO     | Yes      | `"Flux.2 [pro]"`<br />`"Flux.2 [max]"` | The Flux.2 model version to use. Selecting a model unlocks additional parameters for width, height, and optional reference images. |
| `seed`    | INT       | Yes      | 0 to 18446744073709551615              | The random seed used for creating the noise. Can be set to randomize after each generation (default: 0).                           |

**Additional Parameters (unlocked by `model` selection):**

When you select a model, the following parameters become available:

| Parameter      | Data Type | Required | Range         | Description                                                                            |
| -------------- | --------- | -------- | ------------- | -------------------------------------------------------------------------------------- |
| `model.width`  | INT       | Yes      | 256 to 1440   | The width of the generated image in pixels.                                            |
| `model.height` | INT       | Yes      | 256 to 1440   | The height of the generated image in pixels.                                           |
| `model.images` | IMAGE     | No       | 0 to 8 images | Optional reference images to guide the generation. A maximum of 8 images is supported. |

**Constraints:**

* The maximum number of reference images is 8. If more than 8 images are provided, an error will be raised.
* The `model.width` and `model.height` values affect the cost of the generation (see price badge logic in source code).

## Outputs

| Output Name | Data Type | Description                                                          |
| ----------- | --------- | -------------------------------------------------------------------- |
| `image`     | IMAGE     | The generated image as a tensor, downloaded from the BFL API result. |

***

**Source fingerprint (SHA-256):** `ce3ee97d5ccb746892f3bfdb0dd5450d79cb4e0775a88d1f8c09569ce43ecbbb`


# FluxProExpandNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProExpandNode

Complete documentation for the FluxProExpandNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProExpandNode/en.md)

Outpaints image based on prompt. This node expands an image by adding pixels to the top, bottom, left, and right sides while generating new content that matches the provided text description.

## Inputs

| Parameter           | Data Type | Required | Range                  | Description                                                                                                                                                                                                                     |
| ------------------- | --------- | -------- | ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`             | IMAGE     | Yes      | -                      | The input image to be expanded                                                                                                                                                                                                  |
| `prompt`            | STRING    | No       | -                      | Prompt for the image generation (default: "")                                                                                                                                                                                   |
| `prompt_upsampling` | BOOLEAN   | No       | -                      | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: False) |
| `top`               | INT       | No       | 0-2048                 | Number of pixels to expand at the top of the image (default: 0)                                                                                                                                                                 |
| `bottom`            | INT       | No       | 0-2048                 | Number of pixels to expand at the bottom of the image (default: 0)                                                                                                                                                              |
| `left`              | INT       | No       | 0-2048                 | Number of pixels to expand at the left of the image (default: 0)                                                                                                                                                                |
| `right`             | INT       | No       | 0-2048                 | Number of pixels to expand at the right of the image (default: 0)                                                                                                                                                               |
| `guidance`          | FLOAT     | No       | 1.5-100                | Guidance strength for the image generation process (default: 60)                                                                                                                                                                |
| `steps`             | INT       | No       | 15-50                  | Number of steps for the image generation process (default: 50)                                                                                                                                                                  |
| `seed`              | INT       | No       | 0-18446744073709551615 | The random seed used for creating the noise. (default: 0)                                                                                                                                                                       |

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `image`     | IMAGE     | The expanded output image |

***

**Source fingerprint (SHA-256):** `d8ef7e28fecd0d08fa8f61c714ada054162668bb961008230bd4d342564af713`


# FluxProFillNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProFillNode

Complete documentation for the FluxProFillNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProFillNode/en.md)

Inpaints image based on mask and prompt. This node uses the Flux.1 model to fill in masked areas of an image according to the provided text description, generating new content that matches the surrounding image.

## Inputs

| Parameter           | Data Type | Required | Range                  | Description                                                                                                                                                                                                                     |
| ------------------- | --------- | -------- | ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`             | IMAGE     | Yes      | -                      | The input image to be inpainted                                                                                                                                                                                                 |
| `mask`              | MASK      | Yes      | -                      | The mask defining which areas of the image should be filled                                                                                                                                                                     |
| `prompt`            | STRING    | No       | -                      | Prompt for the image generation (default: empty string)                                                                                                                                                                         |
| `prompt_upsampling` | BOOLEAN   | No       | -                      | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: false) |
| `guidance`          | FLOAT     | No       | 1.5-100                | Guidance strength for the image generation process (default: 60)                                                                                                                                                                |
| `steps`             | INT       | No       | 15-50                  | Number of steps for the image generation process (default: 50)                                                                                                                                                                  |
| `seed`              | INT       | No       | 0-18446744073709551615 | The random seed used for creating the noise. (default: 0)                                                                                                                                                                       |

## Outputs

| Output Name    | Data Type | Description                                                              |
| -------------- | --------- | ------------------------------------------------------------------------ |
| `output_image` | IMAGE     | The generated image with the masked areas filled according to the prompt |

***

**Source fingerprint (SHA-256):** `68f9834a58d6e2d14743adafb1f791880f0af30fdb65cb6201af5616945bb56b`


# FluxProUltraImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FluxProUltraImageNode

Complete documentation for the FluxProUltraImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FluxProUltraImageNode/en.md)

Generates images using Flux Pro 1.1 Ultra via API based on prompt and resolution. This node connects to an external service to create images according to your text description and specified dimensions.

## Inputs

| Parameter               | Data Type | Required | Range                     | Description                                                                                                                                                                                                                     |
| ----------------------- | --------- | -------- | ------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`                | STRING    | Yes      | -                         | Prompt for the image generation (default: empty string)                                                                                                                                                                         |
| `prompt_upsampling`     | BOOLEAN   | No       | -                         | Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result). (default: False) |
| `seed`                  | INT       | No       | 0 to 18446744073709551615 | The random seed used for creating the noise. (default: 0)                                                                                                                                                                       |
| `aspect_ratio`          | STRING    | No       | -                         | Aspect ratio of image; must be between 1:4 and 4:1. (default: "16:9")                                                                                                                                                           |
| `raw`                   | BOOLEAN   | No       | -                         | When True, generate less processed, more natural-looking images. (default: False)                                                                                                                                               |
| `image_prompt`          | IMAGE     | No       | -                         | Optional reference image to guide generation                                                                                                                                                                                    |
| `image_prompt_strength` | FLOAT     | No       | 0.0 to 1.0                | Blend between the prompt and the image prompt. (default: 0.1)                                                                                                                                                                   |

**Note:** The `aspect_ratio` parameter must be between 1:4 and 4:1. When `image_prompt` is provided, `image_prompt_strength` becomes active and controls how much the reference image influences the final output. If `image_prompt` is not provided, the `prompt` parameter is validated to ensure it is not empty.

## Outputs

| Output Name    | Data Type | Description                                 |
| -------------- | --------- | ------------------------------------------- |
| `output_image` | IMAGE     | The generated image from Flux Pro 1.1 Ultra |

***

**Source fingerprint (SHA-256):** `9a0e3c676456da395845a2bd869abaaca30ed63ee3faf56449a2548fbab46b5c`


# GLSLShader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GLSLShader

Complete documentation for the GLSLShader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GLSLShader/en.md)

The **GLSL Shader** node lets you write custom fragment shaders in **GLSL ES 3.00** (WebGL 2.0 compatible) to process images directly on the GPU. You can create image effects like blurs, color grading, film grain, glow, and much more - all running at GPU speed.

<Note>
  The GLSL Shader node is currently marked as **experimental**, so the node may be updated and extended in future releases.
</Note>

## Minimal Shader

The simplest possible shader - a passthrough that outputs the input image unchanged:

```glsl theme={null}
#version 300 es
precision highp float;

uniform sampler2D u_image0;

in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;

void main() {
    fragColor0 = texture(u_image0, v_texCoord);
}
```

<Note>
  **Why GLSL ES 3.00?** Shaders need to run in two environments: the **browser** (via WebGL 2.0, which only supports GLSL ES 3.00) for live preview in the ComfyUI frontend, and the **Python backend** (via desktop OpenGL) when the workflow executes. GLSL ES 3.00 is the common denominator that works in both places.
</Note>

## Available Uniforms

These uniforms are automatically set by ComfyUI. You don't need to declare all of them - only declare the ones you use.

### Images

| Uniform                 | Type        | Description                                                                                                                                            |
| ----------------------- | ----------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `u_image0` – `u_image4` | `sampler2D` | Input images (up to 5). Sampled with `texture(u_image0, v_texCoord)`. Images are RGBA float textures with linear filtering and clamp-to-edge wrapping. |

### Floats

| Uniform                  | Type    | Description                                                                                |
| ------------------------ | ------- | ------------------------------------------------------------------------------------------ |
| `u_float0` – `u_float19` | `float` | Up to 20 user-controlled float values. Mapped from the **floats** input group on the node. |

### Integers

| Uniform              | Type  | Description                                                                                |
| -------------------- | ----- | ------------------------------------------------------------------------------------------ |
| `u_int0` – `u_int19` | `int` | Up to 20 user-controlled integer values. Mapped from the **ints** input group on the node. |

<Note>
  **Using int uniforms as dropdowns:** Int uniforms pair well with the **Custom Combo** node's index output - users pick an option from a dropdown and the shader receives the selected item's index.

  ```glsl theme={null}
  const int BLEND_SCREEN  = 0;
  const int BLEND_OVERLAY = 1;
  const int BLEND_MULTIPLY = 2;

  // ...

  if (u_int0 == BLEND_SCREEN) {
      // ...
  }
  ```
</Note>

### Booleans

| Uniform               | Type   | Description                                                                                 |
| --------------------- | ------ | ------------------------------------------------------------------------------------------- |
| `u_bool0` – `u_bool9` | `bool` | Up to 10 user-controlled boolean values. Mapped from the **bools** input group on the node. |

### Curves (1D LUTs)

| Uniform                 | Type        | Description                                                                                                                       |
| ----------------------- | ----------- | --------------------------------------------------------------------------------------------------------------------------------- |
| `u_curve0` – `u_curve3` | `sampler2D` | Up to 4 user-editable curve LUTs from the **curves** input group. Each curve is a 1D lookup table stored as a single-row texture. |

<Note>
  **Using curve uniforms:** Curves let users draw arbitrary tone-mapping graphs in the UI (e.g. for contrast, gamma, per-channel grading, or any custom `input → output` remap). Sample the curve using your input value as the X coordinate - remember to clamp it to `[0, 1]` first:

  ```glsl theme={null}
  float applyCurve(sampler2D curve, float value) {
      return texture(curve, vec2(clamp(value, 0.0, 1.0), 0.5)).r;
  }

  // Usage: remap each RGB channel through a master curve
  color.r = applyCurve(u_curve0, color.r);
  color.g = applyCurve(u_curve0, color.g);
  color.b = applyCurve(u_curve0, color.b);
  ```

  Common uses: master RGB curves, per-channel R/G/B curves, luminance-driven remaps, custom gamma, and any effect where you want the user to shape a response curve visually.
</Note>

### Resolution

| Uniform        | Type   | Description                                                                                                                                                                     |
| -------------- | ------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `u_resolution` | `vec2` | **Output** framebuffer dimensions in pixels (`width, height`). This is the size you're writing to, which may differ from any input image's size when `size_mode` is `"custom"`. |

<Note>
  **Computing texel size for sampling:** Don't use `1.0 / u_resolution` to step one pixel in an input texture. `u_resolution` is the *output* size, which may not match the input's size. Instead use `textureSize()` on the actual texture you're sampling:

  ```glsl theme={null}
  vec2 texel = 1.0 / vec2(textureSize(u_image0, 0));
  ```

  Use `u_resolution` only when you need the output framebuffer dimensions themselves (e.g. computing `gl_FragCoord.xy / u_resolution` to get screen-space UVs).
</Note>

### Multi-Pass

| Uniform  | Type  | Description                                                                                                                                                    |
| -------- | ----- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `u_pass` | `int` | Current pass index (0-based). Only meaningful when using `#pragma passes` - see [Multi-Pass Ping-Pong Rendering](#multi-pass-ping-pong-rendering) for details. |

### Vertex Shader Output

| Varying      | Type   | Description                                                                  |
| ------------ | ------ | ---------------------------------------------------------------------------- |
| `v_texCoord` | `vec2` | Texture coordinates ranging from (0,0) at bottom-left to (1,1) at top-right. |

## Multiple Outputs (MRT)

The node supports up to **4 simultaneous outputs** using Multiple Render Targets. Declare additional outputs with explicit locations:

```glsl theme={null}
#version 300 es
precision highp float;

uniform sampler2D u_image0;

in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;
layout(location = 1) out vec4 fragColor1;
layout(location = 2) out vec4 fragColor2;
layout(location = 3) out vec4 fragColor3;

void main() {
    vec4 color = texture(u_image0, v_texCoord);
    fragColor0 = vec4(vec3(color.r), 1.0);  // Red channel
    fragColor1 = vec4(vec3(color.g), 1.0);  // Green channel
    fragColor2 = vec4(vec3(color.b), 1.0);  // Blue channel
    fragColor3 = vec4(vec3(color.a), 1.0);  // Alpha channel
}
```

Each `fragColor` maps to the corresponding `IMAGE` output on the node. ComfyUI auto-detects which outputs you use - unused outputs will be black.

## Multi-Pass Ping-Pong Rendering

Some effects (like separable blur) need multiple passes over the image. Use the `#pragma passes N` directive to enable this:

```glsl theme={null}
#version 300 es
#pragma passes 2
precision highp float;

uniform sampler2D u_image0;
uniform float u_float0;  // Blur radius
uniform int u_pass;

in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;

void main() {
    vec2 texel = 1.0 / vec2(textureSize(u_image0, 0));
    int radius = int(ceil(u_float0));

    // Pass 0 = horizontal blur, Pass 1 = vertical blur
    vec2 dir = (u_pass == 0) ? vec2(1.0, 0.0) : vec2(0.0, 1.0);

    vec4 color = vec4(0.0);
    float total = 0.0;

    for (int i = -radius; i <= radius; i++) {
        vec2 offset = dir * float(i) * texel;
        float w = 1.0;  // box blur weight
        color += texture(u_image0, v_texCoord + offset) * w;
        total += w;
    }

    fragColor0 = color / total;
}
```

### How ping-pong works

1. **Pass 0**: Reads from the original `u_image0` input, writes to an internal ping-pong texture.
2. **Pass 1–N**: Reads from the *previous pass output* via `u_image0` (the binding is swapped automatically), writes to the other ping-pong texture.
3. **Final pass**: Writes to the actual output framebuffer (`fragColor0`).

<Note>
  When using multi-pass with MRT (multiple outputs), only the first output (`fragColor0`) participates in ping-pong. The final pass writes all outputs.
</Note>

## Examples

### Grayscale Conversion

```glsl theme={null}
#version 300 es
precision highp float;

uniform sampler2D u_image0;
in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;

void main() {
    vec4 color = texture(u_image0, v_texCoord);
    float gray = dot(color.rgb, vec3(0.2126, 0.7152, 0.0722));
    fragColor0 = vec4(vec3(gray), color.a);
}
```

### Image Blending

Blend two input images using a float parameter as the mix factor:

```glsl theme={null}
#version 300 es
precision highp float;

uniform sampler2D u_image0;
uniform sampler2D u_image1;
uniform float u_float0;  // mix factor [0.0 – 1.0]

in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;

void main() {
    vec4 a = texture(u_image0, v_texCoord);
    vec4 b = texture(u_image1, v_texCoord);
    fragColor0 = mix(a, b, clamp(u_float0, 0.0, 1.0));
}
```

## Using an LLM to Generate Shaders

You can use any LLM (Claude, ChatGPT, etc.) to write GLSL shaders for you. Copy the following prompt and fill in your desired effect:

````markdown theme={null}
Write a GLSL ES 3.00 fragment shader for ComfyUI's GLSLShader node.

**Effect I want:** [DESCRIBE YOUR DESIRED EFFECT HERE]

**Requirements:**
- Must start with `#version 300 es`
- Use `precision highp float;`
- The vertex shader provides `in vec2 v_texCoord` (0–1 UV coordinates, bottom-left origin)
- Output to `layout(location = 0) out vec4 fragColor0` (RGBA)
- Additional outputs available: `fragColor1`, `fragColor2`, `fragColor3` at locations 1–3

**Template to follow (minimal passthrough shader - use this exact structure):**

```glsl
#version 300 es
precision highp float;

uniform sampler2D u_image0;

in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;

void main() {
    fragColor0 = texture(u_image0, v_texCoord);
}
```

**Available uniforms (declare only what you use):**
- `uniform sampler2D u_image0;` through `u_image4` - up to 5 input images (RGBA float, linear filtering, clamp-to-edge)
- `uniform vec2 u_resolution;` - **output framebuffer** width and height in pixels. This is NOT the input texture size (they can differ when the user sets a custom output size). **To step one pixel in an input texture, use `vec2 texel = 1.0 / vec2(textureSize(u_image0, 0));` - do NOT use `1.0 / u_resolution` for this.**
- `uniform float u_float0;` through `u_float19;` - up to 20 user-controlled float parameters
- `uniform int u_int0;` through `u_int19;` - up to 20 user-controlled integer parameters. Tip: int uniforms can be wired from a **Custom Combo** node's index output, so users select from a dropdown and the shader receives the index. Use this for mode selection (e.g. blend mode, blur type). Define named constants for each option and branch on those - do NOT compare against raw integer literals. For example: `const int BLUR_GAUSSIAN = 0; const int BLUR_BOX = 1; ... if (u_int0 == BLUR_GAUSSIAN) { ... }`.
- `uniform bool u_bool0;` through `u_bool9;` - up to 10 user-controlled boolean parameters (use for feature toggles)
- `uniform sampler2D u_curve0;` through `u_curve3;` - up to 4 user-editable 1D LUT curves. Sample with `texture(u_curve0, vec2(clamp(x, 0.0, 1.0), 0.5)).r` where `x` is 0–1. Use for tone curves, remapping, etc.
- `uniform int u_pass;` - current pass index (when using multi-pass)

**Multi-pass rendering:**
- Add `#pragma passes N` on the second line to enable N passes
- On pass 0, `u_image0` is the original input; on subsequent passes it contains the previous pass output
- Use `u_pass` to vary behavior per pass (e.g., horizontal vs. vertical blur)

**Important constraints:**
- GLSL ES 3.00 only - no GLSL 1.x `varying`/`attribute`, no `gl_FragColor`
- No `#include`, no external textures, no custom vertex shader
- Document each uniform with a comment showing its purpose and expected range
````

### Example prompt fill-in

> **Effect I want:** A chromatic aberration effect that splits RGB channels outward from the center of the image. u\_float0 controls the strength of the offset (0 = no effect, 10 = extremely strong). The offset should scale with distance from the center.

***

**Source fingerprint (SHA-256):** `ded589d5b0cb5413ecc42c7177e3076427ceac1d3218a20cfec6f2e005fe7e27`


# GeminiImage2Node - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiImage2Node

Complete documentation for the GeminiImage2Node node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiImage2Node/en.md)

The GeminiImage2Node generates or edits images using Google's Vertex AI Gemini model. It sends a text prompt and optional reference images or files to the API and returns the generated image and/or a text description.

## Inputs

| Parameter             | Data Type | Required | Range                                                                                                                                         | Description                                                                                                                                                                                                                                              |
| --------------------- | --------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`              | STRING    | Yes      | N/A                                                                                                                                           | Text prompt describing the image to generate or the edits to apply. Include any constraints, styles, or details the model should follow.                                                                                                                 |
| `model`               | COMBO     | Yes      | `"gemini-3-pro-image-preview"`<br />`"Nano Banana 2 (Gemini 3.1 Flash Image)"`                                                                | The specific Gemini model to use for generation. The "Nano Banana 2" option maps to the `gemini-3.1-flash-image-preview` model internally.                                                                                                               |
| `seed`                | INT       | Yes      | 0 to 18446744073709551615                                                                                                                     | When fixed to a specific value, the model makes a best effort to provide the same response for repeated requests. Deterministic output isn't guaranteed. Changing the model or other settings can cause variations even with the same seed. Default: 42. |
| `aspect_ratio`        | COMBO     | Yes      | `"auto"`<br />`"1:1"`<br />`"2:3"`<br />`"3:2"`<br />`"3:4"`<br />`"4:3"`<br />`"4:5"`<br />`"5:4"`<br />`"9:16"`<br />`"16:9"`<br />`"21:9"` | The desired aspect ratio for the output image. If set to 'auto', it matches your input image's aspect ratio; if no image is provided, a 16:9 square is usually generated. Default: "auto".                                                               |
| `resolution`          | COMBO     | Yes      | `"1K"`<br />`"2K"`<br />`"4K"`                                                                                                                | Target output resolution. For 2K/4K the native Gemini upscaler is used.                                                                                                                                                                                  |
| `response_modalities` | COMBO     | Yes      | `"IMAGE+TEXT"`<br />`"IMAGE"`                                                                                                                 | Choose 'IMAGE' for image-only output, or 'IMAGE+TEXT' to return both the generated image and a text response.                                                                                                                                            |
| `images`              | IMAGE     | No       | N/A                                                                                                                                           | Optional reference image(s). To include multiple images, use the Batch Images node (up to 14).                                                                                                                                                           |
| `files`               | CUSTOM    | No       | N/A                                                                                                                                           | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Generate Content Input Files node.                                                                                                                                      |
| `system_prompt`       | STRING    | No       | N/A                                                                                                                                           | Foundational instructions that dictate an AI's behavior. Default: A pre-defined system prompt for image generation.                                                                                                                                      |

**Constraints:**

* The `images` input supports a maximum of 14 images. If more are provided, an error will be raised.
* The `files` input must be connected to a node that outputs the `GEMINI_INPUT_FILES` data type.

## Outputs

| Output Name | Data Type | Description                                                                                             |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------- |
| `image`     | IMAGE     | The image generated or edited by the Gemini model.                                                      |
| `string`    | STRING    | The text response from the model. This output will be empty if `response_modalities` is set to "IMAGE". |

***

**Source fingerprint (SHA-256):** `5814a952815288c0b4b5962f646c69b0e618bfb9ab92b31ba60eab313c68a01c`


# GeminiImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiImageNode

Complete documentation for the GeminiImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiImage/en.md)

The GeminiImage node generates text and image responses from Google's Gemini AI models. It allows you to provide multimodal inputs including text prompts, images, and files to create coherent text and image outputs. The node handles all API communication and response parsing with the latest Gemini models.

## Inputs

| Parameter | Data Type            | Input Type | Default                             | Range                                                                     | Description                                                                                                                                                                                                                                                                                                                                                   |
| --------- | -------------------- | ---------- | ----------------------------------- | ------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`  | STRING               | required   | ""                                  | -                                                                         | Text prompt for generation                                                                                                                                                                                                                                                                                                                                    |
| `model`   | COMBO                | required   | gemini\_2\_5\_flash\_image\_preview | Available Gemini models<br />Options extracted from GeminiImageModel enum | The Gemini model to use for generating responses                                                                                                                                                                                                                                                                                                              |
| `seed`    | INT                  | required   | 42                                  | 0 to 18446744073709551615                                                 | When seed is fixed to a specific value, the model makes a best effort to provide the same response for repeated requests. Deterministic output isn't guaranteed. Also, changing the model or parameter settings, such as the temperature, can cause variations in the response even when you use the same seed value. By default, a random seed value is used |
| `images`  | IMAGE                | optional   | None                                | -                                                                         | Optional image(s) to use as context for the model. To include multiple images, you can use the Batch Images node                                                                                                                                                                                                                                              |
| `files`   | GEMINI\_INPUT\_FILES | optional   | None                                | -                                                                         | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Generate Content Input Files node                                                                                                                                                                                                                                            |

*Note: The node includes hidden parameters (`auth_token`, `comfy_api_key`, `unique_id`) that are automatically handled by the system and do not require user input.*

## Outputs

| Output Name | Data Type | Description                                        |
| ----------- | --------- | -------------------------------------------------- |
| `IMAGE`     | IMAGE     | The generated image response from the Gemini model |
| `STRING`    | STRING    | The generated text response from the Gemini model  |


# GeminiNanoBanana2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiNanoBanana2

Complete documentation for the GeminiNanoBanana2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiNanoBanana2/en.md)

The GeminiNanoBanana2 node generates or edits images using Google's Vertex AI Gemini model. It works by sending a text prompt, along with optional reference images or files, to the API and returns the generated image and any accompanying text.

## Inputs

| Parameter             | Data Type | Required | Range                                                                                                                                         | Description                                                                                                                                                                                                                                                                                                                                                                      |
| --------------------- | --------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`              | STRING    | Yes      | N/A                                                                                                                                           | Text prompt describing the image to generate or the edits to apply. Include any constraints, styles, or details the model should follow.                                                                                                                                                                                                                                         |
| `model`               | COMBO     | Yes      | `"Nano Banana 2 (Gemini 3.1 Flash Image)"`                                                                                                    | The specific Gemini model to use for image generation.                                                                                                                                                                                                                                                                                                                           |
| `seed`                | INT       | Yes      | 0 to 18446744073709551615                                                                                                                     | When the seed is fixed to a specific value, the model makes a best effort to provide the same response for repeated requests. Deterministic output isn't guaranteed. Also, changing the model or parameter settings, such as the temperature, can cause variations in the response even when you use the same seed value. By default, a random seed value is used. (default: 42) |
| `aspect_ratio`        | COMBO     | Yes      | `"auto"`<br />`"1:1"`<br />`"2:3"`<br />`"3:2"`<br />`"3:4"`<br />`"4:3"`<br />`"4:5"`<br />`"5:4"`<br />`"9:16"`<br />`"16:9"`<br />`"21:9"` | If set to 'auto', matches your input image's aspect ratio; if no image is provided, a 16:9 square is usually generated. (default: "auto")                                                                                                                                                                                                                                        |
| `resolution`          | COMBO     | Yes      | `"1K"`<br />`"2K"`<br />`"4K"`                                                                                                                | Target output resolution. For 2K/4K the native Gemini upscaler is used.                                                                                                                                                                                                                                                                                                          |
| `response_modalities` | COMBO     | Yes      | `"IMAGE"`<br />`"IMAGE+TEXT"`                                                                                                                 | Determines the type of content the model will return. (advanced)                                                                                                                                                                                                                                                                                                                 |
| `thinking_level`      | COMBO     | Yes      | `"MINIMAL"`<br />`"HIGH"`                                                                                                                     | Controls the depth of the model's reasoning process.                                                                                                                                                                                                                                                                                                                             |
| `images`              | IMAGE     | No       | N/A                                                                                                                                           | Optional reference image(s). To include multiple images, use the Batch Images node (up to 14).                                                                                                                                                                                                                                                                                   |
| `files`               | CUSTOM    | No       | N/A                                                                                                                                           | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Generate Content Input Files node.                                                                                                                                                                                                                                                              |
| `system_prompt`       | STRING    | No       | N/A                                                                                                                                           | Foundational instructions that dictate an AI's behavior. (advanced)                                                                                                                                                                                                                                                                                                              |

**Note:** The `images` input supports a maximum of 14 images. If more are provided, the node will raise an error.

## Outputs

| Output Name     | Data Type | Description                                                                                                      |
| --------------- | --------- | ---------------------------------------------------------------------------------------------------------------- |
| `image`         | IMAGE     | The primary image generated or edited by the model.                                                              |
| `string`        | STRING    | Any text content returned by the model.                                                                          |
| `thought_image` | IMAGE     | First image from the model's thinking process. Only available with thinking\_level HIGH and IMAGE+TEXT modality. |

***

**Source fingerprint (SHA-256):** `6dae505011e2860cbf2ec6ccb5a32949d5daa3fe3546e85181050fd9ac92b9e5`


# GeminiNanoBanana2V2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiNanoBanana2V2

Complete documentation for the GeminiNanoBanana2V2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiNanoBanana2V2/en.md)

## Overview

This node generates or edits images by sending a text prompt to Google's Vertex AI API. It uses a specific Gemini model to create new images or modify existing ones based on your instructions.

## Inputs

| Parameter             | Data Type | Required | Range                                      | Description                                                                                                                                                                                                                                                                                                                                                                      |
| --------------------- | --------- | -------- | ------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`              | STRING    | Yes      | N/A                                        | Text prompt describing the image to generate or the edits to apply. Include any constraints, styles, or details the model should follow.                                                                                                                                                                                                                                         |
| `model`               | COMBO     | Yes      | `"Nano Banana 2 (Gemini 3.1 Flash Image)"` | Selects the Gemini model to use for image generation. Currently only one option is available. This parameter includes additional sub-parameters for resolution, aspect ratio, thinking level, and image input.                                                                                                                                                                   |
| `seed`                | INT       | Yes      | 0 to 18446744073709551615                  | When the seed is fixed to a specific value, the model makes a best effort to provide the same response for repeated requests. Deterministic output isn't guaranteed. Also, changing the model or parameter settings, such as the temperature, can cause variations in the response even when you use the same seed value. By default, a random seed value is used. (default: 42) |
| `response_modalities` | COMBO     | Yes      | `"IMAGE"`<br />`"IMAGE+TEXT"`              | Determines the format of the response. Choose "IMAGE" to receive only an image, or "IMAGE+TEXT" to receive both an image and a text description. (default: "IMAGE")                                                                                                                                                                                                              |
| `system_prompt`       | STRING    | No       | N/A                                        | Foundational instructions that dictate an AI's behavior. This is an advanced parameter. (default: A pre-defined system prompt instructing the model to always produce an image)                                                                                                                                                                                                  |

**Note on `model` parameter:** The `model` parameter is a dynamic combo that includes additional sub-parameters for resolution, aspect ratio, thinking level, and image input. These sub-parameters are defined within the model selection and are not listed as separate inputs in this table.

**Note on image input:** You can provide up to 14 images as input to the model. These images are passed through the `model` parameter's image sub-field and are used for editing or as visual context for generation.

## Outputs

| Output Name     | Data Type | Description                                                                                                      |
| --------------- | --------- | ---------------------------------------------------------------------------------------------------------------- |
| `IMAGE`         | IMAGE     | The generated or edited image.                                                                                   |
| `STRING`        | STRING    | A text description or caption generated by the model.                                                            |
| `thought_image` | IMAGE     | First image from the model's thinking process. Only available with thinking\_level HIGH and IMAGE+TEXT modality. |

***

**Source fingerprint (SHA-256):** `0b9af4e937874f2e192f3dc0b67f8e769b37d6595fbddb7a326b1f13e3e444d3`


# GrokImageEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokImageEditNode

Complete documentation for the GrokImageEditNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokImageEditNode/en.md)

The Grok Image Edit node modifies an existing image based on a text prompt. It uses the Grok API to generate one or more new images that are variations of the input, guided by your description.

## Inputs

| Parameter          | Data Type | Required | Range                                                                                                                                                                                       | Description                                                                                                                                                                                  |
| ------------------ | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`            | COMBO     | Yes      | `"grok-imagine-image-quality"`<br />`"grok-imagine-image-pro"`<br />`"grok-imagine-image"`<br />`"grok-imagine-image-beta"`                                                                 | The specific AI model to use for image editing.                                                                                                                                              |
| `image`            | IMAGE     | Yes      |                                                                                                                                                                                             | The input image(s) to be edited. Supports up to 3 input images, except for the "pro" model which supports only 1.                                                                            |
| `prompt`           | STRING    | Yes      |                                                                                                                                                                                             | The text prompt used to generate the edited image. Must be at least 1 character after stripping whitespace.                                                                                  |
| `resolution`       | COMBO     | Yes      | `"1K"`<br />`"2K"`                                                                                                                                                                          | The resolution for the output image.                                                                                                                                                         |
| `number_of_images` | INT       | No       | 1 to 10                                                                                                                                                                                     | Number of edited images to generate (default: 1).                                                                                                                                            |
| `seed`             | INT       | No       | 0 to 2147483647                                                                                                                                                                             | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0).                                                                                |
| `aspect_ratio`     | COMBO     | No       | `"auto"`<br />`"1:1"`<br />`"2:3"`<br />`"3:2"`<br />`"3:4"`<br />`"4:3"`<br />`"9:16"`<br />`"16:9"`<br />`"9:19.5"`<br />`"19.5:9"`<br />`"9:20"`<br />`"20:9"`<br />`"1:2"`<br />`"2:1"` | The aspect ratio for the output image. Only allowed when multiple images are connected to the image input. If set to "auto", the aspect ratio is determined automatically (default: "auto"). |

**Important constraints:**

* The `image` input supports up to 3 images, except when using the `grok-imagine-image-pro` model, which supports only 1 input image.
* The `aspect_ratio` parameter can only be set to a custom value (not "auto") when multiple images are connected to the `image` input. Setting a custom aspect ratio with a single input image will cause an error.

## Outputs

| Output Name | Data Type | Description                                                                                                                    |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------ |
| `output`    | IMAGE     | The edited image(s) generated by the node. If `number_of_images` is greater than 1, the outputs are concatenated into a batch. |

***

**Source fingerprint (SHA-256):** `31cfe7ad382033f69330ed4de1ec831ccc25156498563e1541368e2662ed3ddb`


# GrokImageEditNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokImageEditNodeV2

Complete documentation for the GrokImageEditNodeV2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokImageEditNodeV2/en.md)

## Overview

Modify an existing image based on a text prompt. This node sends your images and a text description to the Grok API, which edits the images according to your instructions and returns the result.

## Inputs

| Parameter | Data Type | Required | Range           | Description                                                                                                                                                                                                                                                               |
| --------- | --------- | -------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`  | STRING    | Yes      | N/A             | The text prompt used to generate the image. Must be at least 1 character long after stripping whitespace.                                                                                                                                                                 |
| `model`   | MODEL     | Yes      | See Description | The Grok image model to use. This parameter has multiple sub-options that appear after selecting a model. Available models: `grok-imagine-image-quality`<br />`grok-imagine-image-pro`<br />`grok-imagine-image`. Each model has different capabilities (see note below). |
| `seed`    | INT       | Yes      | 0 to 2147483647 | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed. (default: 0)                                                                                                                                                             |

**Note on `model` parameter constraints:**

* The `model` parameter is a dynamic combo that includes sub-options for `resolution`, `number_of_images`, `images`, and `aspect_ratio`.
* **`grok-imagine-image-quality`**: Supports up to 3 input images and allows custom aspect ratio.
* **`grok-imagine-image-pro`**: Supports only 1 input image and does not allow custom aspect ratio.
* **`grok-imagine-image`**: Supports up to 3 input images and allows custom aspect ratio.
* **At least one input image is required** for editing. The node will raise an error if no images are provided.
* **Custom aspect ratio** (`aspect_ratio` sub-option) is only allowed when multiple images are connected to the image input. If only one image is provided, aspect ratio must be set to "auto".

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `IMAGE`     | IMAGE     | The edited image(s) returned by the Grok API. If a single image is generated, it is returned directly. If multiple images are generated, they are concatenated into a single batch tensor. |

***

**Source fingerprint (SHA-256):** `90ace53f5f2e40da315d4940fa801d84950de6db2d8ed1cf9d715d88a2b1ebf0`


# GrokImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokImageNode

Complete documentation for the GrokImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokImageNode/en.md)

The Grok Image node generates one or more images based on a text description using the Grok AI model. It sends your prompt to an external service and returns the generated images as tensors that can be used in your workflow.

## Inputs

| Parameter          | Data Type | Required | Range                                                                                                                                                                         | Description                                                                                                                                            |
| ------------------ | --------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `model`            | COMBO     | Yes      | `"grok-imagine-image-quality"`<br />`"grok-imagine-image-pro"`<br />`"grok-imagine-image"`<br />`"grok-imagine-image-beta"`                                                   | The specific Grok model to use for image generation. Different models may offer varying quality, speed, or features.                                   |
| `prompt`           | STRING    | Yes      | N/A                                                                                                                                                                           | The text prompt used to generate the image. This description guides the AI on what to create. Must be at least 1 character long.                       |
| `aspect_ratio`     | COMBO     | Yes      | `"1:1"`<br />`"2:3"`<br />`"3:2"`<br />`"3:4"`<br />`"4:3"`<br />`"9:16"`<br />`"16:9"`<br />`"9:19.5"`<br />`"19.5:9"`<br />`"9:20"`<br />`"20:9"`<br />`"1:2"`<br />`"2:1"` | The desired width-to-height ratio for the generated image.                                                                                             |
| `number_of_images` | INT       | No       | 1 to 10                                                                                                                                                                       | Number of images to generate (default: 1).                                                                                                             |
| `seed`             | INT       | No       | 0 to 2147483647                                                                                                                                                               | A seed value to determine if the node should re-run. The actual image results are nondeterministic and will vary even with the same seed (default: 0). |
| `resolution`       | COMBO     | No       | `"1K"`<br />`"2K"`                                                                                                                                                            | The desired output resolution for the generated images (default: "1K").                                                                                |

**Note:** The `seed` parameter is primarily used to control when the node re-executes within a workflow. Due to the nature of the external AI service, the generated images will not be reproducible or identical across runs, even with an identical seed.

**Note on pricing:** The cost of generating images depends on the selected `model`, `resolution`, and `number_of_images`. For example, the "grok-imagine-image-quality" model with "1K" resolution costs $0.05 per image, while "2K" resolution costs $0.07 per image. The "grok-imagine-image-pro" model costs $0.07 per image, and other models cost $0.02 per image.

## Outputs

| Output Name | Data Type | Description                                                                                                                                                       |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `output`    | IMAGE     | The generated image or a batch of images. If `number_of_images` is 1, a single image tensor is returned. If greater than 1, a batch of image tensors is returned. |

***

**Source fingerprint (SHA-256):** `f4af858c6b94fd74be1856849417609f3d45fc0f139e8f2e56cdabb6e3521076`


# HitPawGeneralImageEnhance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HitPawGeneralImageEnhance

Complete documentation for the HitPawGeneralImageEnhance node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HitPawGeneralImageEnhance/en.md)

This node enhances low-resolution images by upscaling them to super-resolution, removing artifacts and noise. It uses an external API to process the image and can automatically adjust the input size to stay within processing limits. The maximum allowed output size is 32 megapixels.

## Inputs

| Parameter        | Data Type | Required | Range                                       | Description                                                                                                                                                                                                                           |
| ---------------- | --------- | -------- | ------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`          | STRING    | Yes      | `"generative_portrait"`<br />`"generative"` | The enhancement model to use. The `generative_portrait` model is optimized for portraits, while `generative` is a general-purpose model.                                                                                              |
| `image`          | IMAGE     | Yes      | -                                           | The input image to be enhanced.                                                                                                                                                                                                       |
| `upscale_factor` | INT       | Yes      | `1`<br />`2`<br />`4`                       | The factor by which to upscale the image's dimensions. A factor of 1 means no upscaling, 2 doubles the dimensions, and 4 quadruples them.                                                                                             |
| `auto_downscale` | BOOLEAN   | No       | -                                           | Automatically downscale input image if output would exceed the limit. When enabled, the node will attempt to reduce the input image size or reduce the upscale factor to fit within the 32 megapixel output limit. (default: `False`) |

**Note:** The node will raise an error if the calculated output size (input height × upscale\_factor × input width × upscale\_factor) exceeds 32,000,000 pixels (32MP) and `auto_downscale` is disabled. When `auto_downscale` is enabled, the node will attempt to downscale the input image to fit within the limit before applying the requested upscale factor. If downscaling by more than 2x would be required, the node will instead reduce the upscale factor.

## Outputs

| Output Name | Data Type | Description                             |
| ----------- | --------- | --------------------------------------- |
| `image`     | IMAGE     | The enhanced and upscaled output image. |

***

**Source fingerprint (SHA-256):** `1cb59c04e517b6ecce3a4cb809d3cad26bb7a0fe6d16ddf72b9729e186e25d53`


# IdeogramV1 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/IdeogramV1

Complete documentation for the IdeogramV1 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/IdeogramV1/en.md)

The IdeogramV1 node generates images using the Ideogram V1 model through an API. It takes text prompts and various generation settings to create one or more images based on your input. The node supports different aspect ratios and generation modes to customize the output.

## Inputs

| Parameter             | Data Type | Required | Range                                                                                                                 | Description                                                                               |
| --------------------- | --------- | -------- | --------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------- |
| `prompt`              | STRING    | Yes      | -                                                                                                                     | Prompt for the image generation (default: empty)                                          |
| `turbo`               | BOOLEAN   | Yes      | -                                                                                                                     | Whether to use turbo mode (faster generation, potentially lower quality) (default: False) |
| `aspect_ratio`        | COMBO     | No       | "1:1"<br />"4:3"<br />"3:4"<br />"16:9"<br />"9:16"<br />"2:1"<br />"1:2"<br />"3:2"<br />"2:3"<br />"4:5"<br />"5:4" | The aspect ratio for image generation (default: "1:1")                                    |
| `magic_prompt_option` | COMBO     | No       | "AUTO"<br />"ON"<br />"OFF"                                                                                           | Determine if MagicPrompt should be used in generation (default: "AUTO")                   |
| `seed`                | INT       | No       | 0-2147483647                                                                                                          | Random seed value for generation (default: 0)                                             |
| `negative_prompt`     | STRING    | No       | -                                                                                                                     | Description of what to exclude from the image (default: empty)                            |
| `num_images`          | INT       | No       | 1-8                                                                                                                   | Number of images to generate (default: 1)                                                 |

**Note:** The `num_images` parameter has a maximum limit of 8 images per generation request.

## Outputs

| Output Name | Data Type | Description                                       |
| ----------- | --------- | ------------------------------------------------- |
| `output`    | IMAGE     | The generated image(s) from the Ideogram V1 model |

***

**Source fingerprint (SHA-256):** `a42654aea292811c5f872911d6ea7303a83ea058c7132737375d81c5c8a77740`


# IdeogramV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/IdeogramV2

Complete documentation for the IdeogramV2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/IdeogramV2/en.md)

The Ideogram V2 node generates images using the Ideogram V2 AI model. It takes text prompts and various generation settings to create images through an API service. The node supports different aspect ratios, resolutions, and style options to customize the output images.

## Inputs

| Parameter             | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           | Description                                                                                                          |
| --------------------- | --------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------- |
| `prompt`              | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | Prompt for the image generation (default: empty string)                                                              |
| `turbo`               | BOOLEAN   | No       | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | Whether to use turbo mode (faster generation, potentially lower quality) (default: False)                            |
| `aspect_ratio`        | COMBO     | No       | "1:1"<br />"4:3"<br />"3:4"<br />"16:9"<br />"9:16"<br />"2:1"<br />"1:2"<br />"3:2"<br />"2:3"<br />"4:5"<br />"5:4"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           | The aspect ratio for image generation. Ignored if resolution is not set to AUTO. (default: "1:1")                    |
| `resolution`          | COMBO     | No       | "Auto"<br />"512 x 1536"<br />"576 x 1408"<br />"576 x 1472"<br />"576 x 1536"<br />"640 x 1024"<br />"640 x 1344"<br />"640 x 1408"<br />"640 x 1472"<br />"640 x 1536"<br />"704 x 1152"<br />"704 x 1216"<br />"704 x 1280"<br />"704 x 1344"<br />"704 x 1408"<br />"704 x 1472"<br />"720 x 1280"<br />"736 x 1312"<br />"768 x 1024"<br />"768 x 1088"<br />"768 x 1152"<br />"768 x 1216"<br />"768 x 1232"<br />"768 x 1280"<br />"768 x 1344"<br />"832 x 960"<br />"832 x 1024"<br />"832 x 1088"<br />"832 x 1152"<br />"832 x 1216"<br />"832 x 1248"<br />"864 x 1152"<br />"896 x 960"<br />"896 x 1024"<br />"896 x 1088"<br />"896 x 1120"<br />"896 x 1152"<br />"960 x 832"<br />"960 x 896"<br />"960 x 1024"<br />"960 x 1088"<br />"1024 x 640"<br />"1024 x 768"<br />"1024 x 832"<br />"1024 x 896"<br />"1024 x 960"<br />"1024 x 1024"<br />"1088 x 768"<br />"1088 x 832"<br />"1088 x 896"<br />"1088 x 960"<br />"1120 x 896"<br />"1152 x 704"<br />"1152 x 768"<br />"1152 x 832"<br />"1152 x 864"<br />"1152 x 896"<br />"1216 x 704"<br />"1216 x 768"<br />"1216 x 832"<br />"1232 x 768"<br />"1248 x 832"<br />"1280 x 704"<br />"1280 x 720"<br />"1280 x 768"<br />"1280 x 800"<br />"1312 x 736"<br />"1344 x 640"<br />"1344 x 704"<br />"1344 x 768"<br />"1408 x 576"<br />"1408 x 640"<br />"1408 x 704"<br />"1472 x 576"<br />"1472 x 640"<br />"1472 x 704"<br />"1536 x 512"<br />"1536 x 576"<br />"1536 x 640" | The resolution for image generation. If not set to AUTO, this overrides the aspect\_ratio setting. (default: "Auto") |
| `magic_prompt_option` | COMBO     | No       | "AUTO"<br />"ON"<br />"OFF"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     | Determine if MagicPrompt should be used in generation (default: "AUTO")                                              |
| `seed`                | INT       | No       | 0-2147483647                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    | Random seed for generation (default: 0)                                                                              |
| `style_type`          | COMBO     | No       | "AUTO"<br />"GENERAL"<br />"REALISTIC"<br />"DESIGN"<br />"RENDER\_3D"<br />"ANIME"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             | Style type for generation (V2 only) (default: "NONE")                                                                |
| `negative_prompt`     | STRING    | No       | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | Description of what to exclude from the image (default: empty string)                                                |
| `num_images`          | INT       | No       | 1-8                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             | Number of images to generate (default: 1)                                                                            |

**Note:** When `resolution` is not set to "Auto", it overrides the `aspect_ratio` setting. The `num_images` parameter has a maximum limit of 8 images per generation.

## Outputs

| Output Name | Data Type | Description                                       |
| ----------- | --------- | ------------------------------------------------- |
| `output`    | IMAGE     | The generated image(s) from the Ideogram V2 model |

***

**Source fingerprint (SHA-256):** `6d1f0d536756252434a1a831cd96228ee2386bfcaa60555acfe4bab7d16b61e3`


# IdeogramV3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/IdeogramV3

Complete documentation for the IdeogramV3 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/IdeogramV3/en.md)

The Ideogram V3 node generates images using the Ideogram V3 model. It supports both regular image generation from text prompts and image editing when both an image and mask are provided. The node offers various controls for aspect ratio, resolution, generation speed, and optional character reference images.

## Inputs

| Parameter             | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | Description                                                                                                         |
| --------------------- | --------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------- |
| `prompt`              | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   | Prompt for the image generation or editing (default: empty)                                                         |
| `image`               | IMAGE     | No       | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   | Optional reference image for image editing                                                                          |
| `mask`                | MASK      | No       | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   | Optional mask for inpainting (white areas will be replaced)                                                         |
| `aspect_ratio`        | COMBO     | No       | "1:1"<br />"1:3"<br />"3:1"<br />"1:2"<br />"2:1"<br />"9:16"<br />"16:9"<br />"10:16"<br />"16:10"<br />"2:3"<br />"3:2"<br />"3:4"<br />"4:3"<br />"4:5"<br />"5:4"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | The aspect ratio for image generation. Ignored if resolution is not set to Auto (default: "1:1")                    |
| `resolution`          | COMBO     | No       | "Auto"<br />"512x1536"<br />"576x1408"<br />"576x1472"<br />"576x1536"<br />"640x1344"<br />"640x1408"<br />"640x1472"<br />"640x1536"<br />"704x1152"<br />"704x1216"<br />"704x1280"<br />"704x1344"<br />"704x1408"<br />"704x1472"<br />"736x1312"<br />"768x1088"<br />"768x1216"<br />"768x1280"<br />"768x1344"<br />"800x1280"<br />"832x960"<br />"832x1024"<br />"832x1088"<br />"832x1152"<br />"832x1216"<br />"832x1248"<br />"864x1152"<br />"896x960"<br />"896x1024"<br />"896x1088"<br />"896x1120"<br />"896x1152"<br />"960x832"<br />"960x896"<br />"960x1024"<br />"960x1088"<br />"1024x832"<br />"1024x896"<br />"1024x960"<br />"1024x1024"<br />"1088x768"<br />"1088x832"<br />"1088x896"<br />"1088x960"<br />"1120x896"<br />"1152x704"<br />"1152x832"<br />"1152x864"<br />"1152x896"<br />"1216x704"<br />"1216x768"<br />"1216x832"<br />"1248x832"<br />"1280x704"<br />"1280x768"<br />"1280x800"<br />"1312x736"<br />"1344x640"<br />"1344x704"<br />"1344x768"<br />"1408x576"<br />"1408x640"<br />"1408x704"<br />"1472x576"<br />"1472x640"<br />"1472x704"<br />"1536x512"<br />"1536x576"<br />"1536x640" | The resolution for image generation. If not set to Auto, this overrides the aspect\_ratio setting (default: "Auto") |
| `magic_prompt_option` | COMBO     | No       | "AUTO"<br />"ON"<br />"OFF"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         | Determine if MagicPrompt should be used in generation (default: "AUTO")                                             |
| `seed`                | INT       | No       | 0-2147483647                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        | Random seed for generation (default: 0)                                                                             |
| `num_images`          | INT       | No       | 1-8                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | Number of images to generate (default: 1)                                                                           |
| `rendering_speed`     | COMBO     | No       | "DEFAULT"<br />"TURBO"<br />"QUALITY"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | Controls the trade-off between generation speed and quality (default: "DEFAULT")                                    |
| `character_image`     | IMAGE     | No       | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   | Image to use as character reference                                                                                 |
| `character_mask`      | MASK      | No       | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   | Optional mask for character reference image                                                                         |

**Parameter Constraints:**

* When both `image` and `mask` are provided, the node switches to editing mode
* If only one of `image` or `mask` is provided, an error will occur
* `character_mask` requires `character_image` to be present
* The `aspect_ratio` parameter is ignored when `resolution` is not set to "Auto"
* White areas in the mask will be replaced during inpainting
* Character mask and character image must be the same size

## Outputs

| Output Name | Data Type | Description                      |
| ----------- | --------- | -------------------------------- |
| `output`    | IMAGE     | The generated or edited image(s) |

***

**Source fingerprint (SHA-256):** `b3ddd489ee96b4b378ae432254d8e97bccafc20e38055b213c0ad3b7818cb4c0`


# ImageCrop - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageCrop

Complete documentation for the ImageCrop node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `ImageCrop` node is designed for cropping images to a specified width and height starting from a given x and y coordinate. This functionality is essential for focusing on specific regions of an image or for adjusting the image size to meet certain requirements.

## Inputs

| Field    | Data Type | Description                                                                                                                                                                      |
| -------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`  | `IMAGE`   | The input image to be cropped. This parameter is crucial as it defines the source image from which a region will be extracted based on the specified dimensions and coordinates. |
| `width`  | `INT`     | Specifies the width of the cropped image. This parameter determines how wide the resulting cropped image will be.                                                                |
| `height` | `INT`     | Specifies the height of the cropped image. This parameter determines the height of the resulting cropped image.                                                                  |
| `x`      | `INT`     | The x-coordinate of the top-left corner of the cropping area. This parameter sets the starting point for the width dimension of the crop.                                        |
| `y`      | `INT`     | The y-coordinate of the top-left corner of the cropping area. This parameter sets the starting point for the height dimension of the crop.                                       |

## Outputs

| Field   | Data Type | Description                                                                                                                                           |
| ------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image` | `IMAGE`   | The cropped image as a result of the cropping operation. This output is significant for further processing or analysis of the specified image region. |


# ImageCropV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageCropV2

Complete documentation for the ImageCropV2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageCropV2/en.md)

The Crop Image node extracts a rectangular section from an input image. You define the region to keep by specifying its top-left corner coordinates and its width and height. The node then returns the cropped portion of the original image.

## Inputs

| Parameter     | Data Type   | Required | Range | Description                                                                                                                                                                                                                                                                     |
| ------------- | ----------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`       | IMAGE       | Yes      | N/A   | The input image to be cropped.                                                                                                                                                                                                                                                  |
| `crop_region` | BOUNDINGBOX | Yes      | N/A   | Defines the rectangular area to extract from the image. It is specified by `x` (horizontal start), `y` (vertical start), `width`, and `height`. If the defined region extends beyond the image's borders, it will be automatically adjusted to fit within the image dimensions. |

**Note on Region Constraints:** The crop region is automatically constrained to stay within the bounds of the input image. If the specified `x` or `y` coordinate is greater than the image's width or height, it will be set to the maximum valid position. The resulting crop width and height will be adjusted so the region does not exceed the image's edges.

## Outputs

| Output Name | Data Type | Description                                      |
| ----------- | --------- | ------------------------------------------------ |
| `image`     | IMAGE     | The cropped section of the original input image. |

***

**Source fingerprint (SHA-256):** `c09c68a46c4b0418903a627b98dd848264d53b58bd3ffe99e40ef125b15b3aae`


# ImageFlip - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageFlip

Complete documentation for the ImageFlip node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageFlip/en.md)

The ImageFlip node flips images along different axes. It can flip images vertically along the x-axis or horizontally along the y-axis. The node uses torch.flip operations to perform the flipping based on the selected method.

## Inputs

| Parameter     | Data Type | Required | Range                                            | Description                                                     |
| ------------- | --------- | -------- | ------------------------------------------------ | --------------------------------------------------------------- |
| `image`       | IMAGE     | Yes      | -                                                | The input image to be flipped                                   |
| `flip_method` | STRING    | Yes      | "x-axis: vertically"<br />"y-axis: horizontally" | The flipping direction to apply (default: "x-axis: vertically") |

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `image`     | IMAGE     | The flipped output image |

***

**Source fingerprint (SHA-256):** `481cd167d57746f242fcc4b5f2e3bb0bff0184b5870626d5f24a34422464ddd6`


# ImagePadForOutpaint - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImagePadForOutpaint

Complete documentation for the ImagePadForOutpaint node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed for preparing images for the outpainting process by adding padding around them. It adjusts the image dimensions to ensure compatibility with outpainting algorithms, facilitating the generation of extended image areas beyond the original boundaries.

## Inputs

| Parameter    | Data Type | Description                                                                                                                                   |
| ------------ | --------- | --------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`      | `IMAGE`   | The 'image' input is the primary image to be prepared for outpainting, serving as the base for padding operations.                            |
| `left`       | `INT`     | Specifies the amount of padding to add to the left side of the image, influencing the expanded area for outpainting.                          |
| `top`        | `INT`     | Determines the amount of padding to add to the top of the image, affecting the vertical expansion for outpainting.                            |
| `right`      | `INT`     | Defines the amount of padding to add to the right side of the image, impacting the horizontal expansion for outpainting.                      |
| `bottom`     | `INT`     | Indicates the amount of padding to add to the bottom of the image, contributing to the vertical expansion for outpainting.                    |
| `feathering` | `INT`     | Controls the smoothness of the transition between the original image and the added padding, enhancing the visual integration for outpainting. |

## Outputs

| Parameter | Data Type | Description                                                                                                                       |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The output 'image' represents the padded image, ready for the outpainting process.                                                |
| `mask`    | `MASK`    | The output 'mask' indicates the areas of the original image and the added padding, useful for guiding the outpainting algorithms. |


# ImageRotate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageRotate

Complete documentation for the ImageRotate node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageRotate/en.md)

The ImageRotate node rotates an input image by specified angles. It supports four rotation options: no rotation, 90 degrees clockwise, 180 degrees, and 270 degrees clockwise. The rotation is performed using efficient tensor operations that maintain the image data integrity.

## Inputs

| Parameter  | Data Type | Required | Range                                                          | Description                                                |
| ---------- | --------- | -------- | -------------------------------------------------------------- | ---------------------------------------------------------- |
| `image`    | IMAGE     | Yes      | -                                                              | The input image to be rotated                              |
| `rotation` | STRING    | Yes      | "none"<br />"90 degrees"<br />"180 degrees"<br />"270 degrees" | The rotation angle to apply to the image (default: "none") |

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `image`     | IMAGE     | The rotated output image |

***

**Source fingerprint (SHA-256):** `1de36d9e42e64fe80cc13dd7da96bd946f02ba78d81317f073cf54c4e5bd12f7`


# ImageScale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageScale

Complete documentation for the ImageScale node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The ImageScale node is designed for resizing images to specific dimensions, offering a selection of upscale methods and the ability to crop the resized image. It abstracts the complexity of image upscaling and cropping, providing a straightforward interface for modifying image dimensions according to user-defined parameters.

## Inputs

| Parameter        | Data Type      | Description                                                                                                                                                                                                                                                                |
| ---------------- | -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`          | `IMAGE`        | The input image to be upscaled. This parameter is central to the node's operation, serving as the primary data upon which resizing transformations are applied. The quality and dimensions of the output image are directly influenced by the original image's properties. |
| `upscale_method` | COMBO\[STRING] | Specifies the method used for upscaling the image. The choice of method can affect the quality and characteristics of the upscaled image, influencing the visual fidelity and potential artifacts in the resized output.                                                   |
| `width`          | `INT`          | The target width for the upscaled image. This parameter directly influences the dimensions of the output image, determining the horizontal scale of the resizing operation.                                                                                                |
| `height`         | `INT`          | The target height for the upscaled image. This parameter directly influences the dimensions of the output image, determining the vertical scale of the resizing operation.                                                                                                 |
| `crop`           | COMBO\[STRING] | Determines whether and how the upscaled image should be cropped, offering options for disabled cropping or center cropping. This affects the final composition of the image by potentially removing edges to fit the specified dimensions.                                 |

## Outputs

| Parameter | Data Type | Description                                                                                 |
| --------- | --------- | ------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The upscaled (and optionally cropped) image, ready for further processing or visualization. |


# ImageScaleBy - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageScaleBy

Complete documentation for the ImageScaleBy node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The ImageScaleBy node is designed for upscaling images by a specified scale factor using various interpolation methods. It allows for the adjustment of the image size in a flexible manner, catering to different upscaling needs.

## Inputs

| Parameter        | Data Type      | Description                                                                                                                                         |
| ---------------- | -------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`          | `IMAGE`        | The input image to be upscaled. This parameter is crucial as it provides the base image that will undergo the upscaling process.                    |
| `upscale_method` | COMBO\[STRING] | Specifies the interpolation method to be used for upscaling. The choice of method can affect the quality and characteristics of the upscaled image. |
| `scale_by`       | `FLOAT`        | The factor by which the image will be upscaled. This determines the increase in size of the output image relative to the input image.               |

## Outputs

| Parameter | Data Type | Description                                                                                                                |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The upscaled image, which is larger than the input image according to the specified scale factor and interpolation method. |


# ImageScaleToMaxDimension - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageScaleToMaxDimension

Complete documentation for the ImageScaleToMaxDimension node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageScaleToMaxDimension/en.md)

The ImageScaleToMaxDimension node resizes images to fit within a specified maximum dimension while maintaining the original aspect ratio. It calculates whether the image is portrait or landscape oriented, then scales the larger dimension to match the target size while proportionally adjusting the smaller dimension. The node supports multiple upscaling methods for different quality and performance requirements.

## Inputs

| Parameter        | Data Type | Required | Range                                                                                     | Description                                                           |
| ---------------- | --------- | -------- | ----------------------------------------------------------------------------------------- | --------------------------------------------------------------------- |
| `image`          | IMAGE     | Yes      | -                                                                                         | The input image to be scaled                                          |
| `upscale_method` | STRING    | Yes      | "area"<br />"lanczos"<br />"bilinear"<br />"nearest-exact"<br />"bilinear"<br />"bicubic" | The interpolation method used for scaling the image (default: "area") |
| `largest_size`   | INT       | Yes      | 0 to 16384                                                                                | The maximum dimension for the scaled image (default: 512)             |

## Outputs

| Output Name | Data Type | Description                                                             |
| ----------- | --------- | ----------------------------------------------------------------------- |
| `image`     | IMAGE     | The scaled image with the largest dimension matching the specified size |

***

**Source fingerprint (SHA-256):** `83eba56d9f673fb570edc6504fd82f1274ead1d3e055a1a8bcc207c178388015`


# ImageScaleToTotalPixels - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageScaleToTotalPixels

Complete documentation for the ImageScaleToTotalPixels node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The ImageScaleToTotalPixels node is designed for resizing images to a specified total number of pixels while maintaining the aspect ratio. It provides various methods for upscaling the image to achieve the desired pixel count.

## Inputs

| Parameter        | Data Type      | Description                                                                                                   |
| ---------------- | -------------- | ------------------------------------------------------------------------------------------------------------- |
| `image`          | `IMAGE`        | The input image to be upscaled to the specified total number of pixels.                                       |
| `upscale_method` | COMBO\[STRING] | The method used for upscaling the image. It affects the quality and characteristics of the upscaled image.    |
| `megapixels`     | `FLOAT`        | The target size of the image in megapixels. This determines the total number of pixels in the upscaled image. |

## Outputs

| Parameter | Data Type | Description                                                                                          |
| --------- | --------- | ---------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The upscaled image with the specified total number of pixels, maintaining the original aspect ratio. |


# ImageStitch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageStitch

Complete documentation for the ImageStitch node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node allows you to stitch two images together in a specified direction (up, down, left, right), with support for size matching and spacing between images.

## Inputs

| Parameter Name     | Data Type | Input Type | Default | Range                      | Description                                                                   |
| ------------------ | --------- | ---------- | ------- | -------------------------- | ----------------------------------------------------------------------------- |
| `image1`           | IMAGE     | Required   | -       | -                          | The first image to be stitched                                                |
| `image2`           | IMAGE     | Optional   | None    | -                          | The second image to be stitched, if not provided returns only the first image |
| `direction`        | STRING    | Required   | right   | right/down/left/up         | The direction to stitch the second image: right, down, left, or up            |
| `match_image_size` | BOOLEAN   | Required   | True    | True/False                 | Whether to resize the second image to match the dimensions of the first image |
| `spacing_width`    | INT       | Required   | 0       | 0-1024                     | Width of spacing between images, must be an even number                       |
| `spacing_color`    | STRING    | Required   | white   | white/black/red/green/blue | Color of the spacing between stitched images                                  |

> For `spacing_color`, when using colors other than "white/black", if `match_image_size` is set to `false`, the padding area will be filled with black

## Outputs

| Output Name | Data Type | Description        |
| ----------- | --------- | ------------------ |
| `IMAGE`     | IMAGE     | The stitched image |

## Workflow Example

In the workflow below, we use 3 input images of different sizes as examples:

* image1: 500x300
* image2: 400x250
* image3: 300x300

<img alt="workflow" />

**First Image Stitch Node**

* `match_image_size`: false, images will be stitched at their original sizes
* `direction`: up, `image2` will be placed above `image1`
* `spacing_width`: 20
* `spacing_color`: black

Output image 1:

<img alt="output1" />

**Second Image Stitch Node**

* `match_image_size`: true, the second image will be scaled to match the height or width of the first image
* `direction`: right, `image3` will appear on the right side
* `spacing_width`: 20
* `spacing_color`: white

Output image 2:

<img alt="output2" />


# ImageUpscaleWithModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageUpscaleWithModel

Complete documentation for the ImageUpscaleWithModel node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed for upscaling images using a specified upscale model. It efficiently manages the upscaling process by adjusting the image to the appropriate device, optimizing memory usage, and applying the upscale model in a tiled manner to prevent potential out-of-memory errors.

## Inputs

| Parameter       | Comfy dtype     | Description                                                                                                                   |
| --------------- | --------------- | ----------------------------------------------------------------------------------------------------------------------------- |
| `upscale_model` | `UPSCALE_MODEL` | The upscale model to be used for upscaling the image. It is crucial for defining the upscaling algorithm and its parameters.  |
| `image`         | `IMAGE`         | The image to be upscaled. This input is essential for determining the source content that will undergo the upscaling process. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                              |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The upscaled image, processed by the upscale model. This output is the result of the upscaling operation, showcasing the enhanced resolution or quality. |


# KlingImageGenerationNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingImageGenerationNode

Complete documentation for the KlingImageGenerationNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingImageGenerationNode/en.md)

Kling Image Generation Node generates images from text prompts with the option to use a reference image for guidance. It creates one or more images based on your text description and reference settings, then returns the generated images as output.

## Inputs

| Parameter         | Data Type | Required | Range                                                                                     | Description                                                                                                 |
| ----------------- | --------- | -------- | ----------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------- |
| `prompt`          | STRING    | Yes      | -                                                                                         | Positive text prompt                                                                                        |
| `negative_prompt` | STRING    | Yes      | -                                                                                         | Negative text prompt                                                                                        |
| `image_type`      | COMBO     | Yes      | `"subject_reference"`<br />`"style_reference"`                                            | Image reference type selection (advanced). Required when a reference image is provided.                     |
| `image_fidelity`  | FLOAT     | Yes      | 0.0 - 1.0                                                                                 | Reference intensity for user-uploaded images (default: 0.5, advanced)                                       |
| `human_fidelity`  | FLOAT     | Yes      | 0.0 - 1.0                                                                                 | Subject reference similarity (default: 0.45, advanced)                                                      |
| `model_name`      | COMBO     | Yes      | `"kling-v3"`<br />`"kling-v2"`<br />`"kling-v1-5"`                                        | Model selection for image generation (default: "kling-v3")                                                  |
| `aspect_ratio`    | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"`<br />`"21:9"`<br />`"9:21"` | Aspect ratio for generated images (default: "16:9")                                                         |
| `n`               | INT       | Yes      | 1 - 9                                                                                     | Number of generated images (default: 1)                                                                     |
| `image`           | IMAGE     | No       | -                                                                                         | Optional reference image                                                                                    |
| `seed`            | INT       | No       | 0 - 2147483647                                                                            | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0) |

**Parameter Constraints:**

* The `image` parameter is optional. When a reference image is provided, the `image_type` parameter must be set to either `"subject_reference"` or `"style_reference"`.
* When no reference image is provided, the `image_type`, `image_fidelity`, and `human_fidelity` parameters are not used.
* Prompt and negative prompt have a maximum length of 500 characters.
* The `seed` parameter is optional and does not guarantee deterministic results.

## Outputs

| Output Name | Data Type | Description                                      |
| ----------- | --------- | ------------------------------------------------ |
| `output`    | IMAGE     | Generated image(s) based on the input parameters |

***

**Source fingerprint (SHA-256):** `3c029920c966ac9a3588a790e83e1350021a0864a02677258a25af46a0770dce`


# KlingOmniProImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProImageNode

Complete documentation for the KlingOmniProImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProImageNode/en.md)

The Kling Omni Image (Pro) node creates or edits images using the latest Kling AI model. It generates images based on a text description and can optionally use reference images to guide the style or content. The node sends a request to an external API, which processes the task and returns the final image(s).

## Inputs

| Parameter          | Data Type | Required | Range                                                                                                 | Description                                                                                                                                                                                                                                                                                               |
| :----------------- | :-------- | :------- | :---------------------------------------------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model_name`       | COMBO     | Yes      | `"kling-v3-omni"`<br />`"kling-image-o1"`                                                             | The specific Kling AI model to use for image generation.                                                                                                                                                                                                                                                  |
| `prompt`           | STRING    | Yes      | -                                                                                                     | A text prompt describing the image content. This can include both positive and negative descriptions. The text must be between 1 and 2500 characters long. You can use `@image`, `@image1`, `@image2`, etc. or `@video`, `@video1`, `@video2`, etc. to reference uploaded images or videos in the prompt. |
| `resolution`       | COMBO     | Yes      | `"1K"`<br />`"2K"`<br />`"4K"`                                                                        | The target resolution for the generated image. Note: 4K resolution is not supported for the `kling-image-o1` model.                                                                                                                                                                                       |
| `aspect_ratio`     | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"`<br />`"3:2"`<br />`"2:3"`<br />`"21:9"` | The desired aspect ratio (width to height) for the generated image.                                                                                                                                                                                                                                       |
| `series_amount`    | COMBO     | Yes      | `"disabled"`<br />`"2"`<br />`"3"`<br />`"4"`<br />`"5"`<br />`"6"`<br />`"7"`<br />`"8"`<br />`"9"`  | Generate a series of images. This feature is not supported for the `kling-image-o1` model. (default: "disabled")                                                                                                                                                                                          |
| `reference_images` | IMAGE     | No       | -                                                                                                     | Up to 10 additional reference images. Each image must be at least 300 pixels in both width and height, and its aspect ratio must be between 1:2.5 and 2.5:1.                                                                                                                                              |
| `seed`             | INT       | No       | 0 to 2147483647                                                                                       | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0)                                                                                                                                                                                              |

## Outputs

| Output Name | Data Type | Description                                                                                                                       |
| :---------- | :-------- | :-------------------------------------------------------------------------------------------------------------------------------- |
| `image`     | IMAGE     | The final image(s) generated or edited by the Kling AI model. If a series was requested, multiple images are returned as a batch. |

***

**Source fingerprint (SHA-256):** `b1d25806bc3b8eaa5ee8677a32b1f1f45189b800a2bfe1664635eaa851c34032`


# KlingVirtualTryOnNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingVirtualTryOnNode

Complete documentation for the KlingVirtualTryOnNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingVirtualTryOnNode/en.md)

Kling Virtual Try On Node. Input a human image and a cloth image to try on the cloth on the human. You can merge multiple clothing item pictures into one image with a white background.

## Inputs

| Parameter     | Data Type | Required | Range                        | Description                                                           |
| ------------- | --------- | -------- | ---------------------------- | --------------------------------------------------------------------- |
| `human_image` | IMAGE     | Yes      | -                            | The human image to try clothes on                                     |
| `cloth_image` | IMAGE     | Yes      | -                            | The clothing image to try on the human                                |
| `model_name`  | STRING    | Yes      | `"kolors-virtual-try-on-v1"` | The virtual try-on model to use (default: "kolors-virtual-try-on-v1") |

## Outputs

| Output Name | Data Type | Description                                                           |
| ----------- | --------- | --------------------------------------------------------------------- |
| `output`    | IMAGE     | The resulting image showing the human with the clothing item tried on |

***

**Source fingerprint (SHA-256):** `b642ea6583e971f47a580212030f564e24b055caf77dc99764b79ee21e2988f9`


# Krea2ImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Krea2ImageNode

Complete documentation for the Krea2ImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Krea2ImageNode/en.md)

## Overview

The Krea 2 Image node generates images using the Krea 2 AI model. It supports two model variants: Medium for expressive illustrations and Large for expressive photorealism. You can optionally include a moodboard and up to 10 image style references to influence the generated image.

## Inputs

| Parameter | Data Type | Required | Range           | Description                                                                                           |
| --------- | --------- | -------- | --------------- | ----------------------------------------------------------------------------------------------------- |
| `prompt`  | STRING    | Yes      | N/A             | Text prompt for the image.                                                                            |
| `model`   | DICT      | Yes      | See below       | Krea 2 Medium is best for expressive illustrations; Krea 2 Large is best for expressive photorealism. |
| `seed`    | INT       | Yes      | 0 to 2147483647 | Random seed for reproducibility (default: 0).                                                         |

The `model` parameter is a dictionary with the following sub-parameters:

| Sub-Parameter        | Data Type | Required | Range                                   | Description                                                                                         |
| -------------------- | --------- | -------- | --------------------------------------- | --------------------------------------------------------------------------------------------------- |
| `model`              | STRING    | Yes      | `"krea 2 medium"`<br />`"krea 2 large"` | Selects the Krea 2 model variant.                                                                   |
| `aspect_ratio`       | STRING    | Yes      | N/A                                     | The aspect ratio for the generated image.                                                           |
| `resolution`         | STRING    | Yes      | N/A                                     | The resolution for the generated image.                                                             |
| `creativity`         | FLOAT     | Yes      | N/A                                     | Controls the creativity level of the generation.                                                    |
| `moodboard_id`       | STRING    | No       | N/A                                     | The UUID of a Krea moodboard to influence the image. Must be a valid UUID.                          |
| `moodboard_strength` | FLOAT     | No       | N/A                                     | The strength of the moodboard influence (default: 0.35).                                            |
| `style_reference`    | LIST      | No       | 0 to 10 items                           | A list of image style references. Each reference must have a `url` (STRING) and `strength` (FLOAT). |

**Constraints:**

* `moodboard_id` must be a valid UUID (e.g., `"123e4567-e89b-12d3-a456-426614174000"`). Copy it from the Krea website.
* `style_reference` accepts a maximum of 10 image style references.
* The `prompt` must be at least 1 character long.

## Outputs

| Output Name | Data Type | Description                      |
| ----------- | --------- | -------------------------------- |
| `image`     | IMAGE     | The generated image as a tensor. |

***

**Source fingerprint (SHA-256):** `6aeb2d935ef5df5699a19271c9ceb766892ef4b0e4f67bfa540bf12ffadf362d`


# Krea2StyleReferenceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Krea2StyleReferenceNode

Complete documentation for the Krea2StyleReferenceNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Krea2StyleReferenceNode/en.md)

## Overview

The Krea 2 Style Reference node lets you add a reference image to influence the style of a Krea 2 image generation. You can chain multiple style references together (up to 10 total) and feed the combined result into a Krea 2 Image node. Each image you provide is uploaded to ComfyAPI storage and passed as a URL.

## Inputs

| Parameter         | Data Type  | Required | Range                    | Description                                                                    |
| ----------------- | ---------- | -------- | ------------------------ | ------------------------------------------------------------------------------ |
| `image`           | IMAGE      | Yes      | -                        | Reference image whose style influences the generation.                         |
| `strength`        | FLOAT      | Yes      | -2.0 to 2.0 (step: 0.05) | Reference strength; negative values invert the style influence (default: 1.0). |
| `style_reference` | STYLE\_REF | No       | -                        | Optional incoming chain of style references; this node appends one more.       |

**Note on constraints:** You can chain a maximum of 10 style references in total. If you try to add an 11th reference, the node will raise an error.

## Outputs

| Output Name       | Data Type  | Description                                                                                                             |
| ----------------- | ---------- | ----------------------------------------------------------------------------------------------------------------------- |
| `style_reference` | STYLE\_REF | A list of style reference entries, each containing a URL and strength value. Feed this output into a Krea 2 Image node. |

***

**Source fingerprint (SHA-256):** `7f87568a1cd5038571f3188cfb1d71e15533ea19eee01d7826fe574a1a4dc88d`


# LumaImageEditNode2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaImageEditNode2

Complete documentation for the LumaImageEditNode2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaImageEditNode2/en.md)

## Overview

This node edits an existing image using a text prompt, powered by the Luma UNI-1 model. It takes a source image and a description of the desired change, then generates a new edited version of the image.

## Inputs

| Parameter | Data Type | Required | Range                        | Description                                                                                                 |
| --------- | --------- | -------- | ---------------------------- | ----------------------------------------------------------------------------------------------------------- |
| `source`  | IMAGE     | Yes      | -                            | Source image to edit.                                                                                       |
| `prompt`  | STRING    | Yes      | 1–6000 characters            | Description of the desired edit. Default: "" (empty string).                                                |
| `model`   | MODEL     | Yes      | `"uni-1"`<br />`"uni-1-max"` | Model to use for editing.                                                                                   |
| `seed`    | INT       | Yes      | 0 to 2147483647              | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. Default: 0. |

**Parameter Constraints:**

* The `prompt` must be between 1 and 6000 characters long.
* The `model` parameter is a dynamic combo that, when set to `"uni-1"` or `"uni-1-max"`, provides additional sub-parameters (such as `style`, `web_search`, and `image_ref`). The `image_ref` sub-parameter accepts a maximum of 8 image references.

## Outputs

| Output Name | Data Type | Description                                         |
| ----------- | --------- | --------------------------------------------------- |
| `image`     | IMAGE     | The edited image generated by the Luma UNI-1 model. |

***

**Source fingerprint (SHA-256):** `7d658d8e11b54dbad38d8d679553d55299313dacbdcc76d91079c5f92275d07e`


# LumaImageModifyNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaImageModifyNode

Complete documentation for the LumaImageModifyNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaImageModifyNode/en.md)

Modifies images synchronously based on a text prompt and the original image's aspect ratio. This node takes an input image and transforms it according to the provided prompt, using a configurable image weight to control how much the original image is altered.

## Inputs

| Parameter      | Data Type | Required | Range                                                | Description                                                                                                                                                                            |
| -------------- | --------- | -------- | ---------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`        | IMAGE     | Yes      | -                                                    | The input image to be modified                                                                                                                                                         |
| `prompt`       | STRING    | Yes      | -                                                    | Prompt for the image generation (default: "")                                                                                                                                          |
| `image_weight` | FLOAT     | No       | 0.0-0.98                                             | Weight of the image; the closer to 1.0, the less the image will be modified (default: 0.1). Internally, this value is inverted (1.0 - image\_weight) and clamped between 0.0 and 0.98. |
| `model`        | STRING    | Yes      | `"photon-flash-1"`<br />`"photon-1"`<br />`"photon"` | The Luma model to use for image modification. Different models have different costs.                                                                                                   |
| `seed`         | INT       | No       | 0-18446744073709551615                               | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0)                                                                           |

## Outputs

| Output Name | Data Type | Description                                    |
| ----------- | --------- | ---------------------------------------------- |
| `image`     | IMAGE     | The modified image generated by the Luma model |

***

**Source fingerprint (SHA-256):** `9798382092f179fe55972568687285bd728981ca59f1b0a5e4e2ca4bd9b7c981`


# LumaImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaImageNode

Complete documentation for the LumaImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaImageNode/en.md)

Generates images synchronously based on a text prompt and aspect ratio. This node creates images using text descriptions and allows you to control the image dimensions and style through various reference inputs, including character and style images.

## Inputs

| Parameter            | Data Type | Required | Range                                                                                             | Description                                                                                                  |
| -------------------- | --------- | -------- | ------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------ |
| `prompt`             | STRING    | Yes      | -                                                                                                 | Prompt for the image generation (default: empty string). Must be at least 3 characters long.                 |
| `model`              | COMBO     | Yes      | `photon-flash-1`<br />`photon-1`<br />`photon`                                                    | Model selection for image generation. Different models have different costs.                                 |
| `aspect_ratio`       | COMBO     | Yes      | `16:9`<br />`1:1`<br />`4:3`<br />`3:2`<br />`21:9`<br />`9:16`<br />`3:4`<br />`2:3`<br />`9:21` | Aspect ratio for the generated image (default: `16:9`)                                                       |
| `seed`               | INT       | Yes      | 0 to 18446744073709551615                                                                         | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0) |
| `style_image_weight` | FLOAT     | No       | 0.0 to 1.0                                                                                        | Weight of style image. Ignored if no `style_image` is provided (default: 1.0)                                |
| `image_luma_ref`     | LUMA\_REF | No       | -                                                                                                 | Luma Reference node connection to influence generation with input images; up to 4 images can be considered.  |
| `style_image`        | IMAGE     | No       | -                                                                                                 | Style reference image; only 1 image will be used.                                                            |
| `character_image`    | IMAGE     | No       | -                                                                                                 | Character reference images; can be a batch of multiple, up to 4 images can be considered.                    |

**Parameter Constraints:**

* The `prompt` must be at least 3 characters long after stripping whitespace.
* The `image_luma_ref` parameter can accept up to 4 reference images.
* The `character_image` parameter can accept up to 4 character reference images.
* The `style_image` parameter accepts only 1 style reference image.
* The `style_image_weight` parameter is only used when `style_image` is provided.

## Outputs

| Output Name | Data Type | Description                                        |
| ----------- | --------- | -------------------------------------------------- |
| `output`    | IMAGE     | The generated image based on the input parameters. |

***

**Source fingerprint (SHA-256):** `353d99868c8c09edfab212e49f127585a6cbe1a24d6ee8fe584169adcded2961`


# LumaImageNode2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaImageNode2

Complete documentation for the LumaImageNode2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaImageNode2/en.md)

## Overview

This node generates images from text descriptions using the Luma UNI-1 model. It takes a text prompt and optional settings like aspect ratio and style, then sends the request to the Luma API to create an image.

## Inputs

| Parameter | Data Type | Required | Range                        | Description                                                                                                  |
| --------- | --------- | -------- | ---------------------------- | ------------------------------------------------------------------------------------------------------------ |
| `prompt`  | STRING    | Yes      | 1–6000 characters            | Text description of the desired image.                                                                       |
| `model`   | COMBO     | Yes      | `"uni-1"`<br />`"uni-1-max"` | Model to use for generation. Selecting a model reveals additional settings for that model.                   |
| `seed`    | INT       | Yes      | 0 to 2147483647              | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) |

### Model-specific Inputs

When `"uni-1"` or `"uni-1-max"` is selected for the `model` parameter, the following inputs become available:

| Parameter      | Data Type | Required | Range                                                                                                                           | Description                                                                                      |
| -------------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------ |
| `aspect_ratio` | COMBO     | Yes      | `"auto"`<br />`"3:1"`<br />`"2:1"`<br />`"16:9"`<br />`"3:2"`<br />`"1:1"`<br />`"2:3"`<br />`"9:16"`<br />`"1:2"`<br />`"1:3"` | Output image aspect ratio. `"auto"` lets the model pick based on the prompt. (default: `"auto"`) |
| `style`        | COMBO     | Yes      | `"auto"`<br />`"manga"`                                                                                                         | The visual style for the generated image. (default: `"auto"`)                                    |
| `web_search`   | BOOLEAN   | Yes      | True / False                                                                                                                    | Whether to allow the model to search the web for additional context. (default: False)            |
| `image_ref`    | IMAGE     | No       | Up to 9 images                                                                                                                  | Reference images to guide the generation.                                                        |

**Note on `style` and `aspect_ratio` constraints:** If `style` is set to `"manga"`, the `aspect_ratio` must be either `"auto"` or one of the following portrait ratios: `"2:3"`, `"9:16"`, `"1:2"`, `"1:3"`. Using a landscape or square ratio with `"manga"` style will cause an error.

## Outputs

| Output Name | Data Type | Description                      |
| ----------- | --------- | -------------------------------- |
| `image`     | IMAGE     | The generated image as a tensor. |

***

**Source fingerprint (SHA-256):** `cd680f8b9e6bcf5fa415aa2d9ec3126bf8873d14bd6f4cd127491cfa242e5548`


# LumaReferenceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaReferenceNode

Complete documentation for the LumaReferenceNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaReferenceNode/en.md)

This node holds an image and weight value for use with the Luma Generate Image node. It creates a reference chain that can be passed to other Luma nodes to influence image generation. The node can either start a new reference chain or add to an existing one.

## Inputs

| Parameter  | Data Type | Required | Range     | Description                                       |
| ---------- | --------- | -------- | --------- | ------------------------------------------------- |
| `image`    | IMAGE     | Yes      | -         | Image to use as reference.                        |
| `weight`   | FLOAT     | Yes      | 0.0 - 1.0 | Weight of image reference (default: 1.0).         |
| `luma_ref` | LUMA\_REF | No       | -         | Optional existing Luma reference chain to add to. |

## Outputs

| Output Name | Data Type | Description                                               |
| ----------- | --------- | --------------------------------------------------------- |
| `luma_ref`  | LUMA\_REF | The Luma reference chain containing the image and weight. |

***

**Source fingerprint (SHA-256):** `1cca0ddc397a72c03bb7d6d24135c09795934f566b23368298a89b90a14dc8cc`


# MagnificImageRelightNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MagnificImageRelightNode

Complete documentation for the MagnificImageRelightNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MagnificImageRelightNode/en.md)

The Magnific Image Relight node adjusts the lighting of an input image. It can apply stylistic lighting based on a text prompt or transfer the lighting characteristics from an optional reference image. The node offers various controls for fine-tuning the brightness, contrast, and overall mood of the final output.

## Inputs

| Parameter                   | Data Type    | Required | Range                                                                                                                                           | Description                                                                                                                                                                      |
| --------------------------- | ------------ | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`                     | IMAGE        | Yes      | N/A                                                                                                                                             | The image to relight. Exactly one image is required. Minimum dimensions are 160x160 pixels. Aspect ratio must be between 1:3 and 3:1.                                            |
| `prompt`                    | STRING       | No       | N/A                                                                                                                                             | Descriptive guidance for lighting. Supports emphasis notation (1-1.4). Default is an empty string.                                                                               |
| `light_transfer_strength`   | INT          | Yes      | 0 to 100                                                                                                                                        | Intensity of light transfer application. Default: 100.                                                                                                                           |
| `style`                     | COMBO        | Yes      | `"standard"`<br />`"darker_but_realistic"`<br />`"clean"`<br />`"smooth"`<br />`"brighter"`<br />`"contrasted_n_hdr"`<br />`"just_composition"` | Stylistic output preference.                                                                                                                                                     |
| `interpolate_from_original` | BOOLEAN      | Yes      | N/A                                                                                                                                             | Restricts generation freedom to match original more closely. Default: False.                                                                                                     |
| `change_background`         | BOOLEAN      | Yes      | N/A                                                                                                                                             | Modifies background based on prompt/reference. Default: True.                                                                                                                    |
| `preserve_details`          | BOOLEAN      | Yes      | N/A                                                                                                                                             | Maintains texture and fine details from original. Default: True.                                                                                                                 |
| `advanced_settings`         | DYNAMICCOMBO | Yes      | `"disabled"`<br />`"enabled"`                                                                                                                   | Fine-tuning options for advanced lighting control. When set to `"enabled"`, additional parameters become available.                                                              |
| `reference_image`           | IMAGE        | No       | N/A                                                                                                                                             | Optional reference image to transfer lighting from. If provided, exactly one image is required. Minimum dimensions are 160x160 pixels. Aspect ratio must be between 1:3 and 3:1. |

**Note on Advanced Settings:** When `advanced_settings` is set to `"enabled"`, the following nested parameters become active:

* `whites`: Adjusts the brightest tones in the image. Range: 0 to 100. Default: 50.
* `blacks`: Adjusts the darkest tones in the image. Range: 0 to 100. Default: 50.
* `brightness`: Overall brightness adjustment. Range: 0 to 100. Default: 50.
* `contrast`: Contrast adjustment. Range: 0 to 100. Default: 50.
* `saturation`: Color saturation adjustment. Range: 0 to 100. Default: 50.
* `engine`: Processing engine selection. Options: `"automatic"`, `"balanced"`, `"cool"`, `"real"`, `"illusio"`, `"fairy"`, `"colorful_anime"`, `"hard_transform"`, `"softy"`.
* `transfer_light_a`: The intensity of light transfer. Options: `"automatic"`, `"low"`, `"medium"`, `"normal"`, `"high"`, `"high_on_faces"`.
* `transfer_light_b`: Also modifies light transfer intensity. Can be combined with the previous control for varied effects. Options: `"automatic"`, `"composition"`, `"straight"`, `"smooth_in"`, `"smooth_out"`, `"smooth_both"`, `"reverse_both"`, `"soft_in"`, `"soft_out"`, `"soft_mid"`, `"style_shift"`, `"strong_shift"`.
* `fixed_generation`: Ensures consistent output with the same settings. Default: True.

## Outputs

| Output Name | Data Type | Description      |
| ----------- | --------- | ---------------- |
| `image`     | IMAGE     | The relit image. |

***

**Source fingerprint (SHA-256):** `52d6a2c2ab8b03397ed78222c4da936f96f816cde01e2c9cccc3d4915042330f`


# MagnificImageSkinEnhancerNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MagnificImageSkinEnhancerNode

Complete documentation for the MagnificImageSkinEnhancerNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MagnificImageSkinEnhancerNode/en.md)

The Magnific Image Skin Enhancer node applies specialized AI processing to portrait images to improve skin appearance. It offers three distinct modes for different enhancement goals: creative for artistic effects, faithful for preserving the original look, and flexible for targeted improvements like lighting or realism. The node uploads the image to an external API for processing and returns the enhanced result.

## Inputs

| Parameter       | Data Type | Required | Range                                                                                                                 | Description                                                                                                                                                            |
| --------------- | --------- | -------- | --------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`         | IMAGE     | Yes      | -                                                                                                                     | The portrait image to enhance.                                                                                                                                         |
| `sharpen`       | INT       | No       | 0 to 100                                                                                                              | Sharpening intensity level (default: 0).                                                                                                                               |
| `smart_grain`   | INT       | No       | 0 to 100                                                                                                              | Smart grain intensity level (default: 2).                                                                                                                              |
| `mode`          | COMBO     | Yes      | `"creative"`<br />`"faithful"`<br />`"flexible"`                                                                      | The processing mode to use. `"creative"` is for artistic enhancement, `"faithful"` for preserving the original appearance, and `"flexible"` for targeted optimization. |
| `skin_detail`   | INT       | No       | 0 to 100                                                                                                              | Skin detail enhancement level. This input is only available when the `mode` is set to `"faithful"` (default: 80).                                                      |
| `optimized_for` | COMBO     | No       | `"enhance_skin"`<br />`"improve_lighting"`<br />`"enhance_everything"`<br />`"transform_to_real"`<br />`"no_make_up"` | Enhancement optimization target. This input is only available when the `mode` is set to `"flexible"`.                                                                  |

**Constraints:**

* The node accepts exactly one input image.
* The input image must have a minimum height and width of 160 pixels.
* The input image aspect ratio must be between 1:3 and 3:1 (non-strict validation).
* The `skin_detail` parameter is only active when `mode` is set to `"faithful"`.
* The `optimized_for` parameter is only active when `mode` is set to `"flexible"`.

## Outputs

| Output Name | Data Type | Description                  |
| ----------- | --------- | ---------------------------- |
| `image`     | IMAGE     | The enhanced portrait image. |

***

**Source fingerprint (SHA-256):** `1c87ba8a71ccac4fd17c35ad5bf2ee9b27c8bcb45a9d76cd077d6c0614f1ecc1`


# MagnificImageStyleTransferNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MagnificImageStyleTransferNode

Complete documentation for the MagnificImageStyleTransferNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MagnificImageStyleTransferNode/en.md)

This node applies the visual style from a reference image to your input image. It uses an external AI service to process the images, allowing you to control the strength of the style transfer and the preservation of the original image's structure.

## Inputs

| Parameter             | Data Type | Required | Range                                                                                                                                            | Description                                                                                                                  |
| --------------------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------- |
| `image`               | IMAGE     | Yes      | -                                                                                                                                                | The image to apply style transfer to.                                                                                        |
| `reference_image`     | IMAGE     | Yes      | -                                                                                                                                                | The reference image to extract style from.                                                                                   |
| `prompt`              | STRING    | No       | -                                                                                                                                                | An optional text prompt to guide the style transfer.                                                                         |
| `style_strength`      | INT       | No       | 0 to 100                                                                                                                                         | Percentage of style strength (default: 100).                                                                                 |
| `structure_strength`  | INT       | No       | 0 to 100                                                                                                                                         | Maintains the structure of the original image (default: 50).                                                                 |
| `flavor`              | COMBO     | No       | "faithful"<br />"gen\_z"<br />"psychedelia"<br />"detaily"<br />"clear"<br />"donotstyle"<br />"donotstyle\_sharp"                               | Style transfer flavor.                                                                                                       |
| `engine`              | COMBO     | No       | "balanced"<br />"definio"<br />"illusio"<br />"3d\_cartoon"<br />"colorful\_anime"<br />"caricature"<br />"real"<br />"super\_real"<br />"softy" | Processing engine selection.                                                                                                 |
| `portrait_mode`       | COMBO     | No       | "disabled"<br />"enabled"                                                                                                                        | Enable portrait mode for facial enhancements.                                                                                |
| `portrait_style`      | COMBO     | No       | "standard"<br />"pop"<br />"super\_pop"                                                                                                          | Visual style applied to portrait images. This input is only available when `portrait_mode` is set to "enabled".              |
| `portrait_beautifier` | COMBO     | No       | "none"<br />"beautify\_face"<br />"beautify\_face\_max"                                                                                          | Facial beautification intensity on portraits. This input is only available when `portrait_mode` is set to "enabled".         |
| `fixed_generation`    | BOOLEAN   | No       | -                                                                                                                                                | When disabled, expect each generation to introduce a degree of randomness, leading to more diverse outcomes (default: True). |

**Constraints:**

* Exactly one `image` and one `reference_image` are required.
* Both images must have an aspect ratio between 1:3 and 3:1.
* Both images must have a minimum height and width of 160 pixels.
* The `portrait_style` and `portrait_beautifier` parameters are only active when `portrait_mode` is set to "enabled".

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `image`     | IMAGE     | The resulting image after style transfer has been applied. |

***

**Source fingerprint (SHA-256):** `2a008de2ad1345360c8313da90721c1118b1d7447647a0a9a4676ff71461e142`


# MagnificImageUpscalerCreativeNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MagnificImageUpscalerCreativeNode

Complete documentation for the MagnificImageUpscalerCreativeNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MagnificImageUpscalerCreativeNode/en.md)

This node uses the Magnific AI service to upscale and creatively enhance an image. It allows you to guide the enhancement with a text prompt, choose a specific style to optimize for, and control various aspects of the creative process like detail, resemblance to the original, and stylization strength. The node outputs an upscaled image at your chosen factor (2x, 4x, 8x, or 16x), with a maximum output size of 25.3 megapixels.

## Inputs

| Parameter        | Data Type | Required | Range                                                                                                                                                                                                                              | Description                                                                                                                                                                                                   |
| ---------------- | --------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`          | IMAGE     | Yes      | -                                                                                                                                                                                                                                  | The input image to be upscaled and enhanced.                                                                                                                                                                  |
| `prompt`         | STRING    | No       | -                                                                                                                                                                                                                                  | A text description to guide the creative enhancement of the image. This is optional (default: empty).                                                                                                         |
| `scale_factor`   | COMBO     | Yes      | `"2x"`<br />`"4x"`<br />`"8x"`<br />`"16x"`                                                                                                                                                                                        | The factor by which to upscale the image's dimensions.                                                                                                                                                        |
| `optimized_for`  | COMBO     | Yes      | `"standard"`<br />`"soft_portraits"`<br />`"hard_portraits"`<br />`"art_n_illustration"`<br />`"videogame_assets"`<br />`"nature_n_landscapes"`<br />`"films_n_photography"`<br />`"3d_renders"`<br />`"science_fiction_n_horror"` | The style or content type to optimize the enhancement process for.                                                                                                                                            |
| `creativity`     | INT       | No       | -10 to 10                                                                                                                                                                                                                          | Controls the level of creative interpretation applied to the image (default: 0).                                                                                                                              |
| `hdr`            | INT       | No       | -10 to 10                                                                                                                                                                                                                          | The level of definition and detail (default: 0).                                                                                                                                                              |
| `resemblance`    | INT       | No       | -10 to 10                                                                                                                                                                                                                          | The level of resemblance to the original image (default: 0).                                                                                                                                                  |
| `fractality`     | INT       | No       | -10 to 10                                                                                                                                                                                                                          | The strength of the prompt and intricacy per square pixel (default: 0).                                                                                                                                       |
| `engine`         | COMBO     | Yes      | `"automatic"`<br />`"magnific_illusio"`<br />`"magnific_sharpy"`<br />`"magnific_sparkle"`                                                                                                                                         | The specific AI engine to use for processing. This is an advanced parameter.                                                                                                                                  |
| `auto_downscale` | BOOLEAN   | No       | -                                                                                                                                                                                                                                  | When enabled, the node will automatically downscale the input image if the requested upscale would exceed the maximum allowed output size of 25.3 megapixels. This is an advanced parameter (default: False). |

**Constraints:**

* The input `image` must be exactly one image.
* The input image must have a minimum height and width of 160 pixels.
* The input image's aspect ratio must be between 1:3 and 3:1.
* The final output size (input dimensions multiplied by the `scale_factor`) cannot exceed 25,300,000 pixels. If `auto_downscale` is disabled and this limit would be exceeded, the node will raise an error.

## Outputs

| Output Name | Data Type | Description                                        |
| ----------- | --------- | -------------------------------------------------- |
| `image`     | IMAGE     | The creatively enhanced and upscaled output image. |

***

**Source fingerprint (SHA-256):** `3eb5ce7887ba67a3a49d06820851df90d1c1c73f28ded62288054154bcb2d7e8`


# MagnificImageUpscalerPreciseV2Node - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MagnificImageUpscalerPreciseV2Node

Complete documentation for the MagnificImageUpscalerPreciseV2Node node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MagnificImageUpscalerPreciseV2Node/en.md)

The Magnific Image Upscale (Precise V2) node performs high-fidelity image upscaling with precise control over sharpness, grain, and detail enhancement. It processes images through an external API, supporting up to a maximum output resolution of 10060×10060 pixels. The node offers different processing styles and can automatically downscale the input if the requested output would exceed the maximum allowed size.

## Inputs

| Parameter        | Data Type | Required | Range                                              | Description                                                                                                                                                                                                                                  |
| ---------------- | --------- | -------- | -------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`          | IMAGE     | Yes      | -                                                  | The input image to be upscaled. Exactly one image is required. Minimum dimensions are 160x160 pixels. The aspect ratio must be between 1:3 and 3:1.                                                                                          |
| `scale_factor`   | STRING    | Yes      | `"2x"`<br />`"4x"`<br />`"8x"`<br />`"16x"`        | The desired upscaling multiplier.                                                                                                                                                                                                            |
| `flavor`         | STRING    | Yes      | `"sublime"`<br />`"photo"`<br />`"photo_denoiser"` | The processing style. "sublime" is for general use, "photo" is optimized for photographs, and "photo\_denoiser" is for noisy photos.                                                                                                         |
| `sharpen`        | INT       | No       | 0 to 100                                           | Controls the intensity of image sharpening to increase edge definition and clarity. Higher values produce a sharper result. Default: 7.                                                                                                      |
| `smart_grain`    | INT       | No       | 0 to 100                                           | Adds intelligent grain or texture enhancement to prevent the upscaled image from looking too smooth or artificial. Default: 7.                                                                                                               |
| `ultra_detail`   | INT       | No       | 0 to 100                                           | Controls the amount of fine detail, textures, and micro-details added during the upscaling process. Default: 30.                                                                                                                             |
| `auto_downscale` | BOOLEAN   | No       | -                                                  | When enabled, the node will automatically downscale the input image if the calculated output dimensions would exceed the maximum allowed resolution of 10060x10060 pixels. This helps prevent errors but may affect quality. Default: False. |

**Note:** If `auto_downscale` is disabled and the requested output size (input dimensions × `scale_factor`) exceeds 10060x10060 pixels, the node will raise an error.

## Outputs

| Output Name | Data Type | Description                   |
| ----------- | --------- | ----------------------------- |
| `image`     | IMAGE     | The resulting upscaled image. |

***

**Source fingerprint (SHA-256):** `83559e99f86398b894c659996bdde48633a49f857a4769127fdf7ab6e80d6b0d`


# MaskToImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MaskToImage

Complete documentation for the MaskToImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `MaskToImage` node is designed to convert a mask into an image format. This transformation allows for the visualization and further processing of masks as images, facilitating a bridge between mask-based operations and image-based applications.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                                         |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `mask`    | `MASK`    | The mask input is essential for the conversion process, serving as the source data that will be transformed into an image format. This input dictates the shape and content of the resulting image. |

## Outputs

| Parameter | Data Type | Description                                                                                                                |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The output is an image representation of the input mask, enabling visual inspection and further image-based manipulations. |


# OpenAIDalle2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIDalle2

Complete documentation for the OpenAIDalle2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIDalle2/en.md)

# OpenAIDalle2

Generates images synchronously via OpenAI's DALL·E 2 endpoint.

## How It Works

This node connects to OpenAI's DALL·E 2 API to create images based on text descriptions. When you provide a text prompt, the node sends it to OpenAI's servers which generate corresponding images and return them to ComfyUI. The node can operate in two modes: standard image generation using just a text prompt, or image editing mode when both an image and mask are provided. In editing mode, it uses the mask to determine which parts of the original image should be modified while keeping other areas unchanged.

## Inputs

| Parameter | Data Type | Input Type | Default     | Range                             | Description                                                 |
| --------- | --------- | ---------- | ----------- | --------------------------------- | ----------------------------------------------------------- |
| `prompt`  | STRING    | required   | ""          | -                                 | Text prompt for DALL·E                                      |
| `seed`    | INT       | optional   | 0           | 0 to 2147483647                   | not implemented yet in backend                              |
| `size`    | COMBO     | optional   | "1024x1024" | "256x256", "512x512", "1024x1024" | Image size                                                  |
| `n`       | INT       | optional   | 1           | 1 to 8                            | How many images to generate                                 |
| `image`   | IMAGE     | optional   | None        | -                                 | Optional reference image for image editing.                 |
| `mask`    | MASK      | optional   | None        | -                                 | Optional mask for inpainting (white areas will be replaced) |

## Outputs

| Output Name | Data Type | Description                                    |
| ----------- | --------- | ---------------------------------------------- |
| `IMAGE`     | IMAGE     | The generated or edited image(s) from DALL·E 2 |

***

**Source fingerprint (SHA-256):** `ad10b149ac28559ad18c09e0f071286509680603d953833106ad6a2d578f7efe`


# OpenAIDalle3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIDalle3

Complete documentation for the OpenAIDalle3 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIDalle3/en.md)

Generates images synchronously via OpenAI's DALL·E 3 endpoint. This node takes a text prompt and creates corresponding images using OpenAI's DALL·E 3 model, allowing you to specify image quality, style, and dimensions.

## Inputs

| Parameter | Data Type | Required | Range                                         | Description                                                                                                                                                                              |
| --------- | --------- | -------- | --------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`  | STRING    | Yes      | -                                             | Text prompt for DALL·E (default: "")                                                                                                                                                     |
| `seed`    | INT       | No       | 0 to 2147483647                               | Not implemented yet in backend (default: 0)                                                                                                                                              |
| `quality` | COMBO     | No       | "standard"<br />"hd"                          | Image quality (default: "standard")                                                                                                                                                      |
| `style`   | COMBO     | No       | "natural"<br />"vivid"                        | Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images. (default: "natural") |
| `size`    | COMBO     | No       | "1024x1024"<br />"1024x1792"<br />"1792x1024" | Image size (default: "1024x1024")                                                                                                                                                        |

## Outputs

| Output Name | Data Type | Description                       |
| ----------- | --------- | --------------------------------- |
| `IMAGE`     | IMAGE     | The generated image from DALL·E 3 |

***

**Source fingerprint (SHA-256):** `f100a8564689c2c54cc5c22df554af7e5c166bd4f15bc9234bade4d0819a09dd`


# OpenAIGPTImage1 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIGPTImage1

Complete documentation for the OpenAIGPTImage1 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIGPTImage1/en.md)

Generates images synchronously via OpenAI's GPT Image endpoint. This node can create new images from text prompts or edit existing images when provided with an input image and optional mask. It supports multiple GPT Image models, including gpt-image-1, gpt-image-1.5, and gpt-image-2.

## Inputs

| Parameter       | Data Type | Required | Range                                                                                                                                                        | Description                                                                                         |
| --------------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------- |
| `prompt`        | STRING    | Yes      | -                                                                                                                                                            | Text prompt for GPT Image (default: "")                                                             |
| `seed`          | INT       | No       | 0 to 2147483647                                                                                                                                              | Random seed for generation (default: 0) - not implemented yet in backend                            |
| `quality`       | COMBO     | No       | "low"<br />"medium"<br />"high"                                                                                                                              | Image quality, affects cost and generation time (default: "low")                                    |
| `background`    | COMBO     | No       | "auto"<br />"opaque"<br />"transparent"                                                                                                                      | Return image with or without background (default: "auto")                                           |
| `size`          | COMBO     | No       | "auto"<br />"1024x1024"<br />"1024x1536"<br />"1536x1024"<br />"2048x2048"<br />"2048x1152"<br />"1152x2048"<br />"3840x2160"<br />"2160x3840"<br />"Custom" | Image size. Select "Custom" to use the custom width and height (GPT Image 2 only) (default: "auto") |
| `n`             | INT       | No       | 1 to 8                                                                                                                                                       | How many images to generate (default: 1)                                                            |
| `image`         | IMAGE     | No       | -                                                                                                                                                            | Optional reference image for image editing                                                          |
| `mask`          | MASK      | No       | -                                                                                                                                                            | Optional mask for inpainting (white areas will be replaced)                                         |
| `model`         | COMBO     | No       | "gpt-image-1"<br />"gpt-image-1.5"<br />"gpt-image-2"                                                                                                        | GPT Image model to use (default: "gpt-image-2")                                                     |
| `custom_width`  | INT       | No       | 1024 to 3840                                                                                                                                                 | Used only when `size` is "Custom". Must be a multiple of 16 (GPT Image 2 only) (default: 1024)      |
| `custom_height` | INT       | No       | 1024 to 3840                                                                                                                                                 | Used only when `size` is "Custom". Must be a multiple of 16 (GPT Image 2 only) (default: 1024)      |

**Parameter Constraints:**

* When `image` is provided, the node switches to image editing mode
* `mask` can only be used when `image` is provided
* When using `mask`, only single images are supported (batch size must be 1)
* `mask` and `image` must be the same size
* Custom resolution (`size` = "Custom") is only supported by the gpt-image-2 model
* Custom width and height must be multiples of 16
* Custom resolution aspect ratio must not exceed 3:1
* Custom resolution total pixels must be between 655,360 and 8,294,400
* Transparent background is not supported for the gpt-image-2 model
* Sizes larger than 1536x1024 (e.g., 2048x2048, 3840x2160) are only supported by the gpt-image-2 model

## Outputs

| Output Name | Data Type | Description                  |
| ----------- | --------- | ---------------------------- |
| `IMAGE`     | IMAGE     | Generated or edited image(s) |

***

**Source fingerprint (SHA-256):** `826d393831ee38e97dad3ea238877d0aeb5bf16778612c51cdc0ca4816efead2`


# OpenAIGPTImageNodeV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIGPTImageNodeV2

Complete documentation for the OpenAIGPTImageNodeV2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIGPTImageNodeV2/en.md)

## Overview

This node generates images using OpenAI's GPT Image API. It supports multiple models, allows you to provide input images for editing, and can use a mask to specify which parts of an image to modify.

## Inputs

| Parameter             | Data Type | Required | Range                                                                                                                                                                            | Description                                                                                                         |
| --------------------- | --------- | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------- |
| `prompt`              | STRING    | Yes      | N/A                                                                                                                                                                              | Text prompt for GPT Image (default: "").                                                                            |
| `model`               | COMBO     | Yes      | `"gpt-image-2"`<br />`"gpt-image-1.5"`<br />`"gpt-image-1"`                                                                                                                      | The OpenAI GPT Image model to use. Selecting a model reveals additional parameters specific to that model.          |
| `model.size`          | COMBO     | Yes      | `"auto"`<br />`"1024x1024"`<br />`"1024x1536"`<br />`"1536x1024"`<br />`"2048x2048"`<br />`"2048x1152"`<br />`"1152x2048"`<br />`"3840x2160"`<br />`"2160x3840"`<br />`"Custom"` | Image size. Select 'Custom' to use the custom width and height (default: "auto"). Only available for `gpt-image-2`. |
| `model.custom_width`  | INT       | No       | 1024 to 3840                                                                                                                                                                     | Used only when `size` is 'Custom'. Must be a multiple of 16 (default: 1024). Only available for `gpt-image-2`.      |
| `model.custom_height` | INT       | No       | 1024 to 3840                                                                                                                                                                     | Used only when `size` is 'Custom'. Must be a multiple of 16 (default: 1024). Only available for `gpt-image-2`.      |
| `model.background`    | COMBO     | Yes      | `"auto"`<br />`"opaque"`                                                                                                                                                         | Return image with or without background (default: "auto"). Only available for `gpt-image-2`.                        |
| `model.quality`       | COMBO     | Yes      | `"standard"`<br />`"hd"`                                                                                                                                                         | The quality of the generated image. Only available for `gpt-image-2`.                                               |
| `model.images`        | IMAGE     | No       | N/A                                                                                                                                                                              | Input images for editing. Only available for `gpt-image-2`.                                                         |
| `model.mask`          | MASK      | No       | N/A                                                                                                                                                                              | A mask to specify which parts of the input image to edit. Only available for `gpt-image-2`.                         |
| `n`                   | INT       | Yes      | 1 to 8                                                                                                                                                                           | How many images to generate (default: 1).                                                                           |
| `seed`                | INT       | Yes      | 0 to 2147483647                                                                                                                                                                  | Seed for reproducibility (default: 0). Note: not implemented yet in backend.                                        |

**Parameter Constraints and Limitations:**

* When using `gpt-image-2` with a `model.size` of "Custom", the `custom_width` and `custom_height` must be multiples of 16, the maximum edge must be less than or equal to 3840, the aspect ratio must not exceed 3:1, and the total pixel count must be between 655,360 and 8,294,400.
* If a `mask` is provided, an input image (`model.images`) is required. A mask cannot be used without an input image.
* A mask cannot be used with multiple input images.
* When a mask is provided, the mask dimensions must match the input image dimensions.
* The `seed` parameter is currently not functional.

## Outputs

| Output Name | Data Type | Description                    |
| ----------- | --------- | ------------------------------ |
| `image`     | IMAGE     | The generated image or images. |

***

**Source fingerprint (SHA-256):** `dcea500ebbbbfe87f8b0dd2d714cf2356edf2030312c2cc6e41d64bd2ad04ea6`


# QuiverImageToSVGNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/QuiverImageToSVGNode

Complete documentation for the QuiverImageToSVGNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/QuiverImageToSVGNode/en.md)

This node converts a raster image into a scalable vector graphic (SVG) using Quiver AI's vectorization models. It sends the image to an external API which processes it and returns the vectorized result.

## Inputs

| Parameter   | Data Type    | Required | Range                      | Description                                                                                                                                                                                                                                 |
| ----------- | ------------ | -------- | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`     | IMAGE        | Yes      | N/A                        | Input image to vectorize.                                                                                                                                                                                                                   |
| `auto_crop` | BOOLEAN      | No       | `True`<br />`False`        | Automatically crop to the dominant subject. This is an advanced parameter (default: `False`).                                                                                                                                               |
| `model`     | DYNAMICCOMBO | Yes      | Multiple options available | Model to use for SVG vectorization. Selecting a model reveals additional parameters specific to that model: `target_size` (square resize target in pixels, default: 1024, range: 128-4096), `temperature`, `top_p`, and `presence_penalty`. |
| `seed`      | INT          | No       | 0 to 2147483647            | Seed to determine if the node should re-run; the actual results are nondeterministic regardless of the seed value. This parameter has "control after generate" functionality (default: 0).                                                  |

## Outputs

| Output Name | Data Type | Description                |
| ----------- | --------- | -------------------------- |
| `SVG`       | SVG       | The vectorized SVG output. |

***

**Source fingerprint (SHA-256):** `f2e411bd3ed235d04a94cb3e5c26990eb30404c3329e9c91e705d3039d2d8089`


# QuiverTextToSVGNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/QuiverTextToSVGNode

Complete documentation for the QuiverTextToSVGNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/QuiverTextToSVGNode/en.md)

The Quiver Text to SVG node generates a Scalable Vector Graphic (SVG) image from a text description using Quiver AI's models. You can optionally provide reference images and style instructions to guide the generation process.

## Inputs

| Parameter          | Data Type | Required | Range                                                                       | Description                                                                                                  |
| ------------------ | --------- | -------- | --------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------ |
| `prompt`           | STRING    | Yes      | N/A                                                                         | Text description of the desired SVG output. This is the main instruction for what to generate.               |
| `instructions`     | STRING    | No       | N/A                                                                         | Additional style or formatting guidance. This is an optional, advanced parameter.                            |
| `reference_images` | IMAGE     | No       | 0 to 4 images                                                               | Up to 4 reference images to guide the generation. This is an optional input.                                 |
| `model`            | COMBO     | Yes      | `"Quiver SVG v1"`<br />`"Quiver SVG v1 Max"`<br />`"Quiver SVG v1 Preview"` | Model to use for SVG generation. The available options are determined by the Quiver API.                     |
| `seed`             | INT       | Yes      | 0 to 2147483647                                                             | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed. Default: 0. |

**Note:** The `reference_images` input accepts a maximum of 4 images. If more are provided, the node will raise an error.

## Outputs

| Output Name | Data Type | Description                                        |
| ----------- | --------- | -------------------------------------------------- |
| `SVG`       | SVG       | The generated Scalable Vector Graphic (SVG) image. |

***

**Source fingerprint (SHA-256):** `dd5edd1be1c3cfd4b651896a1b020da7005f72097e0dcf09b947be0b771b8756`


# RandomCropImages - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RandomCropImages

Complete documentation for the RandomCropImages node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RandomCropImages/en.md)

The Random Crop Images node randomly selects a rectangular section from each input image and crops it to a specified width and height. This is commonly used for data augmentation to create variations of training images. The random position for the crop is determined by a seed value, ensuring the same crop can be reproduced.

## Inputs

| Parameter | Data Type | Required | Range                    | Description                                                            |
| --------- | --------- | -------- | ------------------------ | ---------------------------------------------------------------------- |
| `image`   | IMAGE     | Yes      | -                        | The image to be cropped.                                               |
| `width`   | INT       | No       | 1 - 8192                 | The width of the crop area (default: 512).                             |
| `height`  | INT       | No       | 1 - 8192                 | The height of the crop area (default: 512).                            |
| `seed`    | INT       | No       | 0 - 18446744073709551615 | A number used to control the random position of the crop (default: 0). |

**Note:** The `width` and `height` parameters must be less than or equal to the dimensions of the input image. If a specified dimension is larger than the image, the crop will be limited to the image's boundary.

## Outputs

| Output Name | Data Type | Description                                                 |
| ----------- | --------- | ----------------------------------------------------------- |
| `image`     | IMAGE     | The resulting image after the random crop has been applied. |

***

**Source fingerprint (SHA-256):** `8452a07a1cf66a520fb482f5239df3f33cfe3a77a28e289894ccd1d2544ecf40`


# RecraftColorRGB - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftColorRGB

Complete documentation for the RecraftColorRGB node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftColorRGB/en.md)

Create a Recraft color by specifying individual red, green, and blue values. This node takes RGB integer values (0-255) and converts them into a Recraft color format that can be used in other Recraft operations. You can also optionally provide an existing Recraft color chain to extend it with the new color.

## Inputs

| Parameter       | Data Type | Required | Range | Description                                                            |
| --------------- | --------- | -------- | ----- | ---------------------------------------------------------------------- |
| `r`             | INT       | Yes      | 0-255 | Red value of color (default: 0)                                        |
| `g`             | INT       | Yes      | 0-255 | Green value of color (default: 0)                                      |
| `b`             | INT       | Yes      | 0-255 | Blue value of color (default: 0)                                       |
| `recraft_color` | COLOR     | No       | -     | Optional existing Recraft color chain to extend with the new RGB color |

## Outputs

| Output Name     | Data Type | Description                                                                                                                       |
| --------------- | --------- | --------------------------------------------------------------------------------------------------------------------------------- |
| `recraft_color` | COLOR     | The created Recraft color object containing the specified RGB values, or the extended color chain if an existing one was provided |

***

**Source fingerprint (SHA-256):** `3c645f17232a1c646b6b64dab658a48dc4aa4c10c2daee9451977f824c3bf2c2`


# RecraftControls - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftControls

Complete documentation for the RecraftControls node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftControls/en.md)

Creates Recraft Controls for customizing Recraft generation. This node allows you to configure color settings that will be used during the Recraft image generation process.

## Inputs

| Parameter          | Data Type | Required | Range | Description                          |
| ------------------ | --------- | -------- | ----- | ------------------------------------ |
| `colors`           | COLOR     | No       | -     | Color settings for the main elements |
| `background_color` | COLOR     | No       | -     | Background color setting             |

## Outputs

| Output Name        | Data Type | Description                                               |
| ------------------ | --------- | --------------------------------------------------------- |
| `recraft_controls` | CONTROLS  | The configured Recraft controls containing color settings |

***

**Source fingerprint (SHA-256):** `3d07c8ca226e19849ebe5d37d93f129c77930a6971e58fe73abc2a47a58ee42e`


# RecraftCreateStyleNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftCreateStyleNode

Complete documentation for the RecraftCreateStyleNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftCreateStyleNode/en.md)

This node creates a custom style for image generation by uploading reference images. You can upload between 1 and 5 images to define the new style, and the node will return a unique style ID that can be used with other Recraft nodes. The total combined file size of all uploaded images must not exceed 5 MB.

## Inputs

| Parameter | Data Type | Required | Range                                             | Description                                                       |
| --------- | --------- | -------- | ------------------------------------------------- | ----------------------------------------------------------------- |
| `style`   | STRING    | Yes      | `"realistic_image"`<br />`"digital_illustration"` | The base style of the generated images.                           |
| `images`  | IMAGE     | Yes      | 1 to 5 images                                     | A set of 1 to 5 reference images used to create the custom style. |

**Note:** The total file size of all images in the `images` input must be less than 5 MB. The node will fail if this limit is exceeded.

## Outputs

| Output Name | Data Type | Description                                               |
| ----------- | --------- | --------------------------------------------------------- |
| `style_id`  | STRING    | The unique identifier for the newly created custom style. |

***

**Source fingerprint (SHA-256):** `9f6d6f87621b72fcbf19200e7b2461c9a22160311c77411e9ddd06ee2053dc63`


# RecraftCreativeUpscaleNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftCreativeUpscaleNode

Complete documentation for the RecraftCreativeUpscaleNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftCreativeUpscaleNode/en.md)

The Recraft Creative Upscale Image node enhances a raster image by increasing its resolution. It uses a "creative upscale" process that focuses on improving small details and faces within the image. This operation is performed synchronously through an external API.

## Inputs

| Parameter | Data Type | Required | Range | Description                     |
| --------- | --------- | -------- | ----- | ------------------------------- |
| `image`   | IMAGE     | Yes      |       | The input image to be upscaled. |

## Outputs

| Output Name | Data Type | Description                                         |
| ----------- | --------- | --------------------------------------------------- |
| `image`     | IMAGE     | The resulting upscaled image with enhanced details. |

***

**Source fingerprint (SHA-256):** `1dc5cd9d6f0c5a269d20ad94e417d31abc20c4ef8dd673f926ab4aceb2b6d924`


# RecraftCrispUpscaleNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftCrispUpscaleNode

Complete documentation for the RecraftCrispUpscaleNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftCrispUpscaleNode/en.md)

Upscale image synchronously. Enhances a given raster image using the 'crisp upscale' tool, increasing image resolution, making the image sharper and cleaner.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                |
| --------- | --------- | -------- | ----- | ---------------------------------------------------------- |
| `image`   | IMAGE     | Yes      | -     | The input image to be upscaled. Accepts a batch of images. |

## Outputs

| Output Name | Data Type | Description                                                                                                          |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------------------- |
| `image`     | IMAGE     | The upscaled image with enhanced resolution and clarity. Returns a batch of images if a batch was provided as input. |

***

**Source fingerprint (SHA-256):** `4683d62ca72ce624ad96b41e4abbbcf3df8c8e11f473f1729a675fba78a9ccc0`


# RecraftImageInpaintingNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftImageInpaintingNode

Complete documentation for the RecraftImageInpaintingNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftImageInpaintingNode/en.md)

This node modifies specific areas of an image based on a text prompt and a mask. It uses the Recraft API to intelligently edit only the masked regions while keeping the rest of the image unchanged.

## Inputs

| Parameter         | Data Type | Required | Range                  | Description                                                                                                  |
| ----------------- | --------- | -------- | ---------------------- | ------------------------------------------------------------------------------------------------------------ |
| `image`           | IMAGE     | Yes      | -                      | The input image to be modified                                                                               |
| `mask`            | MASK      | Yes      | -                      | The mask defining which areas of the image should be modified                                                |
| `prompt`          | STRING    | Yes      | -                      | Prompt for the image generation (default: empty string, maximum length: 1000 characters)                     |
| `n`               | INT       | Yes      | 1-6                    | The number of images to generate (default: 1, minimum: 1, maximum: 6)                                        |
| `seed`            | INT       | Yes      | 0-18446744073709551615 | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0) |
| `recraft_style`   | STYLEV3   | No       | -                      | Optional style parameter for the Recraft API. If not provided, defaults to "realistic\_image" style          |
| `negative_prompt` | STRING    | No       | -                      | An optional text description of undesired elements on an image (default: empty string)                       |

*Note: The `image` and `mask` must be provided together for the inpainting operation to work. The mask will be automatically resized to match the image dimensions. The `prompt` is validated and has a maximum length of 1000 characters. If a `style_id` from the Infinite Style Library is used, ensure it is not a Vector art style, as this may cause the API to return SVG data instead of an image.*

## Outputs

| Output Name | Data Type | Description                                                                                                                     |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------- |
| `image`     | IMAGE     | The modified image(s) generated based on the prompt and mask. Returns one image per input image multiplied by the `n` parameter |

***

**Source fingerprint (SHA-256):** `c0871ae6510d42f5525701dd622f2f84a65103a7eec053635c4bd64102a2a4e6`


# RecraftImageToImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftImageToImageNode

Complete documentation for the RecraftImageToImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftImageToImageNode/en.md)

This node modifies an existing image based on a text prompt and strength parameter. It uses the Recraft API to transform the input image according to the provided description while maintaining some similarity to the original image based on the strength setting.

## Inputs

| Parameter          | Data Type | Required | Range                  | Description                                                                                                                                            |
| ------------------ | --------- | -------- | ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `image`            | IMAGE     | Yes      | -                      | The input image to be modified                                                                                                                         |
| `prompt`           | STRING    | Yes      | -                      | Prompt for the image generation (default: "", max length: 1000 characters)                                                                             |
| `n`                | INT       | Yes      | 1-6                    | The number of images to generate (default: 1)                                                                                                          |
| `strength`         | FLOAT     | Yes      | 0.0-1.0                | Defines the difference with the original image, should lie in \[0, 1], where 0 means almost identical, and 1 means miserable similarity (default: 0.5) |
| `seed`             | INT       | Yes      | 0-18446744073709551615 | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0)                                           |
| `recraft_style`    | STYLEV3   | No       | -                      | Optional style selection for the image generation. If not provided, defaults to `realistic_image`                                                      |
| `negative_prompt`  | STRING    | No       | -                      | An optional text description of undesired elements on an image (default: "")                                                                           |
| `recraft_controls` | CONTROLS  | No       | -                      | Optional additional controls over the generation via the Recraft Controls node                                                                         |

**Note:** The `seed` parameter only triggers re-execution of the node but does not guarantee deterministic results. The strength parameter is rounded to 2 decimal places internally. The prompt is validated and must not exceed 1000 characters. If `recraft_style` is not provided, the node defaults to the `realistic_image` style. If you use a `style_id` from the Infinite Style Library, ensure it is not a Vector art style, as this may cause the node to receive SVG data instead of an image, resulting in an error.

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `image`     | IMAGE     | The generated image(s) based on the input image and prompt |

***

**Source fingerprint (SHA-256):** `15f0f42a1c217abcffeff3836ec77d8a94b37143fdff45d69e1a645f5ffac939`


# RecraftRemoveBackgroundNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftRemoveBackgroundNode

Complete documentation for the RecraftRemoveBackgroundNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftRemoveBackgroundNode/en.md)

This node removes the background from images using the Recraft API service. It processes each image in the input batch and returns both the processed images with transparent backgrounds and corresponding alpha masks that indicate the removed background areas.

## Inputs

| Parameter | Data Type | Required | Range | Description                                          |
| --------- | --------- | -------- | ----- | ---------------------------------------------------- |
| `image`   | IMAGE     | Yes      | -     | The input image(s) to process for background removal |

## Outputs

| Output Name | Data Type | Description                                                 |
| ----------- | --------- | ----------------------------------------------------------- |
| `image`     | IMAGE     | Processed images with transparent backgrounds               |
| `mask`      | MASK      | Alpha channel masks indicating the removed background areas |

***

**Source fingerprint (SHA-256):** `8bced9bb96c179101a2122fb5990cb3015313ad6ca888adf7a37b082b2e8a656`


# RecraftReplaceBackgroundNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftReplaceBackgroundNode

Complete documentation for the RecraftReplaceBackgroundNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftReplaceBackgroundNode/en.md)

Replace background on image, based on provided prompt. This node uses the Recraft API to generate new backgrounds for your images according to your text description, allowing you to completely transform the background while keeping the main subject intact.

## Inputs

| Parameter         | Data Type | Required | Range                  | Description                                                                                                  |
| ----------------- | --------- | -------- | ---------------------- | ------------------------------------------------------------------------------------------------------------ |
| `image`           | IMAGE     | Yes      | -                      | The input image to process                                                                                   |
| `prompt`          | STRING    | Yes      | -                      | Prompt for the image generation (default: empty)                                                             |
| `n`               | INT       | Yes      | 1-6                    | The number of images to generate (default: 1)                                                                |
| `seed`            | INT       | Yes      | 0-18446744073709551615 | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0) |
| `recraft_style`   | STYLEV3   | No       | -                      | Optional style selection for the generated background. If not provided, defaults to "realistic\_image" style |
| `negative_prompt` | STRING    | No       | -                      | An optional text description of undesired elements on an image (default: empty)                              |

**Note:** The `seed` parameter controls when the node re-executes but does not guarantee deterministic results due to the nature of the external API.

## Outputs

| Output Name | Data Type | Description                                     |
| ----------- | --------- | ----------------------------------------------- |
| `IMAGE`     | IMAGE     | The generated image(s) with replaced background |

***

**Source fingerprint (SHA-256):** `ce14005093aaac30de3de84c43bd46c0a3327d0ba8de4ea7ec62afa2028c1cae`


# RecraftStyleV3DigitalIllustration - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftStyleV3DigitalIllustration

Complete documentation for the RecraftStyleV3DigitalIllustration node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftStyleV3DigitalIllustration/en.md)

This node configures a style for use with the Recraft API, specifically selecting the "digital\_illustration" style. It allows you to choose an optional substyle to further refine the artistic direction of the generated image.

## Inputs

| Parameter  | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           | Description                                                                                                                                 |
| ---------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- |
| `substyle` | STRING    | No       | `"digital_illustration"`<br />`"digital_illustration_anime"`<br />`"digital_illustration_cartoon"`<br />`"digital_illustration_comic"`<br />`"digital_illustration_concept_art"`<br />`"digital_illustration_fantasy"`<br />`"digital_illustration_futuristic"`<br />`"digital_illustration_graffiti"`<br />`"digital_illustration_graphic_novel"`<br />`"digital_illustration_hyperrealistic"`<br />`"digital_illustration_ink"`<br />`"digital_illustration_manga"`<br />`"digital_illustration_minimalist"`<br />`"digital_illustration_pixel_art"`<br />`"digital_illustration_pop_art"`<br />`"digital_illustration_retro"`<br />`"digital_illustration_sci_fi"`<br />`"digital_illustration_sticker"`<br />`"digital_illustration_street_art"`<br />`"digital_illustration_surreal"`<br />`"digital_illustration_vector"` | An optional substyle to specify a particular type of digital illustration. If not selected, the base "digital\_illustration" style is used. |

## Outputs

| Output Name     | Data Type | Description                                                                                                                                           |
| --------------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- |
| `recraft_style` | STYLEV3   | A configured style object containing the selected "digital\_illustration" style and optional substyle, ready to be passed to other Recraft API nodes. |

***

**Source fingerprint (SHA-256):** `167b5f875e1d9ec39dd830d98349fe34b23a3ac870cff8329bc834fe13a5fc8f`


# RecraftStyleV3InfiniteStyleLibrary - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftStyleV3InfiniteStyleLibrary

Complete documentation for the RecraftStyleV3InfiniteStyleLibrary node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftStyleV3InfiniteStyleLibrary/en.md)

This node allows you to select a style from Recraft's Infinite Style Library using a preexisting UUID. It retrieves the style information based on the provided style identifier and returns it for use in other Recraft nodes.

## Inputs

| Parameter  | Data Type | Required | Range          | Description                                |
| ---------- | --------- | -------- | -------------- | ------------------------------------------ |
| `style_id` | STRING    | Yes      | Any valid UUID | UUID of style from Infinite Style Library. |

**Note:** The `style_id` input cannot be empty. If an empty string is provided, the node will raise an exception.

## Outputs

| Output Name     | Data Type | Description                                                     |
| --------------- | --------- | --------------------------------------------------------------- |
| `recraft_style` | STYLEV3   | The selected style object from Recraft's Infinite Style Library |

***

**Source fingerprint (SHA-256):** `c613e153fa56f403367f132a2592b853327a28cc640faab061dfe373b0202e21`


# RecraftStyleV3LogoRaster - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftStyleV3LogoRaster

Complete documentation for the RecraftStyleV3LogoRaster node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftStyleV3LogoRaster/en.md)

This node selects the logo raster style and an optional substyle for generating logo images. It specializes in creating logo designs with raster-based visual treatments.

## Inputs

| Parameter  | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | Description                                                                        |
| ---------- | --------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------- |
| `substyle` | STRING    | Yes      | `"none"`<br />`"bold"`<br />`"minimal"`<br />`"vibrant"`<br />`"handdrawn"`<br />`"geometric"`<br />`"vintage"`<br />`"neon"`<br />`"gradient"`<br />`"flat"`<br />`"outline"`<br />`"mascot"`<br />`"badge"`<br />`"abstract"`<br />`"retro"`<br />`"modern"`<br />`"playful"`<br />`"luxury"`<br />`"tech"`<br />`"nature"`<br />`"food"`<br />`"sport"`<br />`"fashion"`<br />`"music"`<br />`"travel"`<br />`"education"`<br />`"health"`<br />`"finance"`<br />`"realestate"`<br />`"nonprofit"` | The specific logo raster substyle to apply for logo generation (default: `"none"`) |

## Outputs

| Output Name     | Data Type | Description                                                                                   |
| --------------- | --------- | --------------------------------------------------------------------------------------------- |
| `recraft_style` | CUSTOM    | The selected Recraft style configuration, including the logo raster style and chosen substyle |

***

**Source fingerprint (SHA-256):** `a9912e3a9f634cf3e4402cc71e934a636a448ecbfa7664f5167289d4526e4d4f`


# RecraftStyleV3RealisticImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftStyleV3RealisticImage

Complete documentation for the RecraftStyleV3RealisticImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftStyleV3RealisticImage/en.md)

This node creates a style configuration for generating realistic images using Recraft's API. It selects the `realistic_image` style and lets you choose an optional substyle to fine-tune the output appearance.

## Inputs

| Parameter  | Data Type | Required | Range                                                  | Description                                                                                                  |
| ---------- | --------- | -------- | ------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------ |
| `substyle` | STRING    | Yes      | Multiple options available (determined by Recraft API) | The specific substyle to apply to the realistic\_image style. If set to "None", no substyle will be applied. |

## Outputs

| Output Name     | Data Type | Description                                                                                                                                                                                    |
| --------------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `recraft_style` | STYLEV3   | A Recraft style configuration object containing the `realistic_image` style and the selected substyle settings. This output can be connected to other Recraft nodes that accept a style input. |

***

**Source fingerprint (SHA-256):** `967e52e32456299da342a3d87f46f180f17aa1505cb2a3d22ee5f50cda79e8e3`


# RecraftStyleV3VectorIllustrationNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftStyleV3VectorIllustrationNode

Complete documentation for the RecraftStyleV3VectorIllustrationNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftStyleV3VectorIllustrationNode/en.md)

This node configures a style for use with the Recraft API, specifically selecting the `vector_illustration` style. It allows you to optionally choose a more specific substyle within that category. The node outputs a style configuration object that can be passed to other Recraft API nodes.

## Inputs

| Parameter  | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        | Description                                                                                                                                |
| ---------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------ |
| `substyle` | STRING    | No       | `"vector_illustration"`<br />`"vector_illustration_flat"`<br />`"vector_illustration_3d"`<br />`"vector_illustration_hand_drawn"`<br />`"vector_illustration_retro"`<br />`"vector_illustration_modern"`<br />`"vector_illustration_abstract"`<br />`"vector_illustration_geometric"`<br />`"vector_illustration_organic"`<br />`"vector_illustration_minimalist"`<br />`"vector_illustration_detailed"`<br />`"vector_illustration_colorful"`<br />`"vector_illustration_monochrome"`<br />`"vector_illustration_grayscale"`<br />`"vector_illustration_pastel"`<br />`"vector_illustration_vibrant"`<br />`"vector_illustration_muted"`<br />`"vector_illustration_warm"`<br />`"vector_illustration_cool"`<br />`"vector_illustration_neutral"`<br />`"vector_illustration_bold"`<br />`"vector_illustration_subtle"`<br />`"vector_illustration_playful"`<br />`"vector_illustration_serious"`<br />`"vector_illustration_elegant"`<br />`"vector_illustration_rustic"`<br />`"vector_illustration_urban"`<br />`"vector_illustration_nature"`<br />`"vector_illustration_fantasy"`<br />`"vector_illustration_sci_fi"`<br />`"vector_illustration_historical"`<br />`"vector_illustration_futuristic"`<br />`"vector_illustration_whimsical"`<br />`"vector_illustration_surreal"`<br />`"vector_illustration_realistic"`<br />`"vector_illustration_stylized"`<br />`"vector_illustration_cartoony"`<br />`"vector_illustration_anime"`<br />`"vector_illustration_comic"`<br />`"vector_illustration_pixel"`<br />`"vector_illustration_low_poly"`<br />`"vector_illustration_high_poly"`<br />`"vector_illustration_isometric"`<br />`"vector_illustration_orthographic"`<br />`"vector_illustration_perspective"`<br />`"vector_illustration_2d"`<br />`"vector_illustration_2.5d"`<br />`"vector_illustration_3d"`<br />`"vector_illustration_4d"` | An optional, more specific style within the `vector_illustration` category. If not selected, the base `vector_illustration` style is used. |

## Outputs

| Output Name     | Data Type | Description                                                                                                                                                       |
| --------------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `recraft_style` | STYLEV3   | A Recraft API style configuration object containing the selected `vector_illustration` style and optional substyle. This can be connected to other Recraft nodes. |

***

**Source fingerprint (SHA-256):** `c57ffa5504fff8430f8193f97d4d991b9373e688a4b412ff4926ef356aef0dc9`


# RecraftTextToImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftTextToImageNode

Complete documentation for the RecraftTextToImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftTextToImageNode/en.md)

Generates images synchronously based on prompt and resolution. This node connects to the Recraft API to create images from text descriptions with specified dimensions and optional style and control parameters.

## Inputs

| Parameter          | Data Type         | Required | Range                                                                                                                                       | Description                                                                                                   |
| ------------------ | ----------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- |
| `prompt`           | STRING            | Yes      | -                                                                                                                                           | Prompt for the image generation. (default: "")                                                                |
| `size`             | COMBO             | Yes      | "1024x1024"<br />"1152x896"<br />"896x1152"<br />"1216x832"<br />"832x1216"<br />"1344x768"<br />"768x1344"<br />"1536x640"<br />"640x1536" | The size of the generated image. (default: "1024x1024")                                                       |
| `n`                | INT               | Yes      | 1-6                                                                                                                                         | The number of images to generate. (default: 1)                                                                |
| `seed`             | INT               | Yes      | 0-18446744073709551615                                                                                                                      | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed. (default: 0) |
| `recraft_style`    | RECRAFT\_STYLE    | No       | Multiple options available                                                                                                                  | Optional style selection for image generation. When not provided, defaults to "realistic\_image" style.       |
| `negative_prompt`  | STRING            | No       | -                                                                                                                                           | An optional text description of undesired elements on an image. (default: "")                                 |
| `recraft_controls` | RECRAFT\_CONTROLS | No       | Multiple options available                                                                                                                  | Optional additional controls over the generation via the Recraft Controls node.                               |

**Note:** The `seed` parameter only controls when the node re-runs but does not make the image generation deterministic. The actual output images will vary even with the same seed value.

**Note:** The `prompt` parameter must be between 1 and 1000 characters in length.

**Note:** If you use a `style_id` from the Infinite Style Library, ensure it is not a Vector art style, as this will return SVG data instead of an image and cause an error.

## Outputs

| Output Name | Data Type | Description                                                                                                                                     |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| `IMAGE`     | IMAGE     | The generated image(s) as a batched tensor output. When multiple images are generated (n > 1), they are concatenated along the batch dimension. |

***

**Source fingerprint (SHA-256):** `946010fbb6a5b99eed11e74de0733f64a270fa62910acf942749c76e0b5448f3`


# RecraftTextToVectorNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftTextToVectorNode

Complete documentation for the RecraftTextToVectorNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftTextToVectorNode/en.md)

Generates SVG vector illustrations synchronously based on a text prompt and resolution. This node sends your prompt to the Recraft API and returns the generated SVG content.

## Inputs

| Parameter          | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   | Description                                                                                                                                      |
| ------------------ | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ |
| `prompt`           | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       | Prompt for the image generation. (default: "")                                                                                                   |
| `substyle`         | COMBO     | Yes      | `"2d_character"`<br />`"2d_gradient"`<br />`"2d_illustration"`<br />`"2d_flat_character"`<br />`"2d_flat_illustration"`<br />`"2d_art"`<br />`"2d_art_character"`<br />`"2d_pattern"`<br />`"2d_pixel_art"`<br />`"2d_cyberpunk"`<br />`"2d_engraving"`<br />`"2d_black_and_white"`<br />`"2d_ink"`<br />`"2d_sketch"`<br />`"2d_watercolor"`<br />`"2d_animation"`<br />`"2d_comic"`<br />`"2d_children_illustration"`<br />`"2d_vintage"`<br />`"2d_retro"`<br />`"2d_hand_drawn"`<br />`"2d_psychedelic"`<br />`"2d_graffiti"`<br />`"2d_ukiyo_e"`<br />`"2d_woodcut"`<br />`"2d_art_deco"`<br />`"2d_art_nouveau"`<br />`"2d_bauhaus"`<br />`"2d_constructivism"`<br />`"2d_cubism"`<br />`"2d_futurism"`<br />`"2d_glitch"`<br />`"2d_impressionism"`<br />`"2d_naive"`<br />`"2d_pointillism"`<br />`"2d_pop_art"`<br />`"2d_realism"`<br />`"2d_renaissance"`<br />`"2d_rococo"`<br />`"2d_romanticism"`<br />`"2d_surrealism"`<br />`"2d_suprematism"`<br />`"2d_symbolism"`<br />`"2d_expressionism"`<br />`"2d_abstract"`<br />`"2d_minimalism"`<br />`"2d_contemporary"`<br />`"2d_modern"`<br />`"2d_brutalism"`<br />`"2d_metaphysical"`<br />`"2d_mannerism"`<br />`"2d_baroque"`<br />`"2d_neoclassicism"`<br />`"2d_orientalism"`<br />`"2d_primitivism"`<br />`"2d_fauvism"`<br />`"2d_rayonism"`<br />`"2d_orphism"`<br />`"2d_vorticism"`<br />`"2d_dadaism"`<br />`"2d_neo_expressionism"`<br />`"2d_transavantgarde"`<br />`"2d_new_wild"`<br />`"2d_graffiti_classic"`<br />`"2d_graffiti_modern"`<br />`"2d_graffiti_wildstyle"`<br />`"2d_graffiti_bubble"`<br />`"2d_graffiti_throwup"`<br />`"2d_graffiti_tag"`<br />`"2d_graffiti_blockbuster"`<br />`"2d_graffiti_mural"`<br />`"2d_graffiti_stencil"`<br />`"2d_graffiti_3d"`<br />`"2d_graffiti_character"`<br />`"2d_graffiti_abstract"`<br />`"2d_graffiti_urban"`<br />`"2d_graffiti_neo_muralism"`<br />`"2d_graffiti_post_graffiti"`<br />`"2d_graffiti_street_art"` | The specific vector illustration style to use for generation.                                                                                    |
| `size`             | COMBO     | Yes      | `"1024x1024"`<br />`"1024x2048"`<br />`"2048x1024"`<br />`"2048x2048"`<br />`"512x512"`<br />`"512x1024"`<br />`"1024x512"`<br />`"2048x512"`<br />`"512x2048"`                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         | The size of the generated image. (default: "1024x1024")                                                                                          |
| `n`                | INT       | Yes      | 1-6                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     | The number of images to generate. (default: 1, min: 1, max: 6)                                                                                   |
| `seed`             | INT       | Yes      | 0-18446744073709551615                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed. (default: 0, min: 0, max: 18446744073709551615) |
| `negative_prompt`  | STRING    | No       | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       | An optional text description of undesired elements on an image. (default: "")                                                                    |
| `recraft_controls` | CONTROLS  | No       | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       | Optional additional controls over the generation via the Recraft Controls node.                                                                  |

**Note:** The `seed` parameter only controls when the node re-runs but does not make the generation results deterministic.

## Outputs

| Output Name | Data Type | Description                                     |
| ----------- | --------- | ----------------------------------------------- |
| `SVG`       | SVG       | The generated vector illustration in SVG format |

***

**Source fingerprint (SHA-256):** `b7b89e929a6d8dba78c0078962c9dde5c803bcff51350b0fb21c0cbd4c725ffe`


# RecraftV4TextToImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftV4TextToImageNode

Complete documentation for the RecraftV4TextToImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftV4TextToImageNode/en.md)

This node generates images from text descriptions using the Recraft V4 or V4 Pro AI models. It sends your prompt to an external API and returns the generated images. You can control the output by specifying the model, image size, and number of images to create.

## Inputs

| Parameter          | Data Type | Required | Range                                | Description                                                                                                                                                                        |
| ------------------ | --------- | -------- | ------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`           | STRING    | Yes      | N/A                                  | Prompt for the image generation. Maximum 10,000 characters.                                                                                                                        |
| `negative_prompt`  | STRING    | No       | N/A                                  | An optional text description of undesired elements on an image.                                                                                                                    |
| `model`            | COMBO     | Yes      | `"recraftv4"`<br />`"recraftv4_pro"` | The model to use for generation. Selecting a model determines the available image sizes.                                                                                           |
| `size`             | COMBO     | Yes      | Varies by model                      | The size of the generated image. The available options depend on the selected model. For `recraftv4`, the default is "1024x1024". For `recraftv4_pro`, the default is "2048x2048". |
| `n`                | INT       | Yes      | 1 to 6                               | The number of images to generate (default: 1).                                                                                                                                     |
| `seed`             | INT       | Yes      | 0 to 18446744073709551615            | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0).                                                                      |
| `recraft_controls` | CUSTOM    | No       | N/A                                  | Optional additional controls over the generation via the Recraft Controls node.                                                                                                    |

**Note:** The `size` parameter is a dynamic input whose available options change based on the selected `model`. The `seed` value does not guarantee reproducible image outputs.

## Outputs

| Output Name | Data Type | Description                             |
| ----------- | --------- | --------------------------------------- |
| `output`    | IMAGE     | The generated image or batch of images. |

***

**Source fingerprint (SHA-256):** `b116fc35810d9cd246742b3ee1e3ce5472e79a467981ffb994cd1e2c53f0f086`


# RecraftV4TextToVectorNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftV4TextToVectorNode

Complete documentation for the RecraftV4TextToVectorNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftV4TextToVectorNode/en.md)

The Recraft V4 Text to Vector node generates Scalable Vector Graphics (SVG) illustrations from a text description. It connects to an external API to use either the Recraft V4 or Recraft V4 Pro model for image generation. The node outputs one or more SVG images based on your prompt.

## Inputs

| Parameter          | Data Type | Required | Range                                                                                                                                                                                                                                                                                                          | Description                                                                                                                                                            |
| ------------------ | --------- | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`           | STRING    | Yes      | N/A                                                                                                                                                                                                                                                                                                            | Prompt for the image generation. Maximum 10,000 characters.                                                                                                            |
| `negative_prompt`  | STRING    | No       | N/A                                                                                                                                                                                                                                                                                                            | An optional text description of undesired elements on an image.                                                                                                        |
| `model`            | COMBO     | Yes      | `"recraftv4"`<br />`"recraftv4_pro"`                                                                                                                                                                                                                                                                           | The model to use for generation. Selecting a model changes the available `size` options.                                                                               |
| `size`             | COMBO     | Yes      | For `recraftv4`: `"1024x1024"`, `"1152x896"`, `"896x1152"`, `"1216x832"`, `"832x1216"`, `"1344x768"`, `"768x1344"`, `"1536x640"`, `"640x1536"`<br />For `recraftv4_pro`: `"2048x2048"`, `"2304x1792"`, `"1792x2304"`, `"2432x1664"`, `"1664x2432"`, `"2688x1536"`, `"1536x2688"`, `"3072x1280"`, `"1280x3072"` | The size of the generated image. The available options depend on the selected `model`. Default is `"1024x1024"` for `recraftv4` and `"2048x2048"` for `recraftv4_pro`. |
| `n`                | INT       | Yes      | 1 to 6                                                                                                                                                                                                                                                                                                         | The number of images to generate (default: 1).                                                                                                                         |
| `seed`             | INT       | Yes      | 0 to 18446744073709551615                                                                                                                                                                                                                                                                                      | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed.                                                                       |
| `recraft_controls` | CUSTOM    | No       | N/A                                                                                                                                                                                                                                                                                                            | Optional additional controls over the generation via the Recraft Controls node.                                                                                        |

**Note:** The `size` parameter is a dynamic input whose available options change based on the selected `model`. The `seed` value does not guarantee reproducible results from the external API.

## Outputs

| Output Name | Data Type | Description                                            |
| ----------- | --------- | ------------------------------------------------------ |
| `output`    | SVG       | The generated Scalable Vector Graphics (SVG) image(s). |

***

**Source fingerprint (SHA-256):** `e2524f2607068f2115cf7a192cb9a4f77fbe4e2535108e3c7167923d599fd212`


# RecraftVectorizeImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RecraftVectorizeImageNode

Complete documentation for the RecraftVectorizeImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RecraftVectorizeImageNode/en.md)

Generates SVG vector graphics from an input image. This node converts raster images into scalable vector format by sending each image to the Recraft API and combining the results into a single SVG output.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                             |
| --------- | --------- | -------- | ----- | --------------------------------------------------------------------------------------- |
| `image`   | IMAGE     | Yes      | -     | The input image to convert to SVG format. Supports batch processing of multiple images. |

## Outputs

| Output Name | Data Type | Description                                                                                     |
| ----------- | --------- | ----------------------------------------------------------------------------------------------- |
| `SVG`       | SVG       | The generated vector graphics output combining all processed images into a single SVG document. |

***

**Source fingerprint (SHA-256):** `de221f8156396cd3c95b30840e446811c2a5f8f09d66028cbc2dbe2a551fc4cd`


# ResizeAndPadImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResizeAndPadImage

Complete documentation for the ResizeAndPadImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResizeAndPadImage/en.md)

The ResizeAndPadImage node resizes an image to fit within specified dimensions while maintaining its original aspect ratio. It scales the image down proportionally to fit within the target width and height, then adds padding around the edges to fill any remaining space. The padding color and interpolation method can be customized to control the appearance of the padded areas and the quality of the resizing.

## Inputs

| Parameter       | Data Type | Required | Range                                                                     | Description                                                                    |
| --------------- | --------- | -------- | ------------------------------------------------------------------------- | ------------------------------------------------------------------------------ |
| `image`         | IMAGE     | Yes      | -                                                                         | The input image to be resized and padded                                       |
| `target_width`  | INT       | Yes      | 1 to MAX\_RESOLUTION                                                      | The desired width of the output image (default: 512)                           |
| `target_height` | INT       | Yes      | 1 to MAX\_RESOLUTION                                                      | The desired height of the output image (default: 512)                          |
| `padding_color` | COMBO     | Yes      | "white"<br />"black"                                                      | The color to use for padding areas around the resized image (default: "white") |
| `interpolation` | COMBO     | Yes      | "area"<br />"bicubic"<br />"nearest-exact"<br />"bilinear"<br />"lanczos" | The interpolation method used for resizing the image (default: "area")         |

## Outputs

| Output Name | Data Type | Description                         |
| ----------- | --------- | ----------------------------------- |
| `image`     | IMAGE     | The resized and padded output image |

***

**Source fingerprint (SHA-256):** `cc516caee9f466d557e1c8e3c7fcef25acc1e33d181bc4b100302dc93530cb95`


# ResizeImagesByLongerEdge - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResizeImagesByLongerEdge

Complete documentation for the ResizeImagesByLongerEdge node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResizeImagesByLongerEdge/en.md)

The Resize Images by Longer Edge node resizes one or more images so that their longest side matches a specified target length. It automatically determines whether the width or height is longer and scales the other dimension proportionally to preserve the original aspect ratio. This node is deprecated and superseded by the Resize Image/Mask node with the resize type set to "scale longer dimension".

## Inputs

| Parameter     | Data Type | Required | Range    | Description                                                                                           |
| ------------- | --------- | -------- | -------- | ----------------------------------------------------------------------------------------------------- |
| `image`       | IMAGE     | Yes      | -        | The input image or batch of images to be resized.                                                     |
| `longer_edge` | INT       | Yes      | 1 - 8192 | Target dimension for the longer edge. The shorter edge will be scaled proportionally. (default: 1024) |

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                 |
| ----------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`     | IMAGE     | The resized image or batch of images. The output will have the same number of images as the input, with each one's longer edge matching the specified `longer_edge` length. |

***

**Source fingerprint (SHA-256):** `bf66808acbc654d5a9ea58b062b5b89d6c13dbec0929d6d92aaa3c8914dcece0`


# ResizeImagesByShorterEdge - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResizeImagesByShorterEdge

Complete documentation for the ResizeImagesByShorterEdge node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResizeImagesByShorterEdge/en.md)

This node resizes images so that the shorter edge matches a specified length while preserving the original aspect ratio. It calculates new dimensions based on the target length for the shorter side and returns the resized image.

## Inputs

| Parameter      | Data Type | Required | Range     | Description                                           |
| -------------- | --------- | -------- | --------- | ----------------------------------------------------- |
| `image`        | IMAGE     | Yes      | -         | The input image to be resized.                        |
| `shorter_edge` | INT       | Yes      | 1 to 8192 | Target dimension for the shorter edge. (default: 512) |

## Outputs

| Output Name | Data Type | Description                                                                   |
| ----------- | --------- | ----------------------------------------------------------------------------- |
| `image`     | IMAGE     | The resized image with the shorter edge matching the specified target length. |

***

**Source fingerprint (SHA-256):** `6bb3e1c974108ee7b75b47406ea02b3f47ca14305f9ee54d3d379eefbb7f26cd`


# ReveImageCreateNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReveImageCreateNode

Complete documentation for the ReveImageCreateNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReveImageCreateNode/en.md)

The Reve Image Create node generates images from text descriptions using the Reve AI model. It sends a text prompt to the Reve API and returns the generated image. You can control the image's aspect ratio and apply optional post-processing effects like upscaling and background removal.

## Inputs

| Parameter           | Data Type | Required | Range                                                                                   | Description                                                                                                                              |
| ------------------- | --------- | -------- | --------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`            | STRING    | Yes      | N/A                                                                                     | Text description of the desired image. Maximum 2560 characters.                                                                          |
| `model`             | COMBO     | Yes      | `"reve-create@20250915"`                                                                | Model version to use for generation. The aspect ratio is selected from the available options within this parameter.                      |
| `aspect_ratio`      | COMBO     | Yes      | `"3:2"`<br />`"16:9"`<br />`"9:16"`<br />`"2:3"`<br />`"4:3"`<br />`"3:4"`<br />`"1:1"` | The desired aspect ratio for the generated image.                                                                                        |
| `test_time_scaling` | COMBO     | Yes      | `"disabled"`<br />`"enabled"`                                                           | Enables or disables test-time scaling, which can improve image quality at the cost of longer generation time.                            |
| `upscale`           | COMBO     | No       | `"disabled"`<br />`"enabled"`                                                           | Enables or disables the upscaling post-processing step. When enabled, you must also select an upscale factor.                            |
| `upscale_factor`    | COMBO     | No       | `2`<br />`3`<br />`4`                                                                   | The factor by which to increase the image's resolution. This parameter is only active when `upscale` is set to `"enabled"`.              |
| `remove_background` | BOOLEAN   | No       | N/A                                                                                     | When enabled, applies a background removal post-processing step to the generated image.                                                  |
| `seed`              | INT       | No       | 0 to 2147483647                                                                         | A seed value that controls whether the node should re-run. Note: Results are non-deterministic regardless of the seed value. Default: 0. |

**Note:** The `upscale_factor` parameter is dependent on the `upscale` parameter being set to `"enabled"`. The `seed` parameter does not guarantee deterministic outputs.

## Outputs

| Output Name | Data Type | Description                                                      |
| ----------- | --------- | ---------------------------------------------------------------- |
| `image`     | IMAGE     | The image generated by the Reve model based on the input prompt. |

***

**Source fingerprint (SHA-256):** `69c81413cb345b7ecd92055e244f89d5b33f2bd67ee83e4225dd7c2168b55d5a`


# ReveImageEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReveImageEditNode

Complete documentation for the ReveImageEditNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReveImageEditNode/en.md)

The Reve Image Edit node allows you to modify an existing image based on a text description. It uses the Reve API to interpret your instructions and apply the requested changes to the image you provide.

## Inputs

| Parameter                 | Data Type | Required | Range                                                                                                 | Description                                                                                                  |
| ------------------------- | --------- | -------- | ----------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------ |
| `image`                   | IMAGE     | Yes      | -                                                                                                     | The image to edit.                                                                                           |
| `edit_instruction`        | STRING    | Yes      | -                                                                                                     | Text description of how to edit the image. Maximum 2560 characters.                                          |
| `model`                   | MODEL     | Yes      | `"reve-edit@20250915"`<br />`"reve-edit-fast@20251030"`                                               | Model version to use for editing.                                                                            |
| `model.aspect_ratio`      | COMBO     | No       | `"auto"`<br />`"16:9"`<br />`"9:16"`<br />`"3:2"`<br />`"2:3"`<br />`"4:3"`<br />`"3:4"`<br />`"1:1"` | The aspect ratio for the edited image. When set to "auto", the aspect ratio is determined automatically.     |
| `model.test_time_scaling` | FLOAT     | No       | -                                                                                                     | Test-time scaling factor for the model. Higher values may improve quality but increase processing time.      |
| `upscale`                 | COMBO     | No       | `"disabled"`<br />`"enabled"`                                                                         | Controls whether to upscale the generated image.                                                             |
| `upscale.upscale_factor`  | FLOAT     | No       | -                                                                                                     | The factor by which to upscale the image when upscaling is enabled.                                          |
| `remove_background`       | BOOLEAN   | No       | -                                                                                                     | Controls whether to remove the background from the generated image.                                          |
| `seed`                    | INT       | No       | 0 to 2147483647                                                                                       | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) |

**Note:** The `upscale.upscale_factor` parameter is only relevant when the `upscale` parameter is set to `"enabled"`.

## Outputs

| Output Name | Data Type | Description                                          |
| ----------- | --------- | ---------------------------------------------------- |
| `image`     | IMAGE     | The edited image generated based on the instruction. |

***

**Source fingerprint (SHA-256):** `21fbe9e23e952eb0132d31a295505a38a6d3640396865d00b999135d0722166f`


# ReveImageRemixNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReveImageRemixNode

Complete documentation for the ReveImageRemixNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReveImageRemixNode/en.md)

The Reve Image Remix node uses the Reve API to generate a new image. It combines one or more reference images with a text prompt to create a new, remixed image based on the provided description.

## Inputs

| Parameter           | Data Type | Required | Range                                                 | Description                                                                                                                                                                    |
| ------------------- | --------- | -------- | ----------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `reference_images`  | IMAGE     | Yes      | 1 to 6 images                                         | One or more reference images to use as a base for the remix. You can add between 1 and 6 images.                                                                               |
| `prompt`            | STRING    | Yes      | 1 to 2560 characters                                  | A text description of the desired image. You can include XML `<img>` tags to reference specific images by their index (e.g., `<img>0</img>`, `<img>1</img>`). (default: empty) |
| `model`             | COMBO     | Yes      | `reve-remix@20250915`<br />`reve-remix-fast@20251030` | The model version to use for remixing. Each model option includes configurable aspect ratios and test-time scaling.                                                            |
| `upscale`           | COMBO     | No       | `"disabled"`<br />`"enabled"`                         | Controls whether to upscale the generated image. When enabled, you can select an upscale factor.                                                                               |
| `remove_background` | BOOLEAN   | No       | `true`<br />`false`                                   | When enabled, attempts to remove the background from the generated image.                                                                                                      |
| `seed`              | INT       | No       | 0 to 2147483647                                       | A seed value. Changing this value will cause the node to re-run, but the results are non-deterministic regardless of seed. (default: 0)                                        |

**Note:** The `model` parameter is a dynamic combo that includes nested settings for `aspect_ratio` (options: "auto", "16:9", "9:16", "3:2", "2:3", "4:3", "3:4", "1:1") and `test_time_scaling`. The `upscale` parameter, when set to "enabled", reveals a nested `upscale_factor` setting.

## Outputs

| Output Name | Data Type | Description                                        |
| ----------- | --------- | -------------------------------------------------- |
| `image`     | IMAGE     | The new image generated by the Reve remix process. |

***

**Source fingerprint (SHA-256):** `eb69d653812ecd63c66be9290233a820a4d0145bdd5be1e23601d8cdd5eb228a`


# RunwayTextToImageNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RunwayTextToImageNode

Complete documentation for the RunwayTextToImageNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RunwayTextToImageNode/en.md)

The Runway Text to Image node generates images from text prompts using Runway's Gen 4 model. You can provide a text description and optionally include a reference image to guide the image generation process. The node handles the API communication and returns the generated image.

## Inputs

| Parameter         | Data Type | Required | Range                                                                                             | Description                                      |
| ----------------- | --------- | -------- | ------------------------------------------------------------------------------------------------- | ------------------------------------------------ |
| `prompt`          | STRING    | Yes      | -                                                                                                 | Text prompt for the generation (default: "")     |
| `ratio`           | COMBO     | Yes      | "16:9"<br />"1:1"<br />"21:9"<br />"2:3"<br />"3:2"<br />"4:5"<br />"5:4"<br />"9:16"<br />"9:21" | Aspect ratio for the generated image             |
| `reference_image` | IMAGE     | No       | -                                                                                                 | Optional reference image to guide the generation |

**Note:** The reference image must have dimensions not exceeding 7999x7999 pixels and an aspect ratio between 0.5 and 2.0. When a reference image is provided, it guides the image generation process.

## Outputs

| Output Name | Data Type | Description                                                               |
| ----------- | --------- | ------------------------------------------------------------------------- |
| `output`    | IMAGE     | The generated image based on the text prompt and optional reference image |

***

**Source fingerprint (SHA-256):** `212eec9ae7ae3df06cefacae361cfd1f623ea7b6b1ca0e4beb4f5b7df76226e5`


# SolidMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SolidMask

Complete documentation for the SolidMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The SolidMask node generates a uniform mask with a specified value across its entire area. It's designed to create masks of specific dimensions and intensity, useful in various image processing and masking tasks.

## Inputs

| Parameter | Data Type | Description                                                                                                       |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------------- |
| `value`   | FLOAT     | Specifies the intensity value of the mask, affecting its overall appearance and utility in subsequent operations. |
| `width`   | INT       | Determines the width of the generated mask, directly influencing its size and aspect ratio.                       |
| `height`  | INT       | Sets the height of the generated mask, affecting its size and aspect ratio.                                       |

## Outputs

| Parameter | Data Type | Description                                                     |
| --------- | --------- | --------------------------------------------------------------- |
| `mask`    | MASK      | Outputs a uniform mask with the specified dimensions and value. |


# StabilityStableImageSD_3_5Node - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityStableImageSD_3_5Node

Complete documentation for the StabilityStableImageSD_3_5Node node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityStableImageSD_3_5Node/en.md)

This node generates images synchronously using Stability AI's Stable Diffusion 3.5 model. It creates images based on text prompts and can also modify existing images when provided as input. The node supports various aspect ratios and style presets to customize the output.

## Inputs

| Parameter         | Data Type | Required | Range                                                                                                                                                                                                                                                                                                             | Description                                                                                                                                                                     |
| ----------------- | --------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`          | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                 | What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results. (default: empty string) |
| `model`           | COMBO     | Yes      | `sd3.5-large`<br />`sd3.5-large-turbo`<br />`sd3.5-medium`                                                                                                                                                                                                                                                        | The Stable Diffusion 3.5 model to use for generation.                                                                                                                           |
| `aspect_ratio`    | COMBO     | Yes      | `16:9`<br />`1:1`<br />`21:9`<br />`2:3`<br />`3:2`<br />`4:5`<br />`5:4`<br />`9:16`<br />`9:21`                                                                                                                                                                                                                 | Aspect ratio of generated image. (default: 1:1)                                                                                                                                 |
| `style_preset`    | COMBO     | No       | `3d-model`<br />`analog-film`<br />`anime`<br />`cinematic`<br />`comic-book`<br />`digital-art`<br />`enhance`<br />`fantasy-art`<br />`isometric`<br />`line-art`<br />`low-poly`<br />`modeling-compound`<br />`neon-punk`<br />`origami`<br />`photographic`<br />`pixel-art`<br />`tile-texture`<br />`None` | Optional desired style of generated image. Select "None" for no style preset.                                                                                                   |
| `cfg_scale`       | FLOAT     | Yes      | 1.0 to 10.0                                                                                                                                                                                                                                                                                                       | How strictly the diffusion process adheres to the prompt text (higher values keep your image closer to your prompt). (default: 4.0)                                             |
| `seed`            | INT       | Yes      | 0 to 4294967294                                                                                                                                                                                                                                                                                                   | The random seed used for creating the noise. (default: 0)                                                                                                                       |
| `image`           | IMAGE     | No       | -                                                                                                                                                                                                                                                                                                                 | Optional input image for image-to-image generation. When provided, the node switches to image-to-image mode and the `aspect_ratio` parameter is ignored.                        |
| `negative_prompt` | STRING    | No       | -                                                                                                                                                                                                                                                                                                                 | Keywords of what you do not wish to see in the output image. This is an advanced feature. (default: empty string)                                                               |
| `image_denoise`   | FLOAT     | No       | 0.0 to 1.0                                                                                                                                                                                                                                                                                                        | Denoise of input image; 0.0 yields image identical to input, 1.0 is as if no image was provided at all. (default: 0.5) This parameter is only used when an `image` is provided. |

**Note:** When an `image` is provided, the node switches to image-to-image generation mode and the `aspect_ratio` parameter is automatically determined from the input image. When no `image` is provided, the `image_denoise` parameter is ignored.

## Outputs

| Output Name | Data Type | Description                      |
| ----------- | --------- | -------------------------------- |
| `image`     | IMAGE     | The generated or modified image. |

***

**Source fingerprint (SHA-256):** `aa071616da3ff645dfbc885c84706324d555c18772d3cc0d603b5699a0e7dfff`


# StabilityStableImageUltraNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityStableImageUltraNode

Complete documentation for the StabilityStableImageUltraNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityStableImageUltraNode/en.md)

Generates images synchronously based on prompt and resolution. This node creates images using Stability AI's Stable Image Ultra model, processing your text prompt and generating a corresponding image with the specified aspect ratio and style.

## Inputs

| Parameter         | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                   | Description                                                                                                                                                                                                                                                                                                                                                                                                                                                             |
| ----------------- | --------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`          | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                                       | What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results. To control the weight of a given word use the format `(word:weight)`, where `word` is the word you'd like to control the weight of and `weight` is a value between 0 and 1. For example: `The sky was a crisp (blue:0.3) and (green:0.8)` would convey a sky that was blue and green, but more green than blue. |
| `aspect_ratio`    | COMBO     | Yes      | `"1:1"`<br />`"16:9"`<br />`"21:9"`<br />`"2:3"`<br />`"3:2"`<br />`"4:5"`<br />`"5:4"`<br />`"9:16"`<br />`"9:21"`                                                                                                                                                                                                                     | Aspect ratio of generated image (default: "1:1").                                                                                                                                                                                                                                                                                                                                                                                                                       |
| `style_preset`    | COMBO     | No       | `"3d-model"`<br />`"analog-film"`<br />`"anime"`<br />`"cinematic"`<br />`"comic-book"`<br />`"digital-art"`<br />`"enhance"`<br />`"fantasy-art"`<br />`"isometric"`<br />`"line-art"`<br />`"low-poly"`<br />`"modeling-compound"`<br />`"neon-punk"`<br />`"origami"`<br />`"photographic"`<br />`"pixel-art"`<br />`"tile-texture"` | Optional desired style of generated image. Select "None" to not apply any style preset.                                                                                                                                                                                                                                                                                                                                                                                 |
| `seed`            | INT       | Yes      | 0 - 4294967294                                                                                                                                                                                                                                                                                                                          | The random seed used for creating the noise.                                                                                                                                                                                                                                                                                                                                                                                                                            |
| `image`           | IMAGE     | No       | -                                                                                                                                                                                                                                                                                                                                       | Optional input image for image-to-image generation.                                                                                                                                                                                                                                                                                                                                                                                                                     |
| `negative_prompt` | STRING    | No       | -                                                                                                                                                                                                                                                                                                                                       | A blurb of text describing what you do not wish to see in the output image. This is an advanced feature.                                                                                                                                                                                                                                                                                                                                                                |
| `image_denoise`   | FLOAT     | No       | 0.0 - 1.0                                                                                                                                                                                                                                                                                                                               | Denoise of input image; 0.0 yields image identical to input, 1.0 is as if no image was provided at all (default: 0.5).                                                                                                                                                                                                                                                                                                                                                  |

**Note:** When an input image is not provided, the `image_denoise` parameter is automatically disabled and ignored.

## Outputs

| Output Name | Data Type | Description                                        |
| ----------- | --------- | -------------------------------------------------- |
| `output`    | IMAGE     | The generated image based on the input parameters. |

***

**Source fingerprint (SHA-256):** `4d516f67a0e2a8c02f601b4da9fe466b7376d50bb96d6e0dc6ca2cc034c79585`


# StabilityUpscaleConservativeNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityUpscaleConservativeNode

Complete documentation for the StabilityUpscaleConservativeNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityUpscaleConservativeNode/en.md)

Upscale image with minimal alterations to 4K resolution. This node uses Stability AI's conservative upscaling to increase image resolution while preserving the original content and making only subtle changes.

## Inputs

| Parameter         | Data Type | Required | Range        | Description                                                                                                                                                                     |
| ----------------- | --------- | -------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`           | IMAGE     | Yes      | -            | The input image to be upscaled                                                                                                                                                  |
| `prompt`          | STRING    | Yes      | -            | What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results. (default: empty string) |
| `creativity`      | FLOAT     | Yes      | 0.2-0.5      | Controls the likelihood of creating additional details not heavily conditioned by the init image. (default: 0.35)                                                               |
| `seed`            | INT       | Yes      | 0-4294967294 | The random seed used for creating the noise. (default: 0)                                                                                                                       |
| `negative_prompt` | STRING    | No       | -            | Keywords of what you do not wish to see in the output image. This is an advanced feature. (default: empty string)                                                               |

## Outputs

| Output Name | Data Type | Description                         |
| ----------- | --------- | ----------------------------------- |
| `image`     | IMAGE     | The upscaled image at 4K resolution |

***

**Source fingerprint (SHA-256):** `7fc0cdf98b4edd991070252d8d9736b48acca6038804209ab7163e5516e1ca34`


# StabilityUpscaleCreativeNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityUpscaleCreativeNode

Complete documentation for the StabilityUpscaleCreativeNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityUpscaleCreativeNode/en.md)

Upscale image with minimal alterations to 4K resolution. This node uses Stability AI's creative upscaling technology to enhance image resolution while preserving the original content and adding subtle creative details.

## Inputs

| Parameter         | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                   | Description                                                                                                                                                                     |
| ----------------- | --------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`           | IMAGE     | Yes      | -                                                                                                                                                                                                                                                                                                                                       | The input image to be upscaled                                                                                                                                                  |
| `prompt`          | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                                       | What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results. (default: empty string) |
| `creativity`      | FLOAT     | Yes      | 0.1-0.5                                                                                                                                                                                                                                                                                                                                 | Controls the likelihood of creating additional details not heavily conditioned by the init image. (default: 0.3)                                                                |
| `style_preset`    | STRING    | Yes      | `"3d-model"`<br />`"analog-film"`<br />`"anime"`<br />`"cinematic"`<br />`"comic-book"`<br />`"digital-art"`<br />`"enhance"`<br />`"fantasy-art"`<br />`"isometric"`<br />`"line-art"`<br />`"low-poly"`<br />`"modeling-compound"`<br />`"neon-punk"`<br />`"origami"`<br />`"photographic"`<br />`"pixel-art"`<br />`"tile-texture"` | Optional desired style of generated image. (default: "None")                                                                                                                    |
| `seed`            | INT       | Yes      | 0-4294967294                                                                                                                                                                                                                                                                                                                            | The random seed used for creating the noise. (default: 0)                                                                                                                       |
| `negative_prompt` | STRING    | No       | -                                                                                                                                                                                                                                                                                                                                       | Keywords of what you do not wish to see in the output image. This is an advanced feature. (default: empty string)                                                               |

## Outputs

| Output Name | Data Type | Description                         |
| ----------- | --------- | ----------------------------------- |
| `image`     | IMAGE     | The upscaled image at 4K resolution |

***

**Source fingerprint (SHA-256):** `1720cc44cc6273b00b3061b44581ba00853e9da32616bc02584335eb6156632c`


# StabilityUpscaleFastNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StabilityUpscaleFastNode

Complete documentation for the StabilityUpscaleFastNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StabilityUpscaleFastNode/en.md)

Quickly upscales an image via Stability API call to 4x its original size. This node is specifically intended for upscaling low-quality or compressed images by sending them to Stability AI's fast upscaling service.

## Inputs

| Parameter | Data Type | Required | Range | Description                    |
| --------- | --------- | -------- | ----- | ------------------------------ |
| `image`   | IMAGE     | Yes      | -     | The input image to be upscaled |

## Outputs

| Output Name | Data Type | Description                                           |
| ----------- | --------- | ----------------------------------------------------- |
| `output`    | IMAGE     | The upscaled image returned from the Stability AI API |

***

**Source fingerprint (SHA-256):** `fd3b033c3454e3b795806f2759f8416ea091df24cb2878b701983e4286da98c9`


# ThresholdMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ThresholdMask

Complete documentation for the ThresholdMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ThresholdMask/en.md)

The ThresholdMask node converts a mask to a binary mask by applying a threshold value. It compares each pixel in the input mask against the specified threshold value and creates a new mask where pixels above the threshold become 1 (white) and pixels below or equal to the threshold become 0 (black).

## Inputs

| Parameter | Data Type | Required | Range     | Description                                         |
| --------- | --------- | -------- | --------- | --------------------------------------------------- |
| `mask`    | MASK      | Yes      | -         | The input mask to be processed                      |
| `value`   | FLOAT     | Yes      | 0.0 - 1.0 | The threshold value for binarization (default: 0.5) |

## Outputs

| Output Name | Data Type | Description                                  |
| ----------- | --------- | -------------------------------------------- |
| `mask`      | MASK      | The resulting binary mask after thresholding |

***

**Source fingerprint (SHA-256):** `eff4479b70c1ca87ba9ba17b771edf5d816cf13c12ac0767cd7ee79d18e326c3`


# TopazImageEnhance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TopazImageEnhance

Complete documentation for the TopazImageEnhance node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TopazImageEnhance/en.md)

The Topaz Image Enhance node provides industry-standard upscaling and image enhancement. It processes a single input image using a cloud-based AI model to improve quality, detail, and resolution. The node offers fine-grained control over the enhancement process, including options for creative guidance, subject focus, and facial preservation.

## Inputs

| Parameter                     | Data Type | Required | Range                                           | Description                                                                                                                                                                         |
| ----------------------------- | --------- | -------- | ----------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`                       | COMBO     | Yes      | `"Reimagine"`                                   | The AI model to use for image enhancement.                                                                                                                                          |
| `image`                       | IMAGE     | Yes      | -                                               | The input image to be enhanced. Only one image is supported.                                                                                                                        |
| `prompt`                      | STRING    | No       | -                                               | An optional text prompt for creative upscaling guidance (default: empty).                                                                                                           |
| `subject_detection`           | COMBO     | No       | `"All"`<br />`"Foreground"`<br />`"Background"` | Controls which part of the image the enhancement focuses on (default: "All").                                                                                                       |
| `face_enhancement`            | BOOLEAN   | No       | -                                               | Enable to enhance faces if they are present in the image (default: True).                                                                                                           |
| `face_enhancement_creativity` | FLOAT     | No       | 0.0 - 1.0                                       | Sets the creativity level for face enhancement (default: 0.0).                                                                                                                      |
| `face_enhancement_strength`   | FLOAT     | No       | 0.0 - 1.0                                       | Controls how sharp enhanced faces are relative to the background (default: 1.0).                                                                                                    |
| `crop_to_fill`                | BOOLEAN   | No       | -                                               | By default, the image is letterboxed when the output aspect ratio differs. Enable to crop the image to fill the output dimensions instead (default: False).                         |
| `output_width`                | INT       | No       | 0 - 32000                                       | The desired width of the output image. A value of 0 means it will be calculated automatically, usually based on the original size or the `output_height` if specified (default: 0). |
| `output_height`               | INT       | No       | 0 - 32000                                       | The desired height of the output image. A value of 0 means it will be calculated automatically, usually based on the original size or the `output_width` if specified (default: 0). |
| `creativity`                  | INT       | No       | 1 - 9                                           | Controls the overall creativity level of the enhancement (default: 3).                                                                                                              |
| `face_preservation`           | BOOLEAN   | No       | -                                               | Preserve the facial identity of subjects in the image (default: True).                                                                                                              |
| `color_preservation`          | BOOLEAN   | No       | -                                               | Preserve the original colors of the input image (default: True).                                                                                                                    |

**Note:** This node can only process a single input image. Providing a batch of multiple images will result in an error.

## Outputs

| Output Name | Data Type | Description                |
| ----------- | --------- | -------------------------- |
| `image`     | IMAGE     | The enhanced output image. |

***

**Source fingerprint (SHA-256):** `c569f4873f5e008f62ccae9a93ef40fe79554c003e7e52c5ac91241b0d08978a`


# VOIDQuadmaskPreprocess - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VOIDQuadmaskPreprocess

Complete documentation for the VOIDQuadmaskPreprocess node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VOIDQuadmaskPreprocess/en.md)

## Overview

The VOIDQuadmaskPreprocess node prepares a mask for VOID inpainting by converting it into a special four-level "quadmask." It takes an input mask, optionally dilates the primary region, then quantizes the mask values into four distinct levels representing different semantic regions (primary object, overlap, affected area, and background). Finally, it inverts and normalizes the mask so the output values are in the range \[0, 1], where 1.0 indicates the area to remove and 0.0 indicates the area to keep.

## Inputs

| Parameter      | Data Type | Required | Range             | Description                                                                                          |
| -------------- | --------- | -------- | ----------------- | ---------------------------------------------------------------------------------------------------- |
| `mask`         | MASK      | Yes      | N/A               | The input mask to be preprocessed.                                                                   |
| `dilate_width` | INT       | No       | 0 to 50 (step: 1) | Dilation radius for the primary mask region. A value of 0 means no dilation is applied. (default: 0) |

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                                            |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `quadmask`  | MASK      | The preprocessed quadmask with values in \[0, 1], representing four discrete levels: 1.0 (primary object to remove), \~0.75 (overlap of primary and affected), \~0.50 (affected region), and 0.0 (background to keep). |

***

**Source fingerprint (SHA-256):** `a972ff74686baaa3a3659a74517d3b6f7335e8f62d09be9329d0e71d1fad137a`


# WanDancerPadKeyframes - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanDancerPadKeyframes

Complete documentation for the WanDancerPadKeyframes node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanDancerPadKeyframes/en.md)

## Overview

This node prepares a sequence of keyframes for a specific segment of a longer video generation process. It takes a batch of input images and an audio track, calculates how many total frames the full video should have based on the audio duration, and then distributes the input images as keyframes across the chosen segment, padding the rest with blank frames. It also extracts the corresponding portion of the audio for that segment.

## Inputs

| Parameter        | Data Type | Required | Range           | Description                                                            |
| ---------------- | --------- | -------- | --------------- | ---------------------------------------------------------------------- |
| `images`         | IMAGE     | Yes      | Batch of images | The input images to be distributed as keyframes.                       |
| `segment_length` | INT       | Yes      | 1 to 10000      | Length of this segment in frames (default: 149).                       |
| `segment_index`  | INT       | Yes      | 0 to 100        | Which segment this is (0 for first, 1 for second, etc., default: 0).   |
| `audio`          | AUDIO     | Yes      | Audio data      | Audio to calculate total output frames from and extract segment audio. |

## Outputs

| Output Name          | Data Type | Description                                                                      |
| -------------------- | --------- | -------------------------------------------------------------------------------- |
| `keyframes_sequence` | IMAGE     | Padded keyframe sequence for the specified segment.                              |
| `keyframes_mask`     | MASK      | Mask indicating valid frames (1 for keyframe positions, 0 for padded positions). |
| `audio_segment`      | AUDIO     | Audio segment for this video segment.                                            |

***

**Source fingerprint (SHA-256):** `93393e39cb1968b6e8720dfad213c16c534857bcfafcc577be64e0733ab3a760`


# WanDancerPadKeyframesList - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanDancerPadKeyframesList

Complete documentation for the WanDancerPadKeyframesList node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanDancerPadKeyframesList/en.md)

## Overview

This node takes a sequence of images and an optional audio track, and splits them into a specified number of padded segments. It is designed to prepare keyframe sequences for video generation, where each segment is padded to a consistent length and a corresponding mask is created to indicate which frames are valid.

## Inputs

| Parameter        | Data Type | Required | Range      | Description                                             |
| ---------------- | --------- | -------- | ---------- | ------------------------------------------------------- |
| `images`         | IMAGE     | Yes      | N/A        | The input image sequence to be split into segments.     |
| `segment_length` | INT       | Yes      | 1 to 10000 | Length of each segment in frames (default: 149).        |
| `num_segments`   | INT       | Yes      | 1 to 100   | How many padded segments to emit as lists (default: 1). |
| `audio`          | AUDIO     | No       | N/A        | Audio to slice for each emitted segment.                |

## Outputs

| Output Name          | Data Type | Description                                                |
| -------------------- | --------- | ---------------------------------------------------------- |
| `keyframes_sequence` | IMAGE     | A list of padded keyframe sequences, one for each segment. |
| `keyframes_mask`     | MASK      | A list of masks indicating valid frames for each segment.  |
| `audio_segment`      | AUDIO     | A list of audio segments, one for each video segment.      |

***

**Source fingerprint (SHA-256):** `f9918166a75f688f1de6a09008780bc629bbdfb3b8d547de9ba8661ef07fc97e`


# WanImageToImageApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanImageToImageApi

Complete documentation for the WanImageToImageApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanImageToImageApi/en.md)

The Wan Image to Image node generates an image from one or two input images and a text prompt. It transforms your input images based on the description you provide, creating a new image that maintains the aspect ratio of your original input. The output image is fixed at 1.6 megapixels regardless of the input size.

## Inputs

| Parameter         | Data Type | Required | Range                | Description                                                                                        |
| ----------------- | --------- | -------- | -------------------- | -------------------------------------------------------------------------------------------------- |
| `model`           | COMBO     | Yes      | "wan2.5-i2i-preview" | Model to use (default: "wan2.5-i2i-preview").                                                      |
| `image`           | IMAGE     | Yes      | -                    | Single-image editing or multi-image fusion, maximum 2 images.                                      |
| `prompt`          | STRING    | Yes      | -                    | Prompt describing the elements and visual features. Supports English and Chinese (default: empty). |
| `negative_prompt` | STRING    | No       | -                    | Negative prompt describing what to avoid (default: empty).                                         |
| `seed`            | INT       | No       | 0 to 2147483647      | Seed to use for generation (default: 0).                                                           |
| `watermark`       | BOOLEAN   | No       | -                    | Whether to add an AI-generated watermark to the result (default: false).                           |

**Note:** This node accepts exactly 1 or 2 input images. If you provide more than 2 images or no images at all, the node will return an error.

## Outputs

| Output Name | Data Type | Description                                                     |
| ----------- | --------- | --------------------------------------------------------------- |
| `image`     | IMAGE     | The generated image based on the input images and text prompts. |

***

**Source fingerprint (SHA-256):** `c9afd38e3df8c080f489c4b569ea647eab5718fa78d95c65e294706344bb8067`


# WanTextToImageApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanTextToImageApi

Complete documentation for the WanTextToImageApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanTextToImageApi/en.md)

The Wan Text to Image node generates images based on text descriptions. It uses AI models to create visual content from written prompts, supporting both English and Chinese text input. The node provides various controls to adjust the output image size, quality, and style preferences.

## Inputs

| Parameter         | Data Type | Required | Range                | Description                                                                                       |
| ----------------- | --------- | -------- | -------------------- | ------------------------------------------------------------------------------------------------- |
| `model`           | STRING    | Yes      | "wan2.5-t2i-preview" | Model to use (default: "wan2.5-t2i-preview")                                                      |
| `prompt`          | STRING    | Yes      | -                    | Prompt describing the elements and visual features. Supports English and Chinese (default: empty) |
| `negative_prompt` | STRING    | No       | -                    | Negative prompt describing what to avoid (default: empty)                                         |
| `width`           | INT       | No       | 768-1440             | Image width in pixels (default: 1024, step: 32)                                                   |
| `height`          | INT       | No       | 768-1440             | Image height in pixels (default: 1024, step: 32)                                                  |
| `seed`            | INT       | No       | 0-2147483647         | Seed to use for generation (default: 0)                                                           |
| `prompt_extend`   | BOOLEAN   | No       | -                    | Whether to enhance the prompt with AI assistance (default: True)                                  |
| `watermark`       | BOOLEAN   | No       | -                    | Whether to add an AI-generated watermark to the result (default: False)                           |

## Outputs

| Output Name | Data Type | Description                                  |
| ----------- | --------- | -------------------------------------------- |
| `output`    | IMAGE     | The generated image based on the text prompt |

***

**Source fingerprint (SHA-256):** `4ab8fe7b1e6a0b781b006e03719203b65ed58aec75aaee780d479170ed6425ea`


# WavespeedImageUpscaleNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WavespeedImageUpscaleNode

Complete documentation for the WavespeedImageUpscaleNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WavespeedImageUpscaleNode/en.md)

The WaveSpeed Image Upscale node uses an external AI service to increase the resolution and quality of an image. It takes a single input photo and upscales it to a higher target resolution, such as 2K, 4K, or 8K, producing a sharper and more detailed result.

## Inputs

| Parameter           | Data Type | Required | Range                          | Description                                                                                            |
| ------------------- | --------- | -------- | ------------------------------ | ------------------------------------------------------------------------------------------------------ |
| `model`             | STRING    | Yes      | `"SeedVR2"`<br />`"Ultimate"`  | The AI model to use for upscaling. "SeedVR2" and "Ultimate" offer different quality and pricing tiers. |
| `image`             | IMAGE     | Yes      |                                | The input image to be upscaled. Exactly one image is required.                                         |
| `target_resolution` | STRING    | Yes      | `"2K"`<br />`"4K"`<br />`"8K"` | The desired output resolution for the upscaled image.                                                  |

**Note:** This node requires exactly one input image. Providing a batch of images will result in an error.

## Outputs

| Output Name | Data Type | Description                                 |
| ----------- | --------- | ------------------------------------------- |
| `image`     | IMAGE     | The upscaled, high-resolution output image. |

***

**Source fingerprint (SHA-256):** `9ed5a897cf067a9dbf8bee95f44cfc02c98349b1520e0f42d5f52c120d248014`


# ARVideoI2V - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ARVideoI2V

Complete documentation for the ARVideoI2V node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ARVideoI2V/en.md)

## Overview

This node prepares an image-to-video generation setup for AR (Auto-Regressive) video models. It takes a starting image, encodes it into the latent space using a VAE, and stores the encoded image in the model's configuration. This allows the video sampling process to use the image as the first frame, effectively seeding the generation without needing a separate image-to-video model architecture.

## Inputs

| Parameter     | Data Type | Required | Range                 | Description                                                                  |
| ------------- | --------- | -------- | --------------------- | ---------------------------------------------------------------------------- |
| `model`       | MODEL     | Yes      | -                     | The AR video model to be used for generation.                                |
| `vae`         | VAE       | Yes      | -                     | The VAE model used to encode the starting image into latent space.           |
| `start_image` | IMAGE     | Yes      | -                     | The initial image that will serve as the first frame of the generated video. |
| `width`       | INT       | Yes      | 16 to 8192 (step: 16) | The width of the generated video frames (default: 832).                      |
| `height`      | INT       | Yes      | 16 to 8192 (step: 16) | The height of the generated video frames (default: 480).                     |
| `length`      | INT       | Yes      | 1 to 1024 (step: 4)   | The total number of frames in the generated video (default: 81).             |
| `batch_size`  | INT       | Yes      | 1 to 64               | The number of video sequences to generate in a single batch (default: 1).    |

## Outputs

| Output Name | Data Type | Description                                                                                     |
| ----------- | --------- | ----------------------------------------------------------------------------------------------- |
| `MODEL`     | MODEL     | The cloned model with the encoded start image stored in its configuration for video generation. |
| `LATENT`    | LATENT    | An empty latent tensor with the correct dimensions for the video generation process.            |

***

**Source fingerprint (SHA-256):** `0445b279ba49fa946050cfa70d1e6b13240eaa600b99dfe63f27c3203dc4b61b`


# AudioEncoderEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioEncoderEncode

Complete documentation for the AudioEncoderEncode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioEncoderEncode/en.md)

The AudioEncoderEncode node processes audio data by encoding it using an audio encoder model. It takes audio input and converts it into an encoded representation that can be used for further processing in the conditioning pipeline. This node transforms raw audio waveforms into a format suitable for audio-based machine learning applications.

## Inputs

| Parameter       | Data Type      | Required | Range | Description                                                    |
| --------------- | -------------- | -------- | ----- | -------------------------------------------------------------- |
| `audio_encoder` | AUDIO\_ENCODER | Yes      | -     | The audio encoder model used to process the audio input        |
| `audio`         | AUDIO          | Yes      | -     | The audio data containing waveform and sample rate information |

## Outputs

| Output Name | Data Type              | Description                                                     |
| ----------- | ---------------------- | --------------------------------------------------------------- |
| `output`    | AUDIO\_ENCODER\_OUTPUT | The encoded audio representation generated by the audio encoder |

***

**Source fingerprint (SHA-256):** `abd34445d7b959a6421fe0fe6bed0498b3754ee313019e3315cbed399f68bbe6`


# CLIPTextEncodeLumina2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CLIPTextEncodeLumina2

Complete documentation for the CLIPTextEncodeLumina2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncodeLumina2/en.md)

The CLIP Text Encode for Lumina2 node encodes a system prompt and a user prompt using a CLIP model into an embedding that can guide the diffusion model to generate specific images. It combines a pre-defined system prompt with your custom text prompt and processes them through the CLIP model to create conditioning data for image generation.

## Inputs

| Parameter       | Data Type | Required | Range                           | Description                                                                                                                                                                                              |
| --------------- | --------- | -------- | ------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `system_prompt` | STRING    | Yes      | `"superior"`<br />`"alignment"` | Lumina2 provides two types of system prompts: "superior" generates images with superior image-text alignment; "alignment" generates high-quality images with the highest degree of image-text alignment. |
| `user_prompt`   | STRING    | Yes      | N/A                             | The text to be encoded. Supports multiline input and dynamic prompts.                                                                                                                                    |
| `clip`          | CLIP      | Yes      | N/A                             | The CLIP model used for encoding the text.                                                                                                                                                               |

**Note:** The `clip` input is required and cannot be None. If the clip input is invalid, the node will raise an error indicating that the checkpoint may not contain a valid CLIP or text encoder model.

## Outputs

| Output Name    | Data Type    | Description                                                                    |
| -------------- | ------------ | ------------------------------------------------------------------------------ |
| `CONDITIONING` | CONDITIONING | A conditioning containing the embedded text used to guide the diffusion model. |

***

**Source fingerprint (SHA-256):** `e9d5f685a666a4f0737739e56afa3eb854a4abcbd8a76480c7a050cd503b53b2`


# CLIPSetLastLayer - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipSetLastLayer

Complete documentation for the CLIPSetLastLayer node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPSetLastLayer/en.md)

`CLIP Set Last Layer` is a core node in ComfyUI for controlling the processing depth of CLIP models. It allows users to precisely control where the CLIP text encoder stops processing, affecting both the depth of text understanding and the style of generated images.

Imagine the CLIP model as a 24-layer intelligent brain:

* Shallow layers (1-8): Recognize basic letters and words
* Middle layers (9-16): Understand grammar and sentence structure
* Deep layers (17-24): Grasp abstract concepts and complex semantics

`CLIP Set Last Layer` works like a **"thinking depth controller"**:

-1: Use all 24 layers (complete understanding)
-2: Stop at layer 23 (slightly simplified)
-12: Stop at layer 13 (medium understanding)
-24: Use only layer 1 (basic understanding)

## Inputs

| Parameter            | Data Type | Required | Range     | Description                                                                                                        |
| -------------------- | --------- | -------- | --------- | ------------------------------------------------------------------------------------------------------------------ |
| `clip`               | CLIP      | Yes      | -         | The CLIP model to be modified                                                                                      |
| `stop_at_clip_layer` | INT       | Yes      | -24 to -1 | Specifies which layer to stop at. A value of -1 uses all layers, while -24 uses only the first layer (default: -1) |

## Outputs

| Output Name | Data Type | Description                                                          |
| ----------- | --------- | -------------------------------------------------------------------- |
| `clip`      | CLIP      | The modified CLIP model with the specified layer set as the last one |

## Why Set the Last Layer

* **Performance Optimization**: Like not needing a PhD to understand simple sentences, sometimes shallow understanding is enough and faster
* **Style Control**: Different levels of understanding produce different artistic styles
* **Compatibility**: Some models might perform better at specific layers

***

**Source fingerprint (SHA-256):** `82f3e7fb1d4c0bdd2b242a449085a5497ba8af8616d1800c5c0ee7a85ab42c15`


# CLIPTextEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipTextEncode

Complete documentation for the CLIPTextEncode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CLIPTextEncode/en.md)

`CLIP Text Encode (CLIPTextEncode)` acts as a translator, converting your text descriptions into a format that AI can understand. This helps the AI interpret your input and generate the desired image.

Think of it as communicating with an artist who speaks a different language. The CLIP model, trained on vast image-text pairs, bridges this gap by converting your descriptions into "instructions" that the AI model can follow.

## Inputs

| Parameter | Data Type | Required | Range              | Description                                                            |
| --------- | --------- | -------- | ------------------ | ---------------------------------------------------------------------- |
| `text`    | STRING    | Yes      | Any text           | The text to be encoded. Supports multi-line input and dynamic prompts. |
| `clip`    | CLIP      | Yes      | Loaded CLIP models | The CLIP model used for encoding the text.                             |

## Outputs

| Output Name    | Data Type    | Description                                                                    |
| -------------- | ------------ | ------------------------------------------------------------------------------ |
| `CONDITIONING` | CONDITIONING | A conditioning containing the embedded text used to guide the diffusion model. |

## Prompt Features

### Embedding Models

Embedding models allow you to apply specific artistic effects or styles. Supported formats include `.safetensors`, `.pt`, and `.bin`. To use an embedding model:

1. Place the file in the `ComfyUI/models/embeddings` folder.
2. Reference it in your text using `embedding:model_name`.

Example: If you have a model named `EasyNegative.pt` in your `ComfyUI/models/embeddings` folder, then you can use it like this:

```
worst quality, embedding:EasyNegative, bad quality
```

**IMPORTANT**: When using embedding models, verify that the file name matches and is compatible with your model's architecture. For example an embedding designed for SD1.5 will not work correctly for a SDXL model.

### Prompt Weight Adjustment

You can adjust the importance of certain parts of your description using parentheses. For example:

* `(beautiful:1.2)` increases the weight of "beautiful".
* `(beautiful:0.8)` decrease the weight of "beautiful".
* Plain parentheses `(beautiful)` will apply a default weight of 1.1.

You can use the keyboard shortcuts `ctrl + up/down arrow` to quickly adjust weights. The weight adjustment step size can be modified in the settings.

If you want to include literal parentheses in your prompt without changing the weight, you can escape them using a backslash e.g. `\(word\)`.

### Wildcard/Dynamic Prompts

Use `{}` to create dynamic prompts. For example, `{day|night|morning}` will randomly select one option each time the prompt is processed.

If you want to include literal curly braces in your prompt without triggering dynamic behavior, you can escape them using a backslash e.g. `\{word\}`.

**Source fingerprint (SHA-256):** `e8f286cdec879c529270e110ccf5959ed6df77737cfb5a8019379afac9266118`


# CLIPVisionEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipVisionEncode

Complete documentation for the CLIPVisionEncode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `CLIP Vision Encode` node is an image encoding node in ComfyUI, used to convert input images into visual feature vectors through the CLIP Vision model. This node is an important bridge connecting image and text understanding, and is widely used in various AI image generation and processing workflows.

**Node Functionality**

* **Image feature extraction**: Converts input images into high-dimensional feature vectors
* **Multimodal bridging**: Provides a foundation for joint processing of images and text
* **Conditional generation**: Provides visual conditions for image-based conditional generation

## Inputs

| Parameter Name | Data Type    | Description                                                          |
| -------------- | ------------ | -------------------------------------------------------------------- |
| `clip_vision`  | CLIP\_VISION | CLIP vision model, usually loaded via the CLIPVisionLoader node      |
| `image`        | IMAGE        | The input image to be encoded                                        |
| `crop`         | Dropdown     | Image cropping method, options: center (center crop), none (no crop) |

## Outputs

| Output Name          | Data Type            | Description             |
| -------------------- | -------------------- | ----------------------- |
| CLIP\_VISION\_OUTPUT | CLIP\_VISION\_OUTPUT | Encoded visual features |

This output object contains:

* `last_hidden_state`: The last hidden state
* `image_embeds`: Image embedding vector
* `penultimate_hidden_states`: The penultimate hidden state
* `mm_projected`: Multimodal projection result (if available)


# ConditioningCombine - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningCombine

Complete documentation for the ConditioningCombine node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node combines two conditioning inputs into a single output, effectively merging their information. The two conditions are combined using list concatenation.

## Inputs

| Parameter Name   | Data Type      | Description                                                                                                             |
| ---------------- | -------------- | ----------------------------------------------------------------------------------------------------------------------- |
| `conditioning_1` | `CONDITIONING` | The first conditioning input to be combined. It has equal importance with `conditioning_2` in the combination process.  |
| `conditioning_2` | `CONDITIONING` | The second conditioning input to be combined. It has equal importance with `conditioning_1` in the combination process. |

## Outputs

| Parameter Name | Data Type      | Description                                                                                          |
| -------------- | -------------- | ---------------------------------------------------------------------------------------------------- |
| `conditioning` | `CONDITIONING` | The result of combining `conditioning_1` and `conditioning_2`, encapsulating the merged information. |

## Usage Scenarios

Compare the two groups below: the left side uses the ConditioningCombine node, while the right side shows normal output.

<img alt="Compare" />

In this example, the two conditions used in `Conditioning Combine` have equivalent importance. Therefore, you can use different text encodings for image style, subject features, etc., allowing the prompt features to be output more completely. The second prompt uses the combined complete prompt, but semantic understanding may encode completely different conditions.

Using this node, you can achieve:

* Basic text merging: Connect the outputs of two `CLIP Text Encode` nodes to the two input ports of `Conditioning Combine`
* Complex prompt combination: Combine positive and negative prompts, or separately encode main descriptions and style descriptions before merging
* Conditional chain combination: Multiple `Conditioning Combine` nodes can be used in series to achieve gradual combination of multiple conditions


# ConditioningConcat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningConcat

Complete documentation for the ConditioningConcat node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The ConditioningConcat node is designed to concatenate conditioning vectors, specifically merging the 'conditioning\_from' vector into the 'conditioning\_to' vector. This operation is fundamental in scenarios where the conditioning information from two sources needs to be combined into a single, unified representation.

## Inputs

| Parameter           | Comfy dtype    | Description                                                                                                                                                                                           |
| ------------------- | -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `conditioning_to`   | `CONDITIONING` | Represents the primary set of conditioning vectors to which the 'conditioning\_from' vectors will be concatenated. It serves as the base for the concatenation process.                               |
| `conditioning_from` | `CONDITIONING` | Consists of conditioning vectors that are to be concatenated to the 'conditioning\_to' vectors. This parameter allows for additional conditioning information to be integrated into the existing set. |

## Outputs

| Parameter      | Comfy dtype    | Description                                                                                                                                                |
| -------------- | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `conditioning` | `CONDITIONING` | The output is a unified set of conditioning vectors, resulting from the concatenation of 'conditioning\_from' vectors into the 'conditioning\_to' vectors. |


# ConditioningSetArea - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetArea

Complete documentation for the ConditioningSetArea node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to modify the conditioning information by setting specific areas within the conditioning context. It allows for the precise spatial manipulation of conditioning elements, enabling targeted adjustments and enhancements based on specified dimensions and strength.

## Inputs

| Parameter      | Data Type    | Description                                                                                                                                  |
| -------------- | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The conditioning data to be modified. It serves as the base for applying spatial adjustments.                                                |
| `width`        | `INT`        | Specifies the width of the area to be set within the conditioning context, influencing the horizontal scope of the adjustment.               |
| `height`       | `INT`        | Determines the height of the area to be set, affecting the vertical extent of the conditioning modification.                                 |
| `x`            | `INT`        | The horizontal starting point of the area to be set, positioning the adjustment within the conditioning context.                             |
| `y`            | `INT`        | The vertical starting point for the area adjustment, establishing its position within the conditioning context.                              |
| `strength`     | `FLOAT`      | Defines the intensity of the conditioning modification within the specified area, allowing for nuanced control over the adjustment's impact. |

## Outputs

| Parameter      | Data Type    | Description                                                                             |
| -------------- | ------------ | --------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The modified conditioning data, reflecting the specified area settings and adjustments. |


# ConditioningSetAreaPercentage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetAreaPercentage

Complete documentation for the ConditioningSetAreaPercentage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The ConditioningSetAreaPercentage node specializes in adjusting the area of influence for conditioning elements based on percentage values. It allows for the specification of the area's dimensions and position as percentages of the total image size, alongside a strength parameter to modulate the intensity of the conditioning effect.

## Inputs

| Parameter      | Data Type    | Description                                                                                                                                        |
| -------------- | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | Represents the conditioning elements to be modified, serving as the foundation for applying area and strength adjustments.                         |
| `width`        | `FLOAT`      | Specifies the width of the area as a percentage of the total image width, influencing how much of the image the conditioning affects horizontally. |
| `height`       | `FLOAT`      | Determines the height of the area as a percentage of the total image height, affecting the vertical extent of the conditioning's influence.        |
| `x`            | `FLOAT`      | Indicates the horizontal starting point of the area as a percentage of the total image width, positioning the conditioning effect.                 |
| `y`            | `FLOAT`      | Specifies the vertical starting point of the area as a percentage of the total image height, positioning the conditioning effect.                  |
| `strength`     | `FLOAT`      | Controls the intensity of the conditioning effect within the specified area, allowing for fine-tuning of its impact.                               |

## Outputs

| Parameter      | Data Type    | Description                                                                                                                        |
| -------------- | ------------ | ---------------------------------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | Returns the modified conditioning elements with updated area and strength parameters, ready for further processing or application. |


# ConditioningSetAreaPercentageVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetAreaPercentageVideo

Complete documentation for the ConditioningSetAreaPercentageVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningSetAreaPercentageVideo/en.md)

The ConditioningSetAreaPercentageVideo node modifies conditioning data by defining a specific area and temporal region for video generation. It allows you to set the position, size, and duration of the area where the conditioning will be applied using percentage values relative to the overall dimensions. This is useful for focusing the generation on specific parts of a video sequence.

## Inputs

| Parameter      | Data Type    | Input Type | Default | Range      | Description                                                                      |
| -------------- | ------------ | ---------- | ------- | ---------- | -------------------------------------------------------------------------------- |
| `conditioning` | CONDITIONING | Required   | -       | -          | The conditioning data to be modified                                             |
| `width`        | FLOAT        | Required   | 1.0     | 0.0 - 1.0  | The width of the area as a percentage of the total width                         |
| `height`       | FLOAT        | Required   | 1.0     | 0.0 - 1.0  | The height of the area as a percentage of the total height                       |
| `temporal`     | FLOAT        | Required   | 1.0     | 0.0 - 1.0  | The temporal duration of the area as a percentage of the total video length      |
| `x`            | FLOAT        | Required   | 0.0     | 0.0 - 1.0  | The horizontal starting position of the area as a percentage                     |
| `y`            | FLOAT        | Required   | 0.0     | 0.0 - 1.0  | The vertical starting position of the area as a percentage                       |
| `z`            | FLOAT        | Required   | 0.0     | 0.0 - 1.0  | The temporal starting position of the area as a percentage of the video timeline |
| `strength`     | FLOAT        | Required   | 1.0     | 0.0 - 10.0 | The strength multiplier applied to the conditioning within the defined area      |

## Outputs

| Output Name    | Data Type    | Description                                                                          |
| -------------- | ------------ | ------------------------------------------------------------------------------------ |
| `conditioning` | CONDITIONING | The modified conditioning data with the specified area and strength settings applied |

***

**Source fingerprint (SHA-256):** `72d4bef4f8ddc4765cf69863f7ad03d34992f0ff30a963dbe2dc1b7d69815410`


# ConditioningSetAreaStrength - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetAreaStrength

Complete documentation for the ConditioningSetAreaStrength node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to modify the strength attribute of a given conditioning set, allowing for the adjustment of the influence or intensity of the conditioning on the generation process.

## Inputs

| Parameter      | Data Type    | Description                                                                                                                 |
| -------------- | ------------ | --------------------------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The conditioning set to be modified, representing the current state of conditioning that influences the generation process. |
| `strength`     | `FLOAT`      | The strength value to be applied to the conditioning set, dictating the intensity of its influence.                         |

## Outputs

| Parameter      | Data Type    | Description                                                                  |
| -------------- | ------------ | ---------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The modified conditioning set with updated strength values for each element. |


# ConditioningSetMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningSetMask

Complete documentation for the ConditioningSetMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to modify the conditioning of a generative model by applying a mask with a specified strength to certain areas. It allows for targeted adjustments within the conditioning, enabling more precise control over the generation process.

## Inputs

### Required

| Parameter       | Data Type      | Description                                                                                                                                            |
| --------------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `CONDITIONING`  | CONDITIONING   | The conditioning data to be modified. It serves as the basis for applying the mask and strength adjustments.                                           |
| `mask`          | `MASK`         | A mask tensor that specifies the areas within the conditioning to be modified.                                                                         |
| `strength`      | `FLOAT`        | The strength of the mask's effect on the conditioning, allowing for fine-tuning of the applied modifications.                                          |
| `set_cond_area` | COMBO\[STRING] | Determines whether the mask's effect is applied to the default area or bounded by the mask itself, offering flexibility in targeting specific regions. |

## Outputs

| Parameter      | Data Type    | Description                                                                     |
| -------------- | ------------ | ------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The modified conditioning data, with the mask and strength adjustments applied. |


# ConditioningStableAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConditioningStableAudio

Complete documentation for the ConditioningStableAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConditioningStableAudio/en.md)

The ConditioningStableAudio node adds timing information to both positive and negative conditioning inputs for audio generation. It sets the start time and total duration parameters that help control when and how long audio content should be generated. This node modifies existing conditioning data by appending audio-specific timing metadata.

## Inputs

| Parameter       | Data Type    | Required | Range         | Description                                                                  |
| --------------- | ------------ | -------- | ------------- | ---------------------------------------------------------------------------- |
| `positive`      | CONDITIONING | Yes      | -             | The positive conditioning input to be modified with audio timing information |
| `negative`      | CONDITIONING | Yes      | -             | The negative conditioning input to be modified with audio timing information |
| `seconds_start` | FLOAT        | Yes      | 0.0 to 1000.0 | The starting time in seconds for audio generation (default: 0.0)             |
| `seconds_total` | FLOAT        | Yes      | 0.0 to 1000.0 | The total duration in seconds for audio generation (default: 47.0)           |

## Outputs

| Output Name | Data Type    | Description                                                              |
| ----------- | ------------ | ------------------------------------------------------------------------ |
| `positive`  | CONDITIONING | The modified positive conditioning with audio timing information applied |
| `negative`  | CONDITIONING | The modified negative conditioning with audio timing information applied |

***

**Source fingerprint (SHA-256):** `16ad6c3f133df718bf05a1e55a2faf0b840570fd42dc177e1474d0d3e4837b79`


# ControlNetApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ControlNetApply

Complete documentation for the ControlNetApply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

Using controlNet requires preprocessing of input images. Since ComfyUI initial nodes do not come with preprocessors and controlNet models, please first install ControlNet preprocessors [download preprocessors here](https://github.com/Fannovel16/comfy_controlnet_preprocessors) and corresponding controlNet models.

## Inputs

| Parameter       | Data Type      | Function                                                                                                                                                                                                                                                                                                                              |
| --------------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`      | `CONDITIONING` | Positive conditioning data, from CLIP Text Encoder or other conditioning inputs                                                                                                                                                                                                                                                       |
| `negative`      | `CONDITIONING` | Negative conditioning data, from CLIP Text Encoder or other conditioning inputs                                                                                                                                                                                                                                                       |
| `control_net`   | `CONTROL_NET`  | The controlNet model to apply, typically input from ControlNet Loader                                                                                                                                                                                                                                                                 |
| `image`         | `IMAGE`        | Image for controlNet application, needs to be processed by preprocessor                                                                                                                                                                                                                                                               |
| `vae`           | `VAE`          | Vae model input                                                                                                                                                                                                                                                                                                                       |
| `strength`      | `FLOAT`        | Controls the strength of network adjustments, value range 0~~10. Recommended values between 0.5~~1.5 are reasonable. Lower values allow more model freedom, higher values impose stricter constraints. Too high values may result in strange images. You can test and adjust this value to fine-tune the control network's influence. |
| `start_percent` | `FLOAT`        | Value 0.000\~1.000, determines when to start applying controlNet as a percentage, e.g., 0.2 means ControlNet guidance will start influencing image generation at 20% of the diffusion process                                                                                                                                         |
| `end_percent`   | `FLOAT`        | Value 0.000\~1.000, determines when to stop applying controlNet as a percentage, e.g., 0.8 means ControlNet guidance will stop influencing image generation at 80% of the diffusion process                                                                                                                                           |

### Outputs

| Parameter  | Data Type      | Function                                                                                                |
| ---------- | -------------- | ------------------------------------------------------------------------------------------------------- |
| `positive` | `CONDITIONING` | Positive conditioning data processed by ControlNet, can be output to next ControlNet or K Sampler nodes |
| `negative` | `CONDITIONING` | Negative conditioning data processed by ControlNet, can be output to next ControlNet or K Sampler nodes |


# ControlNetApplyAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ControlNetApplyAdvanced

Complete documentation for the ControlNetApplyAdvanced node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node applies advanced control net transformations to conditioning data based on an image and a control net model. It allows for fine-tuned adjustments of the control net's influence over the generated content, enabling more precise and varied modifications to the conditioning.

## Inputs

| Parameter       | Data Type      | Description                                                                                                                                                                                                                                                                                                               |
| --------------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`      | `CONDITIONING` | The positive conditioning data to which the control net transformations will be applied. It represents the desired attributes or features to enhance or maintain in the generated content.                                                                                                                                |
| `negative`      | `CONDITIONING` | The negative conditioning data, representing attributes or features to diminish or remove from the generated content. The control net transformations are applied to this data as well, allowing for a balanced adjustment of the content's characteristics.                                                              |
| `control_net`   | `CONTROL_NET`  | The control net model is crucial for defining the specific adjustments and enhancements to the conditioning data. It interprets the reference image and strength parameters to apply transformations, significantly influencing the final output by modifying attributes in both positive and negative conditioning data. |
| `image`         | `IMAGE`        | The image serving as a reference for the control net transformations. It influences the adjustments made by the control net to the conditioning data, guiding the enhancement or suppression of specific features.                                                                                                        |
| `strength`      | `FLOAT`        | A scalar value determining the intensity of the control net's influence on the conditioning data. Higher values result in more pronounced adjustments.                                                                                                                                                                    |
| `start_percent` | `FLOAT`        | The starting percentage of the control net's effect, allowing for gradual application of transformations over a specified range.                                                                                                                                                                                          |
| `end_percent`   | `FLOAT`        | The ending percentage of the control net's effect, defining the range over which the transformations are applied. This enables more nuanced control over the adjustment process.                                                                                                                                          |

## Outputs

| Parameter  | Data Type      | Description                                                                                                                                                                             |
| ---------- | -------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive` | `CONDITIONING` | The modified positive conditioning data after the application of control net transformations, reflecting the enhancements made based on the input parameters.                           |
| `negative` | `CONDITIONING` | The modified negative conditioning data after the application of control net transformations, reflecting the suppression or removal of specific features based on the input parameters. |


# ControlNetApplySD3 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ControlNetApplySD3

Complete documentation for the ControlNetApplySD3 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ControlNetApplySD3/en.md)

This node applies ControlNet guidance to Stable Diffusion 3 conditioning. It takes positive and negative conditioning inputs along with a ControlNet model and image, then applies the control guidance with adjustable strength and timing parameters to influence the generation process.

**Note:** This node has been marked as deprecated and may be removed in future versions.

## Inputs

| Parameter       | Data Type    | Required | Range      | Description                                                                                  |
| --------------- | ------------ | -------- | ---------- | -------------------------------------------------------------------------------------------- |
| `positive`      | CONDITIONING | Yes      | -          | The positive conditioning to apply ControlNet guidance to                                    |
| `negative`      | CONDITIONING | Yes      | -          | The negative conditioning to apply ControlNet guidance to                                    |
| `control_net`   | CONTROL\_NET | Yes      | -          | The ControlNet model to use for guidance                                                     |
| `vae`           | VAE          | Yes      | -          | The VAE model used in the process                                                            |
| `image`         | IMAGE        | Yes      | -          | The input image that ControlNet will use as guidance                                         |
| `strength`      | FLOAT        | Yes      | 0.0 - 10.0 | The strength of the ControlNet effect (default: 1.0)                                         |
| `start_percent` | FLOAT        | Yes      | 0.0 - 1.0  | The starting point in the generation process where ControlNet begins to apply (default: 0.0) |
| `end_percent`   | FLOAT        | Yes      | 0.0 - 1.0  | The ending point in the generation process where ControlNet stops applying (default: 1.0)    |

## Outputs

| Output Name | Data Type    | Description                                                         |
| ----------- | ------------ | ------------------------------------------------------------------- |
| `positive`  | CONDITIONING | The modified positive conditioning with ControlNet guidance applied |
| `negative`  | CONDITIONING | The modified negative conditioning with ControlNet guidance applied |

***

**Source fingerprint (SHA-256):** `b79f03a85250f8eda6786fbdb6a96712f5fc60c9ede3b073a1cc8aef31a3f6b0`


# ControlNetInpaintingAliMamaApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ControlNetInpaintingAliMamaApply

Complete documentation for the ControlNetInpaintingAliMamaApply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ControlNetInpaintingAliMamaApply/en.md)

The ControlNetInpaintingAliMamaApply node applies ControlNet conditioning for inpainting tasks by combining positive and negative conditioning with a control image and mask. It processes the input image and mask to create modified conditioning that guides the generation process, allowing for precise control over which areas of the image are inpainted. The node supports strength adjustment and timing controls to fine-tune the ControlNet's influence during different stages of the generation process.

## Inputs

| Parameter       | Data Type    | Required | Range       | Description                                                                                             |
| --------------- | ------------ | -------- | ----------- | ------------------------------------------------------------------------------------------------------- |
| `positive`      | CONDITIONING | Yes      | -           | The positive conditioning that guides the generation toward desired content                             |
| `negative`      | CONDITIONING | Yes      | -           | The negative conditioning that guides the generation away from unwanted content                         |
| `control_net`   | CONTROL\_NET | Yes      | -           | The ControlNet model that provides additional control over the generation                               |
| `vae`           | VAE          | Yes      | -           | The VAE (Variational Autoencoder) used for encoding and decoding images                                 |
| `image`         | IMAGE        | Yes      | -           | The input image that serves as control guidance for the ControlNet                                      |
| `mask`          | MASK         | Yes      | -           | The mask that defines which areas of the image should be inpainted                                      |
| `strength`      | FLOAT        | Yes      | 0.0 to 10.0 | The strength of the ControlNet effect (default: 1.0)                                                    |
| `start_percent` | FLOAT        | Yes      | 0.0 to 1.0  | The starting point (as percentage) of when ControlNet influence begins during generation (default: 0.0) |
| `end_percent`   | FLOAT        | Yes      | 0.0 to 1.0  | The ending point (as percentage) of when ControlNet influence stops during generation (default: 1.0)    |

**Note:** When the ControlNet has `concat_mask` enabled, the mask is inverted and applied to the image before processing, and the mask is included in the extra concatenation data sent to the ControlNet.

## Outputs

| Output Name | Data Type    | Description                                                               |
| ----------- | ------------ | ------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | The modified positive conditioning with ControlNet applied for inpainting |
| `negative`  | CONDITIONING | The modified negative conditioning with ControlNet applied for inpainting |

***

**Source fingerprint (SHA-256):** `bd44dcff4f0d06b3b81a66dd45ae57e54b72374308f75b3089e50db8de1398cd`


# ControlNetLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ControlNetLoader

Complete documentation for the ControlNetLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node will detect models located in the `ComfyUI/models/controlnet` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The ControlNetLoader node is designed to load a ControlNet model from a specified path. It plays a crucial role in initializing ControlNet models, which are essential for applying control mechanisms over generated content or modifying existing content based on control signals.

## Inputs

| Field              | Comfy dtype     | Description                                                                                                                     |
| ------------------ | --------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| `control_net_name` | `COMBO[STRING]` | Specifies the name of the ControlNet model to be loaded, used to locate the model file within a predefined directory structure. |

## Outputs

| Field         | Comfy dtype   | Description                                                                                                  |
| ------------- | ------------- | ------------------------------------------------------------------------------------------------------------ |
| `control_net` | `CONTROL_NET` | Returns the loaded ControlNet model, ready for use in controlling or modifying content generation processes. |


# CosmosImageToVideoLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CosmosImageToVideoLatent

Complete documentation for the CosmosImageToVideoLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CosmosImageToVideoLatent/en.md)

The CosmosImageToVideoLatent node creates video latent representations from input images. It generates a blank video latent and optionally encodes start and/or end images into the beginning and/or end frames of the video sequence. When images are provided, it also creates corresponding noise masks to indicate which parts of the latent should be preserved during generation.

## Inputs

| Parameter     | Data Type | Required | Range                 | Description                                                     |
| ------------- | --------- | -------- | --------------------- | --------------------------------------------------------------- |
| `vae`         | VAE       | Yes      | -                     | The VAE model used for encoding images into latent space        |
| `width`       | INT       | Yes      | 16 to MAX\_RESOLUTION | The width of the output video in pixels (default: 1280)         |
| `height`      | INT       | Yes      | 16 to MAX\_RESOLUTION | The height of the output video in pixels (default: 704)         |
| `length`      | INT       | Yes      | 1 to MAX\_RESOLUTION  | The number of frames in the video sequence (default: 121)       |
| `batch_size`  | INT       | Yes      | 1 to 4096             | The number of latent batches to generate (default: 1)           |
| `start_image` | IMAGE     | No       | -                     | Optional image to encode at the beginning of the video sequence |
| `end_image`   | IMAGE     | No       | -                     | Optional image to encode at the end of the video sequence       |

**Note:** When neither `start_image` nor `end_image` are provided, the node returns a blank latent without any noise mask. When either image is provided, the corresponding sections of the latent are encoded and masked accordingly.

## Outputs

| Output Name | Data Type | Description                                                                                          |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------- |
| `latent`    | LATENT    | The generated video latent representation with optional encoded images and corresponding noise masks |

***

**Source fingerprint (SHA-256):** `4fefd1b6c38c93c260ef8376e8d69ba610a556b3c8555863016a1afd45885eaf`


# CosmosPredict2ImageToVideoLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CosmosPredict2ImageToVideoLatent

Complete documentation for the CosmosPredict2ImageToVideoLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CosmosPredict2ImageToVideoLatent/en.md)

The CosmosPredict2ImageToVideoLatent node creates video latent representations from images for video generation. It can generate a blank video latent or incorporate start and end images to create video sequences with specified dimensions and duration. The node handles the encoding of images into the appropriate latent space format for video processing.

## Inputs

| Parameter     | Data Type | Required | Range                 | Description                                                                      |
| ------------- | --------- | -------- | --------------------- | -------------------------------------------------------------------------------- |
| `vae`         | VAE       | Yes      | -                     | The VAE model used for encoding images into latent space                         |
| `width`       | INT       | Yes      | 16 to MAX\_RESOLUTION | The width of the output video in pixels (default: 848, must be divisible by 16)  |
| `height`      | INT       | Yes      | 16 to MAX\_RESOLUTION | The height of the output video in pixels (default: 480, must be divisible by 16) |
| `length`      | INT       | Yes      | 1 to MAX\_RESOLUTION  | The number of frames in the video sequence (default: 93, step: 4)                |
| `batch_size`  | INT       | Yes      | 1 to 4096             | The number of video sequences to generate (default: 1)                           |
| `start_image` | IMAGE     | No       | -                     | Optional starting image for the video sequence                                   |
| `end_image`   | IMAGE     | No       | -                     | Optional ending image for the video sequence                                     |

**Note:** When neither `start_image` nor `end_image` are provided, the node generates a blank video latent. When images are provided, they are encoded and positioned at the beginning and/or end of the video sequence with appropriate masking.

## Outputs

| Output Name  | Data Type | Description                                                                       |
| ------------ | --------- | --------------------------------------------------------------------------------- |
| `samples`    | LATENT    | The generated video latent representation containing the encoded video sequence   |
| `noise_mask` | LATENT    | A mask indicating which parts of the latent should be preserved during generation |

***

**Source fingerprint (SHA-256):** `5c470c35afaa9b994b431f0a8655e108da420182ec5c223fa54ec2c233ba9fd3`


# EmptyImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyImage

Complete documentation for the EmptyImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

## Function Description

The EmptyImage node is used to create blank images with specified dimensions and colors. It can generate solid-color background images, commonly used as starting points or background images for image processing workflows.

## Working Principle

Just like a painter preparing a blank canvas before starting to create, the EmptyImage node provides you with a "digital canvas". You can specify the canvas size (width and height), choose the base color of the canvas, and even prepare multiple canvases of the same specifications at once. This node is like an intelligent art supply store that can create standardized canvases that perfectly meet your size and color requirements.

## Inputs

| Parameter Name | Data Type | Description                                                                                                                   |
| -------------- | --------- | ----------------------------------------------------------------------------------------------------------------------------- |
| `width`        | INT       | Sets the width of the generated image (in pixels), determining the horizontal dimensions of the canvas                        |
| `height`       | INT       | Sets the height of the generated image (in pixels), determining the vertical dimensions of the canvas                         |
| `batch_size`   | INT       | The number of images to generate at once, used for batch creation of images with the same specifications                      |
| `color`        | INT       | The background color of the image. You can input hexadecimal color settings, which will be automatically converted to decimal |

## Outputs

| Output Name | Data Type | Description                                                                                                          |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------------------- |
| `image`     | IMAGE     | The generated blank image tensor, formatted as \[batch\_size, height, width, 3], containing RGB three color channels |

## Common Color Reference Values

Since the current color input for this node is not user-friendly, with all color values being converted to decimal, here are some common color values that can be used directly for quick application.

| Color Name | Hexadecimal Value |
| ---------- | ----------------- |
| Black      | 0x000000          |
| White      | 0xFFFFFF          |
| Red        | 0xFF0000          |
| Green      | 0x00FF00          |
| Blue       | 0x0000FF          |
| Yellow     | 0xFFFF00          |
| Cyan       | 0x00FFFF          |
| Magenta    | 0xFF00FF          |
| Orange     | 0xFF8000          |
| Purple     | 0x8000FF          |
| Pink       | 0xFF80C0          |
| Brown      | 0x8B4513          |
| Dark Gray  | 0x404040          |
| Light Gray | 0xC0C0C0          |
| Navy Blue  | 0x000080          |
| Dark Green | 0x008000          |
| Dark Red   | 0x800000          |
| Gold       | 0xFFD700          |
| Silver     | 0xC0C0C0          |
| Beige      | 0xF5F5DC          |


# GLIGENTextBoxApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GLIGENTextBoxApply

Complete documentation for the GLIGENTextBoxApply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `GLIGENTextBoxApply` node is designed to integrate text-based conditioning into a generative model's input, specifically by applying text box parameters and encoding them using a CLIP model. This process enriches the conditioning with spatial and textual information, facilitating more precise and context-aware generation.

## Inputs

| Parameter              | Comfy dtype    | Description                                                                                                                                                                                                            |
| ---------------------- | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `conditioning_to`      | `CONDITIONING` | Specifies the initial conditioning input to which the text box parameters and encoded text information will be appended. It plays a crucial role in determining the final output by integrating new conditioning data. |
| `clip`                 | `CLIP`         | The CLIP model used for encoding the provided text into a format that can be utilized by the generative model. It's essential for converting textual information into a compatible conditioning format.                |
| `gligen_textbox_model` | `GLIGEN`       | Represents the specific GLIGEN model configuration to be used for generating the text box. It's crucial for ensuring that the text box is generated according to the desired specifications.                           |
| `text`                 | `STRING`       | The text content to be encoded and integrated into the conditioning. It provides the semantic information that guides the generative model.                                                                            |
| `width`                | `INT`          | The width of the text box in pixels. It defines the spatial dimension of the text box within the generated image.                                                                                                      |
| `height`               | `INT`          | The height of the text box in pixels. Similar to width, it defines the spatial dimension of the text box within the generated image.                                                                                   |
| `x`                    | `INT`          | The x-coordinate of the top-left corner of the text box within the generated image. It specifies the text box's position horizontally.                                                                                 |
| `y`                    | `INT`          | The y-coordinate of the top-left corner of the text box within the generated image. It specifies the text box's position vertically.                                                                                   |

## Outputs

| Parameter      | Comfy dtype    | Description                                                                                                                                                                                                                                 |
| -------------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `conditioning` | `CONDITIONING` | The enriched conditioning output, which includes the original conditioning data along with the newly appended text box parameters and encoded text information. It's used to guide the generative model in producing context-aware outputs. |


# GenerateTracks - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GenerateTracks

Complete documentation for the GenerateTracks node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GenerateTracks/en.md)

The `GenerateTracks` node creates multiple parallel motion paths for video generation. It defines a primary path from a start point to an end point, then generates a set of tracks that run parallel to this path, spaced evenly apart. You can control the shape of the path (straight line or Bezier curve), the speed of movement along it, and which frames the tracks are visible in.

## Inputs

| Parameter       | Data Type | Required | Range                                                                                | Description                                                                                                              |
| --------------- | --------- | -------- | ------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------ |
| `width`         | INT       | Yes      | 16 - 4096                                                                            | The width of the video frame in pixels. The default value is 832.                                                        |
| `height`        | INT       | Yes      | 16 - 4096                                                                            | The height of the video frame in pixels. The default value is 480.                                                       |
| `start_x`       | FLOAT     | Yes      | 0.0 - 1.0                                                                            | Normalized X coordinate (0-1) for start position. The default value is 0.0.                                              |
| `start_y`       | FLOAT     | Yes      | 0.0 - 1.0                                                                            | Normalized Y coordinate (0-1) for start position. The default value is 0.0.                                              |
| `end_x`         | FLOAT     | Yes      | 0.0 - 1.0                                                                            | Normalized X coordinate (0-1) for end position. The default value is 1.0.                                                |
| `end_y`         | FLOAT     | Yes      | 0.0 - 1.0                                                                            | Normalized Y coordinate (0-1) for end position. The default value is 1.0.                                                |
| `num_frames`    | INT       | Yes      | 1 - 1024                                                                             | The total number of frames for which to generate track positions. The default value is 81.                               |
| `num_tracks`    | INT       | Yes      | 1 - 100                                                                              | The number of parallel tracks to generate. The default value is 5.                                                       |
| `track_spread`  | FLOAT     | Yes      | 0.0 - 1.0                                                                            | Normalized distance between tracks. Tracks are spread perpendicular to the motion direction. The default value is 0.025. |
| `bezier`        | BOOLEAN   | Yes      | True / False                                                                         | Enable Bezier curve path using the mid point as control point. The default value is False.                               |
| `mid_x`         | FLOAT     | Yes      | 0.0 - 1.0                                                                            | Normalized X control point for Bezier curve. Only used when 'bezier' is enabled. The default value is 0.5.               |
| `mid_y`         | FLOAT     | Yes      | 0.0 - 1.0                                                                            | Normalized Y control point for Bezier curve. Only used when 'bezier' is enabled. The default value is 0.5.               |
| `interpolation` | COMBO     | Yes      | `"linear"`<br />`"ease_in"`<br />`"ease_out"`<br />`"ease_in_out"`<br />`"constant"` | Controls the timing/speed of movement along the path. The default value is "linear".                                     |
| `track_mask`    | MASK      | No       | -                                                                                    | Optional mask to indicate visible frames.                                                                                |

**Note:** The `mid_x` and `mid_y` parameters are only used when the `bezier` parameter is set to `True`. When `bezier` is `False`, the path is a straight line from the start to the end point.

## Outputs

| Output Name    | Data Type | Description                                                                                                            |
| -------------- | --------- | ---------------------------------------------------------------------------------------------------------------------- |
| `TRACKS`       | TRACKS    | A tracks object containing the generated path coordinates and visibility information for all tracks across all frames. |
| `track_length` | INT       | The number of frames for which tracks were generated, matching the input `num_frames`.                                 |

***

**Source fingerprint (SHA-256):** `e4070f3f092bccaf8410800e36b97f5dc56584847221cfeca469b2bb4ca44355`


# GetICLoRAParameters - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GetICLoRAParameters

Complete documentation for the GetICLoRAParameters node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GetICLoRAParameters/en.md)

## Overview

This node extracts IC-LoRA parameters from the metadata of a LoRA-loaded model. It reads the safetensors metadata to find values like the reference downscale factor and outputs them as a structured parameter object, which can be connected to the LTXVAddGuide node for special guide handling.

## Inputs

| Parameter      | Data Type | Required | Range | Description                                                                                   |
| -------------- | --------- | -------- | ----- | --------------------------------------------------------------------------------------------- |
| `iclora_model` | MODEL     | Yes      | N/A   | Direct output from a LoRA Loader for the specific IC-LoRA from which to extract the metadata. |

## Outputs

| Output Name         | Data Type            | Description                                                                                                                                                            |
| ------------------- | -------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `iclora_parameters` | IC\_LORA\_PARAMETERS | IC-LoRA parameters extracted from the LoRA metadata (e.g., reference\_downscale\_factor). Connect to LTXVAddGuide if the LoRA requires special handling of the guides. |

***

**Source fingerprint (SHA-256):** `44673f0b06cb258014efd77f734c076865d59338ddf825598d85592f000aca50`


# GetImageSize - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GetImageSize

Complete documentation for the GetImageSize node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GetImageSize/en.md)

The GetImageSize node extracts the dimensions and batch information from an input image. It returns the width, height, and batch size of the image while also displaying this information as progress text on the node interface. The original image data passes through unchanged.

## Inputs

| Parameter | Data Type | Required | Range | Description                                            |
| --------- | --------- | -------- | ----- | ------------------------------------------------------ |
| `image`   | IMAGE     | Yes      | -     | The input image from which to extract size information |

## Outputs

| Output Name  | Data Type | Description                             |
| ------------ | --------- | --------------------------------------- |
| `width`      | INT       | The width of the input image in pixels  |
| `height`     | INT       | The height of the input image in pixels |
| `batch_size` | INT       | The number of images in the batch       |

***

**Source fingerprint (SHA-256):** `251c8480ccb1a1462a8d7656ce2b7ef33f2b9f6527b8b306a0850af16ef4094d`


# HiDreamO1ReferenceImages - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HiDreamO1ReferenceImages

Complete documentation for the HiDreamO1ReferenceImages node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HiDreamO1ReferenceImages/en.md)

## Overview

Attach reference images to both positive and negative conditioning. This node allows you to provide one or more reference images that will be used to guide the image generation process, either for editing based on an instruction or for subject-driven personalization.

## Inputs

| Parameter  | Data Type    | Required | Range          | Description                                                                                                                     |
| ---------- | ------------ | -------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| `positive` | CONDITIONING | Yes      | -              | The positive conditioning to attach reference images to.                                                                        |
| `negative` | CONDITIONING | Yes      | -              | The negative conditioning to attach reference images to.                                                                        |
| `images`   | IMAGE        | Yes      | 1 to 10 images | Reference images. 1 image enables instruction-based editing; 2-10 images enable multi-reference subject-driven personalization. |

**Note on `images` parameter:** This is an autogrow input that accepts between 1 and 10 images. The images are labeled `image_1` through `image_10`. You must provide at least 1 image. The number of images determines the mode of operation: a single image is used for edit instructions, while multiple images (2-10) are used for subject-driven personalization.

## Outputs

| Output Name | Data Type    | Description                                                   |
| ----------- | ------------ | ------------------------------------------------------------- |
| `positive`  | CONDITIONING | The positive conditioning with the reference images attached. |
| `negative`  | CONDITIONING | The negative conditioning with the reference images attached. |

***

**Source fingerprint (SHA-256):** `b14a8fc2acd44618370bd7e94758d469ff37530f2e19498a6c72ee3748559303`


# Hunyuan3Dv2Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Hunyuan3Dv2Conditioning

Complete documentation for the Hunyuan3Dv2Conditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Hunyuan3Dv2Conditioning/en.md)

The Hunyuan3Dv2Conditioning node processes CLIP vision output to generate conditioning data for 3D models. It extracts the last hidden state embeddings from the vision output and creates both positive and negative conditioning pairs. The positive conditioning uses the actual embeddings while the negative conditioning uses zero-valued embeddings of the same shape.

## Inputs

| Parameter            | Data Type            | Required | Range | Description                                                      |
| -------------------- | -------------------- | -------- | ----- | ---------------------------------------------------------------- |
| `clip_vision_output` | CLIP\_VISION\_OUTPUT | Yes      | -     | The output from a CLIP vision model containing visual embeddings |

## Outputs

| Output Name | Data Type    | Description                                                                                         |
| ----------- | ------------ | --------------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Positive conditioning data containing the CLIP vision embeddings                                    |
| `negative`  | CONDITIONING | Negative conditioning data containing zero-valued embeddings matching the positive embeddings shape |

***

**Source fingerprint (SHA-256):** `93ee88ca001f59a344c7e3113da0200c75d7a566de9084103f69efe3270231e8`


# Hunyuan3Dv2ConditioningMultiView - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Hunyuan3Dv2ConditioningMultiView

Complete documentation for the Hunyuan3Dv2ConditioningMultiView node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Hunyuan3Dv2ConditioningMultiView/en.md)

The Hunyuan3Dv2ConditioningMultiView node processes multi-view CLIP vision embeddings for 3D video generation. It takes optional front, left, back, and right view embeddings and combines them with positional encoding to create conditioning data for video models. The node outputs both positive conditioning from the combined embeddings and negative conditioning with zero values.

## Inputs

| Parameter | Data Type            | Required | Range | Description                           |
| --------- | -------------------- | -------- | ----- | ------------------------------------- |
| `front`   | CLIP\_VISION\_OUTPUT | No       | -     | CLIP vision output for the front view |
| `left`    | CLIP\_VISION\_OUTPUT | No       | -     | CLIP vision output for the left view  |
| `back`    | CLIP\_VISION\_OUTPUT | No       | -     | CLIP vision output for the back view  |
| `right`   | CLIP\_VISION\_OUTPUT | No       | -     | CLIP vision output for the right view |

**Note:** At least one view input must be provided for the node to function. The node will only process views that contain valid CLIP vision output data.

## Outputs

| Output Name | Data Type    | Description                                                                                  |
| ----------- | ------------ | -------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Positive conditioning containing the combined multi-view embeddings with positional encoding |
| `negative`  | CONDITIONING | Negative conditioning with zero values for contrastive learning                              |

***

**Source fingerprint (SHA-256):** `b1e745e1b626508c974d3a90029f70b224bfefbe0988e98462fc9cb68d46a8f2`


# HunyuanImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanImageToVideo

Complete documentation for the HunyuanImageToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanImageToVideo/en.md)

The HunyuanImageToVideo node converts images into video latent representations using the Hunyuan video model. It takes conditioning inputs and optional starting images to generate video latents that can be further processed by video generation models. The node supports different guidance types for controlling how the starting image influences the video generation process.

## Inputs

| Parameter       | Data Type    | Required | Range                                           | Description                                                                                |
| --------------- | ------------ | -------- | ----------------------------------------------- | ------------------------------------------------------------------------------------------ |
| `positive`      | CONDITIONING | Yes      | -                                               | Positive conditioning input for guiding the video generation                               |
| `vae`           | VAE          | Yes      | -                                               | VAE model used for encoding images into latent space                                       |
| `width`         | INT          | Yes      | 16 to MAX\_RESOLUTION                           | Width of the output video in pixels (default: 848, step: 16)                               |
| `height`        | INT          | Yes      | 16 to MAX\_RESOLUTION                           | Height of the output video in pixels (default: 480, step: 16)                              |
| `length`        | INT          | Yes      | 1 to MAX\_RESOLUTION                            | Number of frames in the output video (default: 53, step: 4)                                |
| `batch_size`    | INT          | Yes      | 1 to 4096                                       | Number of videos to generate simultaneously (default: 1)                                   |
| `guidance_type` | COMBO        | Yes      | "v1 (concat)"<br />"v2 (replace)"<br />"custom" | Method for incorporating the starting image into video generation (default: "v1 (concat)") |
| `start_image`   | IMAGE        | No       | -                                               | Optional starting image to initialize the video generation                                 |

**Note:** When `start_image` is provided, the node uses different guidance methods based on the selected `guidance_type`:

* "v1 (concat)": Concatenates the image latent with the video latent and applies a mask to blend the image into the video
* "v2 (replace)": Replaces initial video frames with the image latent and applies a noise mask
* "custom": Uses the image as a reference latent for guidance

## Outputs

| Output Name | Data Type    | Description                                                                              |
| ----------- | ------------ | ---------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Modified positive conditioning with image guidance applied when start\_image is provided |
| `latent`    | LATENT       | Video latent representation ready for further processing by video generation models      |

***

**Source fingerprint (SHA-256):** `171e60e0ff5bbe2715b83693212e91dd9a3e2236e7b4437c7e33929d6143ae4f`


# HunyuanRefinerLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanRefinerLatent

Complete documentation for the HunyuanRefinerLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanRefinerLatent/en.md)

The HunyuanRefinerLatent node processes conditioning and latent inputs for refinement operations. It applies noise augmentation to both positive and negative conditioning while incorporating latent image data, and generates a new latent output with specific dimensions for further processing.

## Inputs

| Parameter            | Data Type    | Required | Range     | Description                                               |
| -------------------- | ------------ | -------- | --------- | --------------------------------------------------------- |
| `positive`           | CONDITIONING | Yes      | -         | The positive conditioning input to be processed           |
| `negative`           | CONDITIONING | Yes      | -         | The negative conditioning input to be processed           |
| `latent`             | LATENT       | Yes      | -         | The latent representation input                           |
| `noise_augmentation` | FLOAT        | Yes      | 0.0 - 1.0 | The amount of noise augmentation to apply (default: 0.10) |

## Outputs

| Output Name | Data Type    | Description                                                                                        |
| ----------- | ------------ | -------------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | The processed positive conditioning with applied noise augmentation and latent image concatenation |
| `negative`  | CONDITIONING | The processed negative conditioning with applied noise augmentation and latent image concatenation |
| `latent`    | LATENT       | A new latent output with dimensions \[batch\_size, 32, height, width, channels]                    |

***

**Source fingerprint (SHA-256):** `da9ba6729a4ff9147e3783841200ae5b6a9a20ab396e82d7ac6300faec3dc8f9`


# HunyuanVideo15ImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanVideo15ImageToVideo

Complete documentation for the HunyuanVideo15ImageToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanVideo15ImageToVideo/en.md)

The HunyuanVideo15ImageToVideo node prepares conditioning and latent space data for video generation based on the HunyuanVideo 1.5 model. It creates an initial latent representation for a video sequence and can optionally integrate a starting image or a CLIP vision output to guide the generation process.

## Inputs

| Parameter            | Data Type            | Required | Range                           | Description                                                                                                                                                                             |
| -------------------- | -------------------- | -------- | ------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`           | CONDITIONING         | Yes      | -                               | The positive conditioning prompts that describe what the video should contain.                                                                                                          |
| `negative`           | CONDITIONING         | Yes      | -                               | The negative conditioning prompts that describe what the video should avoid.                                                                                                            |
| `vae`                | VAE                  | Yes      | -                               | The VAE (Variational Autoencoder) model used to encode the starting image into the latent space.                                                                                        |
| `width`              | INT                  | No       | 16 to MAX\_RESOLUTION, step: 16 | The width of the output video frames in pixels. Must be divisible by 16. (default: 848)                                                                                                 |
| `height`             | INT                  | No       | 16 to MAX\_RESOLUTION, step: 16 | The height of the output video frames in pixels. Must be divisible by 16. (default: 480)                                                                                                |
| `length`             | INT                  | No       | 1 to MAX\_RESOLUTION, step: 4   | The total number of frames in the video sequence. Must be a multiple of 4. (default: 33)                                                                                                |
| `batch_size`         | INT                  | No       | 1 to 4096                       | The number of video sequences to generate in a single batch. (default: 1)                                                                                                               |
| `start_image`        | IMAGE                | No       | -                               | An optional starting image to initialize the video generation. If provided, it is encoded and used to condition the first frames. Only the first `length` frames of the image are used. |
| `clip_vision_output` | CLIP\_VISION\_OUTPUT | No       | -                               | Optional CLIP vision embeddings to provide additional visual conditioning for the generation.                                                                                           |

**Note:** When a `start_image` is provided, it is automatically resized to match the specified `width` and `height` using bilinear interpolation. The first `length` frames of the image batch are used. The encoded image is then added to both the `positive` and `negative` conditioning as a `concat_latent_image` with a corresponding `concat_mask`. The mask is set to 0.0 for the frames covered by the starting image and 1.0 for the remaining frames.

## Outputs

| Output Name | Data Type    | Description                                                                                                      |
| ----------- | ------------ | ---------------------------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | The modified positive conditioning, which may now include the encoded starting image or CLIP vision output.      |
| `negative`  | CONDITIONING | The modified negative conditioning, which may now include the encoded starting image or CLIP vision output.      |
| `latent`    | LATENT       | An empty latent tensor with dimensions configured for the specified batch size, video length, width, and height. |

***

**Source fingerprint (SHA-256):** `383b965a2e67c3643a13991ea5969c4d31ce17e48a57a400f89974f64e4b1e04`


# HunyuanVideo15SuperResolution - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanVideo15SuperResolution

Complete documentation for the HunyuanVideo15SuperResolution node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanVideo15SuperResolution/en.md)

The HunyuanVideo15SuperResolution node prepares conditioning data for a video super-resolution process. It takes a latent representation of a video and, optionally, a starting image, and packages them along with noise augmentation and CLIP vision data into a format that can be used by a model to generate a higher-resolution output.

## Inputs

| Parameter            | Data Type            | Required | Range     | Description                                                                                                                          |
| -------------------- | -------------------- | -------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------ |
| `positive`           | CONDITIONING         | Yes      | N/A       | The positive conditioning input to be modified with latent and augmentation data.                                                    |
| `negative`           | CONDITIONING         | Yes      | N/A       | The negative conditioning input to be modified with latent and augmentation data.                                                    |
| `vae`                | VAE                  | No       | N/A       | The VAE used to encode the optional `start_image`. Required if `start_image` is provided.                                            |
| `start_image`        | IMAGE                | No       | N/A       | An optional starting image to guide the super-resolution. If provided, it will be upscaled and encoded into the conditioning latent. |
| `clip_vision_output` | CLIP\_VISION\_OUTPUT | No       | N/A       | Optional CLIP vision embeddings to add to the conditioning.                                                                          |
| `latent`             | LATENT               | Yes      | N/A       | The input latent video representation that will be incorporated into the conditioning.                                               |
| `noise_augmentation` | FLOAT                | No       | 0.0 - 1.0 | The strength of noise augmentation to apply to the conditioning (default: 0.70).                                                     |

**Note:** If you provide a `start_image`, you must also connect a `vae` for it to be encoded. The `start_image` will be automatically upscaled to match the dimensions implied by the input `latent`.

## Outputs

| Output Name | Data Type    | Description                                                                                                                    |
| ----------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------ |
| `positive`  | CONDITIONING | The modified positive conditioning, now containing the concatenated latent, noise augmentation, and optional CLIP vision data. |
| `negative`  | CONDITIONING | The modified negative conditioning, now containing the concatenated latent, noise augmentation, and optional CLIP vision data. |
| `latent`    | LATENT       | The input latent is passed through unchanged.                                                                                  |

***

**Source fingerprint (SHA-256):** `12bb48e731a265f806e5961950b3fc9c64e30148785e443a40c8d9f3ad9484e4`


# ImageBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageBatch

Complete documentation for the ImageBatch node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `ImageBatch` node is designed for combining two images into a single batch. If the dimensions of the images do not match, it automatically rescales the second image to match the first one's dimensions before combining them.

## Inputs

| Parameter | Data Type | Description                                                                                                                                           |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image1`  | `IMAGE`   | The first image to be combined into the batch. It serves as the reference for the dimensions to which the second image will be adjusted if necessary. |
| `image2`  | `IMAGE`   | The second image to be combined into the batch. It is automatically rescaled to match the dimensions of the first image if they differ.               |

## Outputs

| Parameter | Data Type | Description                                                                                                 |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The combined batch of images, with the second image rescaled to match the first one's dimensions if needed. |


# ImageCompare - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageCompare

Complete documentation for the ImageCompare node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageCompare/en.md)

The Image Compare node provides a visual interface to compare two images side-by-side using a draggable slider. It is designed as an output node, meaning it does not pass data to other nodes but instead displays the images directly in the user interface for inspection.

## Inputs

| Parameter      | Data Type    | Required | Range | Description                                                    |
| -------------- | ------------ | -------- | ----- | -------------------------------------------------------------- |
| `image_a`      | IMAGE        | No       | -     | The first image to compare.                                    |
| `image_b`      | IMAGE        | No       | -     | The second image to compare.                                   |
| `compare_view` | IMAGECOMPARE | Yes      | -     | The control that enables the slider comparison view in the UI. |

**Note:** This node is an output node. While `image_a` and `image_b` are optional, at least one image must be provided for the node to have a visible effect. The node will display an empty area for any image input that is not connected.

## Outputs

This node is an output node and does not produce any data outputs for use in other nodes. Its function is to display the provided images in the ComfyUI interface.

***

**Source fingerprint (SHA-256):** `78dc2addde0b1b867303b5f534c09b60342a3d94d829d314c71b29ce7707648e`


# ImageInvert - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageInvert

Complete documentation for the ImageInvert node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `ImageInvert` node is designed to invert the colors of an image, effectively transforming each pixel's color value to its complementary color on the color wheel. This operation is useful for creating negative images or for visual effects that require color inversion.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                                                                     |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The 'image' parameter represents the input image to be inverted. It is crucial for specifying the target image whose colors are to be inverted, affecting the node's execution and the visual outcome of the inversion process. |

## Outputs

| Parameter | Data Type | Description                                                                                                                 |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The output is an inverted version of the input image, with each pixel's color value transformed to its complementary color. |


# InpaintModelConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/InpaintModelConditioning

Complete documentation for the InpaintModelConditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The InpaintModelConditioning node is designed to facilitate the conditioning process for inpainting models, enabling the integration and manipulation of various conditioning inputs to tailor the inpainting output. It encompasses a broad range of functionalities, from loading specific model checkpoints and applying style or control net models, to encoding and combining conditioning elements, thereby serving as a comprehensive tool for customizing inpainting tasks.

## Inputs

| Parameter  | Comfy dtype    | Description                                                                                                                                                                                                                                                                      |
| ---------- | -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive` | `CONDITIONING` | Represents the positive conditioning information or parameters that are to be applied to the inpainting model. This input is crucial for defining the context or constraints under which the inpainting operation should be performed, affecting the final output significantly. |
| `negative` | `CONDITIONING` | Represents the negative conditioning information or parameters that are to be applied to the inpainting model. This input is essential for specifying the conditions or contexts to avoid during the inpainting process, thereby influencing the final output.                   |
| `vae`      | `VAE`          | Specifies the VAE model to be used in the conditioning process. This input is crucial for determining the specific architecture and parameters of the VAE model that will be utilized.                                                                                           |
| `pixels`   | `IMAGE`        | Represents the pixel data of the image to be inpainted. This input is essential for providing the visual context necessary for the inpainting task.                                                                                                                              |
| `mask`     | `MASK`         | Specifies the mask to be applied to the image, indicating the areas to be inpainted. This input is crucial for defining the specific regions within the image that require inpainting.                                                                                           |

## Outputs

| Parameter  | Data Type      | Description                                                                                                                                                                                                               |
| ---------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive` | `CONDITIONING` | The modified positive conditioning information after processing, ready to be applied to the inpainting model. This output is essential for guiding the inpainting process according to the specified positive conditions. |
| `negative` | `CONDITIONING` | The modified negative conditioning information after processing, ready to be applied to the inpainting model. This output is essential for guiding the inpainting process according to the specified negative conditions. |
| `latent`   | `LATENT`       | The latent representation derived from the conditioning process. This output is crucial for understanding the underlying features and characteristics of the image being inpainted.                                       |


# InstructPixToPixConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/InstructPixToPixConditioning

Complete documentation for the InstructPixToPixConditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/InstructPixToPixConditioning/en.md)

The InstructPixToPixConditioning node prepares conditioning data for InstructPix2Pix image editing by combining positive and negative text prompts with image data. It processes input images through a VAE encoder to create latent representations and attaches these latents to both positive and negative conditioning data. The node automatically handles image dimensions by cropping to multiples of 8 pixels for compatibility with the VAE encoding process.

## Inputs

| Parameter  | Data Type    | Required | Range | Description                                                                                         |
| ---------- | ------------ | -------- | ----- | --------------------------------------------------------------------------------------------------- |
| `positive` | CONDITIONING | Yes      | -     | Positive conditioning data containing text prompts and settings for desired image characteristics   |
| `negative` | CONDITIONING | Yes      | -     | Negative conditioning data containing text prompts and settings for undesired image characteristics |
| `vae`      | VAE          | Yes      | -     | VAE model used for encoding input images into latent representations                                |
| `pixels`   | IMAGE        | Yes      | -     | Input image to be processed and encoded into latent space                                           |

**Note:** The input image dimensions are automatically adjusted by cropping to the nearest multiple of 8 pixels in both width and height to ensure compatibility with the VAE encoding process.

## Outputs

| Output Name | Data Type    | Description                                                          |
| ----------- | ------------ | -------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Positive conditioning data with attached latent image representation |
| `negative`  | CONDITIONING | Negative conditioning data with attached latent image representation |
| `latent`    | LATENT       | Empty latent tensor with the same dimensions as the encoded image    |

***

**Source fingerprint (SHA-256):** `ac48cc0d3c77f1e399b615068291ae60801f36a6c4e1ae47d624fbc08e0b7264`


# Kandinsky5ImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Kandinsky5ImageToVideo

Complete documentation for the Kandinsky5ImageToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Kandinsky5ImageToVideo/en.md)

The Kandinsky5ImageToVideo node prepares conditioning and latent space data for video generation using the Kandinsky model. It creates an empty video latent tensor and can optionally encode a starting image to guide the initial frames of the generated video, modifying the positive and negative conditioning accordingly.

## Inputs

| Parameter     | Data Type    | Required | Range                | Description                                                                                                               |
| ------------- | ------------ | -------- | -------------------- | ------------------------------------------------------------------------------------------------------------------------- |
| `positive`    | CONDITIONING | Yes      | N/A                  | The positive conditioning prompts to guide the video generation.                                                          |
| `negative`    | CONDITIONING | Yes      | N/A                  | The negative conditioning prompts to steer the video generation away from certain concepts.                               |
| `vae`         | VAE          | Yes      | N/A                  | The VAE model used to encode the optional starting image into the latent space.                                           |
| `width`       | INT          | No       | 16 to 8192 (step 16) | The width of the output video in pixels (default: 768).                                                                   |
| `height`      | INT          | No       | 16 to 8192 (step 16) | The height of the output video in pixels (default: 512).                                                                  |
| `length`      | INT          | No       | 1 to 8192 (step 4)   | The number of frames in the video (default: 121).                                                                         |
| `batch_size`  | INT          | No       | 1 to 4096            | The number of video sequences to generate simultaneously (default: 1).                                                    |
| `start_image` | IMAGE        | No       | N/A                  | An optional starting image. If provided, it is encoded and used to replace the noisy start of the model's output latents. |

**Note:** When a `start_image` is provided, it is automatically resized to match the specified `width` and `height` using bilinear interpolation. The first `length` frames of the image batch are used for encoding. The encoded latent is then injected into both the `positive` and `negative` conditioning to guide the video's initial appearance.

## Outputs

| Output Name   | Data Type    | Description                                                                                                                                                   |
| ------------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`    | CONDITIONING | The modified positive conditioning, potentially updated with encoded start image data.                                                                        |
| `negative`    | CONDITIONING | The modified negative conditioning, potentially updated with encoded start image data.                                                                        |
| `latent`      | LATENT       | An empty video latent tensor with zeros, shaped for the specified dimensions.                                                                                 |
| `cond_latent` | LATENT       | The clean, encoded latent representation of the provided start images. This is used internally to replace the noisy beginning of the generated video latents. |

***

**Source fingerprint (SHA-256):** `c171187b89f102d608ddee9dc981e56674d62b02d936b3cf4dee3ce86760fd0e`


# LTXVAddGuide - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVAddGuide

Complete documentation for the LTXVAddGuide node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVAddGuide/en.md)

The LTXVAddGuide node adds video conditioning guidance to latent sequences by encoding input images or videos and incorporating them as keyframes into the conditioning data. It processes the input through a VAE encoder and strategically places the resulting latents at specified frame positions while updating both positive and negative conditioning with keyframe information. The node handles frame alignment constraints and allows control over the strength of the conditioning influence.

## Inputs

| Parameter           | Data Type            | Required | Range         | Description                                                                                                                                                                                                                                                                                                                        |
| ------------------- | -------------------- | -------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`          | CONDITIONING         | Yes      | -             | Positive conditioning input to be modified with keyframe guidance                                                                                                                                                                                                                                                                  |
| `negative`          | CONDITIONING         | Yes      | -             | Negative conditioning input to be modified with keyframe guidance                                                                                                                                                                                                                                                                  |
| `vae`               | VAE                  | Yes      | -             | VAE model used for encoding the input image/video frames                                                                                                                                                                                                                                                                           |
| `latent`            | LATENT               | Yes      | -             | Input latent sequence that will receive the conditioning frames                                                                                                                                                                                                                                                                    |
| `image`             | IMAGE                | Yes      | -             | Image or video to condition the latent video on. Must be 8*n + 1 frames. If the video is not 8*n + 1 frames, it will be cropped to the nearest 8\*n + 1 frames.                                                                                                                                                                    |
| `frame_idx`         | INT                  | No       | -9999 to 9999 | Frame index to start the conditioning at. For single-frame images or videos with 1-8 frames, any frame\_idx value is acceptable. For videos with 9+ frames, frame\_idx must be divisible by 8, otherwise it will be rounded down to the nearest multiple of 8. Negative values are counted from the end of the video. (default: 0) |
| `strength`          | FLOAT                | No       | 0.0 to 10.0   | Strength of the conditioning influence, where 1.0 applies full conditioning and 0.0 applies no conditioning (default: 1.0)                                                                                                                                                                                                         |
| `attention_mask`    | MASK                 | No       | -             | Optional pixel-space spatial mask. Controls per-region conditioning influence via self-attention, multiplied by strength.                                                                                                                                                                                                          |
| `iclora_parameters` | IC\_LORA\_PARAMETERS | No       | -             | Optional IC-LoRA parameters from a Get IC-LoRA Parameters node. Used for adjusting guide processing as required by certain IC-LoRAs (e.g., those with a reference\_downscale\_factor > 1). When chained, each LTXVAddGuide uses only the parameters connected to it.                                                               |

**Note:** The input image/video must have a frame count following the 8\*n + 1 pattern (e.g., 1, 9, 17, 25 frames). If the input exceeds this pattern, it will be automatically cropped to the nearest valid frame count.

**Note on `iclora_parameters`:** When using IC-LoRA parameters with a `reference_downscale_factor` greater than 1, the latent spatial dimensions (width and height) must be divisible by that factor. The node will raise an error if this condition is not met.

## Outputs

| Output Name | Data Type    | Description                                                                  |
| ----------- | ------------ | ---------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Positive conditioning updated with keyframe guidance information             |
| `negative`  | CONDITIONING | Negative conditioning updated with keyframe guidance information             |
| `latent`    | LATENT       | Latent sequence with incorporated conditioning frames and updated noise mask |

***

**Source fingerprint (SHA-256):** `889348768112c6ecc3ef2e724981d3c49d96339b156617725816cf4186a94b7a`


# LTXVConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVConditioning

Complete documentation for the LTXVConditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVConditioning/en.md)

The LTXVConditioning node adds frame rate information to both positive and negative conditioning inputs for video generation models. It takes existing conditioning data and applies the specified frame rate value to both conditioning sets, making them suitable for video model processing.

## Inputs

| Parameter    | Data Type    | Required | Range        | Description                                                                  |
| ------------ | ------------ | -------- | ------------ | ---------------------------------------------------------------------------- |
| `positive`   | CONDITIONING | Yes      | -            | The positive conditioning input that will receive the frame rate information |
| `negative`   | CONDITIONING | Yes      | -            | The negative conditioning input that will receive the frame rate information |
| `frame_rate` | FLOAT        | Yes      | 0.0 - 1000.0 | The frame rate value to apply to both conditioning sets (default: 25.0)      |

## Outputs

| Output Name | Data Type    | Description                                                   |
| ----------- | ------------ | ------------------------------------------------------------- |
| `positive`  | CONDITIONING | The positive conditioning with frame rate information applied |
| `negative`  | CONDITIONING | The negative conditioning with frame rate information applied |

***

**Source fingerprint (SHA-256):** `8089df723caec60e89d309f004a8cd4bbe376e075bfa39bc881cf5a1bbe359c7`


# LTXVCropGuides - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVCropGuides

Complete documentation for the LTXVCropGuides node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVCropGuides/en.md)

The LTXVCropGuides node processes conditioning and latent inputs for video generation by removing keyframe information and adjusting the latent dimensions. It crops the latent image and noise mask to exclude keyframe sections while clearing keyframe indices from both positive and negative conditioning inputs. This prepares the data for video generation workflows that don't require keyframe guidance.

## Inputs

| Parameter  | Data Type    | Required | Range | Description                                                                                     |
| ---------- | ------------ | -------- | ----- | ----------------------------------------------------------------------------------------------- |
| `positive` | CONDITIONING | Yes      | -     | The positive conditioning input containing guidance information for generation                  |
| `negative` | CONDITIONING | Yes      | -     | The negative conditioning input containing guidance information for what to avoid in generation |
| `latent`   | LATENT       | Yes      | -     | The latent representation containing image samples and noise mask data                          |

## Outputs

| Output Name | Data Type    | Description                                                                                                       |
| ----------- | ------------ | ----------------------------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | The processed positive conditioning with keyframe indices and guide attention entries cleared                     |
| `negative`  | CONDITIONING | The processed negative conditioning with keyframe indices and guide attention entries cleared                     |
| `latent`    | LATENT       | The cropped latent representation with adjusted samples and noise mask, where keyframe sections have been removed |

***

**Source fingerprint (SHA-256):** `b5981a2e685c3590df2ced4b619d6d4596971255c8eb6081d63f917a9a938504`


# LTXVImgToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVImgToVideo

Complete documentation for the LTXVImgToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVImgToVideo/en.md)

The LTXVImgToVideo node converts an input image into a video latent representation for video generation models. It takes a single image and extends it into a sequence of frames using the VAE encoder, then applies conditioning with strength control to determine how much of the original image content is preserved versus modified during video generation.

## Inputs

| Parameter    | Data Type    | Required | Range                 | Description                                                                                                                                                                                                              |
| ------------ | ------------ | -------- | --------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `positive`   | CONDITIONING | Yes      | -                     | Positive conditioning prompts for guiding the video generation                                                                                                                                                           |
| `negative`   | CONDITIONING | Yes      | -                     | Negative conditioning prompts for avoiding certain elements in the video                                                                                                                                                 |
| `vae`        | VAE          | Yes      | -                     | VAE model used for encoding the input image into latent space                                                                                                                                                            |
| `image`      | IMAGE        | Yes      | -                     | Input image to be converted into video frames                                                                                                                                                                            |
| `width`      | INT          | No       | 64 to MAX\_RESOLUTION | Output video width in pixels (default: 768, step: 32)                                                                                                                                                                    |
| `height`     | INT          | No       | 64 to MAX\_RESOLUTION | Output video height in pixels (default: 512, step: 32)                                                                                                                                                                   |
| `length`     | INT          | No       | 9 to MAX\_RESOLUTION  | Number of frames in the generated video (default: 97, step: 8)                                                                                                                                                           |
| `batch_size` | INT          | No       | 1 to 4096             | Number of videos to generate simultaneously (default: 1)                                                                                                                                                                 |
| `strength`   | FLOAT        | No       | 0.0 to 1.0            | Control over how much of the original image content is preserved in the first frame of the generated video. A value of 1.0 preserves the original image completely, while 0.0 allows maximum modification (default: 1.0) |

## Outputs

| Output Name | Data Type    | Description                                                                                   |
| ----------- | ------------ | --------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Processed positive conditioning with video frame masking applied                              |
| `negative`  | CONDITIONING | Processed negative conditioning with video frame masking applied                              |
| `latent`    | LATENT       | Video latent representation containing the encoded frames and noise mask for video generation |

***

**Source fingerprint (SHA-256):** `1f9d897d1f461270106bf44106acc90db422a04e6bce10ad3bca22127e96ffab`


# LTXVImgToVideoInplace - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVImgToVideoInplace

Complete documentation for the LTXVImgToVideoInplace node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVImgToVideoInplace/en.md)

The LTXVImgToVideoInplace node conditions a video latent representation by encoding an input image into its initial frames. It works by using a VAE to encode the image into the latent space and then blending it with the existing latent samples based on a specified strength. This allows an image to serve as a starting point or conditioning signal for video generation.

## Inputs

| Parameter  | Data Type | Required | Range     | Description                                                                                                                                                          |
| ---------- | --------- | -------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `vae`      | VAE       | Yes      | -         | The VAE model used to encode the input image into the latent space.                                                                                                  |
| `image`    | IMAGE     | Yes      | -         | The input image to be encoded and used to condition the video latent.                                                                                                |
| `latent`   | LATENT    | Yes      | -         | The target latent video representation to be modified.                                                                                                               |
| `strength` | FLOAT     | No       | 0.0 - 1.0 | Controls the blending strength of the encoded image into the latent. A value of 1.0 fully replaces the initial frames, while lower values blend them. (default: 1.0) |
| `bypass`   | BOOLEAN   | No       | -         | Bypass the conditioning. When enabled, the node returns the input latent unchanged. (default: False)                                                                 |

**Note:** The `image` will be automatically resized to match the spatial dimensions required by the `vae` for encoding, based on the `latent` input's width and height.

## Outputs

| Output Name | Data Type | Description                                                                                                                                                |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `latent`    | LATENT    | The modified latent video representation. It contains the updated samples and a `noise_mask` that applies the conditioning strength to the initial frames. |

***

**Source fingerprint (SHA-256):** `5824199a55eb455f28399447d6834ede2cc5c33d1be09e550631bbfeef77d785`


# LTXVReferenceAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVReferenceAudio

Complete documentation for the LTXVReferenceAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVReferenceAudio/en.md)

The LTXV Reference Audio node is used for speaker identity transfer in audio generation. It encodes a reference audio clip into the conditioning for a model, allowing the generated audio to adopt the speaker's voice characteristics. It can also apply identity guidance, which runs an extra processing step to amplify the speaker identity effect.

## Inputs

| Parameter                 | Data Type    | Required | Range       | Description                                                                                                                                                            |
| ------------------------- | ------------ | -------- | ----------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`                   | MODEL        | Yes      | -           | The model to be patched with identity guidance.                                                                                                                        |
| `positive`                | CONDITIONING | Yes      | -           | The positive conditioning input.                                                                                                                                       |
| `negative`                | CONDITIONING | Yes      | -           | The negative conditioning input.                                                                                                                                       |
| `reference_audio`         | AUDIO        | Yes      | -           | Reference audio clip whose speaker identity to transfer. \~5 seconds recommended (training duration). Shorter or longer clips may degrade voice identity transfer.     |
| `audio_vae`               | VAE          | Yes      | -           | LTXV Audio VAE for encoding the reference audio.                                                                                                                       |
| `identity_guidance_scale` | FLOAT        | No       | 0.0 - 100.0 | Strength of identity guidance. Runs an extra forward pass without reference each step to amplify speaker identity. Set to 0 to disable (no extra pass). (default: 3.0) |
| `start_percent`           | FLOAT        | No       | 0.0 - 1.0   | Start of the sigma range where identity guidance is active. (default: 0.0)                                                                                             |
| `end_percent`             | FLOAT        | No       | 0.0 - 1.0   | End of the sigma range where identity guidance is active. (default: 1.0)                                                                                               |

## Outputs

| Output Name | Data Type    | Description                                                                 |
| ----------- | ------------ | --------------------------------------------------------------------------- |
| `model`     | MODEL        | The model patched with the identity guidance function.                      |
| `positive`  | CONDITIONING | The positive conditioning, now containing the encoded reference audio data. |
| `negative`  | CONDITIONING | The negative conditioning, now containing the encoded reference audio data. |

***

**Source fingerprint (SHA-256):** `a25e24a08df73b8a34fd476544634e396a0eec5b6dc630e911c371f1b16931b8`


# LoadImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImage

Complete documentation for the LoadImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LoadImage node is designed to load and preprocess images from a specified path. It handles image formats with multiple frames, applies necessary transformations such as rotation based on EXIF data, normalizes pixel values, and optionally generates a mask for images with an alpha channel. This node is essential for preparing images for further processing or analysis within a pipeline.

## Inputs

| Parameter | Data Type      | Description                                                                                                                                                                                                               |
| --------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`   | COMBO\[STRING] | The 'image' parameter specifies the identifier of the image to be loaded and processed. It is crucial for determining the path to the image file and subsequently loading the image for transformation and normalization. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                 |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The processed image, with pixel values normalized and transformations applied as necessary. It is ready for further processing or analysis. |
| `mask`    | `MASK`    | An optional output providing a mask for the image, useful in scenarios where the image includes an alpha channel for transparency.          |


# LoadImageDataSetFromFolder - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageDataSetFromFolder

Complete documentation for the LoadImageDataSetFromFolder node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageDataSetFromFolder/en.md)

This node loads multiple images from a specified subfolder within ComfyUI's input directory. It scans the chosen folder for common image file types and returns them as a list, making it useful for batch processing or dataset preparation.

## Inputs

| Parameter | Data Type | Required | Range                        | Description                                                                                               |
| --------- | --------- | -------- | ---------------------------- | --------------------------------------------------------------------------------------------------------- |
| `folder`  | STRING    | Yes      | *Multiple options available* | The folder to load images from. The options are the subfolders present in ComfyUI's main input directory. |

## Outputs

| Output Name | Data Type | Description                                                                                                      |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------- |
| `images`    | IMAGE     | List of loaded images. The node loads all valid image files (PNG, JPG, JPEG, WEBP) found in the selected folder. |

***

**Source fingerprint (SHA-256):** `62db052cfda66658172a881214d2a30dcfe626bec3ae619d1d32c75e327339c4`


# LoadImageMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageMask

Complete documentation for the LoadImageMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LoadImageMask node is designed to load images and their associated masks from a specified path, processing them to ensure compatibility with further image manipulation or analysis tasks. It focuses on handling various image formats and conditions, such as presence of an alpha channel for masks, and prepares the images and masks for downstream processing by converting them to a standardized format.

## Inputs

| Parameter | Data Type      | Description                                                                                                                                                                                                                                                  |
| --------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `image`   | COMBO\[STRING] | The 'image' parameter specifies the image file to be loaded and processed. It plays a crucial role in determining the output by providing the source image for mask extraction and format conversion.                                                        |
| `channel` | COMBO\[STRING] | The 'channel' parameter specifies the color channel of the image that will be used to generate the mask. This allows for flexibility in mask creation based on different color channels, enhancing the node's utility in various image processing scenarios. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                               |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `mask`    | `MASK`    | This node outputs the mask generated from the specified image and channel, prepared in a standardized format suitable for further processing in image manipulation tasks. |


# LoadImageOutput - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageOutput

Complete documentation for the LoadImageOutput node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageOutput/en.md)

The LoadImageOutput node loads images from the output folder. When you click the refresh button, it updates the list of available images and automatically selects the first one, making it easy to iterate through your generated images.

## Inputs

| Parameter | Data Type | Required | Range                      | Description                                                                                                                                                                                                                                                 |
| --------- | --------- | -------- | -------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`   | COMBO     | Yes      | Multiple options available | Load an image from the output folder. Includes an upload option and refresh button to update the image list. When the refresh button is clicked, the node will update the image list and automatically select the first image, allowing for easy iteration. |

## Outputs

| Output Name | Data Type | Description                               |
| ----------- | --------- | ----------------------------------------- |
| `image`     | IMAGE     | The loaded image from the output folder   |
| `mask`      | MASK      | The mask associated with the loaded image |

***

**Source fingerprint (SHA-256):** `d1de0140765c9d5dd393715faa84dc5c3f0e49117391b8823a51b176bcb568d8`


# LoadImageSetFromFolderNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageSetFromFolderNode

Complete documentation for the LoadImageSetFromFolderNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageSetFromFolderNode/en.md)

The LoadImageSetFromFolderNode loads multiple images from a specified folder directory for training purposes. It automatically detects common image formats and can optionally resize the images using different methods before returning them as a batch.

## Inputs

| Parameter       | Data Type | Required | Range                                        | Description                                              |
| --------------- | --------- | -------- | -------------------------------------------- | -------------------------------------------------------- |
| `folder`        | STRING    | Yes      | Multiple options available                   | The folder to load images from.                          |
| `resize_method` | STRING    | No       | "None"<br />"Stretch"<br />"Crop"<br />"Pad" | The method to use for resizing images (default: "None"). |

## Outputs

| Output Name | Data Type | Description                                    |
| ----------- | --------- | ---------------------------------------------- |
| `IMAGE`     | IMAGE     | The batch of loaded images as a single tensor. |

***

**Source fingerprint (SHA-256):** `46fcfbf6a2ad95e707e32e54ed7b4c06bfd1cc290df122042187689f41bed828`


# LoadImageSetNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageSetNode

Complete documentation for the LoadImageSetNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageSetNode/en.md)

The LoadImageSetNode loads multiple images from the input directory for batch processing and training purposes. It supports various image formats and can optionally resize the images using different methods. This node processes all selected images as a batch and returns them as a single tensor.

## Inputs

| Parameter       | Data Type | Required | Range                                        | Description                                                                                                                                                                                                                   |
| --------------- | --------- | -------- | -------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `images`        | IMAGE     | Yes      | Multiple image files                         | Select multiple images from the input directory. Supports PNG, JPG, JPEG, WEBP, BMP, GIF, JPE, APNG, TIF, and TIFF formats. Allows batch selection of images.                                                                 |
| `resize_method` | STRING    | No       | "None"<br />"Stretch"<br />"Crop"<br />"Pad" | Optional method to resize loaded images (default: "None"). Choose "None" to keep original sizes, "Stretch" to force resize, "Crop" to maintain aspect ratio by cropping, or "Pad" to maintain aspect ratio by adding padding. |

## Outputs

| Output Name | Data Type | Description                                                              |
| ----------- | --------- | ------------------------------------------------------------------------ |
| `IMAGE`     | IMAGE     | A tensor containing all loaded images as a batch for further processing. |

***

**Source fingerprint (SHA-256):** `acf0255bcf170ef3ac3b86a3f3e060c3b81064ca8924918a026ec8e3b86f7ac0`


# LoadImageTextDataSetFromFolder - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageTextDataSetFromFolder

Complete documentation for the LoadImageTextDataSetFromFolder node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageTextDataSetFromFolder/en.md)

This node loads a dataset of images and their corresponding text captions from a specified folder. It searches for image files and automatically looks for matching `.txt` files with the same base name to use as captions. The node also supports a specific folder structure where subfolders can be named with a number prefix (like `10_folder_name`) to indicate that the images inside should be repeated multiple times in the output.

## Inputs

| Parameter | Data Type | Required | Range                                                           | Description                                                                                                                      |
| --------- | --------- | -------- | --------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------- |
| `folder`  | COMBO     | Yes      | *Dynamically loaded from `folder_paths.get_input_subfolders()`* | The folder to load images and text captions from. The available options are the subdirectories within ComfyUI's input directory. |

**Note:** The node expects a specific file structure. For each image file (`.png`, `.jpg`, `.jpeg`, `.webp`), it will look for a `.txt` file with the same name to use as a caption. If a caption file is not found, an empty string is used. The node also supports a special structure where a subfolder's name begins with a number and an underscore (e.g., `5_cats`), which will cause all images inside that subfolder to be repeated that number of times in the final output list.

## Outputs

| Output Name | Data Type | Description                                                 |
| ----------- | --------- | ----------------------------------------------------------- |
| `images`    | IMAGE     | A list of loaded image tensors.                             |
| `texts`     | STRING    | A list of text captions corresponding to each loaded image. |

***

**Source fingerprint (SHA-256):** `c505d580b7bfb84ee71aca8fa98c847eeba531da9e578ddfe17818a2fd2ae5e8`


# LoadImageTextSetFromFolderNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadImageTextSetFromFolderNode

Complete documentation for the LoadImageTextSetFromFolderNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadImageTextSetFromFolderNode/en.md)

Loads a batch of images and their corresponding text captions from a specified directory for training purposes. The node automatically searches for image files and their associated caption text files, processes the images according to specified resize settings, and encodes the captions using the provided CLIP model.

## Inputs

| Parameter       | Data Type | Required | Range                                        | Description                                                                         |
| --------------- | --------- | -------- | -------------------------------------------- | ----------------------------------------------------------------------------------- |
| `folder`        | STRING    | Yes      | -                                            | The folder to load images from.                                                     |
| `clip`          | CLIP      | Yes      | -                                            | The CLIP model used for encoding the text.                                          |
| `resize_method` | COMBO     | No       | "None"<br />"Stretch"<br />"Crop"<br />"Pad" | The method used to resize images (default: "None").                                 |
| `width`         | INT       | No       | -1 to 10000                                  | The width to resize the images to. -1 means use the original width (default: -1).   |
| `height`        | INT       | No       | -1 to 10000                                  | The height to resize the images to. -1 means use the original height (default: -1). |

**Note:** The CLIP input must be valid and cannot be None. If the CLIP model comes from a checkpoint loader node, ensure the checkpoint contains a valid CLIP or text encoder model.

**Note on folder structure:** The node supports the kohya-ss/sd-scripts folder structure. If a subfolder's name starts with a number followed by an underscore (e.g., `5_myclass`), that number is used as a repeat count, and the images inside that subfolder will be loaded that many times.

## Outputs

| Output Name    | Data Type    | Description                                           |
| -------------- | ------------ | ----------------------------------------------------- |
| `IMAGE`        | IMAGE        | The batch of loaded and processed images.             |
| `CONDITIONING` | CONDITIONING | The encoded conditioning data from the text captions. |

***

**Source fingerprint (SHA-256):** `ffd6399783fc281a58bae811112d9ecacb51ab8ea3b512befa9b9fab2c6860de`


# LoraLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraLoader

Complete documentation for the LoraLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node automatically detects models located in the LoRA folder (including subfolders) with the corresponding model path being `ComfyUI\models\loras`. For more information, please refer to Installing LoRA Models

The LoRA Loader node is primarily used to load LoRA models. You can think of LoRA models as filters that can give your images specific styles, content, and details:

* Apply specific artistic styles (like ink painting)
* Add characteristics of certain characters (like game characters)
* Add specific details to the image
  All of these can be achieved through LoRA.

If you need to load multiple LoRA models, you can directly chain multiple nodes together, as shown below:

## Inputs

| Parameter        | Data Type      | Description                                                                                                                                                |
| ---------------- | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`          | MODEL          | Typically used to connect to the base model                                                                                                                |
| `clip`           | CLIP           | Typically used to connect to the CLIP model                                                                                                                |
| `lora_name`      | COMBO\[STRING] | Select the name of the LoRA model to use                                                                                                                   |
| `strength_model` | FLOAT          | Value range from -100.0 to 100.0, typically used between 0\~1 for daily image generation. Higher values result in more pronounced model adjustment effects |
| `strength_clip`  | FLOAT          | Value range from -100.0 to 100.0, typically used between 0\~1 for daily image generation. Higher values result in more pronounced model adjustment effects |

## Outputs

| Parameter | Data Type | Description                                     |
| --------- | --------- | ----------------------------------------------- |
| `model`   | MODEL     | The model with LoRA adjustments applied         |
| `clip`    | CLIP      | The CLIP instance with LoRA adjustments applied |


# LoraLoaderModelOnly - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraLoaderModelOnly

Complete documentation for the LoraLoaderModelOnly node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node will detect models located in the `ComfyUI/models/loras` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

This node specializes in loading a LoRA model without requiring a CLIP model, focusing on enhancing or modifying a given model based on LoRA parameters. It allows for the dynamic adjustment of the model's strength through LoRA parameters, facilitating fine-tuned control over the model's behavior.

## Inputs

| Field            | Comfy dtype     | Description                                                                                             |
| ---------------- | --------------- | ------------------------------------------------------------------------------------------------------- |
| `model`          | `MODEL`         | The base model for modifications, to which LoRA adjustments will be applied.                            |
| `lora_name`      | `COMBO[STRING]` | The name of the LoRA file to be loaded, specifying the adjustments to apply to the model.               |
| `strength_model` | `FLOAT`         | Determines the intensity of the LoRA adjustments, with higher values indicating stronger modifications. |

## Outputs

| Field   | Data Type | Description                                                                                             |
| ------- | --------- | ------------------------------------------------------------------------------------------------------- |
| `model` | `MODEL`   | The modified model with LoRA adjustments applied, reflecting changes in model behavior or capabilities. |


# LotusConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LotusConditioning

Complete documentation for the LotusConditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LotusConditioning/en.md)

The LotusConditioning node provides pre-computed conditioning embeddings for the Lotus model. It uses a frozen encoder with null conditioning and returns hardcoded prompt embeddings to achieve parity with the reference implementation without requiring inference or loading large tensor files. This node outputs a fixed conditioning tensor that can be used directly in the generation pipeline.

## Inputs

| Parameter   | Data Type | Required | Range | Description                                     |
| ----------- | --------- | -------- | ----- | ----------------------------------------------- |
| *No inputs* | -         | -        | -     | This node does not accept any input parameters. |

## Outputs

| Output Name    | Data Type    | Description                                                                                                               |
| -------------- | ------------ | ------------------------------------------------------------------------------------------------------------------------- |
| `conditioning` | CONDITIONING | The pre-computed conditioning embeddings for the Lotus model, containing fixed prompt embeddings and an empty dictionary. |

***

**Source fingerprint (SHA-256):** `950e09b7fda911c7596445cf1a90ec10f451b396534f149b74e86b2da7deacc0`


# NormalizeVideoLatentStart - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/NormalizeVideoLatentStart

Complete documentation for the NormalizeVideoLatentStart node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/NormalizeVideoLatentStart/en.md)

This node adjusts the first few frames of a video latent to make them look more like the frames that come after. It calculates the average and variation from a set of reference frames later in the video and applies those same characteristics to the starting frames. This helps create a smoother and more consistent visual transition at the beginning of a video.

## Inputs

| Parameter               | Data Type | Required | Range                       | Description                                                                      |
| ----------------------- | --------- | -------- | --------------------------- | -------------------------------------------------------------------------------- |
| `latent`                | LATENT    | Yes      | -                           | The video latent representation to process.                                      |
| `start_frame_count`     | INT       | Yes      | 1 to 16384 (max resolution) | Number of latent frames to normalize, counted from the start (default: 4).       |
| `reference_frame_count` | INT       | Yes      | 1 to 16384 (max resolution) | Number of latent frames after the start frames to use as reference (default: 5). |

**Note:** The `reference_frame_count` is automatically limited to the number of frames available after the starting frames. If the video latent is only 1 frame long, no normalization is performed and the original latent is returned unchanged.

## Outputs

| Output Name | Data Type | Description                                                     |
| ----------- | --------- | --------------------------------------------------------------- |
| `latent`    | LATENT    | The processed video latent with the starting frames normalized. |

***

**Source fingerprint (SHA-256):** `ee1f13ddb6ff0d52d5cdaa8d2af9cd4123bc99f38cf4a449b329a0b6663a70ef`


# Painter - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Painter

Complete documentation for the Painter node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Painter/en.md)

The Painter node provides an interactive canvas for creating or editing images and masks directly within ComfyUI. It allows you to start with a blank canvas or an existing image, paint on it using a brush tool, and outputs both the resulting image and a corresponding alpha mask. The mask defines the painted areas, which are then composited over the base image or background color.

## Inputs

| Parameter  | Data Type | Required | Range      | Description                                                                                                                                                                                 |
| ---------- | --------- | -------- | ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`    | IMAGE     | No       | -          | Optional base image to paint over. If not provided, a blank canvas is created using the specified background color, width, and height.                                                      |
| `mask`     | STRING    | Yes      | -          | The painting data, typically generated by the node's built-in interactive widget. This parameter is managed by the UI's painter tool and is not meant to be connected to a standard socket. |
| `width`    | INT       | Yes      | 64 to 4096 | The width of the canvas in pixels, used when no base `image` is provided. The value must be a multiple of 64. Default is 512.                                                               |
| `height`   | INT       | Yes      | 64 to 4096 | The height of the canvas in pixels, used when no base `image` is provided. The value must be a multiple of 64. Default is 512.                                                              |
| `bg_color` | COLOR     | Yes      | -          | The background color for the canvas, specified as a hex code (e.g., #000000). This is only used when no base `image` is provided. Default is black (#000000).                               |

**Note:** The `mask` input is designed to work with the node's specialized UI widget. When you paint on the canvas, the widget automatically populates this value. The `width` and `height` inputs are hidden in the standard UI but define the canvas dimensions when creating a new image. If a base `image` is provided, its dimensions override the `width` and `height` settings.

## Outputs

| Output Name | Data Type | Description                                                                                                                                                       |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `IMAGE`     | IMAGE     | The final composited image. This is the result of blending the painted areas (from the `mask`) over the provided base `image` or the colored background.          |
| `MASK`      | MASK      | The alpha channel (transparency) mask extracted from the painting. White areas represent the painted regions, and black areas represent the untouched background. |

***

**Source fingerprint (SHA-256):** `217a6d8abbad02cb43cab18d0a592bdd5bfbfe321a742d0c14e8f4e1fa5e2630`


# PreviewImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PreviewImage

Complete documentation for the PreviewImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The PreviewImage node is designed for creating temporary preview images. It automatically generates a unique temporary file name for each image, compresses the image to a specified level, and saves it to a temporary directory. This functionality is particularly useful for generating previews of images during processing without affecting the original files.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                                                  |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `images`  | `IMAGE`   | The 'images' input specifies the images to be processed and saved as temporary preview images. This is the primary input for the node, determining which images will undergo the preview generation process. |

## Outputs

The node doesn't have output types.


# ResizeImageMaskNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResizeImageMaskNode

Complete documentation for the ResizeImageMaskNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResizeImageMaskNode/en.md)

The Resize Image/Mask node provides multiple methods to change the dimensions of an input image or mask. It can scale by a multiplier, set specific dimensions, match the size of another input, or adjust based on pixel count, using various interpolation methods for quality.

## Inputs

| Parameter      | Data Type     | Required | Range                                                                                                                                                                              | Description                                                                                                                                                             |
| -------------- | ------------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `input`        | IMAGE or MASK | Yes      | N/A                                                                                                                                                                                | The image or mask to be resized.                                                                                                                                        |
| `resize_type`  | COMBO         | Yes      | `SCALE_BY`<br />`SCALE_DIMENSIONS`<br />`SCALE_LONGER_DIMENSION`<br />`SCALE_SHORTER_DIMENSION`<br />`SCALE_WIDTH`<br />`SCALE_HEIGHT`<br />`SCALE_TOTAL_PIXELS`<br />`MATCH_SIZE` | The method used to determine the new size. The required parameters change based on the selected type.                                                                   |
| `multiplier`   | FLOAT         | No       | 0.01 to 8.0                                                                                                                                                                        | The scaling factor. Required when `resize_type` is `SCALE_BY` (default: 1.00).                                                                                          |
| `width`        | INT           | No       | 0 to 8192                                                                                                                                                                          | The target width in pixels. Required when `resize_type` is `SCALE_DIMENSIONS` or `SCALE_WIDTH` (default: 512).                                                          |
| `height`       | INT           | No       | 0 to 8192                                                                                                                                                                          | The target height in pixels. Required when `resize_type` is `SCALE_DIMENSIONS` or `SCALE_HEIGHT` (default: 512).                                                        |
| `crop`         | COMBO         | No       | `"disabled"`<br />`"center"`                                                                                                                                                       | The cropping method to apply when dimensions don't match the aspect ratio. Only available when `resize_type` is `SCALE_DIMENSIONS` or `MATCH_SIZE` (default: "center"). |
| `longer_size`  | INT           | No       | 0 to 8192                                                                                                                                                                          | The target size for the longer side of the image. Required when `resize_type` is `SCALE_LONGER_DIMENSION` (default: 512).                                               |
| `shorter_size` | INT           | No       | 0 to 8192                                                                                                                                                                          | The target size for the shorter side of the image. Required when `resize_type` is `SCALE_SHORTER_DIMENSION` (default: 512).                                             |
| `megapixels`   | FLOAT         | No       | 0.01 to 16.0                                                                                                                                                                       | The target total number of megapixels. Required when `resize_type` is `SCALE_TOTAL_PIXELS` (default: 1.0).                                                              |
| `match`        | IMAGE or MASK | No       | N/A                                                                                                                                                                                | An image or mask whose dimensions the input will be resized to match. Required when `resize_type` is `MATCH_SIZE`.                                                      |
| `scale_method` | COMBO         | Yes      | `"nearest-exact"`<br />`"bilinear"`<br />`"area"`<br />`"bicubic"`<br />`"lanczos"`                                                                                                | The interpolation algorithm used for scaling (default: "area").                                                                                                         |

**Note:** The `crop` parameter is only available and relevant when the `resize_type` is set to `SCALE_DIMENSIONS` or `MATCH_SIZE`. When using `SCALE_WIDTH` or `SCALE_HEIGHT`, the other dimension is automatically scaled to maintain the original aspect ratio.

## Outputs

| Output Name | Data Type     | Description                                                     |
| ----------- | ------------- | --------------------------------------------------------------- |
| `resized`   | IMAGE or MASK | The resized image or mask, matching the data type of the input. |

***

**Source fingerprint (SHA-256):** `9ac0b153608ac971bb11d9d12ebd1f0f4d6e926604e8727a1bc3a311d95fbc03`


# SD_4XUpscale_Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SD_4XUpscale_Conditioning

Complete documentation for the SD_4XUpscale_Conditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SD_4XUpscale_Conditioning/en.md)

The SD\_4XUpscale\_Conditioning node prepares conditioning data for upscaling images using diffusion models. It takes input images and conditioning data, then applies scaling and noise augmentation to create modified conditioning that guides the upscaling process. The node outputs both positive and negative conditioning along with latent representations for the upscaled dimensions.

## Inputs

| Parameter            | Data Type    | Required | Range      | Description                                                                      |
| -------------------- | ------------ | -------- | ---------- | -------------------------------------------------------------------------------- |
| `images`             | IMAGE        | Yes      | -          | Input images to be upscaled                                                      |
| `positive`           | CONDITIONING | Yes      | -          | Positive conditioning data that guides the generation toward desired content     |
| `negative`           | CONDITIONING | Yes      | -          | Negative conditioning data that steers the generation away from unwanted content |
| `scale_ratio`        | FLOAT        | No       | 0.0 - 10.0 | Scaling factor applied to the input images (default: 4.0)                        |
| `noise_augmentation` | FLOAT        | No       | 0.0 - 1.0  | Amount of noise to add during the upscaling process (default: 0.0)               |

## Outputs

| Output Name | Data Type    | Description                                                       |
| ----------- | ------------ | ----------------------------------------------------------------- |
| `positive`  | CONDITIONING | Modified positive conditioning with upscaling information applied |
| `negative`  | CONDITIONING | Modified negative conditioning with upscaling information applied |
| `latent`    | LATENT       | Empty latent representation matching the upscaled dimensions      |

***

**Source fingerprint (SHA-256):** `06e8e451cc939019e1d7213ab24ff1e4a9937540733194d66edbc5d32d352e16`


# SV3D_Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SV3D_Conditioning

Complete documentation for the SV3D_Conditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SV3D_Conditioning/en.md)

The SV3D\_Conditioning node prepares conditioning data for 3D video generation using the SV3D model. It takes an initial image and processes it through CLIP vision and VAE encoders to create positive and negative conditioning, along with a latent representation. The node generates camera elevation and azimuth sequences for multi-frame video generation based on the specified number of video frames.

## Inputs

| Parameter      | Data Type    | Required | Range                 | Description                                                                             |
| -------------- | ------------ | -------- | --------------------- | --------------------------------------------------------------------------------------- |
| `clip_vision`  | CLIP\_VISION | Yes      | -                     | The CLIP vision model used for encoding the input image                                 |
| `init_image`   | IMAGE        | Yes      | -                     | The initial image that serves as the starting point for 3D video generation             |
| `vae`          | VAE          | Yes      | -                     | The VAE model used for encoding the image into latent space                             |
| `width`        | INT          | Yes      | 16 to MAX\_RESOLUTION | The output width for the generated video frames (default: 576, must be divisible by 8)  |
| `height`       | INT          | Yes      | 16 to MAX\_RESOLUTION | The output height for the generated video frames (default: 576, must be divisible by 8) |
| `video_frames` | INT          | Yes      | 1 to 4096             | The number of frames to generate for the video sequence (default: 21)                   |
| `elevation`    | FLOAT        | Yes      | -90.0 to 90.0         | The camera elevation angle in degrees for the 3D view (default: 0.0)                    |

## Outputs

| Output Name | Data Type    | Description                                                                                     |
| ----------- | ------------ | ----------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | The positive conditioning data containing image embeddings and camera parameters for generation |
| `negative`  | CONDITIONING | The negative conditioning data with zeroed embeddings for contrastive generation                |
| `latent`    | LATENT       | An empty latent tensor with dimensions matching the specified video frames and resolution       |

***

**Source fingerprint (SHA-256):** `a1d4b7f0106bcdc7c9640f6e12986d9b452f785882caaa2072ba1a5da0913f69`


# SaveAnimatedPNG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveAnimatedPNG

Complete documentation for the SaveAnimatedPNG node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The SaveAnimatedPNG node is designed for creating and saving animated PNG images from a sequence of frames. It handles the assembly of individual image frames into a cohesive animation, allowing for customization of frame duration, looping, and metadata inclusion.

## Inputs

| Field             | Data Type | Description                                                                                                                |
| ----------------- | --------- | -------------------------------------------------------------------------------------------------------------------------- |
| `images`          | `IMAGE`   | A list of images to be processed and saved as an animated PNG. Each image in the list represents a frame in the animation. |
| `filename_prefix` | `STRING`  | Specifies the base name for the output file, which will be used as a prefix for the generated animated PNG files.          |
| `fps`             | `FLOAT`   | The frames per second rate for the animation, controlling how quickly the frames are displayed.                            |
| `compress_level`  | `INT`     | The level of compression applied to the animated PNG files, affecting file size and image clarity.                         |

## Outputs

| Field | Data Type | Description                                                                                                                               |
| ----- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------- |
| `ui`  | N/A       | Provides a UI component displaying the generated animated PNG images and indicating whether the animation is single-frame or multi-frame. |


# SaveAnimatedWEBP - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveAnimatedWEBP

Complete documentation for the SaveAnimatedWEBP node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed for saving a sequence of images as an animated WEBP file. It handles the aggregation of individual frames into a cohesive animation, applying specified metadata, and optimizing the output based on quality and compression settings.

## Inputs

| Field             | Data Type      | Description                                                                                                                                                                             |
| ----------------- | -------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `images`          | `IMAGE`        | A list of images to be saved as frames in the animated WEBP. This parameter is essential for defining the visual content of the animation.                                              |
| `filename_prefix` | `STRING`       | Specifies the base name for the output file, which will be appended with a counter and the '.webp' extension. This parameter is crucial for identifying and organizing the saved files. |
| `fps`             | `FLOAT`        | The frames per second rate for the animation, influencing the playback speed.                                                                                                           |
| `lossless`        | `BOOLEAN`      | A boolean indicating whether to use lossless compression, affecting the file size and quality of the animation.                                                                         |
| `quality`         | `INT`          | A value between 0 and 100 that sets the compression quality level, with higher values resulting in better image quality but larger file sizes.                                          |
| `method`          | COMBO\[STRING] | Specifies the compression method to use, which can impact the encoding speed and file size.                                                                                             |

## Outputs

| Field | Data Type | Description                                                                                                                                  |
| ----- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------- |
| `ui`  | N/A       | Provides a UI component displaying the saved animated WEBP images along with their metadata, and indicates whether the animation is enabled. |


# SaveImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveImage

Complete documentation for the SaveImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveImage/en.md)

The SaveImage node saves the images it receives to your `ComfyUI/output` directory. It saves each image as a PNG file and can embed workflow metadata, such as the prompt, into the saved file for future reference.

## Inputs

| Parameter         | Data Type | Required | Range | Description                                                                                                                                                                             |
| ----------------- | --------- | -------- | ----- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `images`          | IMAGE     | Yes      | -     | The images to save.                                                                                                                                                                     |
| `filename_prefix` | STRING    | Yes      | -     | The prefix for the file to save. This may include formatting information such as `%date:yyyy-MM-dd%` or `%Empty Latent Image.width%` to include values from nodes (default: "ComfyUI"). |

## Outputs

| Output Name | Data Type  | Description                                                                                                                                                     |
| ----------- | ---------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `ui`        | UI\_RESULT | This node outputs a UI result containing a list of the saved images with their filenames and subfolders. It does not output data for connecting to other nodes. |

***

**Source fingerprint (SHA-256):** `fa88c26e5e03f788dcc545434a54124c5e9d03b559da67f0857b52faec0e97e7`


# SaveImageAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveImageAdvanced

Complete documentation for the SaveImageAdvanced node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveImageAdvanced/en.md)

# SaveImageAdvanced

The **SaveImageAdvanced** node saves images to your ComfyUI output directory with advanced control over file format, bit depth, and color space. It supports saving as PNG or EXR files and can embed workflow metadata into the saved files.

## Inputs

| Parameter           | Data Type | Required          | Range                                                                 | Description                                                                                                                                                    |
| ------------------- | --------- | ----------------- | --------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `images`            | IMAGE     | Yes               | -                                                                     | The images to save.                                                                                                                                            |
| `filename_prefix`   | STRING    | Yes               | -                                                                     | The prefix for the file to save. May include formatting tokens such as `%date:yyyy-MM-dd%` or `%Empty Latent Image.width%`. (default: "ComfyUI")               |
| `format`            | COMBO     | Yes               | `"png"`<br />`"exr"`                                                  | The file format in which to save the image. Selecting a format reveals additional options for that format.                                                     |
| `bit_depth`         | COMBO     | Yes (conditional) | For PNG: `"8-bit"`<br />`"16-bit"`<br />For EXR: `"32-bit float"`     | The bit depth for the selected format. This parameter appears when a format is chosen. (default: "8-bit" for PNG, "32-bit float" for EXR)                      |
| `input_color_space` | COMBO     | Yes (conditional) | For PNG: `"sRGB"`<br />For EXR: `"sRGB"`<br />`"HDR"`<br />`"linear"` | Colorspace of the input tensor. For PNG, only sRGB is available. For EXR, the image is always written as scene-linear in the matching gamut. (default: "sRGB") |

**Notes on Parameter Dependencies:**

* The `bit_depth` and `input_color_space` parameters are only available when a specific `format` is selected.
* For PNG format, only "8-bit" and "16-bit" bit depths are available, and only "sRGB" color space.
* For EXR format, only "32-bit float" bit depth is available, with "sRGB", "HDR", or "linear" color spaces.
* The `input_color_space` parameter for EXR determines how the input tensor is interpreted:
  * `"sRGB"` — input is sRGB-encoded Rec.709; the inverse sRGB EOTF is applied.
  * `"HDR"` — input is HLG-encoded Rec.2020 (BT.2100); the inverse HLG OETF is applied to get scene-linear light.
  * `"linear"` — input is already scene-linear (Rec.709 primaries); written through unchanged. Use this for renderer/compositor output.

## Outputs

| Output Name | Data Type | Description                                                                                                                               |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------- |
| `images`    | IMAGE     | A list of saved image results, each containing the filename, subfolder, and type ("output"). This output is used for UI display purposes. |

***

**Source fingerprint (SHA-256):** `61e52bab8c28437cf648e4790823c15dbe0f758478635b0bd8b5cce785421fe5`


# SaveImageDataSetToFolder - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveImageDataSetToFolder

Complete documentation for the SaveImageDataSetToFolder node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveImageDataSetToFolder/en.md)

This node saves a list of images to a specified folder within ComfyUI's output directory. It takes multiple images as input and writes them to disk with a customizable filename prefix.

## Inputs

| Parameter         | Data Type | Required | Range | Description                                                                                     |
| ----------------- | --------- | -------- | ----- | ----------------------------------------------------------------------------------------------- |
| `images`          | IMAGE     | Yes      | N/A   | List of images to save.                                                                         |
| `folder_name`     | STRING    | No       | N/A   | Name of the folder to save images to (inside output directory). The default value is "dataset". |
| `filename_prefix` | STRING    | No       | N/A   | Prefix for saved image filenames. The default value is "image".                                 |

**Note:** The `images` input is a list, meaning it can receive and process multiple images at once. The `folder_name` and `filename_prefix` parameters are scalar values; if a list is connected, only the first value from that list will be used.

## Outputs

This node does not have any outputs. It is an output node that performs a save operation to the filesystem.

***

**Source fingerprint (SHA-256):** `6a3f5de6e3ef12743bb46f8cbd311ecbed28ea041fe34ae123e918420a444774`


# SaveImageTextDataSetToFolder - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveImageTextDataSetToFolder

Complete documentation for the SaveImageTextDataSetToFolder node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveImageTextDataSetToFolder/en.md)

The Save Image and Text Dataset to Folder node saves a list of images and their corresponding text captions to a specified folder within ComfyUI's output directory. For each image saved as a PNG file, a matching text file with the same base name is created to store its caption. This is useful for creating organized datasets of generated images and their descriptions.

## Inputs

| Parameter         | Data Type | Required | Range | Description                                                                          |
| ----------------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------ |
| `images`          | IMAGE     | Yes      | -     | List of images to save.                                                              |
| `texts`           | STRING    | No       | -     | List of text captions to save. This input is optional.                               |
| `folder_name`     | STRING    | No       | -     | Name of the folder to save images to (inside output directory). (default: "dataset") |
| `filename_prefix` | STRING    | No       | -     | Prefix for saved image filenames. (default: "image")                                 |

**Note:** The `images` input is a list. The `texts` input is optional; if provided, it should be a list of text captions. The node expects the number of text captions to match the number of images provided. Each caption will be saved in a `.txt` file corresponding to its paired image.

## Outputs

| Output Name | Data Type | Description                                                                     |
| ----------- | --------- | ------------------------------------------------------------------------------- |
| -           | -         | This node does not have any outputs. It saves files directly to the filesystem. |

***

**Source fingerprint (SHA-256):** `e772e0f9b56af1dfd65a384e22eda2065215c8a9ca0360c93885e39721b0c767`


# SaveSVGNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveSVGNode

Complete documentation for the SaveSVGNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveSVGNode/en.md)

Save SVG files on disk. This node takes SVG data as input and saves it to your output directory with optional metadata embedding. The node automatically handles file naming with counter suffixes and can embed workflow prompt information directly into the SVG file.

## Inputs

| Parameter         | Data Type | Required | Range | Description                                                                                                                                                                             |
| ----------------- | --------- | -------- | ----- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `svg`             | SVG       | Yes      | -     | The SVG data to be saved to disk                                                                                                                                                        |
| `filename_prefix` | STRING    | Yes      | -     | The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes. (default: "svg/ComfyUI") |

## Outputs

| Output Name | Data Type | Description                                                                                           |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------- |
| `ui`        | DICT      | Returns file information including filename, subfolder, and type for display in the ComfyUI interface |

**Note:** This node automatically embeds workflow metadata (prompt and extra PNG information) into the SVG file when available. The metadata is inserted as a CDATA section within the SVG's metadata element.

***

**Source fingerprint (SHA-256):** `f8ac0c8aef01229f605c9b5b18e3f36996ef8bf6333fe31c9ebf32ae7ed76907`


# SetUnionControlNetType - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetUnionControlNetType

Complete documentation for the SetUnionControlNetType node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SetUnionControlNetType/en.md)

The SetUnionControlNetType node allows you to specify the type of control network to use for conditioning. It takes an existing control network and sets its control type based on your selection, creating a modified copy of the control network with the specified type configuration.

## Inputs

| Parameter     | Data Type    | Required | Range                                                     | Description                                                                                                                                                       |
| ------------- | ------------ | -------- | --------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `control_net` | CONTROL\_NET | Yes      | -                                                         | The control network to modify with a new type setting                                                                                                             |
| `type`        | STRING       | Yes      | `"auto"`<br />All available UNION\_CONTROLNET\_TYPES keys | The control network type to apply. Use "auto" for automatic type detection or select a specific control network type from the available options (default: "auto") |

## Outputs

| Output Name   | Data Type    | Description                                                          |
| ------------- | ------------ | -------------------------------------------------------------------- |
| `control_net` | CONTROL\_NET | The modified control network with the specified type setting applied |

***

**Source fingerprint (SHA-256):** `a2f8695c64490f0700a035c8c2e724b9c29796fb220ed7fdd13651545a3158e6`


# StableCascade_StageB_Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableCascade_StageB_Conditioning

Complete documentation for the StableCascade_StageB_Conditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableCascade_StageB_Conditioning/en.md)

The StableCascade\_StageB\_Conditioning node prepares conditioning data for Stable Cascade Stage B generation by combining existing conditioning information with prior latent representations from Stage C. It modifies the conditioning data to include the latent samples from Stage C, enabling the generation process to leverage the prior information for more coherent outputs.

## Inputs

| Parameter      | Data Type    | Required | Range | Description                                                                      |
| -------------- | ------------ | -------- | ----- | -------------------------------------------------------------------------------- |
| `conditioning` | CONDITIONING | Yes      | -     | The conditioning data to be modified with Stage C prior information              |
| `stage_c`      | LATENT       | Yes      | -     | The latent representation from Stage C containing prior samples for conditioning |

## Outputs

| Output Name    | Data Type    | Description                                                              |
| -------------- | ------------ | ------------------------------------------------------------------------ |
| `CONDITIONING` | CONDITIONING | The modified conditioning data with Stage C prior information integrated |

***

**Source fingerprint (SHA-256):** `1679f61320f7f7b929f5166d6f038426256a9e12cc7f72639452fd2734cf712c`


# StableZero123_Conditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableZero123_Conditioning

Complete documentation for the StableZero123_Conditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableZero123_Conditioning/en.md)

The StableZero123\_Conditioning node processes an input image and camera angles to generate conditioning data and latent representations for 3D model generation. It uses a CLIP vision model to encode the image features, combines them with camera embedding information based on elevation and azimuth angles, and produces positive and negative conditioning along with a latent representation for downstream 3D generation tasks.

## Inputs

| Parameter     | Data Type    | Required | Range                 | Description                                                                        |
| ------------- | ------------ | -------- | --------------------- | ---------------------------------------------------------------------------------- |
| `clip_vision` | CLIP\_VISION | Yes      | -                     | The CLIP vision model used to encode image features                                |
| `init_image`  | IMAGE        | Yes      | -                     | The input image to be processed and encoded                                        |
| `vae`         | VAE          | Yes      | -                     | The VAE model used for encoding pixels to latent space                             |
| `width`       | INT          | Yes      | 16 to MAX\_RESOLUTION | Output width for the latent representation (default: 256, must be divisible by 8)  |
| `height`      | INT          | Yes      | 16 to MAX\_RESOLUTION | Output height for the latent representation (default: 256, must be divisible by 8) |
| `batch_size`  | INT          | Yes      | 1 to 4096             | Number of samples to generate in the batch (default: 1)                            |
| `elevation`   | FLOAT        | Yes      | -180.0 to 180.0       | Camera elevation angle in degrees (default: 0.0)                                   |
| `azimuth`     | FLOAT        | Yes      | -180.0 to 180.0       | Camera azimuth angle in degrees (default: 0.0)                                     |

**Note:** The `width` and `height` parameters must be divisible by 8 as the node automatically divides them by 8 to create the latent representation dimensions.

## Outputs

| Output Name | Data Type    | Description                                                                  |
| ----------- | ------------ | ---------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Positive conditioning data combining image features and camera embeddings    |
| `negative`  | CONDITIONING | Negative conditioning data with zero-initialized features                    |
| `latent`    | LATENT       | Latent representation with dimensions \[batch\_size, 4, height//8, width//8] |

***

**Source fingerprint (SHA-256):** `197b4efaf13837500f2c3aaf589facc384b3f0bbd026aaa75a7fee509bd0bc51`


# StableZero123_Conditioning_Batched - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableZero123_Conditioning_Batched

Complete documentation for the StableZero123_Conditioning_Batched node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableZero123_Conditioning_Batched/en.md)

The StableZero123\_Conditioning\_Batched node processes an input image and generates conditioning data for 3D model generation. It encodes the image using CLIP vision and VAE models, then creates camera embeddings based on elevation and azimuth angles to produce positive and negative conditioning along with latent representations for batch processing.

## Inputs

| Parameter                   | Data Type    | Required | Range                 | Description                                                                      |
| --------------------------- | ------------ | -------- | --------------------- | -------------------------------------------------------------------------------- |
| `clip_vision`               | CLIP\_VISION | Yes      | -                     | The CLIP vision model used for encoding the input image                          |
| `init_image`                | IMAGE        | Yes      | -                     | The initial input image to be processed and encoded                              |
| `vae`                       | VAE          | Yes      | -                     | The VAE model used for encoding image pixels into latent space                   |
| `width`                     | INT          | No       | 16 to MAX\_RESOLUTION | The output width for the processed image (default: 256, must be divisible by 8)  |
| `height`                    | INT          | No       | 16 to MAX\_RESOLUTION | The output height for the processed image (default: 256, must be divisible by 8) |
| `batch_size`                | INT          | No       | 1 to 4096             | The number of conditioning samples to generate in the batch (default: 1)         |
| `elevation`                 | FLOAT        | No       | -180.0 to 180.0       | The initial camera elevation angle in degrees (default: 0.0)                     |
| `azimuth`                   | FLOAT        | No       | -180.0 to 180.0       | The initial camera azimuth angle in degrees (default: 0.0)                       |
| `elevation_batch_increment` | FLOAT        | No       | -180.0 to 180.0       | The amount to increment elevation for each batch item (default: 0.0)             |
| `azimuth_batch_increment`   | FLOAT        | No       | -180.0 to 180.0       | The amount to increment azimuth for each batch item (default: 0.0)               |

**Note:** The `width` and `height` parameters must be divisible by 8 as the node internally divides these dimensions by 8 for latent space generation.

## Outputs

| Output Name | Data Type    | Description                                                                      |
| ----------- | ------------ | -------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | The positive conditioning data containing image embeddings and camera parameters |
| `negative`  | CONDITIONING | The negative conditioning data with zero-initialized embeddings                  |
| `latent`    | LATENT       | The latent representation of the processed image with batch indexing information |

***

**Source fingerprint (SHA-256):** `fb181f43076087cb040db9404a42e27a39ac7eac7af3da283b3e040342374c74`


# StyleModelApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StyleModelApply

Complete documentation for the StyleModelApply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node applies a style model to a given conditioning, enhancing or altering its style based on the output of a CLIP vision model. It integrates the style model's conditioning into the existing conditioning, allowing for a seamless blend of styles in the generation process.

## Inputs

### Required

| Parameter            | Comfy dtype          | Description                                                                                                                                                                   |
| -------------------- | -------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `conditioning`       | `CONDITIONING`       | The original conditioning data to which the style model's conditioning will be applied. It's crucial for defining the base context or style that will be enhanced or altered. |
| `style_model`        | `STYLE_MODEL`        | The style model used to generate new conditioning based on the CLIP vision model's output. It plays a key role in defining the new style to be applied.                       |
| `clip_vision_output` | `CLIP_VISION_OUTPUT` | The output from a CLIP vision model, which is used by the style model to generate new conditioning. It provides the visual context necessary for style application.           |

## Outputs

| Parameter      | Comfy dtype    | Description                                                                                                                                                            |
| -------------- | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `conditioning` | `CONDITIONING` | The enhanced or altered conditioning, incorporating the style model's output. It represents the final, styled conditioning ready for further processing or generation. |


# VOIDInpaintConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VOIDInpaintConditioning

Complete documentation for the VOIDInpaintConditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VOIDInpaintConditioning/en.md)

The VOIDInpaintConditioning node prepares the conditioning data needed for inpainting with CogVideoX models. It takes a source video and a preprocessed quadmask, encodes them through the VAE, and combines them into a 32-channel conditioning signal that the model uses to fill in the masked areas.

## Inputs

| Parameter    | Data Type    | Required | Range                           | Description                                                                                                                                                                             |
| ------------ | ------------ | -------- | ------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`   | CONDITIONING | Yes      | -                               | The positive conditioning to be augmented with the inpainting latent information                                                                                                        |
| `negative`   | CONDITIONING | Yes      | -                               | The negative conditioning to be augmented with the inpainting latent information                                                                                                        |
| `vae`        | VAE          | Yes      | -                               | The VAE model used to encode the mask and masked video into latent space                                                                                                                |
| `video`      | IMAGE        | Yes      | -                               | Source video frames \[T, H, W, 3]                                                                                                                                                       |
| `quadmask`   | MASK         | Yes      | -                               | Preprocessed quadmask from VOIDQuadmaskPreprocess \[T, H, W]                                                                                                                            |
| `width`      | INT          | Yes      | 16 to MAX\_RESOLUTION (step: 8) | The width to resize the video and mask to (default: 672)                                                                                                                                |
| `height`     | INT          | Yes      | 16 to MAX\_RESOLUTION (step: 8) | The height to resize the video and mask to (default: 384)                                                                                                                               |
| `length`     | INT          | Yes      | 1 to MAX\_RESOLUTION (step: 1)  | Number of pixel frames to process. For CogVideoX-Fun-V1.5 (patch\_size\_t=2), latent\_t must be even — lengths that produce odd latent\_t are rounded down (e.g. 49 → 45) (default: 45) |
| `batch_size` | INT          | Yes      | 1 to 64                         | The batch size for the output noise latent (default: 1)                                                                                                                                 |

## Outputs

| Output Name | Data Type    | Description                                                                                      |
| ----------- | ------------ | ------------------------------------------------------------------------------------------------ |
| `positive`  | CONDITIONING | The positive conditioning with the inpainting latent information added                           |
| `negative`  | CONDITIONING | The negative conditioning with the inpainting latent information added                           |
| `latent`    | LATENT       | A zero-filled noise latent tensor with shape \[batch\_size, 16, latent\_t, latent\_h, latent\_w] |

***

**Source fingerprint (SHA-256):** `47c40f8bb7527bc28178f3ad78e7bfb579e07d42efd0398d5760335c6b5b3c44`


# Wan22FunControlToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan22FunControlToVideo

Complete documentation for the Wan22FunControlToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan22FunControlToVideo/en.md)

The Wan22FunControlToVideo node prepares conditioning and latent representations for video generation using the Wan video model architecture. It processes positive and negative conditioning inputs along with optional reference images and control videos to create the necessary latent space representations for video synthesis. The node handles spatial scaling and temporal dimensions to generate appropriate conditioning data for video models.

## Inputs

| Parameter       | Data Type    | Required | Range                 | Description                                                   |
| --------------- | ------------ | -------- | --------------------- | ------------------------------------------------------------- |
| `positive`      | CONDITIONING | Yes      | -                     | Positive conditioning input for guiding the video generation  |
| `negative`      | CONDITIONING | Yes      | -                     | Negative conditioning input for guiding the video generation  |
| `vae`           | VAE          | Yes      | -                     | VAE model used for encoding images to latent space            |
| `width`         | INT          | Yes      | 16 to MAX\_RESOLUTION | Output video width in pixels (default: 832, step: 16)         |
| `height`        | INT          | Yes      | 16 to MAX\_RESOLUTION | Output video height in pixels (default: 480, step: 16)        |
| `length`        | INT          | Yes      | 1 to MAX\_RESOLUTION  | Number of frames in the video sequence (default: 81, step: 4) |
| `batch_size`    | INT          | Yes      | 1 to 4096             | Number of video sequences to generate (default: 1)            |
| `ref_image`     | IMAGE        | No       | -                     | Optional reference image for providing visual guidance        |
| `control_video` | IMAGE        | No       | -                     | Optional control video for guiding the generation process     |

**Note:** The `length` parameter is processed in chunks of 4 frames, and the node automatically handles temporal scaling for the latent space. When `ref_image` is provided, it influences the conditioning through reference latents. When `control_video` is provided, it directly affects the concat latent representation used in conditioning. The `start_image` parameter is not exposed as an input in this node's schema but is referenced in the execution logic.

## Outputs

| Output Name | Data Type    | Description                                                                                                                             |
| ----------- | ------------ | --------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Modified positive conditioning with video-specific latent data including concat latent, mask, and optional reference latents            |
| `negative`  | CONDITIONING | Modified negative conditioning with video-specific latent data including concat latent, mask, and optional reference latents            |
| `latent`    | LATENT       | Empty latent tensor with appropriate dimensions for video generation based on batch size, latent channels, and spatial/temporal scaling |

***

**Source fingerprint (SHA-256):** `3cc49969226d304e73ec924ccce902c7ae1eee819b4274ad4ffa10e67a4ea211`


# Wan22ImageToVideoLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan22ImageToVideoLatent

Complete documentation for the Wan22ImageToVideoLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan22ImageToVideoLatent/en.md)

The Wan22ImageToVideoLatent node creates video latent representations from images. It generates a blank video latent space with specified dimensions and can optionally encode a starting image sequence into the beginning frames. When a start image is provided, it encodes the image into the latent space and creates a corresponding noise mask for the inpainted regions.

## Inputs

| Parameter     | Data Type | Required | Range                 | Description                                                       |
| ------------- | --------- | -------- | --------------------- | ----------------------------------------------------------------- |
| `vae`         | VAE       | Yes      | -                     | The VAE model used for encoding images into latent space          |
| `width`       | INT       | Yes      | 32 to MAX\_RESOLUTION | The width of the output video in pixels (default: 1280, step: 32) |
| `height`      | INT       | Yes      | 32 to MAX\_RESOLUTION | The height of the output video in pixels (default: 704, step: 32) |
| `length`      | INT       | Yes      | 1 to MAX\_RESOLUTION  | The number of frames in the video sequence (default: 49, step: 4) |
| `batch_size`  | INT       | Yes      | 1 to 4096             | The number of batches to generate (default: 1)                    |
| `start_image` | IMAGE     | No       | -                     | Optional starting image sequence to encode into the video latent  |

**Note:** When `start_image` is provided, the node encodes the image sequence into the beginning frames of the latent space and generates a corresponding noise mask. The width and height parameters must be divisible by 16 for proper latent space dimensions. The `length` parameter determines the number of frames in the video latent; the latent space's temporal dimension is calculated as `((length - 1) // 4) + 1`.

## Outputs

| Output Name  | Data Type | Description                                                                  |
| ------------ | --------- | ---------------------------------------------------------------------------- |
| `samples`    | LATENT    | The generated video latent representation                                    |
| `noise_mask` | LATENT    | The noise mask indicating which regions should be denoised during generation |

***

**Source fingerprint (SHA-256):** `d12982594b1e38e7db26630fe3d5bde84bcd540e95abb6ce50cac196ea953901`


# WanAnimateToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanAnimateToVideo

Complete documentation for the WanAnimateToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanAnimateToVideo/en.md)

The WanAnimateToVideo node generates video content by combining multiple conditioning inputs including pose references, facial expressions, and background elements. It processes various video inputs to create coherent animated sequences while maintaining temporal consistency across frames. The node handles latent space operations and can extend existing videos by continuing motion patterns.

## Inputs

| Parameter                    | Data Type            | Required | Range                 | Description                                                                                                                                                                                                    |
| ---------------------------- | -------------------- | -------- | --------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`                   | CONDITIONING         | Yes      | -                     | Positive conditioning for guiding the generation towards desired content                                                                                                                                       |
| `negative`                   | CONDITIONING         | Yes      | -                     | Negative conditioning for steering the generation away from unwanted content                                                                                                                                   |
| `vae`                        | VAE                  | Yes      | -                     | VAE model used for encoding and decoding image data                                                                                                                                                            |
| `width`                      | INT                  | Yes      | 16 to MAX\_RESOLUTION | Output video width in pixels (default: 832, step: 16)                                                                                                                                                          |
| `height`                     | INT                  | Yes      | 16 to MAX\_RESOLUTION | Output video height in pixels (default: 480, step: 16)                                                                                                                                                         |
| `length`                     | INT                  | Yes      | 1 to MAX\_RESOLUTION  | Number of frames to generate (default: 77, step: 4)                                                                                                                                                            |
| `batch_size`                 | INT                  | Yes      | 1 to 4096             | Number of videos to generate simultaneously (default: 1)                                                                                                                                                       |
| `clip_vision_output`         | CLIP\_VISION\_OUTPUT | No       | -                     | Optional CLIP vision model output for additional conditioning                                                                                                                                                  |
| `reference_image`            | IMAGE                | No       | -                     | Reference image used as starting point for generation                                                                                                                                                          |
| `face_video`                 | IMAGE                | No       | -                     | Video input providing facial expression guidance                                                                                                                                                               |
| `pose_video`                 | IMAGE                | No       | -                     | Video input providing pose and motion guidance                                                                                                                                                                 |
| `continue_motion_max_frames` | INT                  | Yes      | 1 to MAX\_RESOLUTION  | Maximum number of frames to continue from previous motion (default: 5, step: 4)                                                                                                                                |
| `background_video`           | IMAGE                | No       | -                     | Background video to composite with generated content                                                                                                                                                           |
| `character_mask`             | MASK                 | No       | -                     | Mask defining character regions for selective processing                                                                                                                                                       |
| `continue_motion`            | IMAGE                | No       | -                     | Previous motion sequence to continue from for temporal consistency                                                                                                                                             |
| `video_frame_offset`         | INT                  | Yes      | 0 to MAX\_RESOLUTION  | The amount of frames to seek in all the input videos. Used for generating longer videos by chunk. Connect to the video\_frame\_offset output of the previous node for extending a video. (default: 0, step: 1) |

**Parameter Constraints:**

* When `pose_video` is provided, the output length will be adjusted to match the pose video duration if the `trim_to_pose_video` logic is active (currently set to `False` in the source code)
* `face_video` is automatically resized to 512x512 resolution and normalized to a range of -1.0 to 1.0 when processed
* `continue_motion` frames are limited by the `continue_motion_max_frames` parameter; only the last `continue_motion_max_frames` frames from the input are used
* Input videos (`face_video`, `pose_video`, `background_video`, `character_mask`) are offset by `video_frame_offset` before processing; if the offset exceeds the video length, the input is ignored
* If `character_mask` contains only one frame, it will be repeated across all frames
* When `clip_vision_output` is provided, it's applied to both positive and negative conditioning
* If `reference_image` is not provided, a black image (all zeros) is used as the default reference
* If `continue_motion` is not provided, the initial frames are filled with gray (0.5 intensity) noise

## Outputs

| Output Name          | Data Type    | Description                                                                                                                                                                                  |
| -------------------- | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`           | CONDITIONING | Modified positive conditioning with additional video context including CLIP vision output, pose video latent, face video pixels, concatenated latent image, and concatenated mask            |
| `negative`           | CONDITIONING | Modified negative conditioning with additional video context including CLIP vision output, pose video latent, face video pixels (inverted), concatenated latent image, and concatenated mask |
| `latent`             | LATENT       | Generated video content in latent space format with shape \[batch\_size, 16, latent\_length + trim\_latent, latent\_height, latent\_width]                                                   |
| `trim_latent`        | INT          | Latent space trimming information indicating the number of latent frames to trim from the beginning (corresponds to reference image latent frames)                                           |
| `trim_image`         | INT          | Image space trimming information for reference motion frames, indicating the number of image frames to trim from the beginning                                                               |
| `video_frame_offset` | INT          | Updated frame offset for continuing video generation in chunks, calculated as the previous offset plus the generated length                                                                  |

***

**Source fingerprint (SHA-256):** `2ec2afbc57f58a5b7ce0ecc3730618633d435439ce2d650b18be531c1edddff0`


# WanCameraEmbedding - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanCameraEmbedding

Complete documentation for the WanCameraEmbedding node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanCameraEmbedding/en.md)

The WanCameraEmbedding node generates camera trajectory embeddings using Plücker embeddings based on camera motion parameters. It creates a sequence of camera poses that simulate different camera movements and converts them into embedding tensors suitable for video generation pipelines.

## Inputs

| Parameter     | Data Type | Required | Range                                                                                                                                                    | Description                                                         |
| ------------- | --------- | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------- |
| `camera_pose` | COMBO     | Yes      | "Static"<br />"Pan Up"<br />"Pan Down"<br />"Pan Left"<br />"Pan Right"<br />"Zoom In"<br />"Zoom Out"<br />"Anti Clockwise (ACW)"<br />"ClockWise (CW)" | The type of camera movement to simulate (default: "Static")         |
| `width`       | INT       | Yes      | 16 to MAX\_RESOLUTION                                                                                                                                    | The width of the output in pixels (default: 832, step: 16)          |
| `height`      | INT       | Yes      | 16 to MAX\_RESOLUTION                                                                                                                                    | The height of the output in pixels (default: 480, step: 16)         |
| `length`      | INT       | Yes      | 1 to MAX\_RESOLUTION                                                                                                                                     | The length of the camera trajectory sequence (default: 81, step: 4) |
| `speed`       | FLOAT     | No       | 0.0 to 10.0                                                                                                                                              | The speed of the camera movement (default: 1.0, step: 0.1)          |
| `fx`          | FLOAT     | No       | 0.0 to 1.0                                                                                                                                               | The focal length x parameter (default: 0.5, step: 0.000000001)      |
| `fy`          | FLOAT     | No       | 0.0 to 1.0                                                                                                                                               | The focal length y parameter (default: 0.5, step: 0.000000001)      |
| `cx`          | FLOAT     | No       | 0.0 to 1.0                                                                                                                                               | The principal point x coordinate (default: 0.5, step: 0.01)         |
| `cy`          | FLOAT     | No       | 0.0 to 1.0                                                                                                                                               | The principal point y coordinate (default: 0.5, step: 0.01)         |

## Outputs

| Output Name        | Data Type | Description                                                              |
| ------------------ | --------- | ------------------------------------------------------------------------ |
| `camera_embedding` | TENSOR    | The generated camera embedding tensor containing the trajectory sequence |
| `width`            | INT       | The width value that was used for processing                             |
| `height`           | INT       | The height value that was used for processing                            |
| `length`           | INT       | The length value that was used for processing                            |

***

**Source fingerprint (SHA-256):** `9c13c4504ca58b7623f106eaf07ceb2aef7739a9b9ce24e321445078b1f953c9`


# WanCameraImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanCameraImageToVideo

Complete documentation for the WanCameraImageToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanCameraImageToVideo/en.md)

The WanCameraImageToVideo node prepares conditioning and latent data for video generation from images. It takes positive and negative conditioning prompts, along with optional starting images and camera controls, and outputs modified conditioning and an empty latent tensor ready for a video model to fill in.

## Inputs

| Parameter            | Data Type              | Required | Range                 | Description                                                                                                                                                                                                                                                                |
| -------------------- | ---------------------- | -------- | --------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`           | CONDITIONING           | Yes      | -                     | Positive conditioning prompts for video generation                                                                                                                                                                                                                         |
| `negative`           | CONDITIONING           | Yes      | -                     | Negative conditioning prompts to avoid in video generation                                                                                                                                                                                                                 |
| `vae`                | VAE                    | Yes      | -                     | VAE model for encoding images to latent space                                                                                                                                                                                                                              |
| `width`              | INT                    | Yes      | 16 to MAX\_RESOLUTION | Output video width in pixels (default: 832, step: 16)                                                                                                                                                                                                                      |
| `height`             | INT                    | Yes      | 16 to MAX\_RESOLUTION | Output video height in pixels (default: 480, step: 16)                                                                                                                                                                                                                     |
| `length`             | INT                    | Yes      | 1 to MAX\_RESOLUTION  | Number of frames in the video sequence (default: 81, step: 4)                                                                                                                                                                                                              |
| `batch_size`         | INT                    | Yes      | 1 to 4096             | Number of videos to generate simultaneously (default: 1)                                                                                                                                                                                                                   |
| `clip_vision_output` | CLIP\_VISION\_OUTPUT   | No       | -                     | Optional CLIP vision output for additional conditioning                                                                                                                                                                                                                    |
| `start_image`        | IMAGE                  | No       | -                     | Optional starting image to initialize the video sequence. When provided, the first frames of the video will be based on this image, with a mask applied to blend the starting frames with generated content. The image is resized to match the specified width and height. |
| `camera_conditions`  | WAN\_CAMERA\_EMBEDDING | No       | -                     | Optional camera embedding conditions for video generation. When provided, these conditions are applied to both positive and negative conditioning.                                                                                                                         |

**Note:** When `start_image` is provided, the node uses it to initialize the video sequence and applies masking to blend the starting frames with generated content. The `camera_conditions` and `clip_vision_output` parameters are optional but when provided, they modify the conditioning for both positive and negative prompts.

## Outputs

| Output Name | Data Type    | Description                                                                                                                                                                                                  |
| ----------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `positive`  | CONDITIONING | Modified positive conditioning with applied camera conditions, clip vision outputs, and/or starting image data                                                                                               |
| `negative`  | CONDITIONING | Modified negative conditioning with applied camera conditions, clip vision outputs, and/or starting image data                                                                                               |
| `latent`    | LATENT       | Generated empty video latent representation for use with video models. The latent tensor has dimensions \[batch\_size, 16, frames, height/8, width/8] where frames is calculated as ((length - 1) // 4) + 1. |

***

**Source fingerprint (SHA-256):** `e2309b40f78d5a2487242f1684f82d9e4dd8405ef256615f82da2f701418fd4a`


# WanDancerEncodeAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanDancerEncodeAudio

Complete documentation for the WanDancerEncodeAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanDancerEncodeAudio/en.md)

## Overview

This node processes an audio input to extract features that can be used to guide a video generation model. It analyzes the audio to detect tempo, beats, and other musical characteristics, then packages this information into a format suitable for conditioning a video model, allowing the generated video to be synchronized with the audio.

## Inputs

| Parameter            | Data Type | Required | Range                                             | Description                                                                                                    |
| -------------------- | --------- | -------- | ------------------------------------------------- | -------------------------------------------------------------------------------------------------------------- |
| `audio`              | AUDIO     | Yes      | -                                                 | The audio input to be analyzed and encoded.                                                                    |
| `video_frames`       | INT       | Yes      | Min: 1, Max: 268435456 (MAX\_RESOLUTION), Step: 4 | The number of frames in the target video. Used to calculate the frame rate for synchronization (default: 149). |
| `audio_inject_scale` | FLOAT     | Yes      | Min: 0.0, Max: 10.0, Step: 0.01                   | The scale for the audio features when injected into the video model (default: 1.0).                            |

## Outputs

| Output Name            | Data Type              | Description                                                                                                                                                                              |
| ---------------------- | ---------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `audio_encoder_output` | AUDIO\_ENCODER\_OUTPUT | A dictionary containing the processed audio features, the calculated frame rate (fps), and the audio injection scale. This output is used to condition the video generation model.       |
| `fps_string`           | STRING                 | A text string describing the calculated frame rate (fps) based on the audio length and the number of video frames. This string is intended to be used in the prompt for the video model. |

***

**Source fingerprint (SHA-256):** `1318323b202ca26c920a860534062dc7f20e3b10d13eb9825a890e26b5fde731`


# WanDancerVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanDancerVideo

Complete documentation for the WanDancerVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanDancerVideo/en.md)

The WanDancerVideo node prepares conditioning data and an empty latent tensor for video generation with the WanDancer model. It combines positive and negative conditioning with optional inputs like a starting image, mask, CLIP vision embeddings, and audio features to control the generated video.

## Inputs

| Parameter                | Data Type              | Required | Range                            | Description                                                                                                                  |
| ------------------------ | ---------------------- | -------- | -------------------------------- | ---------------------------------------------------------------------------------------------------------------------------- |
| `positive`               | CONDITIONING           | Yes      |                                  | The positive conditioning to guide video generation.                                                                         |
| `negative`               | CONDITIONING           | Yes      |                                  | The negative conditioning to guide video generation.                                                                         |
| `vae`                    | VAE                    | Yes      |                                  | The VAE used to encode the start image into the latent space.                                                                |
| `width`                  | INT                    | Yes      | 16 to MAX\_RESOLUTION (step: 16) | The width of the generated video in pixels (default: 480).                                                                   |
| `height`                 | INT                    | Yes      | 16 to MAX\_RESOLUTION (step: 16) | The height of the generated video in pixels (default: 832).                                                                  |
| `length`                 | INT                    | Yes      | 1 to MAX\_RESOLUTION (step: 4)   | The number of frames in the generated video. Should stay 149 for WanDancer (default: 149).                                   |
| `clip_vision_output`     | CLIP\_VISION\_OUTPUT   | No       |                                  | The CLIP vision embeddings for the first frame.                                                                              |
| `clip_vision_output_ref` | CLIP\_VISION\_OUTPUT   | No       |                                  | The CLIP vision embeddings for the reference image.                                                                          |
| `start_image`            | IMAGE                  | No       |                                  | The initial image(s) to be encoded. Can be any number of frames, up to the specified `length`.                               |
| `mask`                   | MASK                   | No       |                                  | Image conditioning mask for the start image(s). White areas are kept, black areas are generated. Used for local generations. |
| `audio_encoder_output`   | AUDIO\_ENCODER\_OUTPUT | No       |                                  | The output from an audio encoder, providing audio features, fps, and inject scale for audio-conditional generation.          |

**Note on Parameter Constraints:**

* The `start_image` and `mask` inputs are optional but can be used together. When `start_image` is provided, it is encoded and concatenated with the latent. If `mask` is also provided, it controls which parts of the start image are kept (white) and which are regenerated (black). If `mask` is not provided, the entire start image area is used as a conditioning guide.
* The `clip_vision_output` and `clip_vision_output_ref` inputs are optional and can be used together to provide visual context for the first frame and a reference image.
* The `audio_encoder_output` input is optional and provides audio features for audio-conditional generation.

## Outputs

| Output Name | Data Type    | Description                                                                                      |
| ----------- | ------------ | ------------------------------------------------------------------------------------------------ |
| `positive`  | CONDITIONING | The positive conditioning with any additional data (concat latent, CLIP vision, audio) attached. |
| `negative`  | CONDITIONING | The negative conditioning with any additional data (concat latent, CLIP vision, audio) attached. |
| `latent`    | LATENT       | An empty latent tensor with dimensions matching the specified video length, height, and width.   |

***

**Source fingerprint (SHA-256):** `0a75b24c8e5c164d81b08eb438862d94d4409ece8dc22c126979347e2350c828`


# WanFirstLastFrameToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanFirstLastFrameToVideo

Complete documentation for the WanFirstLastFrameToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanFirstLastFrameToVideo/en.md)

The WanFirstLastFrameToVideo node creates video conditioning by combining start and end frames with text prompts. It generates a latent representation for video generation by encoding the first and last frames, applying masks to guide the generation process, and incorporating CLIP vision features when available. This node prepares both positive and negative conditioning for video models to generate coherent sequences between specified start and end points.

## Inputs

| Parameter                 | Data Type            | Required | Range                 | Description                                                   |
| ------------------------- | -------------------- | -------- | --------------------- | ------------------------------------------------------------- |
| `positive`                | CONDITIONING         | Yes      | -                     | Positive text conditioning for guiding the video generation   |
| `negative`                | CONDITIONING         | Yes      | -                     | Negative text conditioning for guiding the video generation   |
| `vae`                     | VAE                  | Yes      | -                     | VAE model used for encoding images to latent space            |
| `width`                   | INT                  | Yes      | 16 to MAX\_RESOLUTION | Output video width (default: 832, step: 16)                   |
| `height`                  | INT                  | Yes      | 16 to MAX\_RESOLUTION | Output video height (default: 480, step: 16)                  |
| `length`                  | INT                  | Yes      | 1 to MAX\_RESOLUTION  | Number of frames in the video sequence (default: 81, step: 4) |
| `batch_size`              | INT                  | Yes      | 1 to 4096             | Number of videos to generate simultaneously (default: 1)      |
| `clip_vision_start_image` | CLIP\_VISION\_OUTPUT | No       | -                     | CLIP vision features extracted from the start image           |
| `clip_vision_end_image`   | CLIP\_VISION\_OUTPUT | No       | -                     | CLIP vision features extracted from the end image             |
| `start_image`             | IMAGE                | No       | -                     | Starting frame image for the video sequence                   |
| `end_image`               | IMAGE                | No       | -                     | Ending frame image for the video sequence                     |

**Note:** When both `start_image` and `end_image` are provided, the node creates a video sequence that transitions between these two frames. The `clip_vision_start_image` and `clip_vision_end_image` parameters are optional but when provided, their CLIP vision features are concatenated and applied to both positive and negative conditioning. The `start_image` is cropped to the first `length` frames, and the `end_image` is cropped to the last `length` frames before processing.

## Outputs

| Output Name | Data Type    | Description                                                                      |
| ----------- | ------------ | -------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Positive conditioning with applied video frame encoding and CLIP vision features |
| `negative`  | CONDITIONING | Negative conditioning with applied video frame encoding and CLIP vision features |
| `latent`    | LATENT       | Empty latent tensor with dimensions matching the specified video parameters      |

***

**Source fingerprint (SHA-256):** `c9017cbed8d90e0c22a27c035784396fe1fa1551d586e2ec148e0621228162c0`


# WanFunControlToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanFunControlToVideo

Complete documentation for the WanFunControlToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node was added to support the Alibaba Wan Fun Control model for video generation, and was added after [this commit](https://github.com/comfyanonymous/ComfyUI/commit/3661c833bcc41b788a7c9f0e7bc48524f8ee5f82).

* **Purpose:** Prepare the conditioning information needed for video generation, using the Wan 2.1 Fun Control model.

The WanFunControlToVideo node is a ComfyUI addition designed to support Wan Fun Control models for video generation, aimed at utilizing WanFun control for video creation.

This node serves as a preparation point for essential conditioning information and initializes the center point of the latent space, guiding the subsequent video generation process using the Wan 2.1 Fun model. The node's name clearly indicates its function: it accepts various inputs and converts them into a format suitable for controlling video generation within the WanFun framework.

The node's position in the ComfyUI node hierarchy indicates that it operates in the early stages of the video generation pipeline, focusing on manipulating conditioning signals before actual sampling or decoding of video frames.

## Inputs

| Parameter Name       | Required | Data Type            | Description                                                                                                                                                                                                           | Default Value |
| :------------------- | :------- | :------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------ |
| positive             | Yes      | CONDITIONING         | Standard ComfyUI positive conditioning data, typically from a "CLIP Text Encode" node. The positive prompt describes the content, subject matter, and artistic style that the user envisions for the generated video. | N/A           |
| negative             | Yes      | CONDITIONING         | Standard ComfyUI negative conditioning data, typically generated by a "CLIP Text Encode" node. The negative prompt specifies elements, styles, or artifacts that the user wants to avoid in the generated video.      | N/A           |
| vae                  | Yes      | VAE                  | Requires a VAE (Variational Autoencoder) model compatible with the Wan 2.1 Fun model family, used for encoding and decoding image/video data.                                                                         | N/A           |
| width                | Yes      | INT                  | The desired width of output video frames in pixels, with a default value of 832, minimum value of 16, maximum value determined by nodes.MAX\_RESOLUTION, and a step size of 16.                                       | 832           |
| height               | Yes      | INT                  | The desired height of output video frames in pixels, with a default value of 480, minimum value of 16, maximum value determined by nodes.MAX\_RESOLUTION, and a step size of 16.                                      | 480           |
| length               | Yes      | INT                  | The total number of frames in the generated video, with a default value of 81, minimum value of 1, maximum value determined by nodes.MAX\_RESOLUTION, and a step size of 4.                                           | 81            |
| batch\_size          | Yes      | INT                  | The number of videos generated in a single batch, with a default value of 1, minimum value of 1, and maximum value of 4096.                                                                                           | 1             |
| clip\_vision\_output | No       | CLIP\_VISION\_OUTPUT | (Optional) Visual features extracted by a CLIP vision model, allowing for visual style and content guidance.                                                                                                          | None          |
| start\_image         | No       | IMAGE                | (Optional) An initial image that influences the beginning of the generated video.                                                                                                                                     | None          |
| control\_video       | No       | IMAGE                | (Optional) Allows users to provide a preprocessed ControlNet reference video that will guide the motion and potential structure of the generated video.                                                               | None          |

## Outputs

| Parameter Name | Data Type    | Description                                                                                                 |
| :------------- | :----------- | :---------------------------------------------------------------------------------------------------------- |
| positive       | CONDITIONING | Provides enhanced positive conditioning data, including encoded start\_image and control\_video.            |
| negative       | CONDITIONING | Provides negative conditioning data that has also been enhanced, containing the same concat\_latent\_image. |
| latent         | LATENT       | A dictionary containing an empty latent tensor with the key "samples".                                      |


# WanFunInpaintToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanFunInpaintToVideo

Complete documentation for the WanFunInpaintToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanFunInpaintToVideo/en.md)

The WanFunInpaintToVideo node creates video sequences by inpainting between start and end images. It takes positive and negative conditioning along with optional frame images to generate video latents. The node handles video generation with configurable dimensions and length parameters.

## Inputs

| Parameter            | Data Type            | Required | Range                 | Description                                                   |
| -------------------- | -------------------- | -------- | --------------------- | ------------------------------------------------------------- |
| `positive`           | CONDITIONING         | Yes      | -                     | Positive conditioning prompts for video generation            |
| `negative`           | CONDITIONING         | Yes      | -                     | Negative conditioning prompts to avoid in video generation    |
| `vae`                | VAE                  | Yes      | -                     | VAE model for encoding/decoding operations                    |
| `width`              | INT                  | Yes      | 16 to MAX\_RESOLUTION | Output video width in pixels (default: 832, step: 16)         |
| `height`             | INT                  | Yes      | 16 to MAX\_RESOLUTION | Output video height in pixels (default: 480, step: 16)        |
| `length`             | INT                  | Yes      | 1 to MAX\_RESOLUTION  | Number of frames in the video sequence (default: 81, step: 4) |
| `batch_size`         | INT                  | Yes      | 1 to 4096             | Number of videos to generate in a batch (default: 1)          |
| `clip_vision_output` | CLIP\_VISION\_OUTPUT | No       | -                     | Optional CLIP vision output for additional conditioning       |
| `start_image`        | IMAGE                | No       | -                     | Optional starting frame image for video generation            |
| `end_image`          | IMAGE                | No       | -                     | Optional ending frame image for video generation              |

## Outputs

| Output Name | Data Type    | Description                            |
| ----------- | ------------ | -------------------------------------- |
| `positive`  | CONDITIONING | Processed positive conditioning output |
| `negative`  | CONDITIONING | Processed negative conditioning output |
| `latent`    | LATENT       | Generated video latent representation  |

***

**Source fingerprint (SHA-256):** `16926439268e3748418f1a7c1e9a295ddb1ebc5fcb0ad4914fc8e3215a7950dc`


# WanHuMoImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanHuMoImageToVideo

Complete documentation for the WanHuMoImageToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanHuMoImageToVideo/en.md)

The WanHuMoImageToVideo node converts images to video sequences by generating latent representations for video frames. It processes conditioning inputs and can incorporate reference images and audio embeddings to influence the video generation. The node outputs modified conditioning data and latent representations suitable for video synthesis.

## Inputs

| Parameter              | Data Type          | Required | Range                 | Description                                                                                                      |
| ---------------------- | ------------------ | -------- | --------------------- | ---------------------------------------------------------------------------------------------------------------- |
| `positive`             | CONDITIONING       | Yes      | -                     | Positive conditioning input that guides the video generation toward desired content                              |
| `negative`             | CONDITIONING       | Yes      | -                     | Negative conditioning input that steers the video generation away from unwanted content                          |
| `vae`                  | VAE                | Yes      | -                     | VAE model used for encoding reference images into latent space                                                   |
| `width`                | INT                | Yes      | 16 to MAX\_RESOLUTION | Width of the output video frames in pixels (default: 832, must be divisible by 16)                               |
| `height`               | INT                | Yes      | 16 to MAX\_RESOLUTION | Height of the output video frames in pixels (default: 480, must be divisible by 16)                              |
| `length`               | INT                | Yes      | 1 to MAX\_RESOLUTION  | Number of frames in the generated video sequence (default: 97, must be such that (length - 1) is divisible by 4) |
| `batch_size`           | INT                | Yes      | 1 to 4096             | Number of video sequences to generate simultaneously (default: 1)                                                |
| `audio_encoder_output` | AUDIOENCODEROUTPUT | No       | -                     | Optional audio encoding data that can influence video generation based on audio content                          |
| `ref_image`            | IMAGE              | No       | -                     | Optional reference image used to guide the video generation style and content                                    |

**Note:** When a reference image is provided, it gets encoded and added to both positive and negative conditioning. When audio encoder output is provided, it gets processed and incorporated into the conditioning data. If neither is provided, zero-filled placeholder tensors are used for both reference latents and audio embeddings.

## Outputs

| Output Name | Data Type    | Description                                                                              |
| ----------- | ------------ | ---------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Modified positive conditioning with reference image and/or audio embeddings incorporated |
| `negative`  | CONDITIONING | Modified negative conditioning with reference image and/or audio embeddings incorporated |
| `latent`    | LATENT       | Generated latent representation containing the video sequence data                       |

***

**Source fingerprint (SHA-256):** `4d28fe2617f25e72745d34bf2ec19aec2df6e89ad49eabe086ad045690f42d1f`


# WanImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanImageToVideo

Complete documentation for the WanImageToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanImageToVideo/en.md)

The WanImageToVideo node prepares conditioning and latent representations for video generation tasks. It creates an empty latent space for video generation and can optionally incorporate starting images and CLIP vision outputs to guide the video generation process. The node modifies both positive and negative conditioning inputs based on the provided image and vision data.

## Inputs

| Parameter            | Data Type            | Required | Range                 | Description                                                                                                                                                                                                                                                                 |
| -------------------- | -------------------- | -------- | --------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`           | CONDITIONING         | Yes      | -                     | Positive conditioning input for guiding the generation                                                                                                                                                                                                                      |
| `negative`           | CONDITIONING         | Yes      | -                     | Negative conditioning input for guiding the generation                                                                                                                                                                                                                      |
| `vae`                | VAE                  | Yes      | -                     | VAE model for encoding images to latent space                                                                                                                                                                                                                               |
| `width`              | INT                  | Yes      | 16 to MAX\_RESOLUTION | Width of the output video (default: 832, step: 16)                                                                                                                                                                                                                          |
| `height`             | INT                  | Yes      | 16 to MAX\_RESOLUTION | Height of the output video (default: 480, step: 16)                                                                                                                                                                                                                         |
| `length`             | INT                  | Yes      | 1 to MAX\_RESOLUTION  | Number of frames in the video (default: 81, step: 4)                                                                                                                                                                                                                        |
| `batch_size`         | INT                  | Yes      | 1 to 4096             | Number of videos to generate in a batch (default: 1)                                                                                                                                                                                                                        |
| `clip_vision_output` | CLIP\_VISION\_OUTPUT | No       | -                     | Optional CLIP vision output for additional conditioning                                                                                                                                                                                                                     |
| `start_image`        | IMAGE                | No       | -                     | Optional starting image to initialize the video generation. When provided, the image is resized to match the specified width and height, and the first frames of the video are initialized from this image. The remaining frames are filled with neutral gray (0.5) values. |

**Note:** When `start_image` is provided, the node encodes the image sequence using the VAE and applies a mask to the conditioning inputs. The mask covers all frames except those initialized by the starting image, allowing the generation to build upon the provided image. The `clip_vision_output` parameter, when provided, adds vision-based conditioning to both positive and negative inputs.

## Outputs

| Output Name | Data Type    | Description                                                                                                                 |
| ----------- | ------------ | --------------------------------------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Modified positive conditioning with image and vision data incorporated                                                      |
| `negative`  | CONDITIONING | Modified negative conditioning with image and vision data incorporated                                                      |
| `latent`    | LATENT       | Empty latent space tensor ready for video generation, with shape \[batch\_size, 16, ((length-1)//4)+1, height//8, width//8] |

***

**Source fingerprint (SHA-256):** `9cac4f27f5ec2e0d5247fab78acb00a68eb6317dd747d6f6f46b065240f64a8b`


# WanInfiniteTalkToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanInfiniteTalkToVideo

Complete documentation for the WanInfiniteTalkToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanInfiniteTalkToVideo/en.md)

The WanInfiniteTalkToVideo node generates video sequences from audio input. It uses a video diffusion model, conditioned on audio features extracted from one or two speakers, to produce a latent representation of a talking head video. The node can generate a new sequence or extend an existing one using previous frames for motion context.

## Inputs

| Parameter                | Data Type          | Required | Range                                    | Description                                                                                                                                  |
| ------------------------ | ------------------ | -------- | ---------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------- |
| `mode`                   | COMBO              | Yes      | `"single_speaker"`<br />`"two_speakers"` | The audio input mode. `"single_speaker"` uses one audio input. `"two_speakers"` enables inputs for a second speaker and corresponding masks. |
| `model`                  | MODEL              | Yes      | -                                        | The base video diffusion model.                                                                                                              |
| `model_patch`            | MODELPATCH         | Yes      | -                                        | The model patch containing audio projection layers.                                                                                          |
| `positive`               | CONDITIONING       | Yes      | -                                        | The positive conditioning to guide the generation.                                                                                           |
| `negative`               | CONDITIONING       | Yes      | -                                        | The negative conditioning to guide the generation.                                                                                           |
| `vae`                    | VAE                | Yes      | -                                        | The VAE used for encoding images to and from the latent space.                                                                               |
| `width`                  | INT                | No       | 16 - MAX\_RESOLUTION                     | The width of the output video in pixels. Must be divisible by 16. (default: 832)                                                             |
| `height`                 | INT                | No       | 16 - MAX\_RESOLUTION                     | The height of the output video in pixels. Must be divisible by 16. (default: 480)                                                            |
| `length`                 | INT                | No       | 1 - MAX\_RESOLUTION                      | The number of frames to generate. (default: 81)                                                                                              |
| `clip_vision_output`     | CLIPVISIONOUTPUT   | No       | -                                        | Optional CLIP vision output for additional conditioning.                                                                                     |
| `start_image`            | IMAGE              | No       | -                                        | An optional starting image to initialize the video sequence.                                                                                 |
| `audio_encoder_output_1` | AUDIOENCODEROUTPUT | Yes      | -                                        | The primary audio encoder output containing features for the first speaker.                                                                  |
| `motion_frame_count`     | INT                | No       | 1 - 33                                   | Number of previous frames to use as motion context when extending a sequence. (default: 9)                                                   |
| `audio_scale`            | FLOAT              | No       | -10.0 - 10.0                             | A scaling factor applied to the audio conditioning. (default: 1.0)                                                                           |
| `previous_frames`        | IMAGE              | No       | -                                        | Optional previous video frames to extend from.                                                                                               |
| `audio_encoder_output_2` | AUDIOENCODEROUTPUT | No       | -                                        | The second audio encoder output. Required when `mode` is set to `"two_speakers"`.                                                            |
| `mask_1`                 | MASK               | No       | -                                        | Mask for the first speaker, required if using two audio inputs.                                                                              |
| `mask_2`                 | MASK               | No       | -                                        | Mask for the second speaker, required if using two audio inputs.                                                                             |

**Parameter Constraints:**

* When `mode` is set to `"two_speakers"`, the parameters `audio_encoder_output_2`, `mask_1`, and `mask_2` become required.
* If `audio_encoder_output_2` is provided, both `mask_1` and `mask_2` must also be provided.
* If `mask_1` and `mask_2` are provided, `audio_encoder_output_2` must also be provided.
* If `previous_frames` is provided, it must contain at least as many frames as specified by `motion_frame_count`.

## Outputs

| Output Name  | Data Type    | Description                                                                                                 |
| ------------ | ------------ | ----------------------------------------------------------------------------------------------------------- |
| `model`      | MODEL        | The patched model with audio conditioning applied.                                                          |
| `positive`   | CONDITIONING | The positive conditioning, potentially modified with additional context (e.g., start image, CLIP vision).   |
| `negative`   | CONDITIONING | The negative conditioning, potentially modified with additional context.                                    |
| `latent`     | LATENT       | The generated video sequence in latent space.                                                               |
| `trim_image` | INT          | The number of frames from the start of the motion context that should be trimmed when extending a sequence. |

***

**Source fingerprint (SHA-256):** `1ef125235ce5adb09972737d0e2863255315c536da718c7af230de1b4a7f53e2`


# WanMoveConcatTrack - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanMoveConcatTrack

Complete documentation for the WanMoveConcatTrack node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanMoveConcatTrack/en.md)

The WanMoveConcatTrack node combines two sets of motion tracking data into a single, longer sequence. It works by joining the track paths and visibility masks from the input tracks along their respective dimensions. If only one track input is provided, it simply passes that data through unchanged.

## Inputs

| Parameter  | Data Type | Required | Range | Description                                                                                                   |
| ---------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------- |
| `tracks_1` | TRACKS    | Yes      |       | The first set of motion tracking data to be concatenated.                                                     |
| `tracks_2` | TRACKS    | No       |       | An optional second set of motion tracking data. If not provided, `tracks_1` is passed directly to the output. |

## Outputs

| Output Name | Data Type | Description                                                                                                         |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------- |
| `tracks`    | TRACKS    | The concatenated motion tracking data, containing the combined `track_path` and `track_visibility` from the inputs. |

***

**Source fingerprint (SHA-256):** `96741eecf48ce534fa2deac8a6f62c1374a7cdc4c0b6263ce9b4d757861fc338`


# WanMoveTrackToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanMoveTrackToVideo

Complete documentation for the WanMoveTrackToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanMoveTrackToVideo/en.md)

The WanMoveTrackToVideo node prepares conditioning and latent space data for video generation, incorporating optional motion tracking information. It encodes a starting image sequence into a latent representation and can blend in positional data from object tracks to guide the motion in the generated video. The node outputs modified positive and negative conditioning along with an empty latent tensor ready for a video model.

## Inputs

| Parameter            | Data Type        | Required | Range                | Description                                                             |
| -------------------- | ---------------- | -------- | -------------------- | ----------------------------------------------------------------------- |
| `positive`           | CONDITIONING     | Yes      | -                    | The positive conditioning input to be modified.                         |
| `negative`           | CONDITIONING     | Yes      | -                    | The negative conditioning input to be modified.                         |
| `vae`                | VAE              | Yes      | -                    | The VAE model used to encode the starting image into the latent space.  |
| `tracks`             | TRACKS           | No       | -                    | Optional motion tracking data containing object paths.                  |
| `strength`           | FLOAT            | No       | 0.0 - 100.0          | Strength of the track conditioning. (default: 1.0)                      |
| `width`              | INT              | No       | 16 - MAX\_RESOLUTION | The width of the output video. Must be divisible by 16. (default: 832)  |
| `height`             | INT              | No       | 16 - MAX\_RESOLUTION | The height of the output video. Must be divisible by 16. (default: 480) |
| `length`             | INT              | No       | 1 - MAX\_RESOLUTION  | The number of frames in the video sequence. (default: 81)               |
| `batch_size`         | INT              | No       | 1 - 4096             | The batch size for the latent output. (default: 1)                      |
| `start_image`        | IMAGE            | Yes      | -                    | The starting image or image sequence to encode.                         |
| `clip_vision_output` | CLIPVISIONOUTPUT | No       | -                    | Optional CLIP vision model output to add to the conditioning.           |

**Note:** The `strength` parameter only has an effect when `tracks` are provided. If `tracks` are not provided or `strength` is 0.0, the track conditioning is not applied. The `start_image` is used to create a latent image and mask for the conditioning; if it is not provided, the node only passes through the conditioning and outputs an empty latent.

## Outputs

| Output Name | Data Type    | Description                                                                                                                |
| ----------- | ------------ | -------------------------------------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | The modified positive conditioning, potentially containing `concat_latent_image`, `concat_mask`, and `clip_vision_output`. |
| `negative`  | CONDITIONING | The modified negative conditioning, potentially containing `concat_latent_image`, `concat_mask`, and `clip_vision_output`. |
| `latent`    | LATENT       | An empty latent tensor with dimensions shaped by the `batch_size`, `length`, `height`, and `width` inputs.                 |

***

**Source fingerprint (SHA-256):** `9dc861c3616a3d92c9dc647e1d227bc1f94d5c74c58eed41ffa8d28b445c9160`


# WanMoveTracksFromCoords - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanMoveTracksFromCoords

Complete documentation for the WanMoveTracksFromCoords node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanMoveTracksFromCoords/en.md)

The WanMoveTracksFromCoords node creates motion tracks from a JSON-formatted string of coordinates. It converts the coordinate data into a tensor format that can be used by other video processing nodes, and can optionally apply a mask to control the visibility of tracks over time.

## Inputs

| Parameter      | Data Type | Required | Range | Description                                                                                                         |
| -------------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------- |
| `track_coords` | STRING    | No       | N/A   | A JSON-formatted string containing the coordinate data for the tracks. The default value is an empty list (`"[]"`). |
| `track_mask`   | MASK      | No       | N/A   | An optional mask. When provided, the node uses it to determine the visibility of each track per frame.              |

**Note:** The `track_coords` input expects a specific JSON structure. It should be a list of tracks, where each track is a list of frames, and each frame is an object with `x` and `y` coordinates. The number of frames must be consistent across all tracks.

## Outputs

| Output Name    | Data Type | Description                                                                                          |
| -------------- | --------- | ---------------------------------------------------------------------------------------------------- |
| `tracks`       | TRACKS    | The generated track data, containing the path coordinates and visibility information for each track. |
| `track_length` | INT       | The total number of frames in the generated tracks.                                                  |

***

**Source fingerprint (SHA-256):** `2c02b7bfc51951d8b5d24e9f19d64cdf0eab7b4f1a3436b63e9baf1765417193`


# WanMoveVisualizeTracks - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanMoveVisualizeTracks

Complete documentation for the WanMoveVisualizeTracks node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanMoveVisualizeTracks/en.md)

The WanMoveVisualizeTracks node overlays motion tracking data onto a sequence of images or video frames. It draws visual representations of tracked points, including their movement paths and current positions, making the motion data visible and easier to analyze.

## Inputs

| Parameter         | Data Type | Required | Range     | Description                                                                                                                                 |
| ----------------- | --------- | -------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------- |
| `images`          | IMAGE     | Yes      | -         | The sequence of input images or video frames to visualize the tracks on.                                                                    |
| `tracks`          | TRACKS    | No       | -         | The motion tracking data containing point paths and visibility information. If not provided, the input images are passed through unchanged. |
| `line_resolution` | INT       | Yes      | 1 - 1024  | The number of previous frames to use when drawing the trailing path line for each track (default: 24).                                      |
| `circle_size`     | INT       | Yes      | 1 - 128   | The size of the circle drawn at the current position of each track (default: 12).                                                           |
| `opacity`         | FLOAT     | Yes      | 0.0 - 1.0 | The opacity of the drawn track overlays (default: 0.75).                                                                                    |
| `line_width`      | INT       | Yes      | 1 - 128   | The width of the lines used to draw the track paths (default: 16).                                                                          |

**Note:** If the number of input images does not match the number of frames in the provided `tracks` data, the image sequence will be repeated to match the track length.

## Outputs

| Output Name | Data Type | Description                                                                                                                                        |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
| `IMAGE`     | IMAGE     | The sequence of images with the motion tracking data visualized as overlays. If no `tracks` were provided, the original input images are returned. |

***

**Source fingerprint (SHA-256):** `9912b8cc06a8b4014f73e537d9421be3d8dda3b1a416733f4c0fb0caf8663b6f`


# WanPhantomSubjectToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanPhantomSubjectToVideo

Complete documentation for the WanPhantomSubjectToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanPhantomSubjectToVideo/en.md)

The WanPhantomSubjectToVideo node generates video content by processing conditioning inputs and optional reference images. It creates latent representations for video generation and can incorporate visual guidance from input images when provided. The node prepares conditioning data with time-dimensional concatenation for video models and outputs modified conditioning along with generated latent video data.

## Inputs

| Parameter    | Data Type    | Required | Range                 | Description                                                                   |
| ------------ | ------------ | -------- | --------------------- | ----------------------------------------------------------------------------- |
| `positive`   | CONDITIONING | Yes      | -                     | Positive conditioning input for guiding video generation                      |
| `negative`   | CONDITIONING | Yes      | -                     | Negative conditioning input to avoid certain characteristics                  |
| `vae`        | VAE          | Yes      | -                     | VAE model for encoding images when provided                                   |
| `width`      | INT          | Yes      | 16 to MAX\_RESOLUTION | Output video width in pixels (default: 832, must be divisible by 16)          |
| `height`     | INT          | Yes      | 16 to MAX\_RESOLUTION | Output video height in pixels (default: 480, must be divisible by 16)         |
| `length`     | INT          | Yes      | 1 to MAX\_RESOLUTION  | Number of frames in the generated video (default: 81, must be divisible by 4) |
| `batch_size` | INT          | Yes      | 1 to 4096             | Number of videos to generate simultaneously (default: 1)                      |
| `images`     | IMAGE        | No       | -                     | Optional reference images for time-dimensional conditioning                   |

**Note:** When `images` are provided, they are automatically upscaled to match the specified `width` and `height`, and only the first `length` frames are used for processing.

## Outputs

| Output Name         | Data Type    | Description                                                                                 |
| ------------------- | ------------ | ------------------------------------------------------------------------------------------- |
| `positive`          | CONDITIONING | Modified positive conditioning with time-dimensional concatenation when images are provided |
| `negative_text`     | CONDITIONING | Modified negative conditioning with time-dimensional concatenation when images are provided |
| `negative_img_text` | CONDITIONING | Negative conditioning with zeroed time-dimensional concatenation when images are provided   |
| `latent`            | LATENT       | Generated latent video representation with specified dimensions and length                  |

***

**Source fingerprint (SHA-256):** `9ff1c79f794f96015f099988b5392e3b2e442de3b317c352f2436feb41a1c3ba`


# WanSCAILToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanSCAILToVideo

Complete documentation for the WanSCAILToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanSCAILToVideo/en.md)

The WanSCAILToVideo node prepares conditioning and an empty latent space for video generation. It processes optional inputs like reference images, pose videos, and CLIP vision outputs, embedding them into the positive and negative conditioning for a video model. The node outputs the modified conditioning and a blank latent tensor of the specified video dimensions.

## Inputs

| Parameter            | Data Type            | Required | Range                 | Description                                                                                    |
| -------------------- | -------------------- | -------- | --------------------- | ---------------------------------------------------------------------------------------------- |
| `positive`           | CONDITIONING         | Yes      | -                     | The positive conditioning input.                                                               |
| `negative`           | CONDITIONING         | Yes      | -                     | The negative conditioning input.                                                               |
| `vae`                | VAE                  | Yes      | -                     | The VAE model used for encoding images and video frames.                                       |
| `width`              | INT                  | Yes      | 32 to MAX\_RESOLUTION | The width of the output video in pixels (default: 512). Must be divisible by 8.                |
| `height`             | INT                  | Yes      | 32 to MAX\_RESOLUTION | The height of the output video in pixels (default: 896). Must be divisible by 8.               |
| `length`             | INT                  | Yes      | 1 to MAX\_RESOLUTION  | The number of frames in the video (default: 81). Must be divisible by 4.                       |
| `batch_size`         | INT                  | Yes      | 1 to 4096             | The number of videos to generate in a batch (default: 1).                                      |
| `clip_vision_output` | CLIP\_VISION\_OUTPUT | No       | -                     | Optional CLIP vision output for conditioning.                                                  |
| `reference_image`    | IMAGE                | No       | -                     | An optional reference image for conditioning.                                                  |
| `pose_video`         | IMAGE                | No       | -                     | Video used for pose conditioning. Will be downscaled to half the resolution of the main video. |
| `pose_strength`      | FLOAT                | Yes      | 0.0 to 10.0           | Strength of the pose latent (default: 1.0).                                                    |
| `pose_start`         | FLOAT                | Yes      | 0.0 to 1.0            | Start step to use pose conditioning (default: 0.0).                                            |
| `pose_end`           | FLOAT                | Yes      | 0.0 to 1.0            | End step to use pose conditioning (default: 1.0).                                              |

**Note:** The `pose_video` input is processed only for the first `length` frames. The `reference_image` is processed only for the first image in the batch. When `reference_image` is provided, a zero-filled latent of the same size is used for the negative conditioning. When `clip_vision_output` is provided, it is applied to both positive and negative conditioning. The `pose_video` is downscaled to half the resolution of the main video before encoding.

## Outputs

| Output Name | Data Type    | Description                                                                                                                             |
| ----------- | ------------ | --------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | The modified positive conditioning, potentially containing embedded reference image latents, CLIP vision output, or pose video latents. |
| `negative`  | CONDITIONING | The modified negative conditioning, potentially containing embedded reference image latents, CLIP vision output, or pose video latents. |
| `latent`    | LATENT       | An empty latent tensor of shape `[batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8]`.                                   |

***

**Source fingerprint (SHA-256):** `01c0912474602c33fa0c3e277db90e0eb83edbcea307a860921bab486d267cc8`


# WanSoundImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanSoundImageToVideo

Complete documentation for the WanSoundImageToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanSoundImageToVideo/en.md)

The WanSoundImageToVideo node generates video content from images with optional audio conditioning. It takes positive and negative conditioning prompts along with a VAE model to create video latents, and can incorporate reference images, audio encoding, control videos, and motion references to guide the video generation process.

## Inputs

| Parameter              | Data Type          | Required | Range                 | Description                                                                                                                                                                                                                             |
| ---------------------- | ------------------ | -------- | --------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`             | CONDITIONING       | Yes      | -                     | Positive conditioning prompts that guide what content should appear in the generated video                                                                                                                                              |
| `negative`             | CONDITIONING       | Yes      | -                     | Negative conditioning prompts that specify what content should be avoided in the generated video                                                                                                                                        |
| `vae`                  | VAE                | Yes      | -                     | VAE model used for encoding and decoding the video latent representations                                                                                                                                                               |
| `width`                | INT                | Yes      | 16 to MAX\_RESOLUTION | Width of the output video in pixels (default: 832, must be divisible by 16)                                                                                                                                                             |
| `height`               | INT                | Yes      | 16 to MAX\_RESOLUTION | Height of the output video in pixels (default: 480, must be divisible by 16)                                                                                                                                                            |
| `length`               | INT                | Yes      | 1 to MAX\_RESOLUTION  | Number of frames in the generated video (default: 77, must be divisible by 4)                                                                                                                                                           |
| `batch_size`           | INT                | Yes      | 1 to 4096             | Number of videos to generate simultaneously (default: 1)                                                                                                                                                                                |
| `audio_encoder_output` | AUDIOENCODEROUTPUT | No       | -                     | Optional audio encoding that can influence the video generation based on sound characteristics. When provided, the audio features are interpolated and used to condition the video generation.                                          |
| `ref_image`            | IMAGE              | No       | -                     | Optional reference image that provides visual guidance for the video content. The image is upscaled to match the specified width and height, then encoded into a latent representation.                                                 |
| `control_video`        | IMAGE              | No       | -                     | Optional control video that guides the motion and structure of the generated video. The video is upscaled and encoded, then used to condition the output. Only the first `length` frames are used.                                      |
| `ref_motion`           | IMAGE              | No       | -                     | Optional motion reference that provides guidance for movement patterns in the video. If the input has more than 73 frames, only the last 73 are used. If fewer than 73 frames are provided, the sequence is padded with neutral frames. |

## Outputs

| Output Name | Data Type    | Description                                                                                                                                                                                                                   |
| ----------- | ------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Processed positive conditioning that has been modified for video generation, including audio embeddings, reference latents, motion references, and control video conditioning                                                 |
| `negative`  | CONDITIONING | Processed negative conditioning that has been modified for video generation, including audio embeddings (set to zero), reference latents, motion references, and control video conditioning                                   |
| `latent`    | LATENT       | Generated video representation in latent space that can be decoded into final video frames. The latent tensor has shape \[batch\_size, 16, latent\_t, height/8, width/8] where latent\_t is derived from the length parameter |

***

**Source fingerprint (SHA-256):** `08aa558c23990f7efae9adede91715bf40afca4b50e416a6cadfd18c3d607b75`


# WanSoundImageToVideoExtend - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanSoundImageToVideoExtend

Complete documentation for the WanSoundImageToVideoExtend node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanSoundImageToVideoExtend/en.md)

The WanSoundImageToVideoExtend node extends an existing video latent by generating additional frames, optionally guided by audio, a reference image, and a control video. It takes a starting video latent and produces a longer video sequence, using the provided conditioning and audio cues to influence the new content.

## Inputs

| Parameter              | Data Type          | Required | Range                | Description                                                                                                                                                                                                                        |
| ---------------------- | ------------------ | -------- | -------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`             | CONDITIONING       | Yes      | -                    | Positive conditioning prompts that guide what the video should include                                                                                                                                                             |
| `negative`             | CONDITIONING       | Yes      | -                    | Negative conditioning prompts that specify what the video should avoid                                                                                                                                                             |
| `vae`                  | VAE                | Yes      | -                    | Variational Autoencoder used for encoding and decoding video frames                                                                                                                                                                |
| `length`               | INT                | Yes      | 1 to MAX\_RESOLUTION | Total number of frames to generate for the video sequence (default: 77, step: 4)                                                                                                                                                   |
| `video_latent`         | LATENT             | Yes      | -                    | Initial video latent representation that serves as the starting point for extension. The width, height, batch size, and frame offset are derived from this latent.                                                                 |
| `audio_encoder_output` | AUDIOENCODEROUTPUT | No       | -                    | Optional audio embeddings that can influence video generation based on sound characteristics. When provided, the audio is interpolated and used to create an audio embedding bucket that is added to the conditioning.             |
| `ref_image`            | IMAGE              | No       | -                    | Optional reference image that provides visual guidance for the video generation. The image is upscaled to match the target dimensions and encoded into a latent, which is then added to both positive and negative conditioning.   |
| `control_video`        | IMAGE              | No       | -                    | Optional control video that can guide the motion and style of the generated video. The video is upscaled, encoded, and added to both positive and negative conditioning. The control video is truncated to the specified `length`. |

## Outputs

| Output Name | Data Type    | Description                                                                                                                                                                      |
| ----------- | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `positive`  | CONDITIONING | Processed positive conditioning with video context applied, including audio embeddings, reference latents, reference motion, and control video if provided                       |
| `negative`  | CONDITIONING | Processed negative conditioning with video context applied, including audio embeddings (zeroed out), reference latents, reference motion, and control video if provided          |
| `latent`    | LATENT       | Generated video latent representation containing the extended video sequence, initialized as zeros with dimensions derived from the input `video_latent` and the target `length` |

***

**Source fingerprint (SHA-256):** `73e5aa3dd8085c7c0ed58f5cdafe71db04c20fcc521a965aeb8bbc3364c79031`


# WanTrackToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanTrackToVideo

Complete documentation for the WanTrackToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanTrackToVideo/en.md)

The WanTrackToVideo node converts motion tracking data into video sequences by processing track points and generating corresponding video frames. It takes tracking coordinates as input and produces video conditioning and latent representations that can be used for video generation. When no tracks are provided, it falls back to standard image-to-video conversion.

## Inputs

| Parameter            | Data Type        | Required | Range                 | Description                                                           |
| -------------------- | ---------------- | -------- | --------------------- | --------------------------------------------------------------------- |
| `positive`           | CONDITIONING     | Yes      | -                     | Positive conditioning for video generation                            |
| `negative`           | CONDITIONING     | Yes      | -                     | Negative conditioning for video generation                            |
| `vae`                | VAE              | Yes      | -                     | VAE model for encoding and decoding                                   |
| `tracks`             | STRING           | Yes      | -                     | JSON-formatted tracking data as a multiline string (default: "\[]")   |
| `width`              | INT              | Yes      | 16 to MAX\_RESOLUTION | Output video width in pixels (default: 832, step: 16)                 |
| `height`             | INT              | Yes      | 16 to MAX\_RESOLUTION | Output video height in pixels (default: 480, step: 16)                |
| `length`             | INT              | Yes      | 1 to MAX\_RESOLUTION  | Number of frames in the output video (default: 81, step: 4)           |
| `batch_size`         | INT              | Yes      | 1 to 4096             | Number of videos to generate simultaneously (default: 1)              |
| `temperature`        | FLOAT            | Yes      | 1.0 to 1000.0         | Temperature parameter for motion patching (default: 220.0, step: 0.1) |
| `topk`               | INT              | Yes      | 1 to 10               | Top-k value for motion patching (default: 2)                          |
| `start_image`        | IMAGE            | No       | -                     | Starting image for video generation                                   |
| `clip_vision_output` | CLIPVISIONOUTPUT | No       | -                     | CLIP vision output for additional conditioning                        |

**Note:** When `tracks` contains valid tracking data, the node processes motion tracks to generate video. When `tracks` is empty, it switches to standard image-to-video mode. If `start_image` is provided, it initializes the first frame of the video sequence.

## Outputs

| Output Name | Data Type    | Description                                                 |
| ----------- | ------------ | ----------------------------------------------------------- |
| `positive`  | CONDITIONING | Positive conditioning with motion track information applied |
| `negative`  | CONDITIONING | Negative conditioning with motion track information applied |
| `latent`    | LATENT       | Generated video latent representation                       |

***

**Source fingerprint (SHA-256):** `b4855ec033d14139e8071a78b7831694282faaf0399f797341d3a9e9b926100d`


# WanVaceToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanVaceToVideo

Complete documentation for the WanVaceToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanVaceToVideo/en.md)

The WanVaceToVideo node processes video conditioning data for video generation models. It takes positive and negative conditioning inputs along with video control data and prepares latent representations for video generation. The node handles video upscaling, masking, and VAE encoding to create the appropriate conditioning structure for video models.

## Inputs

| Parameter         | Data Type    | Required | Range                 | Description                                                                                                              |
| ----------------- | ------------ | -------- | --------------------- | ------------------------------------------------------------------------------------------------------------------------ |
| `positive`        | CONDITIONING | Yes      | -                     | Positive conditioning input for guiding the generation                                                                   |
| `negative`        | CONDITIONING | Yes      | -                     | Negative conditioning input for guiding the generation                                                                   |
| `vae`             | VAE          | Yes      | -                     | VAE model used for encoding images and video frames                                                                      |
| `width`           | INT          | Yes      | 16 to MAX\_RESOLUTION | Output video width in pixels (default: 832, step: 16)                                                                    |
| `height`          | INT          | Yes      | 16 to MAX\_RESOLUTION | Output video height in pixels (default: 480, step: 16)                                                                   |
| `length`          | INT          | Yes      | 1 to MAX\_RESOLUTION  | Number of frames in the video (default: 81, step: 4)                                                                     |
| `batch_size`      | INT          | Yes      | 1 to 4096             | Number of videos to generate simultaneously (default: 1)                                                                 |
| `strength`        | FLOAT        | Yes      | 0.0 to 1000.0         | Control strength for video conditioning (default: 1.0, step: 0.01)                                                       |
| `control_video`   | IMAGE        | No       | -                     | Optional input video for control conditioning. If not provided, a neutral gray video is created automatically.           |
| `control_masks`   | MASK         | No       | -                     | Optional masks for controlling which parts of the video to modify. If not provided, a full white mask is used.           |
| `reference_image` | IMAGE        | No       | -                     | Optional reference image for additional conditioning. When provided, it is encoded and prepended to the latent sequence. |

**Note:** When `control_video` is provided, it will be upscaled to match the specified width and height. If `control_masks` are provided, they must match the dimensions of the control video. The `reference_image` is encoded through the VAE and prepended to the latent sequence when provided. The `length` parameter determines the number of frames, and the latent length is calculated as `((length - 1) // 4) + 1`.

## Outputs

| Output Name   | Data Type    | Description                                                                                                     |
| ------------- | ------------ | --------------------------------------------------------------------------------------------------------------- |
| `positive`    | CONDITIONING | Positive conditioning with video control data (vace\_frames, vace\_mask, vace\_strength) applied                |
| `negative`    | CONDITIONING | Negative conditioning with video control data (vace\_frames, vace\_mask, vace\_strength) applied                |
| `latent`      | LATENT       | Empty latent tensor ready for video generation with shape \[batch\_size, 16, latent\_length, height/8, width/8] |
| `trim_latent` | INT          | Number of latent frames to trim when reference image is used (0 if no reference image is provided)              |

***

**Source fingerprint (SHA-256):** `e31638510efa11e35f297becb4a9f070fdb84d34878868aaf3525e589e5abb0b`


# WebcamCapture - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WebcamCapture

Complete documentation for the WebcamCapture node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WebcamCapture/en.md)

The WebcamCapture node captures images from a webcam device and converts them into a format that can be used within ComfyUI workflows. It inherits from the LoadImage node and provides options to control the capture dimensions and timing. When enabled, the node can capture new images each time the workflow queue is processed.

## Inputs

| Parameter          | Data Type | Required | Range                | Description                                                                                  |
| ------------------ | --------- | -------- | -------------------- | -------------------------------------------------------------------------------------------- |
| `image`            | WEBCAM    | Yes      | -                    | The webcam input source to capture images from                                               |
| `width`            | INT       | Yes      | 0 to MAX\_RESOLUTION | The desired width for the captured image (default: 0, uses webcam's native resolution)       |
| `height`           | INT       | Yes      | 0 to MAX\_RESOLUTION | The desired height for the captured image (default: 0, uses webcam's native resolution)      |
| `capture_on_queue` | BOOLEAN   | Yes      | -                    | When enabled, captures a new image each time the workflow queue is processed (default: True) |

**Note:** When both `width` and `height` are set to 0, the node uses the webcam's native resolution. Setting either dimension to a non-zero value will resize the captured image accordingly.

## Outputs

| Output Name | Data Type | Description                                                   |
| ----------- | --------- | ------------------------------------------------------------- |
| `IMAGE`     | IMAGE     | The captured webcam image converted to ComfyUI's image format |

***

**Source fingerprint (SHA-256):** `551368150fc293309f917eabaa066f223b1fa1a016ffd3643b57b80c83f812cc`


# TrimVideoLatent Node
Source: https://docs.comfy.org/built-in-nodes/latent/video/trim-video-latent

Trim video frames in latent space

<img alt="ComfyUI TrimVideoLatent Node" />

The TrimVideoLatent node is used to trim video frames in latent space (LATENT). It is commonly used when processing video latent sequences to remove unwanted frames from the beginning, achieving "forward trimming" of the video.

Basic usage: Input the video latent data to be trimmed into samples, and set trim\_amount to the number of frames to trim. The node will trim the specified number of frames from the beginning of the video and output the remaining latent sequence.
Typical scenarios: Used in video generation, video editing and other scenarios to remove unwanted leading frames, or to work with other nodes to achieve video segment splicing and processing.

## Parameters

### Input Parameters

| Parameter    | Type   | Required | Default | Description                           |
| ------------ | ------ | -------- | ------- | ------------------------------------- |
| samples      | LATENT | Yes      | None    | Input latent video data               |
| trim\_amount | INT    | Yes      | 0       | Number of frames to trim (from start) |

### Output Parameters

| Parameter | Type   | Description               |
| --------- | ------ | ------------------------- |
| samples   | LATENT | Trimmed video latent data |

## Usage Example

<Card title="Wan2.1 VACE Video Generation Workflow Example" icon="book" href="/tutorials/video/wan/vace">
  Wan2.1 VACE Video Generation Workflow Example
</Card>

### Source Code

```python theme={null}
class TrimVideoLatent:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": { "samples": ("LATENT",),
                              "trim_amount": ("INT", {"default": 0, "min": 0, "max": 99999}),
                             }}

    RETURN_TYPES = ("LATENT",)
    FUNCTION = "op"

    CATEGORY = "latent/video"

    EXPERIMENTAL = True

    def op(self, samples, trim_amount):
        samples_out = samples.copy()

        s1 = samples["samples"]
        samples_out["samples"] = s1[:, :, trim_amount:]
        return (samples_out,)

```


# APG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/APG

Complete documentation for the APG node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/APG/en.md)

The APG (Adaptive Projected Guidance) node modifies the sampling process by adjusting how guidance is applied during diffusion. It separates the guidance vector into parallel and orthogonal components relative to the conditional output, allowing for more controlled image generation. The node provides parameters to scale the guidance, normalize its magnitude, and apply momentum for smoother transitions between diffusion steps.

## Inputs

| Parameter        | Data Type | Required | Range         | Description                                                                                                |
| ---------------- | --------- | -------- | ------------- | ---------------------------------------------------------------------------------------------------------- |
| `model`          | MODEL     | Yes      | -             | The diffusion model to apply adaptive projected guidance to                                                |
| `eta`            | FLOAT     | Yes      | -10.0 to 10.0 | Controls the scale of the parallel guidance vector. Default CFG behavior at a setting of 1 (default: 1.0). |
| `norm_threshold` | FLOAT     | Yes      | 0.0 to 50.0   | Normalize guidance vector to this value, normalization disabled at a setting of 0 (default: 5.0).          |
| `momentum`       | FLOAT     | Yes      | -5.0 to 1.0   | Controls a running average of guidance during diffusion, disabled at a setting of 0 (default: 0.0).        |

## Outputs

| Output Name | Data Type | Description                                                                                 |
| ----------- | --------- | ------------------------------------------------------------------------------------------- |
| `model`     | MODEL     | Returns the modified model with adaptive projected guidance applied to its sampling process |

***

**Source fingerprint (SHA-256):** `89e2486bf08f750f82608db93c389f0b25ce0be766f62faa8704d19bd7e41654`


# AudioEncoderLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AudioEncoderLoader

Complete documentation for the AudioEncoderLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AudioEncoderLoader/en.md)

The AudioEncoderLoader node loads an audio encoder model from a file in your audio encoders folder. It takes the filename of an audio encoder model as input and returns the loaded model, which can then be used for audio processing tasks in your workflow.

## Inputs

| Parameter            | Data Type | Required | Range                                                               | Description                                    |
| -------------------- | --------- | -------- | ------------------------------------------------------------------- | ---------------------------------------------- |
| `audio_encoder_name` | STRING    | Yes      | List of available audio encoder files in the audio\_encoders folder | Selects which audio encoder model file to load |

## Outputs

| Output Name     | Data Type      | Description                                                                 |
| --------------- | -------------- | --------------------------------------------------------------------------- |
| `audio_encoder` | AUDIO\_ENCODER | The loaded audio encoder model, ready for use in audio processing workflows |

***

**Source fingerprint (SHA-256):** `66982618292df3881546883ff9efddbb8f8a2eae9aab45507ce0f96719fe6ee0`


# BatchLatentsNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BatchLatentsNode

Complete documentation for the BatchLatentsNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BatchLatentsNode/en.md)

The Batch Latents node combines multiple latent inputs into a single batch. It takes a variable number of latent samples and merges them along the batch dimension, allowing them to be processed together in subsequent nodes. This is useful for generating or processing multiple images in a single operation.

## Inputs

| Parameter | Data Type | Required | Range          | Description                                                                                                                                                                                         |
| --------- | --------- | -------- | -------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `latents` | LATENT    | Yes      | 1 to 50 inputs | A set of latent samples to be combined into a single batch. You must provide at least one latent, and you can add up to 50. The node automatically creates input slots as you connect more latents. |

**Note:** You must provide at least one latent input for the node to function. The node will automatically create input slots as you connect more latents, up to a maximum of 50.

## Outputs

| Output Name | Data Type | Description                                                                      |
| ----------- | --------- | -------------------------------------------------------------------------------- |
| `output`    | LATENT    | A single latent output containing all the input latents combined into one batch. |

***

**Source fingerprint (SHA-256):** `66b2a315c1ce3842e0ee014edd576e87e959591e6d54576c93cba2116b599736`


# CheckpointLoaderSimple - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CheckpointLoaderSimple

Complete documentation for the CheckpointLoaderSimple node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CheckpointLoaderSimple/en.md)

## Overview

Loads a diffusion model checkpoint file and decomposes it into three core components: the main model used for denoising latents, the CLIP text encoder, and the VAE image encoder/decoder. This node automatically detects all model files in the `ComfyUI/models/checkpoints` folder and any additional paths configured in your `extra_model_paths.yaml` file.

## Inputs

| Parameter   | Data Type | Required | Range                                     | Description                                                                                                                                            |
| ----------- | --------- | -------- | ----------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `ckpt_name` | STRING    | Yes      | All model files in the checkpoints folder | The name of the checkpoint (model) to load. Select the checkpoint model file name, which determines the AI model used for subsequent image generation. |

**Note:** If new model files are added while ComfyUI is running, you need to refresh the browser (Ctrl+R) to see the new files in the dropdown list.

## Outputs

| Output Name | Data Type | Description                                                                                                          |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------------------- |
| `MODEL`     | MODEL     | The model used for denoising latents. This is the core diffusion model used for image generation.                    |
| `CLIP`      | CLIP      | The CLIP model used for encoding text prompts, converting text descriptions into information that AI can understand. |
| `VAE`       | VAE       | The VAE model used for encoding and decoding images to and from latent space.                                        |

***

**Source fingerprint (SHA-256):** `2fd8866ae659f8080f46c16d3a9864fa563d2090815d897ea2f42ba8d66d9b39`


# ChromaRadianceOptions - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ChromaRadianceOptions

Complete documentation for the ChromaRadianceOptions node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ChromaRadianceOptions/en.md)

The ChromaRadianceOptions node allows you to configure advanced settings for the Chroma Radiance model. It wraps an existing model and applies specific options during the denoising process based on sigma values, enabling fine-tuned control over NeRF tile size and other radiance-related parameters.

## Inputs

| Parameter          | Data Type | Required | Range        | Description                                                                                                                                         |
| ------------------ | --------- | -------- | ------------ | --------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`            | MODEL     | Yes      | -            | The model to apply Chroma Radiance options to                                                                                                       |
| `preserve_wrapper` | BOOLEAN   | No       | -            | When enabled, will delegate to an existing model function wrapper if it exists. Generally should be left enabled. (default: True)                   |
| `start_sigma`      | FLOAT     | No       | 0.0 to 1.0   | First sigma that these options will be in effect. (default: 1.0)                                                                                    |
| `end_sigma`        | FLOAT     | No       | 0.0 to 1.0   | Last sigma that these options will be in effect. (default: 0.0)                                                                                     |
| `nerf_tile_size`   | INT       | No       | -1 and above | Allows overriding the default NeRF tile size. -1 means use the default (32). 0 means use non-tiling mode (may require a lot of VRAM). (default: -1) |

**Note:** The Chroma Radiance options only take effect when the current sigma value falls between `end_sigma` and `start_sigma` (inclusive). The `nerf_tile_size` parameter is only applied when set to 0 or higher values.

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `model`     | MODEL     | The modified model with Chroma Radiance options applied |

***

**Source fingerprint (SHA-256):** `34e17791e3675c59b4a15b007e853eedcfa0cbbb975fb2f5e71d1115eb2b8781`


# CLIPVisionLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClipVisionLoader

Complete documentation for the CLIPVisionLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node automatically detects models located in the `ComfyUI/models/clip_vision` folder, as well as any additional model paths configured in the `extra_model_paths.yaml` file. If you add models after starting ComfyUI, please **refresh the ComfyUI interface** to ensure the latest model files are listed.

## Inputs

| Field       | Data Type      | Description                                                                 |
| ----------- | -------------- | --------------------------------------------------------------------------- |
| `clip_name` | COMBO\[STRING] | Lists all supported model files in the `ComfyUI/models/clip_vision` folder. |

## Outputs

| Field         | Data Type    | Description                                                                        |
| ------------- | ------------ | ---------------------------------------------------------------------------------- |
| `clip_vision` | CLIP\_VISION | Loaded CLIP Vision model, ready for encoding images or other vision-related tasks. |


# ContextWindowsManual - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ContextWindowsManual

Complete documentation for the ContextWindowsManual node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ContextWindowsManual/en.md)

The Context Windows (Manual) node allows you to manually configure context windows for models during sampling. It creates overlapping context segments with specified length, overlap, and scheduling patterns to process data in manageable chunks while maintaining continuity between segments. This node provides advanced options for controlling how context windows are applied, including noise shuffling, conditioning retention, and causal window fixes.

## Inputs

| Parameter                | Data Type | Required | Range                                                                          | Description                                                                                                                                                                   |
| ------------------------ | --------- | -------- | ------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`                  | MODEL     | Yes      | -                                                                              | The model to apply context windows to during sampling.                                                                                                                        |
| `context_length`         | INT       | No       | 1+                                                                             | The length of the context window (default: 16).                                                                                                                               |
| `context_overlap`        | INT       | No       | 0+                                                                             | The overlap of the context window (default: 4).                                                                                                                               |
| `context_schedule`       | COMBO     | No       | `STATIC_STANDARD`<br />`UNIFORM_STANDARD`<br />`UNIFORM_LOOPED`<br />`BATCHED` | The stride of the context window.                                                                                                                                             |
| `context_stride`         | INT       | No       | 1+                                                                             | The stride of the context window; only applicable to uniform schedules (default: 1).                                                                                          |
| `closed_loop`            | BOOLEAN   | No       | -                                                                              | Whether to close the context window loop; only applicable to looped schedules (default: False).                                                                               |
| `fuse_method`            | COMBO     | No       | `PYRAMID`<br />`LIST_STATIC`                                                   | The method to use to fuse the context windows (default: PYRAMID).                                                                                                             |
| `dim`                    | INT       | No       | 0-5                                                                            | The dimension to apply the context windows to (default: 0).                                                                                                                   |
| `freenoise`              | BOOLEAN   | No       | -                                                                              | Whether to apply FreeNoise noise shuffling, improves window blending (default: False).                                                                                        |
| `cond_retain_index_list` | STRING    | No       | -                                                                              | List of latent indices to retain in the conditioning tensors for each window, for example setting this to '0' will use the initial start image for each window (default: ""). |
| `split_conds_to_windows` | BOOLEAN   | No       | -                                                                              | Whether to split multiple conditionings (created by ConditionCombine) to each window based on region index (default: False).                                                  |
| `causal_window_fix`      | BOOLEAN   | No       | -                                                                              | Whether to add a causal fix frame to non-0-indexed context windows (default: True).                                                                                           |

**Parameter Constraints:**

* `context_stride` is only used when uniform schedules are selected
* `closed_loop` is only applicable to looped schedules
* `dim` must be between 0 and 5 inclusive
* `cond_retain_index_list` expects a comma-separated list of integer indices as a string (e.g., "0,1,2")

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `model`     | MODEL     | The model with context windows applied during sampling. |

***

**Source fingerprint (SHA-256):** `1351789e54e6b4013331014a49b98c6f8b79692ddabed7a64eeb7463cda03cc5`


# DiffControlNetLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DiffControlNetLoader

Complete documentation for the DiffControlNetLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node will detect models located in the `ComfyUI/models/controlnet` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The DiffControlNetLoader node is designed for loading differential control networks, which are specialized models that can modify the behavior of another model based on control net specifications. This node allows for the dynamic adjustment of model behaviors by applying differential control nets, facilitating the creation of customized model outputs.

## Inputs

| Field              | Comfy dtype     | Description                                                                                                               |
| ------------------ | --------------- | ------------------------------------------------------------------------------------------------------------------------- |
| `model`            | `MODEL`         | The base model to which the differential control net will be applied, allowing for customization of the model's behavior. |
| `control_net_name` | `COMBO[STRING]` | Identifies the specific differential control net to be loaded and applied to the base model for modifying its behavior.   |

## Outputs

| Field         | Comfy dtype   | Description                                                                                                           |
| ------------- | ------------- | --------------------------------------------------------------------------------------------------------------------- |
| `control_net` | `CONTROL_NET` | A differential control net that has been loaded and is ready to be applied to a base model for behavior modification. |


# EmptyARVideoLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyARVideoLatent

Complete documentation for the EmptyARVideoLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyARVideoLatent/en.md)

## Overview

The EmptyARVideoLatent node creates a blank, empty latent representation for video generation. It is used to initialize a video generation process by providing a tensor of zeros with the specified dimensions, aspect ratio, and length.

## Inputs

| Parameter    | Data Type | Required | Range                 | Description                                                     |
| ------------ | --------- | -------- | --------------------- | --------------------------------------------------------------- |
| `width`      | INT       | Yes      | 16 to 8192 (step: 16) | The width of the video frames in pixels (default: 832)          |
| `height`     | INT       | Yes      | 16 to 8192 (step: 16) | The height of the video frames in pixels (default: 480)         |
| `length`     | INT       | Yes      | 1 to 1024 (step: 4)   | The number of frames in the video (default: 81)                 |
| `batch_size` | INT       | Yes      | 1 to 64               | The number of videos to generate in a single batch (default: 1) |

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                                                                       |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `LATENT`    | LATENT    | A latent tensor filled with zeros, representing an empty video latent space with the specified dimensions, length, and batch size. The tensor shape is \[batch\_size, 16, lat\_t, height/8, width/8], where lat\_t is calculated from the length. |

***

**Source fingerprint (SHA-256):** `b36c40d768e846bc67ed6a7bfb4145c6e2a4ca55824296250a88f52d5ae305cf`


# EmptyAceStep1.5LatentAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyAceStep1.5LatentAudio

Complete documentation for the EmptyAceStep1.5LatentAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyAceStep1.5LatentAudio/en.md)

The Empty Ace Step 1.5 Latent Audio node creates an empty latent tensor designed for audio processing. It generates a silent audio latent of a specified duration and batch size, which can be used as a starting point for audio generation workflows in ComfyUI. The node calculates the latent length based on the input seconds and a fixed sample rate.

## Inputs

| Parameter    | Data Type | Required | Range        | Description                                                         |
| ------------ | --------- | -------- | ------------ | ------------------------------------------------------------------- |
| `seconds`    | FLOAT     | Yes      | 1.0 - 1000.0 | The duration of the audio to generate, in seconds (default: 120.0). |
| `batch_size` | INT       | Yes      | 1 - 4096     | The number of latent images in the batch (default: 1).              |

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                                           |
| ----------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `LATENT`    | LATENT    | An empty latent tensor representing silent audio, with a type identifier of "audio". The output also includes a `downscale_ratio_temporal` value of 1764, which is used for temporal downscaling in audio processing. |

***

**Source fingerprint (SHA-256):** `dc87da02daa14d19afb0a1b421ee87fdcaf53d5a1e5f5175bfcc8e9fbcd7fa48`


# EmptyAceStepLatentAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyAceStepLatentAudio

Complete documentation for the EmptyAceStepLatentAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyAceStepLatentAudio/en.md)

The EmptyAceStepLatentAudio node creates empty latent audio samples of a specified duration. It generates a batch of silent audio latents filled with zeros, where the length is calculated based on the input seconds and audio processing parameters. This node is useful for initializing audio processing workflows that require latent representations.

## Inputs

| Parameter    | Data Type | Required | Range        | Description                                           |
| ------------ | --------- | -------- | ------------ | ----------------------------------------------------- |
| `seconds`    | FLOAT     | Yes      | 1.0 - 1000.0 | The duration of the audio in seconds (default: 120.0) |
| `batch_size` | INT       | Yes      | 1 - 4096     | The number of latent images in the batch (default: 1) |

## Outputs

| Output Name | Data Type | Description                                                                                                              |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------ |
| `output`    | LATENT    | Returns empty latent audio samples with zeros. The output contains a `samples` tensor and a `type` field set to "audio". |

***

**Source fingerprint (SHA-256):** `be20317ed22bf89eeb35a31de0177842f366105da8653e6d7af71241a84967a0`


# EmptyChromaRadianceLatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyChromaRadianceLatentImage

Complete documentation for the EmptyChromaRadianceLatentImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyChromaRadianceLatentImage/en.md)

The EmptyChromaRadianceLatentImage node creates a blank latent image with specified dimensions for use in chroma radiance workflows. It generates a tensor filled with zeros that serves as a starting point for latent space operations. The node allows you to define the width, height, and batch size of the empty latent image.

## Inputs

| Parameter    | Data Type | Required | Range                 | Description                                                                       |
| ------------ | --------- | -------- | --------------------- | --------------------------------------------------------------------------------- |
| `width`      | INT       | Yes      | 16 to MAX\_RESOLUTION | The width of the latent image in pixels (default: 1024, must be divisible by 16)  |
| `height`     | INT       | Yes      | 16 to MAX\_RESOLUTION | The height of the latent image in pixels (default: 1024, must be divisible by 16) |
| `batch_size` | INT       | No       | 1 to 4096             | The number of latent images to generate in a batch (default: 1)                   |

## Outputs

| Output Name | Data Type | Description                                                       |
| ----------- | --------- | ----------------------------------------------------------------- |
| `samples`   | LATENT    | The generated empty latent image tensor with specified dimensions |

***

**Source fingerprint (SHA-256):** `15f4d3f9803aa3242b07ff4f49946e1f1f409512af07cffe5495e9ce09c587dd`


# EmptyCosmosLatentVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyCosmosLatentVideo

Complete documentation for the EmptyCosmosLatentVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyCosmosLatentVideo/en.md)

The EmptyCosmosLatentVideo node creates an empty latent video tensor with specified dimensions. It generates a zero-filled latent representation that can be used as a starting point for video generation workflows, with configurable width, height, length, and batch size parameters.

## Inputs

| Parameter    | Data Type | Required | Range                 | Description                                                                      |
| ------------ | --------- | -------- | --------------------- | -------------------------------------------------------------------------------- |
| `width`      | INT       | Yes      | 16 to MAX\_RESOLUTION | The width of the latent video in pixels (default: 1280, must be divisible by 16) |
| `height`     | INT       | Yes      | 16 to MAX\_RESOLUTION | The height of the latent video in pixels (default: 704, must be divisible by 16) |
| `length`     | INT       | Yes      | 1 to MAX\_RESOLUTION  | The number of frames in the latent video (default: 121, must be divisible by 8)  |
| `batch_size` | INT       | No       | 1 to 4096             | The number of latent videos to generate in a batch (default: 1)                  |

## Outputs

| Output Name | Data Type | Description                                              |
| ----------- | --------- | -------------------------------------------------------- |
| `samples`   | LATENT    | The generated empty latent video tensor with zero values |

***

**Source fingerprint (SHA-256):** `ed7404f31b4b9fb2c098579f8e96e55befb3c8ed045d4175385d01a7b42035e2`


# EmptyFlux2LatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyFlux2LatentImage

Complete documentation for the EmptyFlux2LatentImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyFlux2LatentImage/en.md)

The EmptyFlux2LatentImage node creates a blank, empty latent representation. It generates a tensor filled with zeros, which serves as a starting point for the Flux model's denoising process. The dimensions of the latent are determined by the input width and height, scaled down by a factor of 16.

## Inputs

| Parameter    | Data Type | Required | Range      | Description                                                                                                               |
| ------------ | --------- | -------- | ---------- | ------------------------------------------------------------------------------------------------------------------------- |
| `width`      | INT       | Yes      | 16 to 8192 | The width of the final image to generate. The latent width will be this value divided by 16. The default value is 1024.   |
| `height`     | INT       | Yes      | 16 to 8192 | The height of the final image to generate. The latent height will be this value divided by 16. The default value is 1024. |
| `batch_size` | INT       | No       | 1 to 4096  | The number of latent samples to generate in a single batch. The default value is 1.                                       |

**Note:** The `width` and `height` inputs must be divisible by 16, as the node internally divides them by this factor to create the latent dimensions.

## Outputs

| Output Name | Data Type | Description                                                                                     |
| ----------- | --------- | ----------------------------------------------------------------------------------------------- |
| `samples`   | LATENT    | A latent tensor filled with zeros. The shape is `[batch_size, 128, height // 16, width // 16]`. |

***

**Source fingerprint (SHA-256):** `337c687b6b3ebb8854618911ab966118940de369ed84bc9c4ed769289b397588`


# EmptyHiDreamO1LatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyHiDreamO1LatentImage

Complete documentation for the EmptyHiDreamO1LatentImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyHiDreamO1LatentImage/en.md)

## Overview

This node creates an empty latent image in pixel space, specifically designed for the HiDream-O1-Image model. It generates a blank tensor of zeros that serves as the starting point for image generation, with dimensions defined by the width, height, and batch size inputs.

## Inputs

| Parameter    | Data Type | Required | Range                 | Description                                                                                                                                                                |
| ------------ | --------- | -------- | --------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `width`      | INT       | Yes      | 64 to 4096 (step: 32) | The width of the latent image in pixels (default: 2048). The model was trained at \~4 megapixels; lower resolutions go off-distribution and quality regresses noticeably.  |
| `height`     | INT       | Yes      | 64 to 4096 (step: 32) | The height of the latent image in pixels (default: 2048). The model was trained at \~4 megapixels; lower resolutions go off-distribution and quality regresses noticeably. |
| `batch_size` | INT       | No       | 1 to 64               | The number of latent images to generate in a single batch (default: 1).                                                                                                    |

## Outputs

| Output Name | Data Type | Description                                                                                                 |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------- |
| `samples`   | LATENT    | A tensor filled with zeros representing the empty latent image, with shape (batch\_size, 3, height, width). |

## Notes

* The HiDream-O1-Image model was trained at approximately 4 megapixels. Using significantly lower resolutions may result in reduced image quality.
* Trained resolutions include: 2048x2048, 2304x1728, 1728x2304, 2560x1440, 1440x2560, 2496x1664, 1664x2496, 3104x1312, 1312x3104, 2304x1792, 1792x2304.

***

**Source fingerprint (SHA-256):** `fca32bbeddf120b4a7f9a9b88814f5345db133b35252c4d86079397be350c15e`


# EmptyHunyuanImageLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyHunyuanImageLatent

Complete documentation for the EmptyHunyuanImageLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyHunyuanImageLatent/en.md)

The EmptyHunyuanImageLatent node creates an empty latent tensor with specific dimensions for use with Hunyuan image generation models. It generates a blank starting point that can be processed through subsequent nodes in the workflow. The node allows you to specify the width, height, and batch size of the latent space.

## Inputs

| Parameter    | Data Type | Required | Range                 | Description                                                                  |
| ------------ | --------- | -------- | --------------------- | ---------------------------------------------------------------------------- |
| `width`      | INT       | Yes      | 64 to MAX\_RESOLUTION | The width of the generated latent image in pixels (default: 2048, step: 32)  |
| `height`     | INT       | Yes      | 64 to MAX\_RESOLUTION | The height of the generated latent image in pixels (default: 2048, step: 32) |
| `batch_size` | INT       | Yes      | 1 to 4096             | The number of latent samples to generate in a batch (default: 1)             |

## Outputs

| Output Name | Data Type | Description                                                                       |
| ----------- | --------- | --------------------------------------------------------------------------------- |
| `LATENT`    | LATENT    | An empty latent tensor with the specified dimensions for Hunyuan image processing |

***

**Source fingerprint (SHA-256):** `990878294736fcc89f4435127a81e9eec390d58640694ab35789ed7f578692a1`


# EmptyHunyuanLatentVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyHunyuanLatentVideo

Complete documentation for the EmptyHunyuanLatentVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `EmptyHunyuanLatentVideo` node is similar to the `EmptyLatentImage` node. You can consider it as a blank canvas for video generation, where width, height, and length define the properties of the canvas, and the batch size determines the number of canvases to create. This node creates empty canvases ready for subsequent video generation tasks.

## Inputs

| Parameter    | Comfy Type | Description                                                                          |
| ------------ | ---------- | ------------------------------------------------------------------------------------ |
| `width`      | `INT`      | Video width, default 848, minimum 16, maximum `nodes.MAX_RESOLUTION`, step size 16.  |
| `height`     | `INT`      | Video height, default 480, minimum 16, maximum `nodes.MAX_RESOLUTION`, step size 16. |
| `length`     | `INT`      | Video length, default 25, minimum 1, maximum `nodes.MAX_RESOLUTION`, step size 4.    |
| `batch_size` | `INT`      | Batch size, default 1, minimum 1, maximum 4096.                                      |

## Outputs

| Parameter | Comfy Type | Description                                                                                        |
| --------- | ---------- | -------------------------------------------------------------------------------------------------- |
| `samples` | `LATENT`   | Generated latent video samples containing zero tensors, ready for processing and generation tasks. |


# EmptyHunyuanVideo15Latent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyHunyuanVideo15Latent

Complete documentation for the EmptyHunyuanVideo15Latent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyHunyuanVideo15Latent/en.md)

This node creates an empty latent tensor specifically formatted for use with the HunyuanVideo 1.5 model. It generates a blank starting point for video generation by allocating a tensor of zeros with the correct channel count and spatial dimensions for the model's latent space.

## Inputs

| Parameter    | Data Type | Required | Range | Description                                                      |
| ------------ | --------- | -------- | ----- | ---------------------------------------------------------------- |
| `width`      | INT       | Yes      | -     | The width of the video frame in pixels.                          |
| `height`     | INT       | Yes      | -     | The height of the video frame in pixels.                         |
| `length`     | INT       | Yes      | -     | The number of frames in the video sequence.                      |
| `batch_size` | INT       | No       | -     | The number of video samples to generate in a batch (default: 1). |

**Note:** The spatial dimensions of the generated latent tensor are calculated by dividing the input `width` and `height` by 16. The temporal dimension (frames) is calculated as `((length - 1) // 4) + 1`.

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                                                    |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `samples`   | LATENT    | An empty latent tensor with dimensions suitable for the HunyuanVideo 1.5 model. The tensor has a shape of `[batch_size, 32, frames, height//16, width//16]`. The output also includes a `downscale_ratio_spacial` value of 16. |

***

**Source fingerprint (SHA-256):** `6f53c99967149dd7c92e4d20a4ee80bd23d856ebab0a14a8201c55db847a525e`


# EmptyLTXVLatentVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyLTXVLatentVideo

Complete documentation for the EmptyLTXVLatentVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyLTXVLatentVideo/en.md)

The EmptyLTXVLatentVideo node creates an empty latent tensor for video processing. It generates a blank starting point with specified dimensions that can be used as input for video generation workflows. The node produces a zero-filled latent representation with the configured width, height, length, and batch size.

## Inputs

| Parameter    | Data Type | Required | Range                 | Description                                                     |
| ------------ | --------- | -------- | --------------------- | --------------------------------------------------------------- |
| `width`      | INT       | Yes      | 64 to MAX\_RESOLUTION | The width of the latent video tensor (default: 768, step: 32)   |
| `height`     | INT       | Yes      | 64 to MAX\_RESOLUTION | The height of the latent video tensor (default: 512, step: 32)  |
| `length`     | INT       | Yes      | 1 to MAX\_RESOLUTION  | The number of frames in the latent video (default: 97, step: 8) |
| `batch_size` | INT       | No       | 1 to 4096             | The number of latent videos to generate in a batch (default: 1) |

## Outputs

| Output Name | Data Type | Description                                                                    |
| ----------- | --------- | ------------------------------------------------------------------------------ |
| `samples`   | LATENT    | The generated empty latent tensor with zero values in the specified dimensions |

***

**Source fingerprint (SHA-256):** `177fa1014ba65feab06a6f7bafc72e1cc536d3dc01f5bebddceb9f15f8df99fd`


# EmptyLatentAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyLatentAudio

Complete documentation for the EmptyLatentAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyLatentAudio/en.md)

The EmptyLatentAudio node creates an empty latent tensor for audio processing. It generates a blank audio latent representation with a specified duration and batch size, which can be used as a starting point for audio generation or processing workflows. The node automatically calculates the appropriate latent dimensions based on the audio duration and sample rate.

## Inputs

| Parameter    | Data Type | Required | Range        | Description                                           |
| ------------ | --------- | -------- | ------------ | ----------------------------------------------------- |
| `seconds`    | FLOAT     | Yes      | 1.0 - 1000.0 | The duration of the audio in seconds (default: 47.6)  |
| `batch_size` | INT       | Yes      | 1 - 4096     | The number of latent images in the batch (default: 1) |

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                                                                                                                                                        |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `LATENT`    | LATENT    | Returns an empty latent tensor for audio processing with the specified duration and batch size. The tensor has a shape of \[batch\_size, 64, length], where length is calculated from the audio duration and sample rate. The output also includes metadata indicating the type is "audio" and a temporal downscale ratio of 2048. |

***

**Source fingerprint (SHA-256):** `02d7623358a6cc8200e74ab36f6a83bcfa059abd6ef91e3fd1c3732706926033`


# EmptyLatentHunyuan3Dv2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyLatentHunyuan3Dv2

Complete documentation for the EmptyLatentHunyuan3Dv2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyLatentHunyuan3Dv2/en.md)

The EmptyLatentHunyuan3Dv2 node creates blank latent tensors specifically formatted for Hunyuan3Dv2 3D generation models. It generates empty latent spaces with the correct dimensions and structure required by the Hunyuan3Dv2 architecture, allowing you to start 3D generation workflows from scratch. The node produces latent tensors filled with zeros that serve as the foundation for subsequent 3D generation processes.

## Inputs

| Parameter    | Data Type | Required | Range    | Description                                                   |
| ------------ | --------- | -------- | -------- | ------------------------------------------------------------- |
| `resolution` | INT       | Yes      | 1 - 8192 | The resolution dimension for the latent space (default: 3072) |
| `batch_size` | INT       | Yes      | 1 - 4096 | The number of latent images in the batch (default: 1)         |

## Outputs

| Output Name | Data Type | Description                                                                              |
| ----------- | --------- | ---------------------------------------------------------------------------------------- |
| `LATENT`    | LATENT    | Returns a latent tensor containing empty samples formatted for Hunyuan3Dv2 3D generation |

***

**Source fingerprint (SHA-256):** `39fa531f819e3fe5e835b79d4140956c30d26cf9627d639359df65a5d3c01c2b`


# EmptyLatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyLatentImage

Complete documentation for the EmptyLatentImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `EmptyLatentImage` node is designed to generate a blank latent space representation with specified dimensions and batch size. This node serves as a foundational step in generating or manipulating images in latent space, providing a starting point for further image synthesis or modification processes.

## Inputs

| Parameter    | Data Type | Description                                                                                                                                                                              |
| ------------ | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `width`      | `INT`     | Specifies the width of the latent image to be generated. This parameter directly influences the spatial dimensions of the resulting latent representation.                               |
| `height`     | `INT`     | Determines the height of the latent image to be generated. This parameter is crucial for defining the spatial dimensions of the latent space representation.                             |
| `batch_size` | `INT`     | Controls the number of latent images to be generated in a single batch. This allows for the generation of multiple latent representations simultaneously, facilitating batch processing. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                         |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The output is a tensor representing a batch of blank latent images, serving as a base for further image generation or manipulation in latent space. |


# EmptyMochiLatentVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyMochiLatentVideo

Complete documentation for the EmptyMochiLatentVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyMochiLatentVideo/en.md)

The EmptyMochiLatentVideo node creates an empty latent video tensor with specified dimensions. It generates a zero-filled latent representation that can be used as a starting point for video generation workflows. The node allows you to define the width, height, length, and batch size for the latent video tensor.

## Inputs

| Parameter    | Data Type | Required | Range                 | Description                                                                                                |
| ------------ | --------- | -------- | --------------------- | ---------------------------------------------------------------------------------------------------------- |
| `width`      | INT       | Yes      | 16 to MAX\_RESOLUTION | The width of the latent video in pixels (default: 848, must be divisible by 16)                            |
| `height`     | INT       | Yes      | 16 to MAX\_RESOLUTION | The height of the latent video in pixels (default: 480, must be divisible by 16)                           |
| `length`     | INT       | Yes      | 7 to MAX\_RESOLUTION  | The number of frames in the latent video (default: 25, must satisfy that `(length - 1)` is divisible by 6) |
| `batch_size` | INT       | No       | 1 to 4096             | The number of latent videos to generate in a batch (default: 1)                                            |

**Note:** The actual latent dimensions are calculated as width/8 and height/8, and the temporal dimension is calculated as `((length - 1) // 6) + 1`. The `length` parameter must satisfy that `(length - 1)` is divisible by 6, meaning valid values are 7, 13, 19, 25, etc.

## Outputs

| Output Name | Data Type | Description                                                                      |
| ----------- | --------- | -------------------------------------------------------------------------------- |
| `samples`   | LATENT    | An empty latent video tensor with the specified dimensions, containing all zeros |

***

**Source fingerprint (SHA-256):** `1e5f70821965a9c8607920554f50ae3b6a0b38643074f669e5b81d81c3e26302`


# EmptyQwenImageLayeredLatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptyQwenImageLayeredLatentImage

Complete documentation for the EmptyQwenImageLayeredLatentImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptyQwenImageLayeredLatentImage/en.md)

The Empty Qwen Image Layered Latent node creates a blank, multi-layered latent representation for use with Qwen image models. It generates a tensor filled with zeros, structured with a specified number of layers, batch size, and spatial dimensions. This empty latent serves as a starting point for subsequent image generation or manipulation workflows.

## Inputs

| Parameter    | Data Type | Required | Range                 | Description                                                                                                                       |
| ------------ | --------- | -------- | --------------------- | --------------------------------------------------------------------------------------------------------------------------------- |
| `width`      | INT       | Yes      | 16 to MAX\_RESOLUTION | The width of the latent image to create. The value must be divisible by 16. (default: 640)                                        |
| `height`     | INT       | Yes      | 16 to MAX\_RESOLUTION | The height of the latent image to create. The value must be divisible by 16. (default: 640)                                       |
| `layers`     | INT       | Yes      | 0 to MAX\_RESOLUTION  | The number of additional layers to add to the latent structure. This defines the depth of the latent representation. (default: 3) |
| `batch_size` | INT       | No       | 1 to 4096             | The number of latent samples to generate in a batch. (default: 1)                                                                 |

**Note:** The `width` and `height` parameters are internally divided by 8 to determine the spatial dimensions of the output latent tensor.

## Outputs

| Output Name | Data Type | Description                                                                                              |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------- |
| `samples`   | LATENT    | A latent tensor filled with zeros. Its shape is `[batch_size, 16, layers + 1, height // 8, width // 8]`. |

***

**Source fingerprint (SHA-256):** `fe97966663c534dd347aa49a908a8026f2c34716631f1d17be97d74eacc3574e`


# EmptySD3LatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/EmptySD3LatentImage

Complete documentation for the EmptySD3LatentImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/EmptySD3LatentImage/en.md)

The EmptySD3LatentImage node creates a blank latent image tensor specifically formatted for Stable Diffusion 3 models. It generates a tensor filled with zeros that has the correct dimensions and structure expected by SD3 pipelines. This is commonly used as a starting point for image generation workflows.

## Inputs

| Parameter    | Data Type | Required | Range                            | Description                                                     |
| ------------ | --------- | -------- | -------------------------------- | --------------------------------------------------------------- |
| `width`      | INT       | Yes      | 16 to MAX\_RESOLUTION (step: 16) | The width of the output latent image in pixels (default: 1024)  |
| `height`     | INT       | Yes      | 16 to MAX\_RESOLUTION (step: 16) | The height of the output latent image in pixels (default: 1024) |
| `batch_size` | INT       | Yes      | 1 to 4096                        | The number of latent images to generate in a batch (default: 1) |

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                              |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `LATENT`    | LATENT    | A latent tensor containing blank samples with SD3-compatible dimensions. The tensor has 16 channels and is spatially downscaled by a factor of 8 compared to the input width and height. |

***

**Source fingerprint (SHA-256):** `7a4b2454807bc905f26b96c0ff98706fa3e248bbf2b3995d5d38ebc3c5663fd6`


# Epsilon Scaling - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Epsilon Scaling

Complete documentation for the Epsilon Scaling node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! \[Edit on GitHub]\([https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui\_embedded\_docs/docs/Epsilon](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Epsilon) Scaling/en.md)

This node implements the Epsilon Scaling method from the research paper "Elucidating the Exposure Bias in Diffusion Models" (arxiv.org/abs/2308.15321v6). It works by scaling the predicted noise during the sampling process to help reduce exposure bias, which can lead to improved quality in the generated images. This implementation uses the "uniform schedule" recommended by the paper for its practicality and effectiveness.

## Inputs

| Parameter        | Data Type | Required | Range     | Description                                                                                                                                               |
| ---------------- | --------- | -------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`          | MODEL     | Yes      | -         | The model to which the epsilon scaling patch will be applied.                                                                                             |
| `scaling_factor` | FLOAT     | No       | 0.5 - 1.5 | The factor by which the predicted noise is scaled. A value greater than 1.0 reduces the noise, while a value less than 1.0 increases it (default: 1.005). |

## Outputs

| Output Name | Data Type | Description                                                                                             |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------- |
| `model`     | MODEL     | A patched version of the input model with the epsilon scaling function applied to its sampling process. |

***

**Source fingerprint (SHA-256):** `245d230ec2db7298493d4fbe58c3d96c15821985da3dc12aaccf64e2bf7922a1`


# FrameInterpolationModelLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FrameInterpolationModelLoader

Complete documentation for the FrameInterpolationModelLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FrameInterpolationModelLoader/en.md)

## Overview

This node loads a frame interpolation model from a file and prepares it for use in the workflow. It automatically detects the model type (FILM or RIFE) and configures the model for optimal performance on your hardware.

## Inputs

| Parameter    | Data Type | Required | Range                                                   | Description                                                                                             |
| ------------ | --------- | -------- | ------------------------------------------------------- | ------------------------------------------------------------------------------------------------------- |
| `model_name` | STRING    | Yes      | List of model files in the `frame_interpolation` folder | Select a frame interpolation model to load. Models must be placed in the 'frame\_interpolation' folder. |

## Outputs

| Output Name                 | Data Type | Description                                                                        |
| --------------------------- | --------- | ---------------------------------------------------------------------------------- |
| `FRAME_INTERPOLATION_MODEL` | MODEL     | The loaded and configured frame interpolation model, ready for use in other nodes. |

***

**Source fingerprint (SHA-256):** `b39f0aee6e02fb4c7e7268289634cf4d061038512e87ca6bd00aede5660d8196`


# FreeU - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FreeU

Complete documentation for the FreeU node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FreeU/en.md)

The FreeU node applies frequency-domain modifications to a model's output blocks to enhance image generation quality. It works by scaling different channel groups and applying Fourier filtering to specific feature maps, allowing for fine-tuned control over the model's behavior during the generation process.

## Inputs

| Parameter | Data Type | Required | Range      | Description                                                                    |
| --------- | --------- | -------- | ---------- | ------------------------------------------------------------------------------ |
| `model`   | MODEL     | Yes      | -          | The model to apply FreeU modifications to                                      |
| `b1`      | FLOAT     | Yes      | 0.0 - 10.0 | Backbone scaling factor for model\_channels × 4 features (default: 1.1)        |
| `b2`      | FLOAT     | Yes      | 0.0 - 10.0 | Backbone scaling factor for model\_channels × 2 features (default: 1.2)        |
| `s1`      | FLOAT     | Yes      | 0.0 - 10.0 | Skip connection scaling factor for model\_channels × 4 features (default: 0.9) |
| `s2`      | FLOAT     | Yes      | 0.0 - 10.0 | Skip connection scaling factor for model\_channels × 2 features (default: 0.2) |

## Outputs

| Output Name | Data Type | Description                                   |
| ----------- | --------- | --------------------------------------------- |
| `model`     | MODEL     | The modified model with FreeU patches applied |

***

**Source fingerprint (SHA-256):** `a0f0b165638aa9e88ea415fc966bdac9bfbc13e9a5dcebc9780b31b63ce91f5c`


# FreeU_V2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FreeU_V2

Complete documentation for the FreeU_V2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FreeU_V2/en.md)

The FreeU\_V2 node enhances image generation quality by applying frequency-based modifications to a diffusion model's U-Net architecture. It uses configurable scaling factors to adjust feature channels in different blocks, improving output without requiring additional training.

## Inputs

| Parameter | Data Type | Required | Range      | Description                                                         |
| --------- | --------- | -------- | ---------- | ------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -          | The diffusion model to apply FreeU enhancement to                   |
| `b1`      | FLOAT     | Yes      | 0.0 - 10.0 | Backbone feature scaling factor for the first block (default: 1.3)  |
| `b2`      | FLOAT     | Yes      | 0.0 - 10.0 | Backbone feature scaling factor for the second block (default: 1.4) |
| `s1`      | FLOAT     | Yes      | 0.0 - 10.0 | Skip feature scaling factor for the first block (default: 0.9)      |
| `s2`      | FLOAT     | Yes      | 0.0 - 10.0 | Skip feature scaling factor for the second block (default: 0.2)     |

## Outputs

| Output Name | Data Type | Description                                                   |
| ----------- | --------- | ------------------------------------------------------------- |
| `model`     | MODEL     | The enhanced diffusion model with FreeU modifications applied |

***

**Source fingerprint (SHA-256):** `adbbf0934f4c17fa736035b1396d26d6a5c847fd19a981ddd42d9624bd90e619`


# GLIGENLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GLIGENLoader

Complete documentation for the GLIGENLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node will detect models located in the `ComfyUI/models/gligen` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The `GLIGENLoader` node is designed for loading GLIGEN models, which are specialized generative models. It facilitates the process of retrieving and initializing these models from specified paths, making them ready for further generative tasks.

## Inputs

| Field         | Comfy dtype     | Description                                                                                                                                      |
| ------------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ |
| `gligen_name` | `COMBO[STRING]` | The name of the GLIGEN model to be loaded, specifying which model file to retrieve and load, crucial for the initialization of the GLIGEN model. |

## Outputs

| Field    | Data Type | Description                                                                                                                          |
| -------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------ |
| `gligen` | `GLIGEN`  | The loaded GLIGEN model, ready for use in generative tasks, representing the fully initialized model loaded from the specified path. |


# HunyuanVideo15LatentUpscaleWithModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HunyuanVideo15LatentUpscaleWithModel

Complete documentation for the HunyuanVideo15LatentUpscaleWithModel node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HunyuanVideo15LatentUpscaleWithModel/en.md)

The Hunyuan Video 15 Latent Upscale With Model node increases the resolution of a latent image representation. It first upscales the latent samples to a specified size using a chosen interpolation method, then refines the upscaled result using a specialized Hunyuan Video 1.5 upscale model to improve quality.

## Inputs

| Parameter        | Data Type              | Required | Range                                                                               | Description                                                                                                                                                                                                                          |
| ---------------- | ---------------------- | -------- | ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `model`          | LATENT\_UPSCALE\_MODEL | Yes      | N/A                                                                                 | The Hunyuan Video 1.5 latent upscale model used to refine the upscaled samples.                                                                                                                                                      |
| `samples`        | LATENT                 | Yes      | N/A                                                                                 | The latent image representation to be upscaled.                                                                                                                                                                                      |
| `upscale_method` | COMBO                  | No       | `"nearest-exact"`<br />`"bilinear"`<br />`"area"`<br />`"bicubic"`<br />`"bislerp"` | The interpolation algorithm used for the initial upscaling step (default: `"bilinear"`).                                                                                                                                             |
| `width`          | INT                    | No       | 0 to 16384                                                                          | The target width for the upscaled latent, in pixels. A value of 0 will calculate the width automatically based on the target height and the original aspect ratio. The final output width will be a multiple of 16 (default: 1280).  |
| `height`         | INT                    | No       | 0 to 16384                                                                          | The target height for the upscaled latent, in pixels. A value of 0 will calculate the height automatically based on the target width and the original aspect ratio. The final output height will be a multiple of 16 (default: 720). |
| `crop`           | COMBO                  | No       | `"disabled"`<br />`"center"`                                                        | Determines how the upscaled latent is cropped to fit the target dimensions.                                                                                                                                                          |

**Note on Dimensions:** If both `width` and `height` are set to 0, the node returns the input `samples` unchanged. If only one dimension is set to 0, the other dimension is calculated to preserve the original aspect ratio. The final dimensions are always adjusted to be at least 64 pixels and are divisible by 16.

## Outputs

| Output Name | Data Type | Description                                                 |
| ----------- | --------- | ----------------------------------------------------------- |
| `LATENT`    | LATENT    | The upscaled and model-refined latent image representation. |

***

**Source fingerprint (SHA-256):** `2d249b1bf8eca3a27952cedfc4001b19efeeaeddb6ce461bdfc9b8bb3f2ada82`


# HyperTile - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HyperTile

Complete documentation for the HyperTile node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HyperTile/en.md)

The HyperTile node applies a tiling technique to the attention mechanism in diffusion models to optimize memory usage during image generation. It divides the latent space into smaller tiles and processes them separately, then reassembles the results. This allows for working with larger image sizes without running out of memory.

## Inputs

| Parameter     | Data Type | Required | Range        | Description                                                                                                                                       |
| ------------- | --------- | -------- | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`       | MODEL     | Yes      | -            | The diffusion model to apply the HyperTile optimization to                                                                                        |
| `tile_size`   | INT       | No       | 1 - 2048     | The target tile size for processing (default: 256). The effective tile size is rounded down to a multiple of 8, with a minimum of 32.             |
| `swap_size`   | INT       | No       | 1 - 128      | Controls how the tiles are rearranged during processing to improve efficiency (default: 2)                                                        |
| `max_depth`   | INT       | No       | 0 - 10       | The maximum depth level (resolution scale) to apply tiling. A value of 0 applies tiling only at the highest resolution (default: 0)               |
| `scale_depth` | BOOLEAN   | No       | True / False | When enabled, the tile size is scaled proportionally at deeper depth levels. This can help maintain quality at lower resolutions (default: False) |

## Outputs

| Output Name | Data Type | Description                                            |
| ----------- | --------- | ------------------------------------------------------ |
| `model`     | MODEL     | The modified model with HyperTile optimization applied |

***

**Source fingerprint (SHA-256):** `ea770eea3c628ffb166c2a15a6f75757cebd99c3fdd6225f041b3ef01a0e73c7`


# HypernetworkLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HypernetworkLoader

Complete documentation for the HypernetworkLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node will detect models located in the `ComfyUI/models/hypernetworks` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The HypernetworkLoader node is designed to enhance or modify the capabilities of a given model by applying a hypernetwork. It loads a specified hypernetwork and applies it to the model, potentially altering its behavior or performance based on the strength parameter. This process allows for dynamic adjustments to the model's architecture or parameters, enabling more flexible and adaptive AI systems.

## Inputs

| Field               | Comfy dtype     | Description                                                                                                                 |
| ------------------- | --------------- | --------------------------------------------------------------------------------------------------------------------------- |
| `model`             | `MODEL`         | The base model to which the hypernetwork will be applied, determining the architecture to be enhanced or modified.          |
| `hypernetwork_name` | `COMBO[STRING]` | The name of the hypernetwork to be loaded and applied to the model, impacting the model's modified behavior or performance. |
| `strength`          | `FLOAT`         | A scalar adjusting the intensity of the hypernetwork's effect on the model, allowing fine-tuning of the alterations.        |

## Outputs

| Field   | Data Type | Description                                                                                                                  |
| ------- | --------- | ---------------------------------------------------------------------------------------------------------------------------- |
| `model` | `MODEL`   | The modified model after the hypernetwork has been applied, showcasing the impact of the hypernetwork on the original model. |


# ImageOnlyCheckpointLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageOnlyCheckpointLoader

Complete documentation for the ImageOnlyCheckpointLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node will detect models located in the `ComfyUI/models/checkpoints` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

This node specializes in loading checkpoints specifically for image-based models within video generation workflows. It efficiently retrieves and configures the necessary components from a given checkpoint, focusing on image-related aspects of the model.

## Inputs

| Field       | Data Type      | Description                                                                                                                              |
| ----------- | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------- |
| `ckpt_name` | COMBO\[STRING] | Specifies the name of the checkpoint to load, crucial for identifying and retrieving the correct checkpoint file from a predefined list. |

## Outputs

| Field         | Data Type     | Description                                                                                                          |
| ------------- | ------------- | -------------------------------------------------------------------------------------------------------------------- |
| `model`       | MODEL         | Returns the main model loaded from the checkpoint, configured for image processing within video generation contexts. |
| `clip_vision` | `CLIP_VISION` | Provides the CLIP vision component from the checkpoint, tailored for image understanding and feature extraction.     |
| `vae`         | VAE           | Delivers the Variational Autoencoder (VAE) component, essential for image manipulation and generation tasks.         |


# LTXVAudioVAEDecode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVAudioVAEDecode

Complete documentation for the LTXVAudioVAEDecode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVAudioVAEDecode/en.md)

The LTXV Audio VAE Decode node converts a latent representation of audio back into an audio waveform. It uses a specialized Audio VAE model to perform this decoding process, producing an audio output with a specific sample rate.

## Inputs

| Parameter   | Data Type | Required | Range | Description                                       |
| ----------- | --------- | -------- | ----- | ------------------------------------------------- |
| `samples`   | LATENT    | Yes      | N/A   | The latent to be decoded.                         |
| `audio_vae` | VAE       | Yes      | N/A   | The Audio VAE model used for decoding the latent. |

**Note:** If the provided latent is nested (contains multiple latents), the node will automatically use the last latent in the sequence for decoding.

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                 |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `Audio`     | AUDIO     | The decoded audio waveform and its associated sample rate. The waveform is a tensor moved to the same device as the input latent, and the sample rate is determined by the Audio VAE model. |

***

**Source fingerprint (SHA-256):** `b410b535f8cfc07b2d5a7814d719970ca813172bbbb04bec22a0ce3be04dfa94`


# LTXVAudioVAEEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVAudioVAEEncode

Complete documentation for the LTXVAudioVAEEncode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVAudioVAEEncode/en.md)

The LTXV Audio VAE Encode node takes an audio input and compresses it into a smaller, latent representation using a specified Audio VAE model. This process is essential for generating or manipulating audio within a latent space workflow, as it converts raw audio data into a format that other nodes in the pipeline can understand and process.

## Inputs

| Parameter   | Data Type | Required | Range | Description                              |
| ----------- | --------- | -------- | ----- | ---------------------------------------- |
| `audio`     | AUDIO     | Yes      | -     | The audio to be encoded.                 |
| `audio_vae` | VAE       | Yes      | -     | The Audio VAE model to use for encoding. |

## Outputs

| Output Name    | Data Type | Description                                                                                                                                               |
| -------------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `Audio Latent` | LATENT    | The compressed latent representation of the input audio. The output includes the latent samples, the sample rate of the VAE model, and a type identifier. |

***

**Source fingerprint (SHA-256):** `0c17491e6d2910febe7dc5c1ecf988c3f160b1a08de70f8c0c4ab52defe897cd`


# LTXVAudioVAELoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVAudioVAELoader

Complete documentation for the LTXVAudioVAELoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVAudioVAELoader/en.md)

The LTXV Audio VAE Loader node loads a pre-trained Audio Variational Autoencoder (VAE) model from a checkpoint file. It reads the specified checkpoint, loads its weights and metadata, and prepares the model for use in audio generation or processing workflows within ComfyUI.

## Inputs

| Parameter   | Data Type | Required | Range                                                                            | Description                                                                                                                       |
| ----------- | --------- | -------- | -------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------- |
| `ckpt_name` | STRING    | Yes      | All files in the `checkpoints` folder.<br />*Example: `"audio_vae.safetensors"`* | Audio VAE checkpoint to load. This is a dropdown list populated with all the files found in your ComfyUI `checkpoints` directory. |

## Outputs

| Output Name | Data Type | Description                                                                                            |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------ |
| `Audio VAE` | VAE       | The loaded Audio Variational Autoencoder model, ready to be connected to other audio processing nodes. |

***

**Source fingerprint (SHA-256):** `bafe0ae9a6175565e95514d8a42cd11ffc32330503d87a097bc7fd2ef113c794`


# LTXVConcatAVLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVConcatAVLatent

Complete documentation for the LTXVConcatAVLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVConcatAVLatent/en.md)

The LTXVConcatAVLatent node combines a video latent representation and an audio latent representation into a single, concatenated latent output. It merges the `samples` tensors from both inputs and, if present, their `noise_mask` tensors as well, preparing them for further processing in a video generation pipeline.

## Inputs

| Parameter      | Data Type | Required | Range | Description                                  |
| -------------- | --------- | -------- | ----- | -------------------------------------------- |
| `video_latent` | LATENT    | Yes      |       | The latent representation of the video data. |
| `audio_latent` | LATENT    | Yes      |       | The latent representation of the audio data. |

**Note:** The `samples` tensors from the `video_latent` and `audio_latent` inputs are concatenated. If either input contains a `noise_mask`, it will be used; if one is missing, a mask of ones (same shape as the corresponding `samples`) is created for it. The resulting masks are then also concatenated.

## Outputs

| Output Name | Data Type | Description                                                                                                                                         |
| ----------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------- |
| `latent`    | LATENT    | A single latent dictionary containing the concatenated `samples` and, if applicable, the concatenated `noise_mask` from the video and audio inputs. |

***

**Source fingerprint (SHA-256):** `ae619048b36d205d63e6054760c443f438b77d561e05458ce2d9d3f4a2024e74`


# LTXVEmptyLatentAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVEmptyLatentAudio

Complete documentation for the LTXVEmptyLatentAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVEmptyLatentAudio/en.md)

The LTXV Empty Latent Audio node creates a batch of empty (zero-filled) latent audio tensors. It uses the configuration from a provided Audio VAE model to determine the correct dimensions for the latent space, such as the number of channels and frequency bins. This empty latent serves as a starting point for audio generation or manipulation workflows within ComfyUI.

## Inputs

| Parameter       | Data Type | Required | Range     | Description                                                                |
| --------------- | --------- | -------- | --------- | -------------------------------------------------------------------------- |
| `frames_number` | INT       | Yes      | 1 to 1000 | Number of frames. The default value is 97.                                 |
| `frame_rate`    | INT       | Yes      | 1 to 1000 | Number of frames per second. The default value is 25.                      |
| `batch_size`    | INT       | Yes      | 1 to 4096 | The number of latent audio samples in the batch. The default value is 1.   |
| `audio_vae`     | VAE       | Yes      | N/A       | The Audio VAE model to get configuration from. This parameter is required. |

**Note:** The `audio_vae` input is mandatory. The node will raise an error if it is not provided.

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                                   |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `Latent`    | LATENT    | An empty latent audio tensor with the structure (batch\_size, z\_channels, num\_audio\_latents, audio\_freq) configured to match the input Audio VAE. The output also includes a `type` field set to "audio". |

***

**Source fingerprint (SHA-256):** `1b0ecbeb1388d952f5c5178cdc70bb06aad1640112a0851802c387594629f4bf`


# LTXVLatentUpsampler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVLatentUpsampler

Complete documentation for the LTXVLatentUpsampler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVLatentUpsampler/en.md)

The LTXVLatentUpsampler node increases the spatial resolution of a video latent representation by a factor of two. It uses a specialized upscale model to process the latent data, which is first un-normalized and then re-normalized using the provided VAE's channel statistics. This node is designed for video workflows within the latent space.

## Inputs

| Parameter       | Data Type              | Required | Range | Description                                                                                                           |
| --------------- | ---------------------- | -------- | ----- | --------------------------------------------------------------------------------------------------------------------- |
| `samples`       | LATENT                 | Yes      |       | The input latent representation of the video to be upscaled.                                                          |
| `upscale_model` | LATENT\_UPSCALE\_MODEL | Yes      |       | The loaded model used to perform the 2x upscaling on the latent data.                                                 |
| `vae`           | VAE                    | Yes      |       | The VAE model used to un-normalize the input latents before upscaling and to normalize the output latents afterwards. |

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                                                                                          |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `LATENT`    | LATENT    | The upscaled latent representation, with spatial dimensions doubled compared to the input. The output latent has the same batch size, number of channels, and temporal length as the input. The `noise_mask` from the input, if present, is removed from the output. |

***

**Source fingerprint (SHA-256):** `b2c726d3a3e4881eee7e1d3bae8c478adf01cd87a9652be882579f4e26c1536f`


# LTXVSeparateAVLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVSeparateAVLatent

Complete documentation for the LTXVSeparateAVLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVSeparateAVLatent/en.md)

The LTXVSeparateAVLatent node takes a combined audio-visual latent representation and splits it into two distinct parts: one for video and one for audio. It separates the samples and, if present, the noise masks from the input latent, creating two new latent objects.

## Inputs

| Parameter   | Data Type | Required | Range | Description                                                      |
| ----------- | --------- | -------- | ----- | ---------------------------------------------------------------- |
| `av_latent` | LATENT    | Yes      | N/A   | The combined audio-visual latent representation to be separated. |

**Note:** The input latent's `samples` tensor is expected to have at least two elements along the first dimension (batch dimension). The first element is used for the video latent, and the second element is used for the audio latent. If a `noise_mask` is present, it is split in the same way.

## Outputs

| Output Name    | Data Type | Description                                                    |
| -------------- | --------- | -------------------------------------------------------------- |
| `video_latent` | LATENT    | The latent representation containing the separated video data. |
| `audio_latent` | LATENT    | The latent representation containing the separated audio data. |

***

**Source fingerprint (SHA-256):** `8e871b6163af27826c197c678214bac7a02c2a5b24279385ba34632c7116356c`


# LatentAdd - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentAdd

Complete documentation for the LatentAdd node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentAdd node is designed for the addition of two latent representations. It facilitates the combination of features or characteristics encoded in these representations by performing element-wise addition.

## Inputs

| Parameter  | Data Type | Description                                                                                                                                                                |
| ---------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples1` | `LATENT`  | The first set of latent samples to be added. It represents one of the inputs whose features are to be combined with another set of latent samples.                         |
| `samples2` | `LATENT`  | The second set of latent samples to be added. It serves as the other input whose features are combined with the first set of latent samples through element-wise addition. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                        |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The result of the element-wise addition of two latent samples, representing a new set of latent samples that combines the features of both inputs. |


# LatentApplyOperation - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentApplyOperation

Complete documentation for the LatentApplyOperation node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentApplyOperation/en.md)

The LatentApplyOperation node applies a specified operation to latent samples. It takes latent data and an operation as inputs, processes the latent samples using the provided operation, and returns the modified latent data. This node allows you to transform or manipulate latent representations in your workflow.

## Inputs

| Parameter   | Data Type         | Required | Range | Description                                         |
| ----------- | ----------------- | -------- | ----- | --------------------------------------------------- |
| `samples`   | LATENT            | Yes      | -     | The latent samples to be processed by the operation |
| `operation` | LATENT\_OPERATION | Yes      | -     | The operation to apply to the latent samples        |

## Outputs

| Output Name | Data Type | Description                                              |
| ----------- | --------- | -------------------------------------------------------- |
| `output`    | LATENT    | The modified latent samples after applying the operation |

***

**Source fingerprint (SHA-256):** `e91307b6426c5220b4eab574d1efd0dd5ff26886b3baf8de9f7b6d9a123920e4`


# LatentApplyOperationCFG - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentApplyOperationCFG

Complete documentation for the LatentApplyOperationCFG node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentApplyOperationCFG/en.md)

The LatentApplyOperationCFG node applies a latent operation to modify the conditioning guidance process in a model. It works by intercepting the conditioning outputs during the classifier-free guidance (CFG) sampling process and applying the specified operation to the latent representations before they are used for generation.

## Inputs

| Parameter   | Data Type         | Required | Range | Description                                                   |
| ----------- | ----------------- | -------- | ----- | ------------------------------------------------------------- |
| `model`     | MODEL             | Yes      | -     | The model to which the CFG operation will be applied          |
| `operation` | LATENT\_OPERATION | Yes      | -     | The latent operation to apply during the CFG sampling process |

## Outputs

| Output Name | Data Type | Description                                                               |
| ----------- | --------- | ------------------------------------------------------------------------- |
| `model`     | MODEL     | The modified model with the CFG operation applied to its sampling process |

***

**Source fingerprint (SHA-256):** `0dd2cdc0561938866f12e11ae44d41fc34d16453ab49e686ba751118d2233c54`


# LatentBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentBatch

Complete documentation for the LatentBatch node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentBatch node is designed to merge two sets of latent samples into a single batch, potentially resizing one set to match the dimensions of the other before concatenation. This operation facilitates the combination of different latent representations for further processing or generation tasks.

## Inputs

| Parameter  | Data Type | Description                                                                                                                                       |
| ---------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples1` | `LATENT`  | The first set of latent samples to be merged. It plays a crucial role in determining the final shape of the merged batch.                         |
| `samples2` | `LATENT`  | The second set of latent samples to be merged. If its dimensions differ from the first set, it is resized to ensure compatibility before merging. |

## Outputs

| Parameter | Data Type | Description                                                                                |
| --------- | --------- | ------------------------------------------------------------------------------------------ |
| `latent`  | `LATENT`  | The merged set of latent samples, now combined into a single batch for further processing. |


# LatentBatchSeedBehavior - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentBatchSeedBehavior

Complete documentation for the LatentBatchSeedBehavior node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentBatchSeedBehavior node is designed to modify the seed behavior of a batch of latent samples. It allows for either randomizing or fixing the seed across the batch, thereby influencing the generation process by either introducing variability or maintaining consistency in the generated outputs.

## Inputs

| Parameter       | Data Type      | Description                                                                                                                                                                                                                                                  |
| --------------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `samples`       | `LATENT`       | The 'samples' parameter represents the batch of latent samples to be processed. Its modification depends on the seed behavior chosen, affecting the consistency or variability of the generated outputs.                                                     |
| `seed_behavior` | COMBO\[STRING] | The 'seed\_behavior' parameter dictates whether the seed for the batch of latent samples should be randomized or fixed. This choice significantly impacts the generation process by either introducing variability or ensuring consistency across the batch. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                                                  |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `latent`  | `LATENT`  | The output is a modified version of the input latent samples, with adjustments made based on the specified seed behavior. It either maintains or alters the batch index to reflect the chosen seed behavior. |


# LatentComposite - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentComposite

Complete documentation for the LatentComposite node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentComposite node is designed to blend or merge two latent representations into a single output. This process is essential for creating composite images or features by combining the characteristics of the input latents in a controlled manner.

## Inputs

| Parameter      | Data Type | Description                                                                                                                                                                                |
| -------------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `samples_to`   | `LATENT`  | The 'samples\_to' latent representation where the 'samples\_from' will be composited onto. It serves as the base for the composite operation.                                              |
| `samples_from` | `LATENT`  | The 'samples\_from' latent representation to be composited onto the 'samples\_to'. It contributes its features or characteristics to the final composite output.                           |
| `x`            | `INT`     | The x-coordinate (horizontal position) where the 'samples\_from' latent will be placed on the 'samples\_to'. It determines the horizontal alignment of the composite.                      |
| `y`            | `INT`     | The y-coordinate (vertical position) where the 'samples\_from' latent will be placed on the 'samples\_to'. It determines the vertical alignment of the composite.                          |
| `feather`      | `INT`     | A boolean indicating whether the 'samples\_from' latent should be resized to match the 'samples\_to' before compositing. This can affect the scale and proportion of the composite result. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                      |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The output is a composite latent representation, blending the features of both 'samples\_to' and 'samples\_from' latents based on the specified coordinates and resizing option. |


# LatentCompositeMasked - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentCompositeMasked

Complete documentation for the LatentCompositeMasked node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentCompositeMasked node is designed for blending two latent representations together at specified coordinates, optionally using a mask for more controlled compositing. This node enables the creation of complex latent images by overlaying parts of one image onto another, with the ability to resize the source image for a perfect fit.

## Inputs

| Parameter       | Data Type | Description                                                                                                                                                                      |
| --------------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `destination`   | `LATENT`  | The latent representation onto which another latent representation will be composited. Acts as the base layer for the composite operation.                                       |
| `source`        | `LATENT`  | The latent representation to be composited onto the destination. This source layer can be resized and positioned according to the specified parameters.                          |
| `x`             | `INT`     | The x-coordinate in the destination latent representation where the source will be placed. Allows for precise positioning of the source layer.                                   |
| `y`             | `INT`     | The y-coordinate in the destination latent representation where the source will be placed, enabling accurate overlay positioning.                                                |
| `resize_source` | `BOOLEAN` | A boolean flag indicating whether the source latent representation should be resized to match the destination's dimensions before compositing.                                   |
| `mask`          | `MASK`    | An optional mask that can be used to control the blending of the source onto the destination. The mask defines which parts of the source will be visible in the final composite. |

## Outputs

| Parameter | Data Type | Description                                                                                                                             |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The resulting latent representation after compositing the source onto the destination, potentially using a mask for selective blending. |


# LatentConcat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentConcat

Complete documentation for the LatentConcat node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentConcat/en.md)

The LatentConcat node combines two latent samples by joining them together along a chosen dimension. It takes two latent inputs and concatenates them along the x, y, or t axis, with the option to control which sample comes first. The node automatically adjusts the batch size of the second input to match the first before performing the concatenation.

## Inputs

| Parameter  | Data Type | Required | Range                                                           | Description                                                                                                                                                                                                                                                        |
| ---------- | --------- | -------- | --------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `samples1` | LATENT    | Yes      | -                                                               | The first latent sample to concatenate                                                                                                                                                                                                                             |
| `samples2` | LATENT    | Yes      | -                                                               | The second latent sample to concatenate                                                                                                                                                                                                                            |
| `dim`      | COMBO     | Yes      | `"x"`<br />`"-x"`<br />`"y"`<br />`"-y"`<br />`"t"`<br />`"-t"` | The dimension along which to concatenate the latent samples. Positive values (x, y, t) place samples1 before samples2 in the result. Negative values (-x, -y, -t) place samples2 before samples1. The dimension mapping is: x = width, y = height, t = time/frames |

**Note:** The second latent sample (`samples2`) is automatically adjusted to match the batch size of the first latent sample (`samples1`) before concatenation.

## Outputs

| Output Name | Data Type | Description                                                                                                  |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------ |
| `output`    | LATENT    | The concatenated latent samples resulting from combining the two input samples along the specified dimension |

***

**Source fingerprint (SHA-256):** `82cc2d659cd7c3d35ad20eee6fc63a7574e7367397618c0bdf3e82924372dff7`


# LatentCrop - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentCrop

Complete documentation for the LatentCrop node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentCrop node is designed to perform cropping operations on latent representations of images. It allows for the specification of the crop dimensions and position, enabling targeted modifications of the latent space.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                         |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples` | `LATENT`  | The 'samples' parameter represents the latent representations to be cropped. It is crucial for defining the data on which the cropping operation will be performed. |
| `width`   | `INT`     | Specifies the width of the crop area. It directly influences the dimensions of the output latent representation.                                                    |
| `height`  | `INT`     | Specifies the height of the crop area, affecting the size of the resulting cropped latent representation.                                                           |
| `x`       | `INT`     | Determines the starting x-coordinate of the crop area, influencing the position of the crop within the original latent representation.                              |
| `y`       | `INT`     | Determines the starting y-coordinate of the crop area, setting the position of the crop within the original latent representation.                                  |

## Outputs

| Parameter | Data Type | Description                                                                     |
| --------- | --------- | ------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The output is a modified latent representation with the specified crop applied. |


# LatentCut - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentCut

Complete documentation for the LatentCut node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentCut/en.md)

The LatentCut node extracts a specific section from latent samples along a chosen dimension. It allows you to cut out a portion of the latent representation by specifying the dimension (x, y, or t), starting position, and amount to extract. The node handles both positive and negative indexing and automatically adjusts the extraction amount to stay within the available bounds.

## Inputs

| Parameter | Data Type | Required | Range                 | Description                                                                                                                                                                                                            |
| --------- | --------- | -------- | --------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples` | LATENT    | Yes      | -                     | The input latent samples to extract from                                                                                                                                                                               |
| `dim`     | COMBO     | Yes      | "x"<br />"y"<br />"t" | The dimension along which to cut the latent samples                                                                                                                                                                    |
| `index`   | INT       | Yes      | -16384 to 16384       | The starting position for the cut (default: 0). Positive values count from the start, negative values count from the end. The node automatically clamps the index to stay within the valid range of the latent samples |
| `amount`  | INT       | Yes      | 1 to 16384            | The number of elements to extract along the specified dimension (default: 1). The node automatically reduces this value if it would exceed the available data beyond the starting index                                |

## Outputs

| Output Name | Data Type | Description                                 |
| ----------- | --------- | ------------------------------------------- |
| `output`    | LATENT    | The extracted portion of the latent samples |

***

**Source fingerprint (SHA-256):** `c05ce7a33d9416bdd8dabeed2c61fbc6102fc9e797d727aefaadb00f375287a9`


# LatentCutToBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentCutToBatch

Complete documentation for the LatentCutToBatch node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentCutToBatch/en.md)

The LatentCutToBatch node splits a latent representation along a chosen dimension into multiple slices and stacks them into a new batch. This allows you to process different parts of a latent sample independently.

## Inputs

| Parameter    | Data Type | Required | Range                       | Description                                                                                                                                                            |
| ------------ | --------- | -------- | --------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples`    | LATENT    | Yes      | -                           | The latent representation to be split and batched.                                                                                                                     |
| `dim`        | COMBO     | Yes      | `"t"`<br />`"x"`<br />`"y"` | The dimension along which to cut the latent samples. `"t"` refers to the temporal dimension, `"x"` to the width, and `"y"` to the height.                              |
| `slice_size` | INT       | Yes      | 1 to 16384 (max resolution) | The size of each slice to cut from the specified dimension. If the dimension's size is not perfectly divisible by this value, the remainder is discarded. (default: 1) |

## Outputs

| Output Name | Data Type | Description                                                            |
| ----------- | --------- | ---------------------------------------------------------------------- |
| `samples`   | LATENT    | The resulting latent batch, containing the sliced and stacked samples. |

***

**Source fingerprint (SHA-256):** `565fd1e72a1353050cf8c32c6ab8dade475afb2e8ee13ba323d30a8467204201`


# LatentFlip - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentFlip

Complete documentation for the LatentFlip node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentFlip node is designed to manipulate latent representations by flipping them either vertically or horizontally. This operation allows for the transformation of the latent space, potentially uncovering new variations or perspectives within the data.

## Inputs

| Parameter     | Data Type      | Description                                                                                                                                                                                                                                                                             |
| ------------- | -------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples`     | `LATENT`       | The 'samples' parameter represents the latent representations to be flipped. The flipping operation alters these representations, either vertically or horizontally, depending on the 'flip\_method' parameter, thus transforming the data in the latent space.                         |
| `flip_method` | COMBO\[STRING] | The 'flip\_method' parameter specifies the axis along which the latent samples will be flipped. It can be either 'x-axis: vertically' or 'y-axis: horizontally', determining the direction of the flip and thus the nature of the transformation applied to the latent representations. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                                            |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `latent`  | `LATENT`  | The output is a modified version of the input latent representations, having been flipped according to the specified method. This transformation can introduce new variations within the latent space. |


# LatentFromBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentFromBatch

Complete documentation for the LatentFromBatch node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to extract a specific subset of latent samples from a given batch based on the specified batch index and length. It allows for selective processing of latent samples, facilitating operations on smaller segments of the batch for efficiency or targeted manipulation.

## Inputs

| Parameter     | Data Type | Description                                                                                                                                                                                            |
| ------------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `samples`     | `LATENT`  | The collection of latent samples from which a subset will be extracted. This parameter is crucial for determining the source batch of samples to be processed.                                         |
| `batch_index` | `INT`     | Specifies the starting index within the batch from which the subset of samples will begin. This parameter enables targeted extraction of samples from specific positions in the batch.                 |
| `length`      | `INT`     | Defines the number of samples to be extracted from the specified starting index. This parameter controls the size of the subset to be processed, allowing for flexible manipulation of batch segments. |

## Outputs

| Parameter | Data Type | Description                                                                               |
| --------- | --------- | ----------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The extracted subset of latent samples, now available for further processing or analysis. |


# LatentInterpolate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentInterpolate

Complete documentation for the LatentInterpolate node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentInterpolate node is designed to perform interpolation between two sets of latent samples based on a specified ratio, blending the characteristics of both sets to produce a new, intermediate set of latent samples.

## Inputs

| Parameter  | Data Type | Description                                                                                                                                                                                               |
| ---------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples1` | `LATENT`  | The first set of latent samples to be interpolated. It serves as the starting point for the interpolation process.                                                                                        |
| `samples2` | `LATENT`  | The second set of latent samples to be interpolated. It serves as the endpoint for the interpolation process.                                                                                             |
| `ratio`    | `FLOAT`   | A floating-point value that determines the weight of each set of samples in the interpolated output. A ratio of 0 produces a copy of the first set, while a ratio of 1 produces a copy of the second set. |

## Outputs

| Parameter | Data Type | Description                                                                                                                              |
| --------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The output is a new set of latent samples that represent an interpolated state between the two input sets, based on the specified ratio. |


# LatentMultiply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentMultiply

Complete documentation for the LatentMultiply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentMultiply node is designed to scale the latent representation of samples by a specified multiplier. This operation allows for the adjustment of the intensity or magnitude of features within the latent space, enabling fine-tuning of generated content or the exploration of variations within a given latent direction.

## Inputs

| Parameter    | Data Type | Description                                                                                                                                                                                                                 |
| ------------ | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples`    | `LATENT`  | The 'samples' parameter represents the latent representations to be scaled. It is crucial for defining the input data on which the multiplication operation will be performed.                                              |
| `multiplier` | `FLOAT`   | The 'multiplier' parameter specifies the scaling factor to be applied to the latent samples. It plays a key role in adjusting the magnitude of the latent features, allowing for nuanced control over the generated output. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                                                         |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The output is a modified version of the input latent samples, scaled by the specified multiplier. This allows for the exploration of variations within the latent space by adjusting the intensity of its features. |


# LatentOperationSharpen - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentOperationSharpen

Complete documentation for the LatentOperationSharpen node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentOperationSharpen/en.md)

The LatentOperationSharpen node applies a sharpening effect to latent representations using a Gaussian kernel. It works by normalizing the latent data, applying a convolution with a custom sharpening kernel, and then restoring the original luminance. This enhances the details and edges in the latent space representation.

## Inputs

| Parameter        | Data Type | Required | Range    | Description                                                   |
| ---------------- | --------- | -------- | -------- | ------------------------------------------------------------- |
| `sharpen_radius` | INT       | No       | 1-31     | The radius of the sharpening kernel (default: 9)              |
| `sigma`          | FLOAT     | No       | 0.1-10.0 | The standard deviation for the Gaussian kernel (default: 1.0) |
| `alpha`          | FLOAT     | No       | 0.0-5.0  | The sharpening intensity factor (default: 0.1)                |

## Outputs

| Output Name | Data Type         | Description                                                       |
| ----------- | ----------------- | ----------------------------------------------------------------- |
| `operation` | LATENT\_OPERATION | Returns a sharpening operation that can be applied to latent data |

***

**Source fingerprint (SHA-256):** `98d80144a7d9ae2794ef9e6803ec7e6383dfac1b42a42fec5e17e93d6a806ca5`


# LatentOperationTonemapReinhard - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentOperationTonemapReinhard

Complete documentation for the LatentOperationTonemapReinhard node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentOperationTonemapReinhard/en.md)

The LatentOperationTonemapReinhard node applies Reinhard tonemapping to latent vectors. This technique normalizes the latent vectors and adjusts their magnitude using a statistical approach based on mean and standard deviation, with the intensity controlled by a multiplier parameter.

## Inputs

| Parameter    | Data Type | Required | Range        | Description                                                     |
| ------------ | --------- | -------- | ------------ | --------------------------------------------------------------- |
| `multiplier` | FLOAT     | Yes      | 0.0 to 100.0 | Controls the intensity of the tonemapping effect (default: 1.0) |

## Outputs

| Output Name | Data Type         | Description                                                           |
| ----------- | ----------------- | --------------------------------------------------------------------- |
| `operation` | LATENT\_OPERATION | Returns a tonemapping operation that can be applied to latent vectors |

***

**Source fingerprint (SHA-256):** `698c142dd4fa084b52c43a12062e8be063870704b0c0dd2de015f3a1142378b8`


# LatentRotate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentRotate

Complete documentation for the LatentRotate node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentRotate node is designed to rotate latent representations of images by specified angles. It abstracts the complexity of manipulating latent space to achieve rotation effects, enabling users to easily transform images in a generative model's latent space.

## Inputs

| Parameter  | Data Type      | Description                                                                                                                                                        |
| ---------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `samples`  | `LATENT`       | The 'samples' parameter represents the latent representations of images to be rotated. It is crucial for determining the starting point of the rotation operation. |
| `rotation` | COMBO\[STRING] | The 'rotation' parameter specifies the angle by which the latent images should be rotated. It directly influences the orientation of the resulting images.         |

## Outputs

| Parameter | Data Type | Description                                                                                           |
| --------- | --------- | ----------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The output is a modified version of the input latent representations, rotated by the specified angle. |


# LatentSubtract - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentSubtract

Complete documentation for the LatentSubtract node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentSubtract node is designed for subtracting one latent representation from another. This operation can be used to manipulate or modify the characteristics of generative models' outputs by effectively removing features or attributes represented in one latent space from another.

## Inputs

| Parameter  | Data Type | Description                                                                                                                                                                       |
| ---------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples1` | `LATENT`  | The first set of latent samples to be subtracted from. It serves as the base for the subtraction operation.                                                                       |
| `samples2` | `LATENT`  | The second set of latent samples that will be subtracted from the first set. This operation can alter the resulting generative model's output by removing attributes or features. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                              |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The result of subtracting the second set of latent samples from the first. This modified latent representation can be used for further generative tasks. |


# LatentUpscale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentUpscale

Complete documentation for the LatentUpscale node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentUpscale node is designed for upscaling latent representations of images. It allows for the adjustment of the output image's dimensions and the method of upscaling, providing flexibility in enhancing the resolution of latent images.

## Inputs

| Parameter        | Data Type      | Description                                                                                                                                   |
| ---------------- | -------------- | --------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples`        | `LATENT`       | The latent representation of an image to be upscaled. This parameter is crucial for determining the starting point of the upscaling process.  |
| `upscale_method` | COMBO\[STRING] | Specifies the method used for upscaling the latent image. Different methods can affect the quality and characteristics of the upscaled image. |
| `width`          | `INT`          | The desired width of the upscaled image. If set to 0, it will be calculated based on the height to maintain the aspect ratio.                 |
| `height`         | `INT`          | The desired height of the upscaled image. If set to 0, it will be calculated based on the width to maintain the aspect ratio.                 |
| `crop`           | COMBO\[STRING] | Determines how the upscaled image should be cropped, affecting the final appearance and dimensions of the output.                             |

## Outputs

| Parameter | Data Type | Description                                                                                  |
| --------- | --------- | -------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The upscaled latent representation of the image, ready for further processing or generation. |


# LatentUpscaleBy - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentUpscaleBy

Complete documentation for the LatentUpscaleBy node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The LatentUpscaleBy node is designed for upscaling latent representations of images. It allows for the adjustment of the scale factor and the method of upscaling, providing flexibility in enhancing the resolution of latent samples.

## Inputs

| Parameter        | Data Type      | Description                                                                                                                                                                             |
| ---------------- | -------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples`        | `LATENT`       | The latent representation of images to be upscaled. This parameter is crucial for determining the input data that will undergo the upscaling process.                                   |
| `upscale_method` | COMBO\[STRING] | Specifies the method used for upscaling the latent samples. The choice of method can significantly affect the quality and characteristics of the upscaled output.                       |
| `scale_by`       | `FLOAT`        | Determines the factor by which the latent samples are scaled. This parameter directly influences the resolution of the output, allowing for precise control over the upscaling process. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                                         |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The upscaled latent representation, ready for further processing or generation tasks. This output is essential for enhancing the resolution of generated images or for subsequent model operations. |


# LatentUpscaleModelLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LatentUpscaleModelLoader

Complete documentation for the LatentUpscaleModelLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LatentUpscaleModelLoader/en.md)

The LatentUpscaleModelLoader node loads a specialized model designed for upscaling latent representations. It reads a model file from the system's designated folder and automatically detects its type (720p, 1080p, or other) to instantiate and configure the correct internal model architecture. The loaded model is then ready to be used by other nodes for latent space super-resolution tasks.

## Inputs

| Parameter    | Data Type | Required | Range                                             | Description                                                                                                                                                                    |
| ------------ | --------- | -------- | ------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `model_name` | STRING    | Yes      | *All files in the `latent_upscale_models` folder* | The name of the latent upscale model file to load. The available options are dynamically populated from the files present in your ComfyUI's `latent_upscale_models` directory. |

## Outputs

| Output Name | Data Type              | Description                                                    |
| ----------- | ---------------------- | -------------------------------------------------------------- |
| `model`     | LATENT\_UPSCALE\_MODEL | The loaded latent upscale model, configured and ready for use. |

***

**Source fingerprint (SHA-256):** `afd35f0d5dacb14a835c00bf34c016d270e85064eca7d7ff42880e67cc64a01f`


# LoadBackgroundRemovalModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadBackgroundRemovalModel

Complete documentation for the LoadBackgroundRemovalModel node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadBackgroundRemovalModel/en.md)

## Overview

Loads a background removal model from a file. This node prepares the model for use in removing backgrounds from images.

## Inputs

| Parameter         | Data Type | Required | Range                         | Description                                                                                                         |
| ----------------- | --------- | -------- | ----------------------------- | ------------------------------------------------------------------------------------------------------------------- |
| `bg_removal_name` | STRING    | Yes      | List of available model files | The model used to remove backgrounds from images. Select from the list of available background removal model files. |

## Outputs

| Output Name | Data Type           | Description                                                                                 |
| ----------- | ------------------- | ------------------------------------------------------------------------------------------- |
| `bg_model`  | BACKGROUND\_REMOVAL | The loaded background removal model, ready to be used by other nodes for processing images. |

***

**Source fingerprint (SHA-256):** `3f2da4d2fcafb7d65f4e5099102011c3be9500f3eec6c59c6897aa9640ae8f04`


# LoadMediaPipeFaceLandmarker - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadMediaPipeFaceLandmarker

Complete documentation for the LoadMediaPipeFaceLandmarker node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadMediaPipeFaceLandmarker/en.md)

## Overview

This node loads a MediaPipe Face Landmarker v2 model, which can detect faces and facial landmarks (like eyes, nose, and mouth) in images. It contains two detection variants (short-range and full-range) along with shared mesh data, blendshapes, and canonical geometry for facial analysis.

## Inputs

| Parameter    | Data Type | Required | Range                                                         | Description                                  |
| ------------ | --------- | -------- | ------------------------------------------------------------- | -------------------------------------------- |
| `model_name` | STRING    | Yes      | List of available models in the `models/detection/` directory | Face detection model from models/detection/. |

## Outputs

| Output Name            | Data Type              | Description                                                                                                                                                                       |
| ---------------------- | ---------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `FACE_DETECTION_MODEL` | FACE\_DETECTION\_MODEL | A loaded FaceLandmarker model object containing both detection variants (short/full), connection sets for facial topology, canonical data, and model patchers for GPU management. |

**Note:** The output is a complex object that can be used by other nodes for face detection and landmark extraction tasks. It contains two detection variants: "short" for close-range detection and "full" for full-range detection.

***

**Source fingerprint (SHA-256):** `b30bf4d04aa06a227f3661c0e1346d3dab3ea1e25d6627fce5b6480198203c26`


# LoadMoGeModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadMoGeModel

Complete documentation for the LoadMoGeModel node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadMoGeModel/en.md)

## Overview

Loads a MoGe (Monocular Geometry) model from a file and prepares it for use in geometry estimation tasks. This node reads a model file from the `geometry_estimation` folder and initializes the MoGe model with its trained weights.

## Inputs

| Parameter    | Data Type | Required | Range                                                             | Description                                                                                                  |
| ------------ | --------- | -------- | ----------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------ |
| `model_name` | STRING    | Yes      | List of available model files in the `geometry_estimation` folder | The name of the MoGe model file to load. Select from the available model files in your ComfyUI installation. |

## Outputs

| Output Name  | Data Type   | Description                                                                     |
| ------------ | ----------- | ------------------------------------------------------------------------------- |
| `MOGE_MODEL` | MOGE\_MODEL | The loaded MoGe model instance, ready for use in geometry estimation workflows. |

***

**Source fingerprint (SHA-256):** `4707002565181ca17936ecf87ea8059630c97c44c17facfecd04053d9581b7d1`


# LoraLoaderBypass - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraLoaderBypass

Complete documentation for the LoraLoaderBypass node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoraLoaderBypass/en.md)

The LoraLoaderBypass node applies a LoRA (Low-Rank Adaptation) to a diffusion model and a CLIP model in a special "bypass" mode. Unlike a standard LoRA loader, this method does not permanently modify the base model's weights. Instead, it computes the output by adding the LoRA's effect to the model's normal forward pass, which is useful for training or when working with models that have their weights offloaded.

## Inputs

| Parameter        | Data Type | Required | Range                          | Description                                                                            |
| ---------------- | --------- | -------- | ------------------------------ | -------------------------------------------------------------------------------------- |
| `model`          | MODEL     | Yes      | -                              | The diffusion model the LoRA will be applied to.                                       |
| `clip`           | CLIP      | Yes      | -                              | The CLIP model the LoRA will be applied to.                                            |
| `lora_name`      | COMBO     | Yes      | *List of available LoRA files* | The name of the LoRA file to apply. The options are loaded from the `loras` folder.    |
| `strength_model` | FLOAT     | Yes      | -100.0 to 100.0                | How strongly to modify the diffusion model. This value can be negative (default: 1.0). |
| `strength_clip`  | FLOAT     | Yes      | -100.0 to 100.0                | How strongly to modify the CLIP model. This value can be negative (default: 1.0).      |

**Note:** If both `strength_model` and `strength_clip` are set to 0, the node will return the original, unmodified `model` and `clip` inputs without processing.

## Outputs

| Output Name | Data Type | Description                                               |
| ----------- | --------- | --------------------------------------------------------- |
| `MODEL`     | MODEL     | The diffusion model with the LoRA applied in bypass mode. |
| `CLIP`      | CLIP      | The CLIP model with the LoRA applied in bypass mode.      |

***

**Source fingerprint (SHA-256):** `2642f4ed98457e5fd08e2103ffb9f2c02f11326590aadf0636fb7db51f484815`


# LoraLoaderBypassModelOnly - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraLoaderBypassModelOnly

Complete documentation for the LoraLoaderBypassModelOnly node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoraLoaderBypassModelOnly/en.md)

This node applies a LoRA (Low-Rank Adaptation) to a model to modify its behavior, but only affects the model component itself. It loads a specified LoRA file and adjusts the model's weights by a given strength, leaving other components like the CLIP text encoder unchanged.

## Inputs

| Parameter        | Data Type | Required | Range                          | Description                                                                                                                                                                       |
| ---------------- | --------- | -------- | ------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`          | MODEL     | Yes      | -                              | The base model to which the LoRA adjustments will be applied.                                                                                                                     |
| `lora_name`      | STRING    | Yes      | (List of available LoRA files) | The name of the LoRA file to load and apply. The options are populated from the files in the `loras` directory.                                                                   |
| `strength_model` | FLOAT     | Yes      | -100.0 to 100.0                | The strength of the LoRA's effect on the model's weights. A positive value applies the LoRA, a negative value applies the inverse, and a value of 0 has no effect (default: 1.0). |

## Outputs

| Output Name | Data Type | Description                                                          |
| ----------- | --------- | -------------------------------------------------------------------- |
| `model`     | MODEL     | The modified model with the LoRA adjustments applied to its weights. |

***

**Source fingerprint (SHA-256):** `e0e1ad2d6481a1b9771d7eae833ffab0737a967d4af6e57b946d1b2223fe45bf`


# LoraModelLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoraModelLoader

Complete documentation for the LoraModelLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoraModelLoader/en.md)

The LoraModelLoader node applies trained LoRA (Low-Rank Adaptation) weights to a diffusion model. It modifies the base model by loading LoRA weights from a trained LoRA model and adjusting their influence strength. This allows you to customize the behavior of diffusion models without retraining them from scratch.

## Inputs

| Parameter        | Data Type   | Required | Range           | Description                                                                                                                                                |
| ---------------- | ----------- | -------- | --------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`          | MODEL       | Yes      | -               | The diffusion model the LoRA will be applied to.                                                                                                           |
| `lora`           | LORA\_MODEL | Yes      | -               | The LoRA model to apply to the diffusion model.                                                                                                            |
| `strength_model` | FLOAT       | Yes      | -100.0 to 100.0 | How strongly to modify the diffusion model. This value can be negative (default: 1.0).                                                                     |
| `bypass`         | BOOLEAN     | Yes      | True or False   | When enabled, applies LoRA in bypass mode without modifying base model weights. Useful for training and when model weights are offloaded (default: False). |

**Note:** When `strength_model` is set to 0, the node returns the original model without applying any LoRA modifications.

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `model`     | MODEL     | The modified diffusion model with LoRA weights applied. |

***

**Source fingerprint (SHA-256):** `dbb0852d4f40ded8a4490244634e13eeb367e5573b664a0f7e37213364793413`


# OpticalFlowLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpticalFlowLoader

Complete documentation for the OpticalFlowLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpticalFlowLoader/en.md)

## Overview

Loads an optical flow model from the `models/optical_flow/` folder. Currently, only torchvision's RAFT-large format is supported, which is the model used by the VOIDWarpedNoise node. ComfyUI does not download optical flow weights automatically; you must place the checkpoint file manually in the `models/optical_flow/` directory.

## Inputs

| Parameter    | Data Type | Required | Range                                          | Description                                                                                                                            |
| ------------ | --------- | -------- | ---------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------- |
| `model_name` | STRING    | Yes      | List of files in `models/optical_flow/` folder | Optical flow model to load. Files must be placed in the `optical_flow` folder. Today only torchvision's `raft_large.pth` is supported. |

## Outputs

| Output Name    | Data Type | Description                                                                        |
| -------------- | --------- | ---------------------------------------------------------------------------------- |
| `OPTICAL_FLOW` | MODEL     | The loaded optical flow model, wrapped in a ModelPatcher for use with other nodes. |

***

**Source fingerprint (SHA-256):** `62f79c2e96fafe4856321481bdc22ca474e65be2bb4c117cb0e929ff33e75d5a`


# PatchModelAddDownscale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PatchModelAddDownscale

Complete documentation for the PatchModelAddDownscale node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PatchModelAddDownscale/en.md)

The PatchModelAddDownscale node implements Kohya Deep Shrink functionality by applying downscaling and upscaling operations to specific blocks in a model. It reduces the resolution of intermediate features during processing and then restores them to their original size, which can improve performance while maintaining quality. The node allows precise control over when and how these scaling operations occur during the model's execution.

## Inputs

| Parameter              | Data Type | Required | Range                                                                     | Description                                                                         |
| ---------------------- | --------- | -------- | ------------------------------------------------------------------------- | ----------------------------------------------------------------------------------- |
| `model`                | MODEL     | Yes      | -                                                                         | The model to apply the downscale patch to                                           |
| `block_number`         | INT       | No       | 1-32                                                                      | The specific block number where downscaling will be applied (default: 3)            |
| `downscale_factor`     | FLOAT     | No       | 0.1-9.0                                                                   | The factor by which to downscale the features (default: 2.0)                        |
| `start_percent`        | FLOAT     | No       | 0.0-1.0                                                                   | The starting point in the denoising process where downscaling begins (default: 0.0) |
| `end_percent`          | FLOAT     | No       | 0.0-1.0                                                                   | The ending point in the denoising process where downscaling stops (default: 0.35)   |
| `downscale_after_skip` | BOOLEAN   | No       | -                                                                         | Whether to apply downscaling after skip connections (default: True)                 |
| `downscale_method`     | COMBO     | No       | "bicubic"<br />"nearest-exact"<br />"bilinear"<br />"area"<br />"bislerp" | The interpolation method used for downscaling operations                            |
| `upscale_method`       | COMBO     | No       | "bicubic"<br />"nearest-exact"<br />"bilinear"<br />"area"<br />"bislerp" | The interpolation method used for upscaling operations                              |

## Outputs

| Output Name | Data Type | Description                                     |
| ----------- | --------- | ----------------------------------------------- |
| `model`     | MODEL     | The modified model with downscale patch applied |

***

**Source fingerprint (SHA-256):** `ee6a1191bd753a669e676a58e2052ca4b47ac74d8f40df562df8550b0c71c3c2`


# PerturbedAttentionGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PerturbedAttentionGuidance

Complete documentation for the PerturbedAttentionGuidance node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PerturbedAttentionGuidance/en.md)

The PerturbedAttentionGuidance node applies perturbed attention guidance to a diffusion model to enhance generation quality. It modifies the model's self-attention mechanism during sampling by replacing it with a simplified version that focuses on value projections. This technique helps improve the coherence and quality of generated images by adjusting the conditional denoising process.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                                                                                                                             |
| --------- | --------- | -------- | ----------- | ------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -           | The diffusion model to apply perturbed attention guidance to                                                                                            |
| `scale`   | FLOAT     | No       | 0.0 - 100.0 | The strength of the perturbed attention guidance effect (default: 3.0). When set to 0, the node has no effect and returns the original denoised result. |

## Outputs

| Output Name | Data Type | Description                                                  |
| ----------- | --------- | ------------------------------------------------------------ |
| `model`     | MODEL     | The modified model with perturbed attention guidance applied |

***

**Source fingerprint (SHA-256):** `b4bcb5e8a0bf990d36d2865c58e6fbf3c9cee9d446f5aced987ddd04387d2b4c`


# RebatchLatents - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RebatchLatents

Complete documentation for the RebatchLatents node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The RebatchLatents node is designed to reorganize a batch of latent representations into a new batch configuration, based on a specified batch size. It ensures that the latent samples are grouped appropriately, handling variations in dimensions and sizes, to facilitate further processing or model inference.

## Inputs

| Parameter    | Data Type | Description                                                                                                                                                                          |
| ------------ | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `latents`    | `LATENT`  | The 'latents' parameter represents the input latent representations to be rebatched. It is crucial for determining the structure and content of the output batch.                    |
| `batch_size` | `INT`     | The 'batch\_size' parameter specifies the desired number of samples per batch in the output. It directly influences the grouping and division of the input latents into new batches. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                 |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The output is a reorganized batch of latent representations, adjusted according to the specified batch size. It facilitates further processing or analysis. |


# RepeatLatentBatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RepeatLatentBatch

Complete documentation for the RepeatLatentBatch node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The RepeatLatentBatch node is designed to replicate a given batch of latent representations a specified number of times, potentially including additional data like noise masks and batch indices. This functionality is crucial for operations that require multiple instances of the same latent data, such as data augmentation or specific generative tasks.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                                                                       |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples` | `LATENT`  | The 'samples' parameter represents the latent representations to be replicated. It is essential for defining the data that will undergo repetition.                                                                               |
| `amount`  | `INT`     | The 'amount' parameter specifies the number of times the input samples should be repeated. It directly influences the size of the output batch, thereby affecting the computational load and the diversity of the generated data. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                                            |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `latent`  | `LATENT`  | The output is a modified version of the input latent representations, replicated according to the specified 'amount'. It may include replicated noise masks and adjusted batch indices, if applicable. |


# ReplaceVideoLatentFrames - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReplaceVideoLatentFrames

Complete documentation for the ReplaceVideoLatentFrames node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReplaceVideoLatentFrames/en.md)

The ReplaceVideoLatentFrames node inserts frames from a source latent video into a destination latent video, starting at a specified frame index. If the source latent is not provided, the destination latent is returned unchanged. The node handles negative indexing and will issue a warning if the source frames do not fit within the destination.

## Inputs

| Parameter     | Data Type | Required | Range                               | Description                                                                                                                                               |
| ------------- | --------- | -------- | ----------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `destination` | LATENT    | Yes      | -                                   | The destination latent where frames will be replaced.                                                                                                     |
| `source`      | LATENT    | No       | -                                   | The source latent providing frames to insert into the destination latent. If not provided, the destination latent is returned unchanged.                  |
| `index`       | INT       | Yes      | -MAX\_RESOLUTION to MAX\_RESOLUTION | The starting latent frame index in the destination latent where the source latent frames will be placed. Negative values count from the end (default: 0). |

**Constraints:**

* The `index` must be within the bounds of the destination latent's frame count. If it is not, a warning is logged and the destination is returned unchanged.
* The source latent frames must fit within the destination latent frames starting from the specified `index`. If they do not, a warning is logged and the destination is returned unchanged.

## Outputs

| Output Name | Data Type | Description                                                       |
| ----------- | --------- | ----------------------------------------------------------------- |
| `output`    | LATENT    | The resulting latent video after the frame replacement operation. |

***

**Source fingerprint (SHA-256):** `c70eb5f907964e00babcee66a98d1bf382c3bc704f920d61598a4a03f4d686f8`


# SUPIRApply - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SUPIRApply

Complete documentation for the SUPIRApply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SUPIRApply/en.md)

The SUPIRApply node applies a SUPIR model patch to a diffusion model. It uses the patch to modify the model's behavior, allowing it to incorporate guidance from an input image during the sampling process. The node also provides controls for adjusting the strength of this guidance over time and includes an optional feature to help maintain fidelity to the original input.

## Inputs

| Parameter            | Data Type  | Required | Range      | Description                                                                                                                                                   |
| -------------------- | ---------- | -------- | ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`              | MODEL      | Yes      | -          | The base diffusion model to which the SUPIR patch will be applied.                                                                                            |
| `model_patch`        | MODELPATCH | Yes      | -          | The SUPIR model patch containing the weights and configuration for modifying the model.                                                                       |
| `vae`                | VAE        | Yes      | -          | The VAE (Variational Autoencoder) used for encoding the input image into a latent representation.                                                             |
| `image`              | IMAGE      | Yes      | -          | The input image used to guide the generation process. Only the first three color channels (RGB) are used.                                                     |
| `strength_start`     | FLOAT      | No       | 0.0 - 10.0 | Control strength at the start of sampling (high sigma). The influence of the image guidance begins at this value. (default: 1.0)                              |
| `strength_end`       | FLOAT      | No       | 0.0 - 10.0 | Control strength at the end of sampling (low sigma). Linearly interpolated from start. The influence of the image guidance ends at this value. (default: 1.0) |
| `restore_cfg`        | FLOAT      | No       | 0.0 - 20.0 | Pulls denoised output toward the input latent. Higher = stronger fidelity to input. 0 to disable. (default: 4.0)                                              |
| `restore_cfg_s_tmin` | FLOAT      | No       | 0.0 - 1.0  | Sigma threshold below which restore\_cfg is disabled. (default: 0.05)                                                                                         |

*Note:* The `image` input is processed to extract only the RGB channels. If an image with an alpha channel is provided, the alpha channel is ignored.

## Outputs

| Output Name | Data Type | Description                                                                                        |
| ----------- | --------- | -------------------------------------------------------------------------------------------------- |
| `model`     | MODEL     | The diffusion model with the SUPIR patch applied and any additional post-CFG functions configured. |

***

**Source fingerprint (SHA-256):** `41900f166aa7c0e325da874a3e250c56b94569822292785b1b3165705eb22e0c`


# ScaleROPE - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ScaleROPE

Complete documentation for the ScaleROPE node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ScaleROPE/en.md)

The ScaleROPE node allows you to modify the Rotary Position Embedding (ROPE) of a model by applying separate scaling and shifting factors to its X, Y, and T (time) components. This is an advanced, experimental node used to adjust the model's positional encoding behavior.

## Inputs

| Parameter | Data Type | Required | Range          | Description                                                                       |
| --------- | --------- | -------- | -------------- | --------------------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -              | The model whose ROPE parameters will be modified.                                 |
| `scale_x` | FLOAT     | No       | 0.0 - 100.0    | The scaling factor to apply to the X component of the ROPE (default: 1.0).        |
| `shift_x` | FLOAT     | No       | -256.0 - 256.0 | The shift value to apply to the X component of the ROPE (default: 0.0).           |
| `scale_y` | FLOAT     | No       | 0.0 - 100.0    | The scaling factor to apply to the Y component of the ROPE (default: 1.0).        |
| `shift_y` | FLOAT     | No       | -256.0 - 256.0 | The shift value to apply to the Y component of the ROPE (default: 0.0).           |
| `scale_t` | FLOAT     | No       | 0.0 - 100.0    | The scaling factor to apply to the T (time) component of the ROPE (default: 1.0). |
| `shift_t` | FLOAT     | No       | -256.0 - 256.0 | The shift value to apply to the T (time) component of the ROPE (default: 0.0).    |

## Outputs

| Output Name | Data Type | Description                                                          |
| ----------- | --------- | -------------------------------------------------------------------- |
| `model`     | MODEL     | The model with the new ROPE scaling and shifting parameters applied. |

***

**Source fingerprint (SHA-256):** `4899aaf380aefd7cb41593edb402f166c34e25029e82edddf718bb38e8c2339d`


# SetLatentNoiseMask - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetLatentNoiseMask

Complete documentation for the SetLatentNoiseMask node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to apply a noise mask to a set of latent samples. It modifies the input samples by integrating a specified mask, thereby altering their noise characteristics.

## Inputs

| Parameter | Data Type | Description                                                                                                                                   |
| --------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples` | `LATENT`  | The latent samples to which the noise mask will be applied. This parameter is crucial for determining the base content that will be modified. |
| `mask`    | `MASK`    | The mask to be applied to the latent samples. It defines the areas and intensity of noise alteration within the samples.                      |

## Outputs

| Parameter | Data Type | Description                                              |
| --------- | --------- | -------------------------------------------------------- |
| `latent`  | `LATENT`  | The modified latent samples with the applied noise mask. |


# StableCascade_EmptyLatentImage - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableCascade_EmptyLatentImage

Complete documentation for the StableCascade_EmptyLatentImage node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableCascade_EmptyLatentImage/en.md)

The StableCascade\_EmptyLatentImage node creates empty latent tensors for Stable Cascade models. It generates two separate latent representations - one for stage C and another for stage B - with appropriate dimensions based on the input resolution and compression settings. This node provides the starting point for the Stable Cascade generation pipeline.

## Inputs

| Parameter     | Data Type | Required | Range                  | Description                                                                                     |
| ------------- | --------- | -------- | ---------------------- | ----------------------------------------------------------------------------------------------- |
| `width`       | INT       | Yes      | 256 to MAX\_RESOLUTION | The width of the output image in pixels (default: 1024, step: 8)                                |
| `height`      | INT       | Yes      | 256 to MAX\_RESOLUTION | The height of the output image in pixels (default: 1024, step: 8)                               |
| `compression` | INT       | Yes      | 4 to 128               | The compression factor that determines the latent dimensions for stage C (default: 42, step: 1) |
| `batch_size`  | INT       | No       | 1 to 4096              | The number of latent samples to generate in a batch (default: 1)                                |

## Outputs

| Output Name | Data Type | Description                                                                                           |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------- |
| `stage_c`   | LATENT    | The stage C latent tensor with dimensions \[batch\_size, 16, height//compression, width//compression] |
| `stage_b`   | LATENT    | The stage B latent tensor with dimensions \[batch\_size, 4, height//4, width//4]                      |

***

**Source fingerprint (SHA-256):** `072c320d415acbc0ebc5b823855b64f0df29082d18b84a15ac63ec016e64ecf8`


# StableCascade_StageC_VAEEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StableCascade_StageC_VAEEncode

Complete documentation for the StableCascade_StageC_VAEEncode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StableCascade_StageC_VAEEncode/en.md)

The StableCascade\_StageC\_VAEEncode node processes an input image through a VAE encoder to generate latent representations for the Stable Cascade model. It first resizes the image based on a compression factor and the VAE's downscale ratio, then encodes the resized image. The node outputs two latent tensors: one for stage C (the actual encoded result) and one for stage B (a zero-filled placeholder).

## Inputs

| Parameter     | Data Type | Required | Range | Description                                                                                                                                                              |
| ------------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `image`       | IMAGE     | Yes      | -     | The input image to be encoded into latent space                                                                                                                          |
| `vae`         | VAE       | Yes      | -     | The VAE model used for encoding the image                                                                                                                                |
| `compression` | INT       | No       | 4-128 | The compression factor applied to the image before encoding. The image dimensions are divided by this value, then multiplied by the VAE's downscale ratio. (default: 42) |

## Outputs

| Output Name | Data Type | Description                                                                                                                                   |
| ----------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------- |
| `stage_c`   | LATENT    | The encoded latent representation for stage C of the Stable Cascade model                                                                     |
| `stage_b`   | LATENT    | A placeholder latent representation for stage B. Currently returns a zero-filled tensor with dimensions calculated from the input image size. |

***

**Source fingerprint (SHA-256):** `6ebdd035349744bc76ab294f16504672d3e79883fccc86d6ea057b4b15faef05`


# StyleModelLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StyleModelLoader

Complete documentation for the StyleModelLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node will detect models located in the `ComfyUI/models/style_models` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The StyleModelLoader node is designed to load a style model from a specified path. It focuses on retrieving and initializing style models that can be used to apply specific artistic styles to images, thereby enabling the customization of visual outputs based on the loaded style model.

## Inputs

| Parameter Name     | Comfy dtype    | Python dtype | Description                                                                                                                                                                                                                                  |
| ------------------ | -------------- | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `style_model_name` | COMBO\[STRING] | `str`        | Specifies the name of the style model to be loaded. This name is used to locate the model file within a predefined directory structure, allowing for the dynamic loading of different style models based on user input or application needs. |

## Outputs

| Parameter Name | Comfy dtype   | Python dtype | Description                                                                                                                                                                 |
| -------------- | ------------- | ------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `style_model`  | `STYLE_MODEL` | `StyleModel` | Returns the loaded style model, ready for use in applying styles to images. This enables the dynamic customization of visual outputs by applying different artistic styles. |


# TemporalScoreRescaling - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TemporalScoreRescaling

Complete documentation for the TemporalScoreRescaling node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TemporalScoreRescaling/en.md)

This node applies Temporal Score Rescaling (TSR) to a diffusion model. It modifies the model's sampling behavior by rescaling the predicted noise or score during the denoising process, which can steer the diversity of the generated output. This is implemented as a post-CFG (Classifier-Free Guidance) function.

## Inputs

| Parameter   | Data Type | Required | Range        | Description                                                                                                                                                                        |
| ----------- | --------- | -------- | ------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`     | MODEL     | Yes      | -            | The diffusion model to be patched with the TSR function.                                                                                                                           |
| `tsr_k`     | FLOAT     | No       | 0.01 - 100.0 | Controls the rescaling strength. Lower k produces more detailed results; higher k produces smoother results in image generation. Setting k = 1 disables rescaling. (default: 0.95) |
| `tsr_sigma` | FLOAT     | No       | 0.01 - 100.0 | Controls how early rescaling takes effect. Larger values take effect earlier. (default: 1.0)                                                                                       |

## Outputs

| Output Name     | Data Type | Description                                                                                              |
| --------------- | --------- | -------------------------------------------------------------------------------------------------------- |
| `patched_model` | MODEL     | The input model, now patched with the Temporal Score Rescaling function applied to its sampling process. |

***

**Source fingerprint (SHA-256):** `c558da8dea80131f705f3217740c4f9df3c9a7a6695e2c089f5798a726730bb8`


# TextEncodeAceStepAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeAceStepAudio

Complete documentation for the TextEncodeAceStepAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeAceStepAudio/en.md)

The TextEncodeAceStepAudio node processes text inputs for audio conditioning by combining tags and lyrics into tokens, then encoding them with adjustable lyrics strength. It takes a CLIP model along with text descriptions and lyrics, tokenizes them together, and generates conditioning data suitable for audio generation tasks. The node allows fine-tuning the influence of lyrics through a strength parameter that controls their impact on the final output.

## Inputs

| Parameter         | Data Type | Required | Range      | Description                                                                                     |
| ----------------- | --------- | -------- | ---------- | ----------------------------------------------------------------------------------------------- |
| `clip`            | CLIP      | Yes      | -          | The CLIP model used for tokenization and encoding                                               |
| `tags`            | STRING    | Yes      | -          | Text tags or descriptions for audio conditioning (supports multiline input and dynamic prompts) |
| `lyrics`          | STRING    | Yes      | -          | Lyrics text for audio conditioning (supports multiline input and dynamic prompts)               |
| `lyrics_strength` | FLOAT     | No       | 0.0 - 10.0 | Controls the strength of lyrics influence on the conditioning output (default: 1.0, step: 0.01) |

## Outputs

| Output Name    | Data Type    | Description                                                                                 |
| -------------- | ------------ | ------------------------------------------------------------------------------------------- |
| `conditioning` | CONDITIONING | The encoded conditioning data containing processed text tokens with applied lyrics strength |

***

**Source fingerprint (SHA-256):** `79cdc3b7d0728a7fdb771243bc1b30f252cc322892df634584698a8f2c4d1633`


# TextEncodeAceStepAudio1.5 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextEncodeAceStepAudio1.5

Complete documentation for the TextEncodeAceStepAudio1.5 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeAceStepAudio1.5/en.md)

The TextEncodeAceStepAudio1.5 node prepares text and audio-related metadata for use with the AceStepAudio 1.5 model. It takes descriptive tags, lyrics, and musical parameters, then uses a CLIP model to convert them into a conditioning format suitable for audio generation.

## Inputs

| Parameter              | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                | Description                                                                                                                                                                                    |
| ---------------------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip`                 | CLIP      | Yes      | N/A                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | The CLIP model used to tokenize and encode the input text.                                                                                                                                     |
| `tags`                 | STRING    | Yes      | N/A                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | Descriptive tags for the audio, such as genre, mood, or instruments. Supports multiline input and dynamic prompts.                                                                             |
| `lyrics`               | STRING    | Yes      | N/A                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | The lyrics for the audio track. Supports multiline input and dynamic prompts.                                                                                                                  |
| `seed`                 | INT       | No       | 0 to 18446744073709551615                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            | A random seed value for reproducible generation. Has a control\_after\_generate widget. Default: 0.                                                                                            |
| `bpm`                  | INT       | No       | 10 to 300                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            | The beats per minute (BPM) for the generated audio. Default: 120.                                                                                                                              |
| `duration`             | FLOAT     | No       | 0.0 to 2000.0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        | The desired duration of the audio in seconds. Default: 120.0.                                                                                                                                  |
| `timesignature`        | COMBO     | No       | `"2"`<br />`"3"`<br />`"4"`<br />`"6"`                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | The musical time signature.                                                                                                                                                                    |
| `language`             | COMBO     | No       | `"ar"`<br />`"az"`<br />`"bg"`<br />`"bn"`<br />`"ca"`<br />`"cs"`<br />`"da"`<br />`"de"`<br />`"el"`<br />`"en"`<br />`"es"`<br />`"fa"`<br />`"fi"`<br />`"fr"`<br />`"he"`<br />`"hi"`<br />`"hr"`<br />`"ht"`<br />`"hu"`<br />`"id"`<br />`"is"`<br />`"it"`<br />`"ja"`<br />`"ko"`<br />`"la"`<br />`"lt"`<br />`"ms"`<br />`"ne"`<br />`"nl"`<br />`"no"`<br />`"pa"`<br />`"pl"`<br />`"pt"`<br />`"ro"`<br />`"ru"`<br />`"sa"`<br />`"sk"`<br />`"sr"`<br />`"sv"`<br />`"sw"`<br />`"ta"`<br />`"te"`<br />`"th"`<br />`"tl"`<br />`"tr"`<br />`"uk"`<br />`"ur"`<br />`"vi"`<br />`"yue"`<br />`"zh"`<br />`"unknown"` | The language of the input text. Default: "en".                                                                                                                                                 |
| `keyscale`             | COMBO     | No       | `"C major"`<br />`"C minor"`<br />`"C# major"`<br />`"C# minor"`<br />`"Db major"`<br />`"Db minor"`<br />`"D major"`<br />`"D minor"`<br />`"D# major"`<br />`"D# minor"`<br />`"Eb major"`<br />`"Eb minor"`<br />`"E major"`<br />`"E minor"`<br />`"F major"`<br />`"F minor"`<br />`"F# major"`<br />`"F# minor"`<br />`"Gb major"`<br />`"Gb minor"`<br />`"G major"`<br />`"G minor"`<br />`"G# major"`<br />`"G# minor"`<br />`"Ab major"`<br />`"Ab minor"`<br />`"A major"`<br />`"A minor"`<br />`"A# major"`<br />`"A# minor"`<br />`"Bb major"`<br />`"Bb minor"`<br />`"B major"`<br />`"B minor"`                     | The musical key and scale (major or minor).                                                                                                                                                    |
| `generate_audio_codes` | BOOLEAN   | No       | N/A                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | Enable the LLM that generates audio codes. This can be slow but will increase the quality of the generated audio. Turn this off if you are giving the model an audio reference. Default: True. |
| `cfg_scale`            | FLOAT     | No       | 0.0 to 100.0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         | The classifier-free guidance scale. Higher values make the output more closely follow the prompt. Default: 2.0.                                                                                |
| `temperature`          | FLOAT     | No       | 0.0 to 2.0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           | A sampling temperature. Lower values make the output more deterministic. Default: 0.85.                                                                                                        |
| `top_p`                | FLOAT     | No       | 0.0 to 2000.0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        | The nucleus sampling probability (top-p). Default: 0.9.                                                                                                                                        |
| `top_k`                | INT       | No       | 0 to 100                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             | The number of highest probability tokens to consider (top-k). Default: 0.                                                                                                                      |
| `min_p`                | FLOAT     | No       | 0.0 to 1.0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           | The minimum probability threshold for token sampling (min-p). Default: 0.000.                                                                                                                  |

## Outputs

| Output Name    | Data Type    | Description                                                                                                 |
| -------------- | ------------ | ----------------------------------------------------------------------------------------------------------- |
| `CONDITIONING` | CONDITIONING | The conditioning data, which contains the encoded text and audio parameters for the AceStepAudio 1.5 model. |

***

**Source fingerprint (SHA-256):** `cf948180c3576cd484593f03e849c04857cfb57a198071123ed44ec7b5067521`


# TomePatchModel - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TomePatchModel

Complete documentation for the TomePatchModel node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TomePatchModel/en.md)

The TomePatchModel node applies Token Merging (ToMe) to a diffusion model to reduce computational requirements during inference. It works by selectively merging similar tokens in the attention mechanism, allowing the model to process fewer tokens while maintaining image quality. This technique helps speed up generation without significant quality loss.

## Inputs

| Parameter | Data Type | Required | Range     | Description                                                                                                                               |
| --------- | --------- | -------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -         | The diffusion model to apply token merging to                                                                                             |
| `ratio`   | FLOAT     | Yes      | 0.0 - 1.0 | The ratio of tokens to merge (default: 0.3). Higher values merge more tokens, resulting in greater speedup but potentially lower quality. |

## Outputs

| Output Name | Data Type | Description                                   |
| ----------- | --------- | --------------------------------------------- |
| `model`     | MODEL     | The modified model with token merging applied |

***

**Source fingerprint (SHA-256):** `f2549a504397ee2ba96a0fa5ad5c3e69da2cd0996087af439d151f1f33f4a51e`


# TrimVideoLatent - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TrimVideoLatent

Complete documentation for the TrimVideoLatent node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TrimVideoLatent/en.md)

The TrimVideoLatent node removes frames from the beginning of a video latent representation. It takes a latent video sample and trims off a specified number of frames from the start, returning the remaining portion of the video. This allows you to shorten video sequences by removing the initial frames.

## Inputs

| Parameter     | Data Type | Required | Range      | Description                                                                     |
| ------------- | --------- | -------- | ---------- | ------------------------------------------------------------------------------- |
| `samples`     | LATENT    | Yes      | -          | The input latent video representation containing the video frames to be trimmed |
| `trim_amount` | INT       | Yes      | 0 to 99999 | The number of frames to remove from the beginning of the video (default: 0)     |

## Outputs

| Output Name | Data Type | Description                                                                                            |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------ |
| `output`    | LATENT    | The trimmed latent video representation with the specified number of frames removed from the beginning |

***

**Source fingerprint (SHA-256):** `176aa42bb489ff6326057c79ff4dcd27543b96d3212e30af77eeeccd77d3926b`


# USOStyleReference - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/USOStyleReference

Complete documentation for the USOStyleReference node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/USOStyleReference/en.md)

The USOStyleReference node applies style reference patches to models using encoded image features from CLIP vision output. It creates a modified version of the input model by incorporating style information extracted from visual inputs, enabling style transfer or reference-based generation capabilities.

## Inputs

| Parameter            | Data Type            | Required | Range | Description                                                       |
| -------------------- | -------------------- | -------- | ----- | ----------------------------------------------------------------- |
| `model`              | MODEL                | Yes      | -     | The base model to apply the style reference patch to              |
| `model_patch`        | MODEL\_PATCH         | Yes      | -     | The model patch containing style reference information            |
| `clip_vision_output` | CLIP\_VISION\_OUTPUT | Yes      | -     | The encoded visual features extracted from CLIP vision processing |

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `model`     | MODEL     | The modified model with applied style reference patches |

***

**Source fingerprint (SHA-256):** `fd800fb927677da29e148bfa1b287efed82895860ce4b0241d662579d2c07ff4`


# UpscaleModelLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/UpscaleModelLoader

Complete documentation for the UpscaleModelLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node will detect models located in the `ComfyUI/models/upscale_models` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The UpscaleModelLoader node is designed for loading upscale models from a specified directory. It facilitates the retrieval and preparation of upscale models for image upscaling tasks, ensuring that the models are correctly loaded and configured for evaluation.

## Inputs

| Field        | Comfy dtype     | Description                                                                                                                                |
| ------------ | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
| `model_name` | `COMBO[STRING]` | Specifies the name of the upscale model to be loaded, identifying and retrieving the correct model file from the upscale models directory. |

## Outputs

| Field           | Comfy dtype     | Description                                                                            |
| --------------- | --------------- | -------------------------------------------------------------------------------------- |
| `upscale_model` | `UPSCALE_MODEL` | Returns the loaded and prepared upscale model, ready for use in image upscaling tasks. |


# VAEDecode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEDecode

Complete documentation for the VAEDecode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The VAEDecode node is designed for decoding latent representations into images using a specified Variational Autoencoder (VAE). It serves the purpose of generating images from compressed data representations, facilitating the reconstruction of images from their latent space encodings.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                                                                         |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `samples` | `LATENT`  | The 'samples' parameter represents the latent representations to be decoded into images. It is crucial for the decoding process as it provides the compressed data from which the images are reconstructed.                         |
| `vae`     | VAE       | The 'vae' parameter specifies the Variational Autoencoder model to be used for decoding the latent representations into images. It is essential for determining the decoding mechanism and the quality of the reconstructed images. |

## Outputs

| Parameter | Data Type | Description                                                                                                 |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------- |
| `image`   | `IMAGE`   | The output is an image reconstructed from the provided latent representation using the specified VAE model. |


# VAEDecodeAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEDecodeAudio

Complete documentation for the VAEDecodeAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEDecodeAudio/en.md)

The VAEDecodeAudio node converts latent representations back into audio waveforms using a Variational Autoencoder. It takes encoded audio samples and processes them through the VAE to reconstruct the original audio, applying normalization to ensure consistent output levels. The resulting audio is returned with a standard sample rate of 44100 Hz, or the sample rate from the input samples if provided.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                           |
| --------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------- |
| `samples` | LATENT    | Yes      | -     | The encoded audio samples in latent space that will be decoded back to audio waveform |
| `vae`     | VAE       | Yes      | -     | The Variational Autoencoder model used to decode the latent samples into audio        |

## Outputs

| Output Name | Data Type | Description                                                                                                                                   |
| ----------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------- |
| `AUDIO`     | AUDIO     | The decoded audio waveform with normalized volume and sample rate (default: 44100 Hz, or the sample rate from the input `samples` if present) |

***

**Source fingerprint (SHA-256):** `4736b987361bf16ad9c5db1a9f8593646fd7ffb37267aed4396285a2a0e6c1cc`


# VAEDecodeAudioTiled - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEDecodeAudioTiled

Complete documentation for the VAEDecodeAudioTiled node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEDecodeAudioTiled/en.md)

This node converts a compressed audio representation (latent samples) back into an audio waveform using a Variational Autoencoder (VAE). It processes the data in smaller, overlapping sections (tiles) to manage memory usage, making it suitable for handling longer audio sequences.

## Inputs

| Parameter   | Data Type | Required | Range      | Description                                                                                                                      |
| ----------- | --------- | -------- | ---------- | -------------------------------------------------------------------------------------------------------------------------------- |
| `samples`   | LATENT    | Yes      | N/A        | The compressed latent representation of the audio to be decoded.                                                                 |
| `vae`       | VAE       | Yes      | N/A        | The Variational Autoencoder model used to perform the decoding.                                                                  |
| `tile_size` | INT       | Yes      | 32 to 8192 | The size of each processing tile. The audio is decoded in sections of this length to conserve memory (default: 512).             |
| `overlap`   | INT       | Yes      | 0 to 1024  | The number of samples that adjacent tiles overlap. This helps to reduce artifacts at the boundaries between tiles (default: 64). |

## Outputs

| Output Name | Data Type | Description                 |
| ----------- | --------- | --------------------------- |
| `output`    | AUDIO     | The decoded audio waveform. |

***

**Source fingerprint (SHA-256):** `d846ec48856b8a1415101b8db06b5dd38b5d1222c117ea4f170daf3347ed1685`


# VAEDecodeHunyuan3D - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEDecodeHunyuan3D

Complete documentation for the VAEDecodeHunyuan3D node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEDecodeHunyuan3D/en.md)

The VAEDecodeHunyuan3D node converts latent representations into 3D voxel data using a VAE decoder. It processes the latent samples through the VAE model with configurable chunking and resolution settings to generate volumetric data suitable for 3D applications.

## Inputs

| Parameter           | Data Type | Required | Range       | Description                                                                             |
| ------------------- | --------- | -------- | ----------- | --------------------------------------------------------------------------------------- |
| `samples`           | LATENT    | Yes      | -           | The latent representation to be decoded into 3D voxel data                              |
| `vae`               | VAE       | Yes      | -           | The VAE model used for decoding the latent samples                                      |
| `num_chunks`        | INT       | Yes      | 1000-500000 | The number of chunks to split the processing into for memory management (default: 8000) |
| `octree_resolution` | INT       | Yes      | 16-512      | The resolution of the octree structure used for 3D voxel generation (default: 256)      |

## Outputs

| Output Name | Data Type | Description                                                        |
| ----------- | --------- | ------------------------------------------------------------------ |
| `voxels`    | VOXEL     | The generated 3D voxel data from the decoded latent representation |

***

**Source fingerprint (SHA-256):** `04818af007257ec0c73873dba703465960e7adae8a9b22649e118116c388da56`


# VAEEncode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEEncode

Complete documentation for the VAEEncode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed for encoding images into a latent space representation using a specified VAE model. It abstracts the complexity of the encoding process, providing a straightforward way to transform images into their latent representations.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                                                                               |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `pixels`  | `IMAGE`   | The 'pixels' parameter represents the image data to be encoded into the latent space. It plays a crucial role in determining the output latent representation by serving as the direct input for the encoding process.                    |
| `vae`     | VAE       | The 'vae' parameter specifies the Variational Autoencoder model to be used for encoding the image data into latent space. It is essential for defining the encoding mechanism and characteristics of the generated latent representation. |

## Outputs

| Parameter | Data Type | Description                                                                                                                |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The output is a latent space representation of the input image, encapsulating its essential features in a compressed form. |


# VAEEncodeAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEEncodeAudio

Complete documentation for the VAEEncodeAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VAEEncodeAudio/en.md)

The VAEEncodeAudio node converts audio data into a latent representation using a Variational Autoencoder (VAE). It takes audio input and processes it through the VAE to generate compressed latent samples that can be used for further audio generation or manipulation tasks. The node automatically resamples audio to match the VAE's expected sample rate if needed before encoding.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                  |
| --------- | --------- | -------- | ----- | ---------------------------------------------------------------------------- |
| `audio`   | AUDIO     | Yes      | -     | The audio data to encode, containing waveform and sample rate information    |
| `vae`     | VAE       | Yes      | -     | The Variational Autoencoder model used to encode the audio into latent space |

**Note:** The audio input is automatically resampled to match the VAE's expected sample rate (default: 44100 Hz) if the original sample rate differs from this value. If the input audio is None (e.g., the source video has no audio track), the node will raise an error.

## Outputs

| Output Name | Data Type | Description                                                                     |
| ----------- | --------- | ------------------------------------------------------------------------------- |
| `LATENT`    | LATENT    | The encoded audio representation in latent space, containing compressed samples |

***

**Source fingerprint (SHA-256):** `5c65a853a121a557a5342d337c27e2ea3acff48e6b911bdaf27c89d4c7dc01b6`


# VAEEncodeForInpaint - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAEEncodeForInpaint

Complete documentation for the VAEEncodeForInpaint node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed for encoding images into a latent representation suitable for inpainting tasks, incorporating additional preprocessing steps to adjust the input image and mask for optimal encoding by the VAE model.

## Inputs

| Parameter      | Data Type | Description                                                                                                                                                                                              |
| -------------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `pixels`       | `IMAGE`   | The input image to be encoded. This image undergoes preprocessing and resizing to match the VAE model's expected input dimensions before encoding.                                                       |
| `vae`          | VAE       | The VAE model used for encoding the image into its latent representation. It plays a crucial role in the transformation process, determining the quality and characteristics of the output latent space. |
| `mask`         | `MASK`    | A mask indicating the regions of the input image to be inpainted. It is used to modify the image before encoding, ensuring that the VAE focuses on the relevant areas.                                   |
| `grow_mask_by` | `INT`     | Specifies how much to expand the inpainting mask to ensure seamless transitions in the latent space. A larger value increases the area affected by inpainting.                                           |

## Outputs

| Parameter | Data Type | Description                                                                                                                        |
| --------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------- |
| `latent`  | `LATENT`  | The output includes the encoded latent representation of the image and a noise mask, both crucial for subsequent inpainting tasks. |


# VAELoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VAELoader

Complete documentation for the VAELoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node will detect models located in the `ComfyUI/models/vae` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The VAELoader node is designed for loading Variational Autoencoder (VAE) models, specifically tailored to handle both standard and approximate VAEs. It supports loading VAEs by name, including specialized handling for 'taesd' and 'taesdxl' models, and dynamically adjusts based on the VAE's specific configuration.

## Inputs

| Field      | Comfy dtype     | Description                                                                                                                                                                      |
| ---------- | --------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `vae_name` | `COMBO[STRING]` | Specifies the name of the VAE to be loaded, determining which VAE model is fetched and loaded, with support for a range of predefined VAE names including 'taesd' and 'taesdxl'. |

## Outputs

| Field | Data Type | Description                                                                                                                                                   |
| ----- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `vae` | `VAE`     | Returns the loaded VAE model, ready for further operations such as encoding or decoding. The output is a model object encapsulating the loaded model's state. |


# VOIDWarpedNoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VOIDWarpedNoise

Complete documentation for the VOIDWarpedNoise node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VOIDWarpedNoise/en.md)

## Overview

Generates temporally-correlated noise for the second pass of the VOID video refinement process. It takes the output video from Pass 1 and warps Gaussian noise along optical flow vectors, creating noise that moves consistently with the video content. This warped noise is used as the starting latent for Pass 2, which improves temporal consistency in the final output.

## Inputs

| Parameter      | Data Type     | Required | Range                          | Description                                                                                                             |
| -------------- | ------------- | -------- | ------------------------------ | ----------------------------------------------------------------------------------------------------------------------- |
| `optical_flow` | OPTICAL\_FLOW | Yes      | -                              | Optical flow model from OpticalFlowLoader (RAFT-large).                                                                 |
| `video`        | IMAGE         | Yes      | -                              | Pass 1 output video frames \[T, H, W, 3].                                                                               |
| `width`        | INT           | Yes      | 16 to MAX\_RESOLUTION (step 8) | Width of the output latent (default: 672).                                                                              |
| `height`       | INT           | Yes      | 16 to MAX\_RESOLUTION (step 8) | Height of the output latent (default: 384).                                                                             |
| `length`       | INT           | Yes      | 1 to MAX\_RESOLUTION (step 1)  | Number of pixel frames. Rounded down to make latent\_t even (patch\_size\_t=2 requirement), e.g. 49 → 45 (default: 45). |
| `batch_size`   | INT           | Yes      | 1 to 64                        | Number of identical noise sequences to generate (default: 1).                                                           |

**Note on `length` parameter:** The `length` value is automatically rounded down to the nearest valid value that produces an even `latent_t` dimension. This is required by the CogVideoX-Fun-V1.5 model's `patch_size_t=2` constraint. A warning is logged when rounding occurs.

## Outputs

| Output Name    | Data Type | Description                                                                                                                    |
| -------------- | --------- | ------------------------------------------------------------------------------------------------------------------------------ |
| `warped_noise` | LATENT    | A 5D tensor (B, C, T, H, W) containing optical-flow warped Gaussian noise, ready for use as the initial latent in VOID Pass 2. |

***

**Source fingerprint (SHA-256):** `fa7f08bd5e050324d1d9681243e82d66b1613b8694a5b69a5949b39974c6bddb`


# WanContextWindowsManual - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanContextWindowsManual

Complete documentation for the WanContextWindowsManual node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanContextWindowsManual/en.md)

The WAN Context Windows (Manual) node allows you to manually configure context windows for WAN-like models with 2-dimensional processing. It applies custom context window settings during sampling by specifying the window length, overlap, scheduling method, and fusion technique. This gives you precise control over how the model processes information across different context regions.

## Inputs

| Parameter          | Data Type | Required | Range                                                                                  | Description                                                                                     |
| ------------------ | --------- | -------- | -------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------- |
| `model`            | MODEL     | Yes      | -                                                                                      | The model to apply context windows to during sampling.                                          |
| `context_length`   | INT       | Yes      | 1 to 1048576                                                                           | The length of the context window (default: 81).                                                 |
| `context_overlap`  | INT       | Yes      | 0 to 1048576                                                                           | The overlap of the context window (default: 30).                                                |
| `context_schedule` | COMBO     | Yes      | `"static_standard"`<br />`"uniform_standard"`<br />`"uniform_looped"`<br />`"batched"` | The stride of the context window.                                                               |
| `context_stride`   | INT       | Yes      | 1 to 1048576                                                                           | The stride of the context window; only applicable to uniform schedules (default: 1).            |
| `closed_loop`      | BOOLEAN   | Yes      | -                                                                                      | Whether to close the context window loop; only applicable to looped schedules (default: False). |
| `fuse_method`      | COMBO     | Yes      | `"pyramid"`<br />`"gaussian"`<br />`"average"`<br />`"overlap"`                        | The method to use to fuse the context windows (default: "pyramid").                             |
| `freenoise`        | BOOLEAN   | Yes      | -                                                                                      | Whether to apply FreeNoise noise shuffling, improves window blending (default: False).          |

**Note:** The `context_stride` parameter only affects uniform schedules, and `closed_loop` only applies to looped schedules. The context length and overlap values are automatically adjusted to ensure minimum valid values during processing. The `fuse_method` parameter now includes additional options beyond just "pyramid".

## Outputs

| Output Name | Data Type | Description                                              |
| ----------- | --------- | -------------------------------------------------------- |
| `model`     | MODEL     | The model with the applied context window configuration. |

***

**Source fingerprint (SHA-256):** `941a12b45162fd97c21e071e8170ba7047487c0f312f20dac572ef1bc751c64d`


# unCLIPCheckpointLoader - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/unCLIPCheckpointLoader

Complete documentation for the unCLIPCheckpointLoader node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node will detect models located in the `ComfyUI/models/checkpoints` folder, and it will also read models from additional paths configured in the extra\_model\_paths.yaml file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder.

The unCLIPCheckpointLoader node is designed for loading checkpoints specifically tailored for unCLIP models. It facilitates the retrieval and initialization of models, CLIP vision modules, and VAEs from a specified checkpoint, streamlining the setup process for further operations or analyses.

## Inputs

| Field       | Comfy dtype     | Description                                                                                                                                                                                         |
| ----------- | --------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `ckpt_name` | `COMBO[STRING]` | Specifies the name of the checkpoint to be loaded, identifying and retrieving the correct checkpoint file from a predefined directory, determining the initialization of models and configurations. |

## Outputs

| Field         | Comfy dtype   | Description                                                                 | Python dtype      |
| ------------- | ------------- | --------------------------------------------------------------------------- | ----------------- |
| `model`       | `MODEL`       | Represents the primary model loaded from the checkpoint.                    | `torch.nn.Module` |
| `clip`        | `CLIP`        | Represents the CLIP module loaded from the checkpoint, if available.        | `torch.nn.Module` |
| `vae`         | `VAE`         | Represents the VAE module loaded from the checkpoint, if available.         | `torch.nn.Module` |
| `clip_vision` | `CLIP_VISION` | Represents the CLIP vision module loaded from the checkpoint, if available. | `torch.nn.Module` |


# unCLIPConditioning - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/unCLIPConditioning

Complete documentation for the unCLIPConditioning node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to integrate CLIP vision outputs into the conditioning process, adjusting the influence of these outputs based on specified strength and noise augmentation parameters. It enriches the conditioning with visual context, enhancing the generation process.

## Inputs

| Parameter            | Comfy dtype          | Description                                                                                                                       |
| -------------------- | -------------------- | --------------------------------------------------------------------------------------------------------------------------------- |
| `conditioning`       | `CONDITIONING`       | The base conditioning data to which the CLIP vision outputs are to be added, serving as the foundation for further modifications. |
| `clip_vision_output` | `CLIP_VISION_OUTPUT` | The output from a CLIP vision model, providing visual context that is integrated into the conditioning.                           |
| `strength`           | `FLOAT`              | Determines the intensity of the CLIP vision output's influence on the conditioning.                                               |
| `noise_augmentation` | `FLOAT`              | Specifies the level of noise augmentation to apply to the CLIP vision output before integrating it into the conditioning.         |

## Outputs

| Parameter      | Comfy dtype    | Description                                                                                                                 |
| -------------- | -------------- | --------------------------------------------------------------------------------------------------------------------------- |
| `conditioning` | `CONDITIONING` | The enriched conditioning data, now containing integrated CLIP vision outputs with applied strength and noise augmentation. |


# AddTextPrefix - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AddTextPrefix

Complete documentation for the AddTextPrefix node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AddTextPrefix/en.md)

The Add Text Prefix node modifies text by adding a specified string to the beginning of each input text. It takes the text and a prefix as input, then returns the combined result.

**Note:** This node is deprecated and superseded by the Concatenate Text node.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                   |
| --------- | --------- | -------- | ----- | ------------------------------------------------------------- |
| `text`    | STRING    | Yes      |       | The text to which the prefix will be added.                   |
| `prefix`  | STRING    | No       |       | The string to add to the beginning of the text (default: ""). |

## Outputs

| Output Name | Data Type | Description                                            |
| ----------- | --------- | ------------------------------------------------------ |
| `text`      | STRING    | The resulting text with the prefix added to the front. |

***

**Source fingerprint (SHA-256):** `71744a8dc3056b8f20eb2cb7ac16002ce86e214a660aa1d145f501d6d7dc5b53`


# AddTextSuffix - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AddTextSuffix

Complete documentation for the AddTextSuffix node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AddTextSuffix/en.md)

This node appends a specified suffix to the end of an input text string. It takes the original text and the suffix as inputs, then returns the combined result. **This node is deprecated** and superseded by the Concatenate Text node.

## Inputs

| Parameter | Data Type | Required | Range | Description                                          |
| --------- | --------- | -------- | ----- | ---------------------------------------------------- |
| `text`    | STRING    | Yes      |       | The original text to which the suffix will be added. |
| `suffix`  | STRING    | No       |       | The suffix to add to the text (default: "").         |

## Outputs

| Output Name | Data Type | Description                                            |
| ----------- | --------- | ------------------------------------------------------ |
| `text`      | STRING    | The resulting text after the suffix has been appended. |

***

**Source fingerprint (SHA-256):** `9b73a9352d21feb5041de550cc4463222c9ccbc1ef4937415d4dc8c5648d3a90`


# AlignYourStepsScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AlignYourStepsScheduler

Complete documentation for the AlignYourStepsScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AlignYourStepsScheduler/en.md)

The AlignYourStepsScheduler node generates sigma values for the denoising process based on different model types. It calculates appropriate noise levels for each step of the sampling process and adjusts the total number of steps according to the denoise parameter. This helps align the sampling steps with the specific requirements of different diffusion models.

## Inputs

| Parameter    | Data Type | Required | Range                              | Description                                                                                                      |
| ------------ | --------- | -------- | ---------------------------------- | ---------------------------------------------------------------------------------------------------------------- |
| `model_type` | STRING    | Yes      | `"SD1"`<br />`"SDXL"`<br />`"SVD"` | Specifies the type of model to use for sigma calculation (default: "SD1")                                        |
| `steps`      | INT       | Yes      | 1 to 10000                         | The total number of sampling steps to generate (default: 10)                                                     |
| `denoise`    | FLOAT     | Yes      | 0.0 to 1.0                         | Controls how much to denoise the image, where 1.0 uses all steps and lower values use fewer steps (default: 1.0) |

## Outputs

| Output Name | Data Type | Description                                                   |
| ----------- | --------- | ------------------------------------------------------------- |
| `sigmas`    | SIGMAS    | Returns the calculated sigma values for the denoising process |

***

**Source fingerprint (SHA-256):** `ea8694299147f6f28a1191f0f3c416c64cff9ca3a73bc54fa9319ab7eaab4ce9`


# AutogrowNamesTestNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AutogrowNamesTestNode

Complete documentation for the AutogrowNamesTestNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AutogrowNamesTestNode/en.md)

This node is a test for the Autogrow input feature. It takes a dynamic number of float inputs, each labeled with a specific name, and combines their values into a single comma-separated string.

## Inputs

| Parameter  | Data Type | Required | Range | Description                                                                                                                                                                         |
| ---------- | --------- | -------- | ----- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `autogrow` | FLOAT     | Yes      | N/A   | A dynamic input group. You can add multiple float inputs, each with a pre-defined name from the list: "a", "b", or "c". The node will accept any combination of these named inputs. |

**Note:** The `autogrow` input is dynamic. You can add or remove individual float inputs (named "a", "b", or "c") as needed for your workflow. The node processes all provided values.

## Outputs

| Output Name | Data Type | Description                                                                                        |
| ----------- | --------- | -------------------------------------------------------------------------------------------------- |
| `output`    | STRING    | A single string containing the values from all provided float inputs, joined together with commas. |

***

**Source fingerprint (SHA-256):** `7c9a6bdcbf7c65112d0810e5709a9d6d59f33c1980cd66fc475826565e35a1a9`


# AutogrowPrefixTestNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/AutogrowPrefixTestNode

Complete documentation for the AutogrowPrefixTestNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/AutogrowPrefixTestNode/en.md)

The AutogrowPrefixTestNode is a logic node designed to test the autogrow input feature. It accepts a dynamic number of float inputs, combines their values into a comma-separated string, and outputs that string.

## Inputs

| Parameter  | Data Type | Required | Range          | Description                                                                                                                                                       |
| ---------- | --------- | -------- | -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `autogrow` | AUTOGROW  | Yes      | 1 to 10 inputs | A dynamic input group that can accept between 1 and 10 float values. Each input in the group is a FLOAT type with a minimum value of 1 and a maximum value of 10. |

**Note:** The `autogrow` input is a special dynamic input. You can add multiple float inputs to this group, up to a maximum of 10. The node will process all provided values. Each individual float input is constrained to a range of 1 to 10.

## Outputs

| Output Name | Data Type | Description                                                                 |
| ----------- | --------- | --------------------------------------------------------------------------- |
| `output`    | STRING    | A single string containing all the input float values, separated by commas. |

***

**Source fingerprint (SHA-256):** `93e3e3d13f8f411206d09e34e7e3b734596af0a2ef066712d6dfbe9dc3eec0cf`


# BasicGuider - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BasicGuider

Complete documentation for the BasicGuider node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BasicGuider/en.md)

The BasicGuider node creates a simple guidance mechanism for the sampling process. It takes a model and conditioning data as inputs and produces a guider object that can be used to guide the generation process during sampling. This node provides the fundamental guidance functionality needed for controlled generation.

## Inputs

| Parameter      | Data Type    | Required | Range | Description                                              |
| -------------- | ------------ | -------- | ----- | -------------------------------------------------------- |
| `model`        | MODEL        | Yes      | -     | The model to be used for guidance                        |
| `conditioning` | CONDITIONING | Yes      | -     | The conditioning data that guides the generation process |

## Outputs

| Output Name | Data Type | Description                                                                      |
| ----------- | --------- | -------------------------------------------------------------------------------- |
| `GUIDER`    | GUIDER    | A guider object that can be used during the sampling process to guide generation |

***

**Source fingerprint (SHA-256):** `87b4662787829c4f00a5cc362f12b1c046fe836f9eb7d90aa40bd48f5cecdf0a`


# BasicScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BasicScheduler

Complete documentation for the BasicScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `BasicScheduler` node is designed to compute a sequence of sigma values for diffusion models based on the provided scheduler, model, and denoising parameters. It dynamically adjusts the total number of steps based on the denoise factor to fine-tune the diffusion process, providing precise "recipes" for different stages in advanced sampling processes that require fine control (such as multi-stage sampling).

## Inputs

| Parameter   | Data Type      | Input Type | Default | Range     | Metaphor Description                                                      | Technical Purpose                                          |
| ----------- | -------------- | ---------- | ------- | --------- | ------------------------------------------------------------------------- | ---------------------------------------------------------- |
| `model`     | MODEL          | Input      | -       | -         | **Canvas Type**: Different canvas materials need different paint formulas | Diffusion model object, determines sigma calculation basis |
| `scheduler` | COMBO\[STRING] | Widget     | -       | 9 options | **Mixing Technique**: Choose how paint concentration changes              | Scheduling algorithm, controls noise decay mode            |
| `steps`     | INT            | Widget     | 20      | 1-10000   | **Mixing Count**: 20 mixes vs 50 mixes precision difference               | Sampling steps, affects generation quality and speed       |
| `denoise`   | FLOAT          | Widget     | 1.0     | 0.0-1.0   | **Creation Intensity**: Control level from fine-tuning to repainting      | Denoising strength, supports partial repainting scenarios  |

### Scheduler Types

Based on source code `comfy.samplers.SCHEDULER_NAMES`, supports the following 9 schedulers:

| Scheduler Name        | Characteristics   | Use Cases                     | Noise Decay Pattern           |
| --------------------- | ----------------- | ----------------------------- | ----------------------------- |
| **normal**            | Standard linear   | General scenarios, balanced   | Uniform decay                 |
| **karras**            | Smooth transition | High quality, detail-rich     | Smooth non-linear decay       |
| **exponential**       | Exponential decay | Fast generation, efficiency   | Exponential rapid decay       |
| **sgm\_uniform**      | SGM uniform       | Specific model optimization   | SGM optimized decay           |
| **simple**            | Simple scheduling | Quick testing, basic use      | Simplified decay              |
| **ddim\_uniform**     | DDIM uniform      | DDIM sampling optimization    | DDIM specific decay           |
| **beta**              | Beta distribution | Special distribution needs    | Beta function decay           |
| **linear\_quadratic** | Linear quadratic  | Complex scenario optimization | Quadratic function decay      |
| **kl\_optimal**       | KL optimal        | Theoretical optimization      | KL divergence optimized decay |

## Outputs

| Parameter | Data Type | Output Type | Metaphor Description                                                           | Technical Meaning                                              |
| --------- | --------- | ----------- | ------------------------------------------------------------------------------ | -------------------------------------------------------------- |
| `sigmas`  | SIGMAS    | Output      | **Paint Recipe Chart**: Detailed paint concentration list for step-by-step use | Noise level sequence, guides diffusion model denoising process |

## Node Role: Artist's Color Mixing Assistant

Imagine you are an artist creating a clear image from a chaotic mixture of paint (noise). `BasicScheduler` acts like your **professional color mixing assistant**, whose job is to prepare a series of precise paint concentration recipes:

### Workflow

* **Step 1**: Use 90% concentration paint (high noise level)
* **Step 2**: Use 80% concentration paint
* **Step 3**: Use 70% concentration paint
* **...**
* **Final Step**: Use 0% concentration (clean canvas, no noise)

### Color Assistant's Special Skills

**Different mixing methods (scheduler)**:

* **"karras" mixing method**: Paint concentration changes very smoothly, like professional artist's gradient technique
* **"exponential" mixing method**: Paint concentration decreases rapidly, suitable for quick creation
* **"linear" mixing method**: Paint concentration decreases uniformly, stable and controllable

**Fine control (steps)**:

* **20 mixes**: Quick painting, efficiency priority
* **50 mixes**: Fine painting, quality priority

**Creation intensity (denoise)**:

* **1.0 = Complete new creation**: Start completely from blank canvas
* **0.5 = Half transformation**: Keep half of original painting, transform half
* **0.2 = Fine adjustment**: Only make subtle adjustments to original painting

### Collaboration with Other Nodes

`BasicScheduler` (Color Assistant) → Prepare Recipe → `SamplerCustom` (Artist) → Actual Painting → Completed Work


# BetaSamplingScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BetaSamplingScheduler

Complete documentation for the BetaSamplingScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BetaSamplingScheduler/en.md)

The BetaSamplingScheduler node generates a sequence of noise levels (sigmas) for the sampling process using a beta scheduling algorithm. It takes a model and configuration parameters to create a customized noise schedule that controls the denoising process during image generation. This scheduler allows fine-tuning of the noise reduction trajectory through alpha and beta parameters.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                                                             |
| --------- | --------- | -------- | ----------- | --------------------------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -           | The model used for sampling, which provides the model sampling object                   |
| `steps`   | INT       | Yes      | 1 to 10000  | The number of sampling steps to generate sigmas for (default: 20)                       |
| `alpha`   | FLOAT     | Yes      | 0.0 to 50.0 | Alpha parameter for the beta scheduler, controlling the scheduling curve (default: 0.6) |
| `beta`    | FLOAT     | Yes      | 0.0 to 50.0 | Beta parameter for the beta scheduler, controlling the scheduling curve (default: 0.6)  |

## Outputs

| Output Name | Data Type | Description                                                       |
| ----------- | --------- | ----------------------------------------------------------------- |
| `SIGMAS`    | SIGMAS    | A sequence of noise levels (sigmas) used for the sampling process |

***

**Source fingerprint (SHA-256):** `4be6f9ba853a1c8ff2b8f58ee3e37829a92e1fe9dc1f042fec20f22e04ae9d77`


# ByteDanceSeedNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceSeedNode

Complete documentation for the ByteDanceSeedNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceSeedNode/en.md)

## Overview

Generate text responses using ByteDance's Seed 2.0 models. Provide a text prompt and optionally include images or videos for multimodal context.

## Inputs

| Parameter       | Data Type | Required | Range                                                          | Description                                                                                                  |
| --------------- | --------- | -------- | -------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------ |
| `prompt`        | STRING    | Yes      | N/A                                                            | Text input to the model.                                                                                     |
| `model`         | COMBO     | Yes      | `"Seed 2.0 Pro"`<br />`"Seed 2.0 Lite"`<br />`"Seed 2.0 Mini"` | The Seed model used to generate the response.                                                                |
| `seed`          | INT       | Yes      | 0 to 2147483647                                                | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) |
| `system_prompt` | STRING    | No       | N/A                                                            | Foundational instructions that dictate the model's behavior. (default: "")                                   |

**Note on `model` parameter:** The `model` parameter is a dynamic combo that also accepts images and videos. You can connect image and video inputs to this parameter to provide multimodal context. A maximum of 20 images and 4 videos are supported per request.

## Outputs

| Output Name | Data Type | Description                                      |
| ----------- | --------- | ------------------------------------------------ |
| `output`    | STRING    | The generated text response from the Seed model. |

***

**Source fingerprint (SHA-256):** `d1ef73cf72e88216d40c0cf727f90c40cf783cecabe3be0e7530fe72dba6c172`


# CFGGuider - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CFGGuider

Complete documentation for the CFGGuider node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CFGGuider/en.md)

The CFGGuider node creates a guidance system for controlling the sampling process in image generation. It takes a model along with positive and negative conditioning inputs, then applies a classifier-free guidance scale to steer the generation toward desired content while avoiding unwanted elements. This node outputs a guider object that can be used by sampling nodes to control the image generation direction.

## Inputs

| Parameter  | Data Type    | Required | Range        | Description                                                                                                             |
| ---------- | ------------ | -------- | ------------ | ----------------------------------------------------------------------------------------------------------------------- |
| `model`    | MODEL        | Yes      | -            | The model to be used for guidance                                                                                       |
| `positive` | CONDITIONING | Yes      | -            | The positive conditioning that guides the generation toward desired content                                             |
| `negative` | CONDITIONING | Yes      | -            | The negative conditioning that steers the generation away from unwanted content                                         |
| `cfg`      | FLOAT        | Yes      | 0.0 to 100.0 | The classifier-free guidance scale that controls how strongly the conditioning influences the generation (default: 8.0) |

## Outputs

| Output Name | Data Type | Description                                                                            |
| ----------- | --------- | -------------------------------------------------------------------------------------- |
| `GUIDER`    | GUIDER    | A guider object that can be passed to sampling nodes to control the generation process |

***

**Source fingerprint (SHA-256):** `a723a359d0e0ac6ae83dc59d9eb459444b0c4a5361d54d54e22fb03ea34c16be`


# CaseConverter - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CaseConverter

Complete documentation for the CaseConverter node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CaseConverter/en.md)

The Case Converter node transforms text strings into different letter case formats. It takes an input string and converts it based on the selected mode, producing an output string with the specified case formatting applied. The node supports four different case conversion options to modify the capitalization of your text.

## Inputs

| Parameter | Data Type | Required | Range                                                                    | Description                                                |
| --------- | --------- | -------- | ------------------------------------------------------------------------ | ---------------------------------------------------------- |
| `string`  | STRING    | Yes      | -                                                                        | The text string to be converted to a different case format |
| `mode`    | STRING    | Yes      | `"UPPERCASE"`<br />`"lowercase"`<br />`"Capitalize"`<br />`"Title Case"` | The case conversion mode to apply (default: `"UPPERCASE"`) |

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `output`    | STRING    | The input string converted to the specified case format |

***

**Source fingerprint (SHA-256):** `6cc933ec8a245ff454195b699ab7d72d2a014ec9a6e920a8c875acf7eb77e01a`


# ClaudeNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ClaudeNode

Complete documentation for the ClaudeNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ClaudeNode/en.md)

## Overview

Generate text responses from an Anthropic Claude model. This node sends a text prompt and optional images to a Claude model and returns the generated text response.

## Inputs

| Parameter       | Data Type | Required | Range                                                                                     | Description                                                                                                  |
| --------------- | --------- | -------- | ----------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------ |
| `prompt`        | STRING    | Yes      | N/A                                                                                       | Text input to the model. (default: empty string)                                                             |
| `model`         | COMBO     | Yes      | `"Opus 4.7"`<br />`"Opus 4.6"`<br />`"Sonnet 4.6"`<br />`"Sonnet 4.5"`<br />`"Haiku 4.5"` | The Claude model used to generate the response.                                                              |
| `seed`          | INT       | Yes      | 0 to 2147483647                                                                           | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0) |
| `images`        | IMAGE     | No       | 0 to 20 images                                                                            | Optional image(s) to use as context for the model. Up to 20 images.                                          |
| `system_prompt` | STRING    | No       | N/A                                                                                       | Foundational instructions that dictate the model's behavior. (default: empty string)                         |

### Parameter Constraints

* **Image Limit**: A maximum of 20 images can be provided per request.
* **Temperature Handling**: When thinking is enabled or when using the "Opus 4.7" model, the temperature parameter is automatically unset (defaults to 1.0) as required by the Anthropic API. For other models, temperature can be set via the model configuration.
* **Thinking/Reasoning**: The model configuration includes a `reasoning_effort` setting that controls whether thinking is enabled. When enabled, the node automatically configures the appropriate thinking mode (adaptive or budget-based) depending on the selected model.

## Outputs

| Output Name | Data Type | Description                                                                                                             |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------------------- |
| `output`    | STRING    | The generated text response from the Claude model. Returns "Empty response from Claude model." if no text is generated. |

***

**Source fingerprint (SHA-256):** `e3bab004535d4d406582aa42f28bb64a2988f8331788d51ec1fa4e943d8d4382`


# ComboOptionTestNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComboOptionTestNode

Complete documentation for the ComboOptionTestNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComboOptionTestNode/en.md)

The ComboOptionTestNode is a logic node designed to test and pass through combo box selections. It takes two combo box inputs, each with a predefined set of options, and outputs the selected values directly without modification.

## Inputs

| Parameter | Data Type | Required | Range                                         | Description                                                      |
| --------- | --------- | -------- | --------------------------------------------- | ---------------------------------------------------------------- |
| `combo`   | COMBO     | Yes      | `"option1"`<br />`"option2"`<br />`"option3"` | The first selection from a set of three test options.            |
| `combo2`  | COMBO     | Yes      | `"option4"`<br />`"option5"`<br />`"option6"` | The second selection from a different set of three test options. |

## Outputs

| Output Name | Data Type | Description                                                      |
| ----------- | --------- | ---------------------------------------------------------------- |
| `output_1`  | COMBO     | Outputs the value selected from the first combo box (`combo`).   |
| `output_2`  | COMBO     | Outputs the value selected from the second combo box (`combo2`). |

***

**Source fingerprint (SHA-256):** `efa45d1310ff9c623afb858b6f561739c3d7ee9fc84b57c64746693a27906bec`


# ComfyAndNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyAndNode

Complete documentation for the ComfyAndNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyAndNode/en.md)

## Overview

The And node performs a logical AND operation on a set of input values. It returns `true` only if all of the provided values are considered truthy according to Python's truthiness rules. This node is useful for checking that multiple conditions are all met before proceeding.

## Inputs

| Parameter | Data Type | Required | Range            | Description                                                                                                                     |
| --------- | --------- | -------- | ---------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| `values`  | ANY       | Yes      | 1 or more values | A list of values to evaluate. The node accepts at least one value, and you can add more by clicking the "+" button on the node. |

**Note:** The node uses Python's truthiness rules to determine if a value is `true` or `false`. For example, an empty string, the number 0, an empty list, and `None` are all considered `false`. All other values are considered `true`.

## Outputs

| Output Name | Data Type | Description                                                               |
| ----------- | --------- | ------------------------------------------------------------------------- |
| `BOOLEAN`   | BOOLEAN   | Returns `true` if all input values are truthy, otherwise returns `false`. |

***

**Source fingerprint (SHA-256):** `fd9d18ce698472a7e35ad3082f2ccff8ae264b11bd887a498f929cd877ff38c4`


# ComfyNotNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyNotNode

Complete documentation for the ComfyNotNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyNotNode/en.md)

## Overview

The Not node performs a logical NOT operation on any input value. It returns True if the input value is considered falsy (like 0, empty string, None, False), and returns False if the input value is truthy. It uses Python's standard rules for determining truthiness.

## Inputs

| Parameter | Data Type | Required | Range     | Description                                                                                              |
| --------- | --------- | -------- | --------- | -------------------------------------------------------------------------------------------------------- |
| `value`   | ANY       | Yes      | Any value | The input value to be inverted. Any data type is accepted and evaluated using Python's truthiness rules. |

## Outputs

| Output Name | Data Type | Description                                                                                               |
| ----------- | --------- | --------------------------------------------------------------------------------------------------------- |
| `output`    | BOOLEAN   | The logical inverse of the input value. Returns True if the input is falsy, False if the input is truthy. |

***

**Source fingerprint (SHA-256):** `fd8f940218538fce28079bc836379703c0e3c04f80351520497855c464176877`


# ComfyOrNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyOrNode

Complete documentation for the ComfyOrNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyOrNode/en.md)

# ComfyOrNode

The ComfyOrNode performs a logical OR operation on a set of input values. It returns `true` if any of the provided values are considered truthy according to Python's standard truthiness rules.

## Inputs

| Parameter | Data Type | Required | Range                    | Description                                                                                                                                          |
| --------- | --------- | -------- | ------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------- |
| `value`   | ANY       | Yes      | Multiple values accepted | A value to evaluate for truthiness. You can provide multiple values by adding more inputs. The node returns `true` if any of these values is truthy. |

**Note:** The node accepts a minimum of 1 input value. You can add more inputs as needed using the autogrow feature.

## Outputs

| Output Name | Data Type | Description                                                                                         |
| ----------- | --------- | --------------------------------------------------------------------------------------------------- |
| `BOOLEAN`   | BOOLEAN   | Returns `true` if any of the input values is truthy; returns `false` if all input values are falsy. |

***

**Source fingerprint (SHA-256):** `00c60d5c80bbddc993af0bcd92e35dc77f153731329c23a6e4e9a980709111b1`


# ComfySoftSwitchNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfySoftSwitchNode

Complete documentation for the ComfySoftSwitchNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfySoftSwitchNode/en.md)

The Soft Switch node selects between two possible input values based on a boolean condition. It outputs the value from the `on_true` input when the `switch` is true, and the value from the `on_false` input when the `switch` is false. This node is designed to be lazy, meaning it only evaluates the input that is needed based on the switch state.

## Inputs

| Parameter  | Data Type   | Required | Range | Description                                                                                                                                                  |
| ---------- | ----------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `switch`   | BOOLEAN     | Yes      |       | The boolean condition that determines which input to pass through. When true, the `on_true` input is selected. When false, the `on_false` input is selected. |
| `on_false` | MATCH\_TYPE | No       |       | The value to output when the `switch` condition is false. This input is optional, but at least one of `on_false` or `on_true` must be connected.             |
| `on_true`  | MATCH\_TYPE | No       |       | The value to output when the `switch` condition is true. This input is optional, but at least one of `on_false` or `on_true` must be connected.              |

**Note:** The `on_false` and `on_true` inputs must be of the same data type, as defined by the node's internal template. At least one of these two inputs must be connected for the node to function.

## Outputs

| Output Name | Data Type   | Description                                                                                     |
| ----------- | ----------- | ----------------------------------------------------------------------------------------------- |
| `output`    | MATCH\_TYPE | The selected value. It will match the data type of the connected `on_false` or `on_true` input. |

***

**Source fingerprint (SHA-256):** `3ddfebaf67642f5bd79b0de38605f93507ede00d95e98cd78ec295f8de98d743`


# ComfySwitchNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfySwitchNode

Complete documentation for the ComfySwitchNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfySwitchNode/en.md)

The Switch node selects between two possible inputs based on a boolean condition. It outputs the `on_true` input when the `switch` is enabled, and the `on_false` input when the `switch` is disabled. This allows you to create conditional logic and choose different data paths in your workflow.

## Inputs

| Parameter  | Data Type   | Required | Range | Description                                                                                                                                                                     |
| ---------- | ----------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `switch`   | BOOLEAN     | Yes      |       | A boolean condition that determines which input to pass through. When enabled (true), the `on_true` input is selected. When disabled (false), the `on_false` input is selected. |
| `on_false` | MATCH\_TYPE | No       |       | The data to be passed to the output when the `switch` is disabled (false). This input is only required when the `switch` is false.                                              |
| `on_true`  | MATCH\_TYPE | No       |       | The data to be passed to the output when the `switch` is enabled (true). This input is only required when the `switch` is true.                                                 |

**Note on Input Requirements:** The `on_false` and `on_true` inputs are conditionally required. The node will request the `on_true` input only when the `switch` is true, and the `on_false` input only when the `switch` is false. Both inputs must be of the same data type.

## Outputs

| Output Name | Data Type   | Description                                                                                                                                                  |
| ----------- | ----------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `output`    | MATCH\_TYPE | The selected data. This will be the value from the `on_true` input if the `switch` is true, or the value from the `on_false` input if the `switch` is false. |

***

**Source fingerprint (SHA-256):** `6709dc66cf1c52bb31bde2cccd70324691261a03dfbab813b7196e20c0a4cb63`


# ConvertStringToComboNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ConvertStringToComboNode

Complete documentation for the ConvertStringToComboNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ConvertStringToComboNode/en.md)

The Convert String to Combo node takes a text string as input and converts it into a Combo data type. This allows you to use a text value as a selection for other nodes that require a Combo input. It simply passes the string value through unchanged but changes its data type.

## Inputs

| Parameter | Data Type | Required | Range | Description                                        |
| --------- | --------- | -------- | ----- | -------------------------------------------------- |
| `string`  | STRING    | Yes      | N/A   | The text string to be converted into a Combo type. |

## Outputs

| Output Name | Data Type | Description                                           |
| ----------- | --------- | ----------------------------------------------------- |
| `output`    | COMBO     | The input string, now formatted as a Combo data type. |

***

**Source fingerprint (SHA-256):** `46ca4f38a4b1054bc6c5ff5c54551fe6c8061cfb8740a3ef46b64a30a05cec05`


# DCTestNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DCTestNode

Complete documentation for the DCTestNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DCTestNode/en.md)

The DCTestNode is a logic node that returns different types of data based on a user's selection from a dynamic combo box. It acts as a conditional router, where the chosen option determines which input field is active and what type of value the node will output.

## Inputs

| Parameter  | Data Type | Required | Range                                                          | Description                                                                                                                          |
| ---------- | --------- | -------- | -------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------ |
| `combo`    | COMBO     | Yes      | `"option1"`<br />`"option2"`<br />`"option3"`<br />`"option4"` | The main selection that determines which input field is active and what the node will output.                                        |
| `string`   | STRING    | No       | -                                                              | A text input field. This field is only active and required when `combo` is set to `"option1"`.                                       |
| `integer`  | INT       | No       | -                                                              | A whole number input field. This field is only active and required when `combo` is set to `"option2"`.                               |
| `image`    | IMAGE     | No       | -                                                              | An image input field. This field is only active and required when `combo` is set to `"option3"`.                                     |
| `subcombo` | COMBO     | No       | `"opt1"`<br />`"opt2"`                                         | A secondary selection that appears when `combo` is set to `"option4"`. It determines which nested input fields are active.           |
| `float_x`  | FLOAT     | No       | -                                                              | A decimal number input. This field is only active and required when `combo` is set to `"option4"` and `subcombo` is set to `"opt1"`. |
| `float_y`  | FLOAT     | No       | -                                                              | A decimal number input. This field is only active and required when `combo` is set to `"option4"` and `subcombo` is set to `"opt1"`. |
| `mask1`    | MASK      | No       | -                                                              | A mask input field. This field is only active when `combo` is set to `"option4"` and `subcombo` is set to `"opt2"`. It is optional.  |

**Parameter Constraints:**

* The `combo` parameter controls the visibility and requirement of all other input fields. Only the inputs associated with the selected `combo` option will be shown and are required (except for `mask1` which is optional).
* When `combo` is set to `"option4"`, the `subcombo` parameter becomes required and controls a second set of nested inputs (`float_x`/`float_y` or `mask1`).

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                               |
| ----------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `output`    | ANYTYPE   | The output depends on the selected `combo` option. It can be a STRING (`"option1"`), an INT (`"option2"`), an IMAGE (`"option3"`), or a string representation of the `subcombo` dictionary (`"option4"`). |

***

**Source fingerprint (SHA-256):** `3a307bad068ef0721fff622c94337ca36fdca981c35b246ae9d5beb183be1620`


# DisableNoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DisableNoise

Complete documentation for the DisableNoise node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DisableNoise/en.md)

The DisableNoise node provides an empty noise configuration that can be used to disable noise generation in sampling processes. It returns a special noise object that contains no noise data, allowing other nodes to skip noise-related operations when connected to this output.

## Inputs

| Parameter             | Data Type | Required | Range | Description                                      |
| --------------------- | --------- | -------- | ----- | ------------------------------------------------ |
| *No input parameters* | -         | -        | -     | This node does not require any input parameters. |

## Outputs

| Output Name | Data Type | Description                                                                                              |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------- |
| `NOISE`     | NOISE     | Returns an empty noise configuration that can be used to disable noise generation in sampling processes. |

***

**Source fingerprint (SHA-256):** `2453a37e98083b879a91c23d6342b9420a16783b78719117a38de627800381b4`


# DualCFGGuider - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/DualCFGGuider

Complete documentation for the DualCFGGuider node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/DualCFGGuider/en.md)

The DualCFGGuider node creates a guidance system for dual classifier-free guidance sampling. It combines two positive conditioning inputs with one negative conditioning input, applying different guidance scales to each conditioning pair to control the influence of each prompt on the generated output.

## Inputs

| Parameter            | Data Type    | Required | Range                   | Description                                                                                                         |
| -------------------- | ------------ | -------- | ----------------------- | ------------------------------------------------------------------------------------------------------------------- |
| `model`              | MODEL        | Yes      | -                       | The model to use for guidance                                                                                       |
| `cond1`              | CONDITIONING | Yes      | -                       | The first positive conditioning input                                                                               |
| `cond2`              | CONDITIONING | Yes      | -                       | The second positive conditioning input                                                                              |
| `negative`           | CONDITIONING | Yes      | -                       | The negative conditioning input                                                                                     |
| `cfg_conds`          | FLOAT        | Yes      | 0.0 - 100.0             | Guidance scale for the first positive conditioning (default: 8.0)                                                   |
| `cfg_cond2_negative` | FLOAT        | Yes      | 0.0 - 100.0             | Guidance scale for the second positive and negative conditioning (default: 8.0)                                     |
| `style`              | COMBO        | Yes      | "regular"<br />"nested" | The guidance style to apply (default: "regular"). When set to "nested", the guidance is applied in a nested fashion |

## Outputs

| Output Name | Data Type | Description                                              |
| ----------- | --------- | -------------------------------------------------------- |
| `GUIDER`    | GUIDER    | A configured guidance system ready for use with sampling |

***

**Source fingerprint (SHA-256):** `5440fb55429b8c30ef88ee0eff74c8a54916b1ce644f93d5d0d5742b5056637d`


# ExponentialScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ExponentialScheduler

Complete documentation for the ExponentialScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `ExponentialScheduler` node is designed to generate a sequence of sigma values following an exponential schedule for diffusion sampling processes. It provides a customizable approach to control the noise levels applied at each step of the diffusion process, allowing for fine-tuning of the sampling behavior.

## Inputs

| Parameter   | Data Type | Description                                                                                                                                                                     |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `steps`     | INT       | Specifies the number of steps in the diffusion process. It influences the length of the generated sigma sequence and thus the granularity of the noise application.             |
| `sigma_max` | FLOAT     | Defines the maximum sigma value, setting the upper limit of noise intensity in the diffusion process. It plays a crucial role in determining the range of noise levels applied. |
| `sigma_min` | FLOAT     | Sets the minimum sigma value, establishing the lower boundary of noise intensity. This parameter helps in fine-tuning the starting point of the noise application.              |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                          |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `sigmas`  | SIGMAS    | A sequence of sigma values generated according to the exponential schedule. These values are used to control the noise levels at each step of the diffusion process. |


# ExtendIntermediateSigmas - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ExtendIntermediateSigmas

Complete documentation for the ExtendIntermediateSigmas node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ExtendIntermediateSigmas/en.md)

The ExtendIntermediateSigmas node takes an existing sequence of sigma values and inserts additional intermediate sigma values between them. It allows you to specify how many extra steps to add, the spacing method for interpolation, and optional start and end sigma boundaries to control where the extension occurs within the sigma sequence.

## Inputs

| Parameter        | Data Type | Required | Range                                    | Description                                                                                                    |
| ---------------- | --------- | -------- | ---------------------------------------- | -------------------------------------------------------------------------------------------------------------- |
| `sigmas`         | SIGMAS    | Yes      | -                                        | The input sigma sequence to extend with intermediate values                                                    |
| `steps`          | INT       | Yes      | 1 to 100                                 | Number of intermediate steps to insert between existing sigmas (default: 2)                                    |
| `start_at_sigma` | FLOAT     | Yes      | -1.0 to 20000.0                          | Upper sigma boundary for extension - only extend sigmas below this value (default: -1.0, which means infinity) |
| `end_at_sigma`   | FLOAT     | Yes      | 0.0 to 20000.0                           | Lower sigma boundary for extension - only extend sigmas above this value (default: 12.0)                       |
| `spacing`        | COMBO     | Yes      | `"linear"`<br />`"cosine"`<br />`"sine"` | The interpolation method for spacing the intermediate sigma values (default: "linear")                         |

**Note:** The node only inserts intermediate sigmas between existing sigma pairs where both the current sigma is less than or equal to `start_at_sigma` and greater than or equal to `end_at_sigma`. When `start_at_sigma` is set to -1.0, it's treated as infinity, meaning only the `end_at_sigma` lower boundary applies.

## Outputs

| Output Name | Data Type | Description                                                              |
| ----------- | --------- | ------------------------------------------------------------------------ |
| `sigmas`    | SIGMAS    | The extended sigma sequence with additional intermediate values inserted |

***

**Source fingerprint (SHA-256):** `111cb74aad64d8d9b2bebd10406c0f4ce718367bde96102104d385d387cef8e5`


# FlipSigmas - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FlipSigmas

Complete documentation for the FlipSigmas node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The `FlipSigmas` node is designed to manipulate the sequence of sigma values used in diffusion models by reversing their order and ensuring the first value is non-zero if originally zero. This operation is crucial for adapting the noise levels in reverse order, facilitating the generation process in models that operate by gradually reducing noise from data.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                                                                                    |
| --------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `sigmas`  | `SIGMAS`  | The 'sigmas' parameter represents the sequence of sigma values to be flipped. This sequence is crucial for controlling the noise levels applied during the diffusion process, and flipping it is essential for the reverse generation process. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                                 |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `sigmas`  | `SIGMAS`  | The output is the modified sequence of sigma values, flipped and adjusted to ensure the first value is non-zero if originally zero, ready for use in subsequent diffusion model operations. |


# Flux2Scheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Flux2Scheduler

Complete documentation for the Flux2Scheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Flux2Scheduler/en.md)

The Flux2Scheduler node generates a sequence of noise levels (sigmas) for the denoising process, specifically tailored for the Flux model. It calculates a schedule based on the number of denoising steps and the dimensions of the target image, which influences the progression of noise removal during image generation.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                                                                                                                  |
| --------- | --------- | -------- | ----------- | -------------------------------------------------------------------------------------------------------------------------------------------- |
| `steps`   | INT       | Yes      | 1 to 4096   | The number of denoising steps to perform. A higher value typically leads to more detailed results but takes longer to process (default: 20). |
| `width`   | INT       | Yes      | 16 to 16384 | The width of the image to be generated, in pixels. This value influences the noise schedule calculation (default: 1024).                     |
| `height`  | INT       | Yes      | 16 to 16384 | The height of the image to be generated, in pixels. This value influences the noise schedule calculation (default: 1024).                    |

## Outputs

| Output Name | Data Type | Description                                                                                   |
| ----------- | --------- | --------------------------------------------------------------------------------------------- |
| `sigmas`    | SIGMAS    | A sequence of noise level values (sigmas) that define the denoising schedule for the sampler. |

***

**Source fingerprint (SHA-256):** `8276ee111ffc2146f9aff5852e2abf469137aecbf7ed098c521045d206cdc104`


# GITSScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GITSScheduler

Complete documentation for the GITSScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GITSScheduler/en.md)

The GITSScheduler node generates noise schedule sigmas for the GITS (Generative Iterative Time Steps) sampling method. It calculates sigma values based on a coefficient parameter and number of steps, with an optional denoising factor that can reduce the total steps used. The node uses pre-defined noise levels and interpolation to create the final sigma schedule.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                                                  |
| --------- | --------- | -------- | ----------- | ---------------------------------------------------------------------------- |
| `coeff`   | FLOAT     | Yes      | 0.80 - 1.50 | The coefficient value that controls the noise schedule curve (default: 1.20) |
| `steps`   | INT       | Yes      | 2 - 1000    | The total number of sampling steps to generate sigmas for (default: 10)      |
| `denoise` | FLOAT     | Yes      | 0.0 - 1.0   | Denoising factor that reduces the number of steps used (default: 1.0)        |

**Note:** When `denoise` is set to 0.0, the node returns an empty tensor. When `denoise` is less than 1.0, the actual number of steps used is calculated as `round(steps * denoise)`. For steps greater than 20, the node uses log-linear interpolation to extend the pre-defined noise levels to the desired number of steps.

## Outputs

| Output Name | Data Type | Description                                       |
| ----------- | --------- | ------------------------------------------------- |
| `sigmas`    | SIGMAS    | The generated sigma values for the noise schedule |

***

**Source fingerprint (SHA-256):** `e58c8c1c0e7cbf79554040a6684f12c1a2c59c69bb50770f9577a13d76ac8eb3`


# GeminiInputFiles - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiInputFiles

Complete documentation for the GeminiInputFiles node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiInputFiles/en.md)

Loads and formats input files for use with the Gemini API. This node allows users to include text (.txt) and PDF (.pdf) files as input context for the Gemini model. Files are converted to the appropriate format required by the API and can be chained together to include multiple files in a single request.

## Inputs

| Parameter            | Data Type            | Required | Range                                                             | Description                                                                                                                                                                     |
| -------------------- | -------------------- | -------- | ----------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `file`               | COMBO                | Yes      | Multiple options available (only .txt and .pdf files under 20 MB) | Input files to include as context for the model. Only accepts text (.txt) and PDF (.pdf) files for now. Files must be smaller than the maximum input file size limit (20 MB).   |
| `GEMINI_INPUT_FILES` | GEMINI\_INPUT\_FILES | No       | N/A                                                               | An optional additional file(s) to batch together with the file loaded from this node. Allows chaining of input files so that a single message can include multiple input files. |

**Note:** The `file` parameter only displays text (.txt) and PDF (.pdf) files that are smaller than 20 MB. Files are automatically filtered and sorted by name.

## Outputs

| Output Name          | Data Type            | Description                                                                                                                |
| -------------------- | -------------------- | -------------------------------------------------------------------------------------------------------------------------- |
| `GEMINI_INPUT_FILES` | GEMINI\_INPUT\_FILES | Formatted file data ready for use with Gemini LLM nodes, containing the loaded file content in the appropriate API format. |

***

**Source fingerprint (SHA-256):** `dc8ddfffc13984b2d0cc08a50f2a8c26f9608724f632ab49fdeff12bc2e5424a`


# GeminiNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GeminiNode

Complete documentation for the GeminiNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GeminiNode/en.md)

This node allows users to interact with Google's Gemini AI models to generate text responses. You can provide multiple types of inputs including text, images, audio, video, and files as context for the model to generate more relevant and meaningful responses. The node handles all API communication and response parsing automatically.

## Inputs

| Parameter       | Data Type            | Required | Range                                                                                                                                                                                             | Description                                                                                                                                                                                                                                                                                                                                                                 |
| --------------- | -------------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`        | STRING               | Yes      | -                                                                                                                                                                                                 | Text inputs to the model, used to generate a response. You can include detailed instructions, questions, or context for the model. Default: empty string.                                                                                                                                                                                                                   |
| `model`         | COMBO                | Yes      | `gemini-2.5-pro-preview-05-06`<br />`gemini-2.5-flash-preview-04-17`<br />`gemini-2.5-pro`<br />`gemini-2.5-flash`<br />`gemini-3-pro-preview`<br />`gemini-3-1-pro`<br />`gemini-3-1-flash-lite` | The Gemini model to use for generating responses. Default: gemini-3-1-pro.                                                                                                                                                                                                                                                                                                  |
| `seed`          | INT                  | Yes      | 0 to 18446744073709551615                                                                                                                                                                         | When seed is fixed to a specific value, the model makes a best effort to provide the same response for repeated requests. Deterministic output isn't guaranteed. Also, changing the model or parameter settings, such as the temperature, can cause variations in the response even when you use the same seed value. By default, a random seed value is used. Default: 42. |
| `images`        | IMAGE                | No       | -                                                                                                                                                                                                 | Optional image(s) to use as context for the model. To include multiple images, you can use the Batch Images node. Default: None.                                                                                                                                                                                                                                            |
| `audio`         | AUDIO                | No       | -                                                                                                                                                                                                 | Optional audio to use as context for the model. Default: None.                                                                                                                                                                                                                                                                                                              |
| `video`         | VIDEO                | No       | -                                                                                                                                                                                                 | Optional video to use as context for the model. Default: None.                                                                                                                                                                                                                                                                                                              |
| `files`         | GEMINI\_INPUT\_FILES | No       | -                                                                                                                                                                                                 | Optional file(s) to use as context for the model. Accepts inputs from the Gemini Generate Content Input Files node. Default: None.                                                                                                                                                                                                                                          |
| `system_prompt` | STRING               | No       | -                                                                                                                                                                                                 | Foundational instructions that dictate an AI's behavior. Default: empty string. This is an advanced parameter.                                                                                                                                                                                                                                                              |

## Outputs

| Output Name | Data Type | Description                                      |
| ----------- | --------- | ------------------------------------------------ |
| `STRING`    | STRING    | The text response generated by the Gemini model. |

***

**Source fingerprint (SHA-256):** `c7f01d4d4f748a3a80c6e68ccd509cc1da03ed041bd2eaa8124887e7d02eb576`


# InvertBooleanNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/InvertBooleanNode

Complete documentation for the InvertBooleanNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/InvertBooleanNode/en.md)

This node takes a single boolean (true/false) input and outputs the opposite value. It performs a logical NOT operation, turning `true` into `false` and `false` into `true`.

## Inputs

| Parameter | Data Type | Required | Range               | Description                             |
| --------- | --------- | -------- | ------------------- | --------------------------------------- |
| `boolean` | BOOLEAN   | Yes      | `true`<br />`false` | The input boolean value to be inverted. |

## Outputs

| Output Name | Data Type | Description                 |
| ----------- | --------- | --------------------------- |
| `output`    | BOOLEAN   | The inverted boolean value. |

***

**Source fingerprint (SHA-256):** `c512b0f8847c971776c2aebe0c6053ca17a66f756b1b90c803d1a6ef9d3d0ad0`


# JsonExtractString - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/JsonExtractString

Complete documentation for the JsonExtractString node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/JsonExtractString/en.md)

The JsonExtractString node reads a text string containing JSON data and extracts the value associated with a specific key. It converts the extracted value into a string. If the JSON is invalid, the key is not found, or the value is null, the node returns an empty string.

## Inputs

| Parameter     | Data Type | Required | Range | Description                                                                                                        |
| ------------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------ |
| `json_string` | STRING    | Yes      | N/A   | The text containing the JSON data to be parsed. This field supports multiline input.                               |
| `key`         | STRING    | Yes      | N/A   | The specific key whose value you want to extract from the JSON object. This field supports single-line input only. |

**Note:** The node only extracts values from JSON objects (dictionaries). If the parsed JSON is not an object or if the specified key does not exist within it, the output will be an empty string. If the value associated with the key is `null`, the node also returns an empty string.

## Outputs

| Output Name | Data Type | Description                                                                                                 |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------- |
| `output`    | STRING    | The string value extracted from the JSON for the specified key, or an empty string if the extraction fails. |

***

**Source fingerprint (SHA-256):** `ef99b7d2aa82dd290624edaf03f509ade91438639e056b4cb67057b0881b9dc3`


# KSampler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KSampler

Complete documentation for the KSampler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The KSampler works like this: it modifies the provided original latent image information based on a specific model and both positive and negative conditions.
First, it adds noise to the original image data according to the set **seed** and **denoise strength**, then inputs the preset **Model** combined with **positive** and **negative** guidance conditions to generate the image.

## Inputs

| Parameter Name           | Data Type    | Required | Default | Range/Options             | Description                                                                        |
| ------------------------ | ------------ | -------- | ------- | ------------------------- | ---------------------------------------------------------------------------------- |
| Model                    | checkpoint   | Yes      | None    | -                         | Input model used for the denoising process                                         |
| seed                     | Int          | Yes      | 0       | 0 \~ 18446744073709551615 | Used to generate random noise, using the same "seed" generates identical images    |
| steps                    | Int          | Yes      | 20      | 1 \~ 10000                | Number of steps to use in denoising process, more steps mean more accurate results |
| cfg                      | float        | Yes      | 8.0     | 0.0 \~ 100.0              | Controls how closely the generated image matches input conditions, 6-8 recommended |
| sampler\_name            | UI Option    | Yes      | None    | Multiple algorithms       | Choose sampler for denoising, affects generation speed and style                   |
| scheduler                | UI Option    | Yes      | None    | Multiple schedulers       | Controls how noise is removed, affects generation process                          |
| Positive                 | conditioning | Yes      | None    | -                         | Positive conditions guiding denoising, what you want to appear in the image        |
| Negative                 | conditioning | Yes      | None    | -                         | Negative conditions guiding denoising, what you don't want in the image            |
| Latent\_Image            | Latent       | Yes      | None    | -                         | Latent image used for denoising                                                    |
| denoise                  | float        | No       | 1.0     | 0.0 \~ 1.0                | Determines noise removal ratio, lower values mean less connection to input image   |
| control\_after\_generate | UI Option    | No       | None    | Random/Inc/Dec/Keep       | Provides ability to change seed after each prompt                                  |

## Output

| Parameter | Function                                   |
| --------- | ------------------------------------------ |
| Latent    | Outputs the latent after sampler denoising |

## Source Code

\[Updated on May 15, 2025]

```Python theme={null}

def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False):
    latent_image = latent["samples"]
    latent_image = comfy.sample.fix_empty_latent_channels(model, latent_image)

    if disable_noise:
        noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
    else:
        batch_inds = latent["batch_index"] if "batch_index" in latent else None
        noise = comfy.sample.prepare_noise(latent_image, seed, batch_inds)

    noise_mask = None
    if "noise_mask" in latent:
        noise_mask = latent["noise_mask"]

    callback = latent_preview.prepare_callback(model, steps)
    disable_pbar = not comfy.utils.PROGRESS_BAR_ENABLED
    samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
                                  denoise=denoise, disable_noise=disable_noise, start_step=start_step, last_step=last_step,
                                  force_full_denoise=force_full_denoise, noise_mask=noise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed)
    out = latent.copy()
    out["samples"] = samples
    return (out, )
class KSampler:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "model": ("MODEL", {"tooltip": "The model used for denoising the input latent."}),
                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "control_after_generate": True, "tooltip": "The random seed used for creating the noise."}),
                "steps": ("INT", {"default": 20, "min": 1, "max": 10000, "tooltip": "The number of steps used in the denoising process."}),
                "cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0, "step":0.1, "round": 0.01, "tooltip": "The Classifier-Free Guidance scale balances creativity and adherence to the prompt. Higher values result in images more closely matching the prompt however too high values will negatively impact quality."}),
                "sampler_name": (comfy.samplers.KSampler.SAMPLERS, {"tooltip": "The algorithm used when sampling, this can affect the quality, speed, and style of the generated output."}),
                "scheduler": (comfy.samplers.KSampler.SCHEDULERS, {"tooltip": "The scheduler controls how noise is gradually removed to form the image."}),
                "positive": ("CONDITIONING", {"tooltip": "The conditioning describing the attributes you want to include in the image."}),
                "negative": ("CONDITIONING", {"tooltip": "The conditioning describing the attributes you want to exclude from the image."}),
                "latent_image": ("LATENT", {"tooltip": "The latent image to denoise."}),
                "denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "The amount of denoising applied, lower values will maintain the structure of the initial image allowing for image to image sampling."}),
            }
        }

    RETURN_TYPES = ("LATENT",)
    OUTPUT_TOOLTIPS = ("The denoised latent.",)
    FUNCTION = "sample"

    CATEGORY = "sampling"
    DESCRIPTION = "Uses the provided model, positive and negative conditioning to denoise the latent image."

    def sample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0):
        return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)

```


# KSamplerAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KSamplerAdvanced

Complete documentation for the KSamplerAdvanced node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The KSamplerAdvanced node is designed to enhance the sampling process by providing advanced configurations and techniques. It aims to offer more sophisticated options for generating samples from a model, improving upon the basic KSampler functionalities.

## Inputs

| Parameter                    | Data Type      | Description                                                                                                                     |
| ---------------------------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| `model`                      | MODEL          | Specifies the model from which samples are to be generated, playing a crucial role in the sampling process.                     |
| `add_noise`                  | COMBO\[STRING] | Determines whether noise should be added to the sampling process, affecting the diversity and quality of the generated samples. |
| `noise_seed`                 | INT            | Sets the seed for noise generation, ensuring reproducibility in the sampling process.                                           |
| `steps`                      | INT            | Defines the number of steps to be taken in the sampling process, impacting the detail and quality of the output.                |
| `cfg`                        | FLOAT          | Controls the conditioning factor, influencing the direction and space of the sampling process.                                  |
| `sampler_name`               | COMBO\[STRING] | Selects the specific sampler to be used, allowing for customization of the sampling technique.                                  |
| `scheduler`                  | COMBO\[STRING] | Chooses the scheduler for controlling the sampling process, affecting the progression and quality of samples.                   |
| `positive`                   | CONDITIONING   | Specifies the positive conditioning to guide the sampling towards desired attributes.                                           |
| `negative`                   | CONDITIONING   | Specifies the negative conditioning to steer the sampling away from certain attributes.                                         |
| `latent_image`               | LATENT         | Provides the initial latent image to be used in the sampling process, serving as a starting point.                              |
| `start_at_step`              | INT            | Determines the starting step of the sampling process, allowing for control over the sampling progression.                       |
| `end_at_step`                | INT            | Sets the ending step of the sampling process, defining the scope of the sampling.                                               |
| `return_with_leftover_noise` | COMBO\[STRING] | Indicates whether to return the sample with leftover noise, affecting the final output's appearance.                            |

## Outputs

| Parameter | Data Type | Description                                                                                                            |
| --------- | --------- | ---------------------------------------------------------------------------------------------------------------------- |
| `latent`  | LATENT    | The output represents the latent image generated from the model, reflecting the applied configurations and techniques. |


# KSamplerSelect - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KSamplerSelect

Complete documentation for the KSamplerSelect node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The KSamplerSelect node is designed to select a specific sampler based on the provided sampler name. It abstracts the complexity of sampler selection, allowing users to easily switch between different sampling strategies for their tasks.

## Inputs

| Parameter      | Data Type      | Description                                                                                                                                                            |
| -------------- | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `sampler_name` | COMBO\[STRING] | Specifies the name of the sampler to be selected. This parameter determines which sampling strategy will be used, impacting the overall sampling behavior and results. |

## Outputs

| Parameter | Data Type | Description                                                               |
| --------- | --------- | ------------------------------------------------------------------------- |
| `sampler` | `SAMPLER` | Returns the selected sampler object, ready to be used for sampling tasks. |


# KarrasScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KarrasScheduler

Complete documentation for the KarrasScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The KarrasScheduler node is designed to generate a sequence of noise levels (sigmas) based on the Karras et al. (2022) noise schedule. This scheduler is useful for controlling the diffusion process in generative models, allowing for fine-tuned adjustments to the noise levels applied at each step of the generation process.

## Inputs

| Parameter   | Data Type | Description                                                                                                                           |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------- |
| `steps`     | INT       | Specifies the number of steps in the noise schedule, affecting the granularity of the generated sigmas sequence.                      |
| `sigma_max` | FLOAT     | The maximum sigma value in the noise schedule, setting the upper bound of noise levels.                                               |
| `sigma_min` | FLOAT     | The minimum sigma value in the noise schedule, setting the lower bound of noise levels.                                               |
| `rho`       | FLOAT     | A parameter that controls the shape of the noise schedule curve, influencing how noise levels progress from sigma\_min to sigma\_max. |

## Outputs

| Parameter | Data Type | Description                                                                                        |
| --------- | --------- | -------------------------------------------------------------------------------------------------- |
| `sigmas`  | SIGMAS    | The generated sequence of noise levels (sigmas) following the Karras et al. (2022) noise schedule. |


# LTXVScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVScheduler

Complete documentation for the LTXVScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVScheduler/en.md)

The LTXVScheduler node generates sigma values for custom sampling processes. It calculates noise schedule parameters based on the number of tokens in the input latent and applies a sigmoid transformation to create the sampling schedule. The node can optionally stretch the resulting sigmas to match a specified terminal value.

## Inputs

| Parameter    | Data Type | Required | Range      | Description                                                              |
| ------------ | --------- | -------- | ---------- | ------------------------------------------------------------------------ |
| `steps`      | INT       | Yes      | 1-10000    | Number of sampling steps (default: 20)                                   |
| `max_shift`  | FLOAT     | Yes      | 0.0-100.0  | Maximum shift value for sigma calculation (default: 2.05)                |
| `base_shift` | FLOAT     | Yes      | 0.0-100.0  | Base shift value for sigma calculation (default: 0.95)                   |
| `stretch`    | BOOLEAN   | Yes      | True/False | Stretch the sigmas to be in the range \[terminal, 1] (default: True)     |
| `terminal`   | FLOAT     | Yes      | 0.0-0.99   | The terminal value of the sigmas after stretching (default: 0.1)         |
| `latent`     | LATENT    | No       | -          | Optional latent input used to calculate token count for sigma adjustment |

**Note:** The `latent` parameter is optional. When not provided, the node uses a default token count of 4096 for calculations.

## Outputs

| Output Name | Data Type | Description                                     |
| ----------- | --------- | ----------------------------------------------- |
| `sigmas`    | SIGMAS    | Generated sigma values for the sampling process |

***

**Source fingerprint (SHA-256):** `63a827c5a5e54370eab4cd259c00ccc3d2bada6e61988011cbd1e779233604bb`


# LaplaceScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LaplaceScheduler

Complete documentation for the LaplaceScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LaplaceScheduler/en.md)

The LaplaceScheduler node generates a sequence of sigma values following a Laplace distribution for use in diffusion sampling. It creates a schedule of noise levels that gradually decrease from a maximum to minimum value, using Laplace distribution parameters to control the progression. This scheduler is commonly used in custom sampling workflows to define the noise schedule for diffusion models.

## Inputs

| Parameter   | Data Type | Required | Range         | Description                                                           |
| ----------- | --------- | -------- | ------------- | --------------------------------------------------------------------- |
| `steps`     | INT       | Yes      | 1 to 10000    | Number of sampling steps in the schedule (default: 20)                |
| `sigma_max` | FLOAT     | Yes      | 0.0 to 5000.0 | Maximum sigma value at the start of the schedule (default: 14.614642) |
| `sigma_min` | FLOAT     | Yes      | 0.0 to 5000.0 | Minimum sigma value at the end of the schedule (default: 0.0291675)   |
| `mu`        | FLOAT     | Yes      | -10.0 to 10.0 | Mean parameter for the Laplace distribution (default: 0.0)            |
| `beta`      | FLOAT     | Yes      | 0.0 to 10.0   | Scale parameter for the Laplace distribution (default: 0.5)           |

## Outputs

| Output Name | Data Type | Description                                                          |
| ----------- | --------- | -------------------------------------------------------------------- |
| `SIGMAS`    | SIGMAS    | A sequence of sigma values following a Laplace distribution schedule |

***

**Source fingerprint (SHA-256):** `fe8a405937a4b59ab988031b8509a9f030a57d8d1a17bb0812dc51eb5ad83717`


# LoadTrainingDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadTrainingDataset

Complete documentation for the LoadTrainingDataset node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadTrainingDataset/en.md)

This node loads an encoded training dataset that has been previously saved to disk. It searches for and reads all data shard files from a specified folder within the ComfyUI output directory, then returns the combined latent vectors and conditioning data for use in training workflows.

## Inputs

| Parameter     | Data Type | Required | Range | Description                                                                                                                  |
| ------------- | --------- | -------- | ----- | ---------------------------------------------------------------------------------------------------------------------------- |
| `folder_name` | STRING    | Yes      | N/A   | Name of the folder containing the saved dataset, located inside the ComfyUI output directory (default: "training\_dataset"). |

## Outputs

| Output Name    | Data Type    | Description                                                                                                |
| -------------- | ------------ | ---------------------------------------------------------------------------------------------------------- |
| `latents`      | LATENT       | A list of latent dictionaries, where each dictionary contains a `"samples"` key with a tensor.             |
| `conditioning` | CONDITIONING | A list of conditioning lists, where each inner list contains conditioning data for a corresponding sample. |

***

**Source fingerprint (SHA-256):** `1d074685317b5bd53d9fb7596126b0f579de6c67b5615717b1a16ba01fc01efd`


# LossGraphNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LossGraphNode

Complete documentation for the LossGraphNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LossGraphNode/en.md)

The LossGraphNode creates a visual graph of training loss values over time and displays it as a preview image. It takes loss data from training processes and generates a line chart showing how the loss changes across training steps. The resulting graph includes axis labels and min/max loss values.

## Inputs

| Parameter         | Data Type | Required | Range | Description                                                     |
| ----------------- | --------- | -------- | ----- | --------------------------------------------------------------- |
| `loss`            | LOSS\_MAP | Yes      | -     | Loss map from training node.                                    |
| `filename_prefix` | STRING    | Yes      | -     | Prefix for the saved loss graph image. (default: "loss\_graph") |

## Outputs

| Output Name | Data Type | Description                                            |
| ----------- | --------- | ------------------------------------------------------ |
| `ui.images` | IMAGE     | The generated loss graph image displayed as a preview. |

***

**Source fingerprint (SHA-256):** `88164045339e4181cefc6ed3a2d3c35921b9cadc2977eb7406fad7e9b353f818`


# MakeTrainingDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MakeTrainingDataset

Complete documentation for the MakeTrainingDataset node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MakeTrainingDataset/en.md)

This node prepares data for training by encoding images and text. It takes a list of images and a corresponding list of text captions, then uses a VAE model to convert the images into latent representations and a CLIP model to convert the text into conditioning data. The resulting paired latents and conditioning are output as lists, ready for use in training workflows.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                                                     |
| --------- | --------- | -------- | ----- | --------------------------------------------------------------------------------------------------------------- |
| `images`  | IMAGE     | Yes      | N/A   | List of images to encode.                                                                                       |
| `vae`     | VAE       | Yes      | N/A   | VAE model for encoding images to latents.                                                                       |
| `clip`    | CLIP      | Yes      | N/A   | CLIP model for encoding text to conditioning.                                                                   |
| `texts`   | STRING    | No       | N/A   | List of text captions. Can be length n (matching images), 1 (repeated for all), or omitted (uses empty string). |

**Parameter Constraints:**

* The number of items in the `texts` list must be 0, 1, or exactly match the number of items in the `images` list. If it is 0, an empty string is used for all images. If it is 1, that single text is repeated for all images.

## Outputs

| Output Name    | Data Type    | Description                 |
| -------------- | ------------ | --------------------------- |
| `latents`      | LATENT       | List of latent dicts.       |
| `conditioning` | CONDITIONING | List of conditioning lists. |

***

**Source fingerprint (SHA-256):** `72f1686aa9da9d50b1948040c323c7e944d4a5c1f4cd2ec5e0987d998c20ea43`


# MergeTextLists - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MergeTextLists

Complete documentation for the MergeTextLists node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MergeTextLists/en.md)

This node merges multiple text lists into a single, combined list. It is designed to receive text inputs as lists and concatenates them together. The node logs the total number of texts in the merged list.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                                                        |
| --------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------ |
| `texts`   | STRING    | Yes      | N/A   | The text lists to be merged. Multiple lists can be connected to the input, and they will be concatenated into one. |

**Note:** This node is configured as a group process (`is_group_process = True`), meaning it automatically handles multiple list inputs by concatenating them before the main processing function runs.

**Note:** This node is deprecated and superseded by the Create List node.

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `texts`     | STRING    | The single, merged list containing all the input texts. |

***

**Source fingerprint (SHA-256):** `bb7f45725c2c41a18d8cd3040d093c11be2ceb03cf1849385aa55d12fd9eb555`


# OpenAIChatConfig - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIChatConfig

Complete documentation for the OpenAIChatConfig node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIChatConfig/en.md)

The OpenAIChatConfig node allows setting additional configuration options for the OpenAI Chat Node. It provides advanced settings that control how the model generates responses, including truncation behavior, output length limits, and custom instructions.

## Inputs

| Parameter           | Data Type | Required | Range                      | Description                                                                                                                                                                                                                                                                                                                                                                                                               |
| ------------------- | --------- | -------- | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `truncation`        | COMBO     | Yes      | `"auto"`<br />`"disabled"` | The truncation strategy to use for the model response. auto: If the context of this response and previous ones exceeds the model's context window size, the model will truncate the response to fit the context window by dropping input items in the middle of the conversation. disabled: If a model response will exceed the context window size for a model, the request will fail with a 400 error (default: "auto") |
| `max_output_tokens` | INT       | No       | 16 to 16384                | An upper bound for the number of tokens that can be generated for a response, including visible output tokens (default: 4096)                                                                                                                                                                                                                                                                                             |
| `instructions`      | STRING    | No       | -                          | Instructions for the model on how to generate the response (multiline input supported)                                                                                                                                                                                                                                                                                                                                    |

## Outputs

| Output Name          | Data Type            | Description                                                                           |
| -------------------- | -------------------- | ------------------------------------------------------------------------------------- |
| `OPENAI_CHAT_CONFIG` | OPENAI\_CHAT\_CONFIG | Configuration object containing the specified settings for use with OpenAI Chat Nodes |

***

**Source fingerprint (SHA-256):** `f9ae6d3b2818ea37543156c2f209fc4d093e40e446907deb4be327ca0c9d70e1`


# OpenAIChatNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIChatNode

Complete documentation for the OpenAIChatNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIChatNode/en.md)

This node generates text responses from an OpenAI model. It sends your text prompt (and optionally images or files) to an OpenAI model and returns the generated text response.

## Inputs

| Parameter          | Data Type            | Required | Range                                                                                                                                                                                 | Description                                                                                                      |
| ------------------ | -------------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------- |
| `prompt`           | STRING               | Yes      | -                                                                                                                                                                                     | Text inputs to the model, used to generate a response (default: empty)                                           |
| `persist_context`  | BOOLEAN              | Yes      | -                                                                                                                                                                                     | This parameter is deprecated and has no effect (default: False)                                                  |
| `model`            | COMBO                | Yes      | `gpt-5.5-pro`<br />`gpt-5.5`<br />`gpt-5`<br />`gpt-5-mini`<br />`gpt-5-nano`<br />`gpt-4.1`<br />`gpt-4.1-mini`<br />`gpt-4.1-nano`<br />`o4-mini`<br />`o3`<br />`o1-pro`<br />`o1` | The model used to generate the response (default: `gpt-5`)                                                       |
| `images`           | IMAGE                | No       | -                                                                                                                                                                                     | Optional image(s) to use as context for the model. To include multiple images, you can use the Batch Images node |
| `files`            | OPENAI\_INPUT\_FILES | No       | -                                                                                                                                                                                     | Optional file(s) to use as context for the model. Accepts inputs from the OpenAI Chat Input Files node           |
| `advanced_options` | OPENAI\_CHAT\_CONFIG | No       | -                                                                                                                                                                                     | Optional configuration for the model. Accepts inputs from the OpenAI Chat Advanced Options node                  |

## Outputs

| Output Name   | Data Type | Description                                     |
| ------------- | --------- | ----------------------------------------------- |
| `output_text` | STRING    | The text response generated by the OpenAI model |

***

**Source fingerprint (SHA-256):** `9adc9685d7fc31fba95bf43fa9e041289b6dbb9ab8f5ed30dc85e0acc015fe5c`


# OpenAIInputFiles - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIInputFiles

Complete documentation for the OpenAIInputFiles node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIInputFiles/en.md)

Loads and formats input files for the OpenAI API. This node prepares text (.txt) and PDF (.pdf) files to include as context inputs for the OpenAI Chat Node. The files will be read by the OpenAI model when generating a response. Multiple OpenAI Input Files nodes can be chained together to include several files in a single message.

## Inputs

| Parameter            | Data Type            | Required | Range                                                                                  | Description                                                                                                                                                                     |
| -------------------- | -------------------- | -------- | -------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `file`               | COMBO                | Yes      | Multiple options available (all .txt and .pdf files in the input directory under 32MB) | Input files to include as context for the model. Only accepts text (.txt) and PDF (.pdf) files for now. Files must be smaller than 32MB.                                        |
| `OPENAI_INPUT_FILES` | OPENAI\_INPUT\_FILES | No       | N/A                                                                                    | An optional additional file(s) to batch together with the file loaded from this node. Allows chaining of input files so that a single message can include multiple input files. |

**File Constraints:**

* Only .txt and .pdf files are supported
* Maximum file size: 32MB
* Files are loaded from the ComfyUI input directory

## Outputs

| Output Name          | Data Type            | Description                                                             |
| -------------------- | -------------------- | ----------------------------------------------------------------------- |
| `OPENAI_INPUT_FILES` | OPENAI\_INPUT\_FILES | Formatted input files ready to be used as context for OpenAI API calls. |

***

**Source fingerprint (SHA-256):** `9e1a60feb48d39646c4247dd12b15c3eb392e1b85b3db2f254571d568d772de0`


# OpenRouterLLMNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenRouterLLMNode

Complete documentation for the OpenRouterLLMNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenRouterLLMNode/en.md)

## Overview

The OpenRouter LLM node sends a text prompt to a curated set of popular language models available through the OpenRouter service and returns the generated text response. It supports models from providers like xAI, DeepSeek, Qwen, Mistral, Z.AI (GLM), Moonshot (Kimi), and Perplexity Sonar, and can optionally include images or videos in the request.

## Inputs

| Parameter       | Data Type | Required | Range                                       | Description                                                                              |
| --------------- | --------- | -------- | ------------------------------------------- | ---------------------------------------------------------------------------------------- |
| `prompt`        | STRING    | Yes      | N/A                                         | Text input to the model.                                                                 |
| `model`         | STRING    | Yes      | Multiple options available (see note below) | The OpenRouter model used to generate the response.                                      |
| `seed`          | INT       | Yes      | 0 to 2147483647                             | Seed for sampling. Set to 0 to omit. Most models treat this as a hint only. (default: 0) |
| `system_prompt` | STRING    | No       | N/A                                         | Foundational instructions that dictate the model's behavior. (default: "")               |

**Note on `model` parameter:** The available model options are dynamically built and may include models with different capabilities. Some models support additional features like reasoning effort, web search, or image/video inputs. The node will validate that the number of images or videos provided does not exceed the model's maximum supported count.

**Note on `seed` parameter:** The `seed` parameter has a "control\_after\_generate" behavior, meaning it can be set to automatically change (e.g., randomize, increment, or fixed) after each node execution, depending on the user's widget settings.

**Note on `system_prompt`:** This parameter is optional and is marked as an advanced parameter in the user interface.

## Outputs

| Output Name | Data Type | Description                                            |
| ----------- | --------- | ------------------------------------------------------ |
| `output`    | STRING    | The generated text response from the OpenRouter model. |

***

**Source fingerprint (SHA-256):** `24757e36bf2356cc1805a6f071db88ca455e17944695672f19845a4cd1826c8a`


# OptimalStepsScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OptimalStepsScheduler

Complete documentation for the OptimalStepsScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OptimalStepsScheduler/en.md)

The OptimalStepsScheduler node calculates noise schedule sigmas for diffusion models based on the selected model type and step configuration. It adjusts the total number of steps according to the denoise parameter and interpolates the noise levels to match the requested step count. The node returns a sequence of sigma values that determine the noise levels used during the diffusion sampling process.

## Inputs

| Parameter    | Data Type | Required | Range                           | Description                                                                                 |
| ------------ | --------- | -------- | ------------------------------- | ------------------------------------------------------------------------------------------- |
| `model_type` | COMBO     | Yes      | "FLUX"<br />"Wan"<br />"Chroma" | The type of diffusion model to use for noise level calculation                              |
| `steps`      | INT       | Yes      | 3-1000                          | The total number of sampling steps to calculate (default: 20)                               |
| `denoise`    | FLOAT     | No       | 0.0-1.0                         | Controls the denoising strength, which adjusts the effective number of steps (default: 1.0) |

**Note:** When `denoise` is set to less than 1.0, the node calculates the effective steps as `steps * denoise`. If `denoise` is set to 0.0, the node returns an empty tensor.

## Outputs

| Output Name | Data Type | Description                                                                       |
| ----------- | --------- | --------------------------------------------------------------------------------- |
| `sigmas`    | SIGMAS    | A sequence of sigma values representing the noise schedule for diffusion sampling |

***

**Source fingerprint (SHA-256):** `19ad2b96d8256b1fd274f09d863215d4a4375f071829509d9f105d244cee3d28`


# PolyexponentialScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PolyexponentialScheduler

Complete documentation for the PolyexponentialScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The PolyexponentialScheduler node is designed to generate a sequence of noise levels (sigmas) based on a polyexponential noise schedule. This schedule is a polynomial function in the logarithm of sigma, allowing for a flexible and customizable progression of noise levels throughout the diffusion process.

## Inputs

| Parameter   | Data Type | Description                                                                                                                                              |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `steps`     | INT       | Specifies the number of steps in the diffusion process, affecting the granularity of the generated noise levels.                                         |
| `sigma_max` | FLOAT     | The maximum noise level, setting the upper bound of the noise schedule.                                                                                  |
| `sigma_min` | FLOAT     | The minimum noise level, setting the lower bound of the noise schedule.                                                                                  |
| `rho`       | FLOAT     | A parameter that controls the shape of the polyexponential noise schedule, influencing how noise levels progress between the minimum and maximum values. |

## Outputs

| Parameter | Data Type | Description                                                                                                 |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------- |
| `sigmas`  | SIGMAS    | The output is a sequence of noise levels (sigmas) tailored to the specified polyexponential noise schedule. |


# PrimitiveBoolean - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveBoolean

Complete documentation for the PrimitiveBoolean node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveBoolean/en.md)

The Boolean node provides a simple way to pass boolean (true/false) values through your workflow. It takes a boolean input value and outputs the same value unchanged, allowing you to control boolean parameters in other nodes.

## Inputs

| Parameter | Data Type | Required | Range           | Description                                |
| --------- | --------- | -------- | --------------- | ------------------------------------------ |
| `value`   | BOOLEAN   | Yes      | true<br />false | The boolean value to pass through the node |

## Outputs

| Output Name | Data Type | Description                                       |
| ----------- | --------- | ------------------------------------------------- |
| `output`    | BOOLEAN   | The same boolean value that was provided as input |

***

**Source fingerprint (SHA-256):** `79442504184760e90a61eea787bb5e67f40e051b2ca8ee9bf6275f149bf7568b`


# PrimitiveBoundingBox - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveBoundingBox

Complete documentation for the PrimitiveBoundingBox node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveBoundingBox/en.md)

The PrimitiveBoundingBox node creates a simple rectangular area defined by its position and size. It takes X and Y coordinates for the top-left corner, along with width and height values, and outputs a bounding box data structure that can be used by other nodes in a workflow.

## Inputs

| Parameter | Data Type | Required | Range     | Description                                                                |
| --------- | --------- | -------- | --------- | -------------------------------------------------------------------------- |
| `x`       | INT       | Yes      | 0 to 8192 | The X-coordinate for the top-left corner of the bounding box (default: 0). |
| `y`       | INT       | Yes      | 0 to 8192 | The Y-coordinate for the top-left corner of the bounding box (default: 0). |
| `width`   | INT       | Yes      | 1 to 8192 | The width of the bounding box (default: 512).                              |
| `height`  | INT       | Yes      | 1 to 8192 | The height of the bounding box (default: 512).                             |

## Outputs

| Output Name    | Data Type     | Description                                                                                          |
| -------------- | ------------- | ---------------------------------------------------------------------------------------------------- |
| `bounding_box` | BOUNDING\_BOX | A data structure containing the `x`, `y`, `width`, and `height` properties of the defined rectangle. |

***

**Source fingerprint (SHA-256):** `3a91a1a2656fa46f8257334bbaf3bcba861ab91da8ebbfcefe7d5f3547dd307f`


# PrimitiveFloat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveFloat

Complete documentation for the PrimitiveFloat node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveFloat/en.md)

The PrimitiveFloat node creates a floating-point number value that can be used in your workflow. It takes a single numeric input and outputs that same value, allowing you to define and pass float values between different nodes in your ComfyUI pipeline.

## Inputs

| Parameter | Data Type | Required | Range                                   | Description                                              |
| --------- | --------- | -------- | --------------------------------------- | -------------------------------------------------------- |
| `value`   | FLOAT     | Yes      | -sys.maxsize to sys.maxsize (step: 0.1) | The floating-point number value to output (default: 0.0) |

## Outputs

| Output Name | Data Type | Description                           |
| ----------- | --------- | ------------------------------------- |
| `output`    | FLOAT     | The input floating-point number value |

***

**Source fingerprint (SHA-256):** `92f1603421dfcc06867f001222ca49b322de1537e05336f94e250a9422236d11`


# RandomNoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RandomNoise

Complete documentation for the RandomNoise node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RandomNoise/en.md)

The RandomNoise node generates random noise patterns based on a seed value. It creates reproducible noise that can be used for various image processing and generation tasks. The same seed will always produce the same noise pattern, allowing for consistent results across multiple runs.

## Inputs

| Parameter    | Data Type | Required | Range                     | Description                                                                                                                     |
| ------------ | --------- | -------- | ------------------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| `noise_seed` | INT       | Yes      | 0 to 18446744073709551615 | The seed value used to generate the random noise pattern (default: 0). The same seed will always produce the same noise output. |

## Outputs

| Output Name | Data Type | Description                                                          |
| ----------- | --------- | -------------------------------------------------------------------- |
| `noise`     | NOISE     | The generated random noise pattern based on the provided seed value. |

***

**Source fingerprint (SHA-256):** `fcbf92e8b1c1ff001da302208ba4a3960deb1246d76179ceba0b31af6be77203`


# RegexExtract - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RegexExtract

Complete documentation for the RegexExtract node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RegexExtract/en.md)

The RegexExtract node searches for patterns in text using regular expressions. It can find the first match, all matches, specific groups from matches, or all groups across multiple matches. The node supports various regex flags for case sensitivity, multiline matching, and dotall behavior.

## Inputs

| Parameter          | Data Type | Required | Range                                                                 | Description                                                                                |
| ------------------ | --------- | -------- | --------------------------------------------------------------------- | ------------------------------------------------------------------------------------------ |
| `string`           | STRING    | Yes      | -                                                                     | The input text to search for patterns                                                      |
| `regex_pattern`    | STRING    | Yes      | -                                                                     | The regular expression pattern to search for                                               |
| `mode`             | COMBO     | Yes      | "First Match"<br />"All Matches"<br />"First Group"<br />"All Groups" | The extraction mode determines what parts of matches are returned (default: "First Match") |
| `case_insensitive` | BOOLEAN   | No       | -                                                                     | Whether to ignore case when matching (default: True)                                       |
| `multiline`        | BOOLEAN   | No       | -                                                                     | Whether to treat the string as multiple lines (default: False)                             |
| `dotall`           | BOOLEAN   | No       | -                                                                     | Whether the dot (.) matches newlines (default: False)                                      |
| `group_index`      | INT       | No       | 0-100                                                                 | The capture group index to extract when using group modes (default: 1)                     |

**Note:** When using "First Group" or "All Groups" modes, the `group_index` parameter specifies which capture group to extract. Group 0 represents the entire match, while groups 1+ represent the numbered capture groups in your regex pattern.

## Outputs

| Output Name | Data Type | Description                                                  |
| ----------- | --------- | ------------------------------------------------------------ |
| `output`    | STRING    | The extracted text based on the selected mode and parameters |

***

**Source fingerprint (SHA-256):** `a879e4fd7429edfada44b2f5778bb71e537a000be6c25d3f67359b9ee802812f`


# RegexMatch - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RegexMatch

Complete documentation for the RegexMatch node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RegexMatch/en.md)

The RegexMatch node checks if a text string contains a match for a given regular expression pattern. It searches the input string and returns a simple yes/no result indicating whether the pattern was found anywhere in the text. You can adjust how the search works by enabling options like case-insensitive matching or multiline mode.

## Inputs

| Parameter          | Data Type | Required | Range | Description                                                          |
| ------------------ | --------- | -------- | ----- | -------------------------------------------------------------------- |
| `string`           | STRING    | Yes      | -     | The text string to search for matches                                |
| `regex_pattern`    | STRING    | Yes      | -     | The regular expression pattern to match against the string           |
| `case_insensitive` | BOOLEAN   | No       | -     | Whether to ignore case when matching (default: True)                 |
| `multiline`        | BOOLEAN   | No       | -     | Whether to enable multiline mode for regex matching (default: False) |
| `dotall`           | BOOLEAN   | No       | -     | Whether to enable dotall mode for regex matching (default: False)    |

## Outputs

| Output Name | Data Type | Description                                                                             |
| ----------- | --------- | --------------------------------------------------------------------------------------- |
| `matches`   | BOOLEAN   | Returns True if the regex pattern matches any part of the input string, False otherwise |

***

**Source fingerprint (SHA-256):** `4f0fa717bde7406e42d9a99599eab546690140166d2bb01bb4fde3c5d60e0397`


# RegexReplace - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RegexReplace

Complete documentation for the RegexReplace node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RegexReplace/en.md)

The RegexReplace node finds and replaces text in strings using regular expression patterns. It allows you to search for text patterns and replace them with new text, with options to control how the pattern matching works including case sensitivity, multiline matching, and limiting the number of replacements.

## Inputs

| Parameter          | Data Type | Required | Range | Description                                                                                                                                                                     |
| ------------------ | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `string`           | STRING    | Yes      | -     | The input text string to search and replace within                                                                                                                              |
| `regex_pattern`    | STRING    | Yes      | -     | The regular expression pattern to search for in the input string                                                                                                                |
| `replace`          | STRING    | Yes      | -     | The replacement text to substitute for matched patterns                                                                                                                         |
| `case_insensitive` | BOOLEAN   | No       | -     | When enabled, makes the pattern matching ignore case differences (default: True)                                                                                                |
| `multiline`        | BOOLEAN   | No       | -     | When enabled, changes the behavior of ^ and \$ to match at the start/end of each line rather than just the start/end of the entire string (default: False)                      |
| `dotall`           | BOOLEAN   | No       | -     | When enabled, the dot (.) character will match any character including newline characters. When disabled, dots won't match newlines (default: False)                            |
| `count`            | INT       | No       | 0-100 | Maximum number of replacements to make. Set to 0 to replace all occurrences (default). Set to 1 to replace only the first match, 2 for the first two matches, etc. (default: 0) |

## Outputs

| Output Name | Data Type | Description                                                 |
| ----------- | --------- | ----------------------------------------------------------- |
| `output`    | STRING    | The modified string with the specified replacements applied |

***

**Source fingerprint (SHA-256):** `58d4ec055aa5901b0e536bb2ca6993053ea85a9269d09cdcdf584df935d6876d`


# ReplaceText - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ReplaceText

Complete documentation for the ReplaceText node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ReplaceText/en.md)

The Replace Text node performs a simple text substitution. It searches for a specified piece of text within the input and replaces every occurrence with a new piece of text. The operation is applied to all text inputs provided to the node.

**Note:** This node is deprecated and superseded by the other Replace Text node.

## Inputs

| Parameter | Data Type | Required | Range | Description                                   |
| --------- | --------- | -------- | ----- | --------------------------------------------- |
| `text`    | STRING    | Yes      | -     | The text to process.                          |
| `find`    | STRING    | Yes      | -     | Text to find (default: empty string).         |
| `replace` | STRING    | Yes      | -     | Text to replace with (default: empty string). |

## Outputs

| Output Name | Data Type | Description                                                                                |
| ----------- | --------- | ------------------------------------------------------------------------------------------ |
| `text`      | STRING    | The processed text with all occurrences of the `find` text replaced by the `replace` text. |

***

**Source fingerprint (SHA-256):** `38beeabc232b19efedf2dcf4e2490f537d9a07d60c89de2811b7a4bddb98cf57`


# ResolutionBucket - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResolutionBucket

Complete documentation for the ResolutionBucket node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResolutionBucket/en.md)

This node organizes a list of latent images and their corresponding conditioning data by their resolution. It groups together items that share the same height and width, creating separate batches for each unique resolution. This process is useful for preparing data for efficient training, as it allows models to process multiple items of the same size together.

## Inputs

| Parameter      | Data Type    | Required | Range | Description                                             |
| -------------- | ------------ | -------- | ----- | ------------------------------------------------------- |
| `latents`      | LATENT       | Yes      | N/A   | List of latent dicts to bucket by resolution.           |
| `conditioning` | CONDITIONING | Yes      | N/A   | List of conditioning lists (must match latents length). |

**Note:** The number of items in the `latents` list must exactly match the number of items in the `conditioning` list. Each latent dictionary can contain a batch of samples, and the corresponding conditioning list must contain a matching number of conditioning items for that batch.

## Outputs

| Output Name    | Data Type    | Description                                              |
| -------------- | ------------ | -------------------------------------------------------- |
| `latents`      | LATENT       | List of batched latent dicts, one per resolution bucket. |
| `conditioning` | CONDITIONING | List of condition lists, one per resolution bucket.      |

***

**Source fingerprint (SHA-256):** `20a0794e5a2c88ac60bb729b60840c5a632a115196de285b764effaf43ab73e0`


# SDTurboScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SDTurboScheduler

Complete documentation for the SDTurboScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

SDTurboScheduler is designed to generate a sequence of sigma values for image sampling, adjusting the sequence based on the denoise level and the number of steps specified. It leverages a specific model's sampling capabilities to produce these sigma values, which are crucial for controlling the denoising process during image generation.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                               |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`   | `MODEL`   | The model parameter specifies the generative model to be used for sigma value generation. It is crucial for determining the specific sampling behavior and capabilities of the scheduler. |
| `steps`   | `INT`     | The steps parameter determines the length of the sigma sequence to be generated, directly influencing the granularity of the denoising process.                                           |
| `denoise` | `FLOAT`   | The denoise parameter adjusts the starting point of the sigma sequence, allowing for finer control over the denoising level applied during image generation.                              |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                        |
| --------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `sigmas`  | `SIGMAS`  | A sequence of sigma values generated based on the specified model, steps, and denoise level. These values are essential for controlling the denoising process in image generation. |


# SamplerARVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerARVideo

Complete documentation for the SamplerARVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerARVideo/en.md)

The Sampler AR Video node provides a specialized sampling method for autoregressive video models, such as those using Causal Forcing or Self-Forcing techniques. It manages all parameters related to the autoregressive (AR) loop directly within the workflow, making it easy to configure how the model generates video frames one step at a time.

## Inputs

| Parameter             | Data Type | Required | Range   | Description                                                                                                                                                                                                                                           |
| --------------------- | --------- | -------- | ------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `num_frame_per_block` | INT       | Yes      | 1 to 64 | Frames per autoregressive block. A value of 1 means the model generates one frame at a time (framewise), while a value of 3 means it generates three frames together (chunkwise). This setting must match the checkpoint's training mode. Default: 1. |

## Outputs

| Output Name | Data Type | Description                                                                                                           |
| ----------- | --------- | --------------------------------------------------------------------------------------------------------------------- |
| `SAMPLER`   | SAMPLER   | A configured sampler object that uses the "ar\_video" sampling function with the specified autoregressive parameters. |

***

**Source fingerprint (SHA-256):** `7f722791f55a4d8bbda1c00becf25c42e67e3a487712fa674ac118e978cf9812`


# SamplerCustom - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerCustom

Complete documentation for the SamplerCustom node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The SamplerCustom node is designed to provide a flexible and customizable sampling mechanism for various applications. It enables users to select and configure different sampling strategies tailored to their specific needs, enhancing the adaptability and efficiency of the sampling process.

## Inputs

| Parameter      | Data Type      | Description                                                                                                                                                                        |
| -------------- | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`        | `MODEL`        | The 'model' input type specifies the model to be used for sampling, playing a crucial role in determining the sampling behavior and output.                                        |
| `add_noise`    | `BOOLEAN`      | The 'add\_noise' input type allows users to specify whether noise should be added to the sampling process, influencing the diversity and characteristics of the generated samples. |
| `noise_seed`   | `INT`          | The 'noise\_seed' input type provides a seed for the noise generation, ensuring reproducibility and consistency in the sampling process when adding noise.                         |
| `cfg`          | `FLOAT`        | The 'cfg' input type sets the configuration for the sampling process, allowing for fine-tuning of the sampling parameters and behavior.                                            |
| `positive`     | `CONDITIONING` | The 'positive' input type represents positive conditioning information, guiding the sampling process towards generating samples that align with specified positive attributes.     |
| `negative`     | `CONDITIONING` | The 'negative' input type represents negative conditioning information, steering the sampling process away from generating samples that exhibit specified negative attributes.     |
| `sampler`      | `SAMPLER`      | The 'sampler' input type selects the specific sampling strategy to be employed, directly impacting the nature and quality of the generated samples.                                |
| `sigmas`       | `SIGMAS`       | The 'sigmas' input type defines the noise levels to be used in the sampling process, affecting the exploration of the sample space and the diversity of the output.                |
| `latent_image` | `LATENT`       | The 'latent\_image' input type provides an initial latent image for the sampling process, serving as a starting point for sample generation.                                       |

## Outputs

| Parameter         | Data Type | Description                                                                                                                                                       |
| ----------------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `output`          | `LATENT`  | The 'output' represents the primary result of the sampling process, containing the generated samples.                                                             |
| `denoised_output` | `LATENT`  | The 'denoised\_output' represents the samples after a denoising process has been applied, potentially enhancing the clarity and quality of the generated samples. |


# SamplerCustomAdvanced - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerCustomAdvanced

Complete documentation for the SamplerCustomAdvanced node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerCustomAdvanced/en.md)

The SamplerCustomAdvanced node performs advanced latent space sampling using custom noise, guidance, and sampling configurations. It processes a latent image through a guided sampling process with customizable noise generation and sigma schedules, producing both the final sampled output and a denoised version when available.

## Inputs

| Parameter      | Data Type | Required | Range | Description                                                                                                                                                                                                                                       |
| -------------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `noise`        | NOISE     | Yes      | -     | The noise generator that provides the initial noise pattern and seed for the sampling process                                                                                                                                                     |
| `guider`       | GUIDER    | Yes      | -     | The guidance model that directs the sampling process toward desired outputs                                                                                                                                                                       |
| `sampler`      | SAMPLER   | Yes      | -     | The sampling algorithm that defines how the latent space is traversed during generation                                                                                                                                                           |
| `sigmas`       | SIGMAS    | Yes      | -     | The sigma schedule that controls the noise levels throughout the sampling steps                                                                                                                                                                   |
| `latent_image` | LATENT    | Yes      | -     | The initial latent representation that serves as the starting point for sampling. Supports optional `noise_mask` for selective denoising, and optional `downscale_ratio_spacial` and `downscale_ratio_temporal` keys for advanced latent handling |

## Outputs

| Output Name       | Data Type | Description                                                                                                                                                                                                                                     |
| ----------------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `output`          | LATENT    | The final sampled latent representation after completing the sampling process. Any `downscale_ratio_spacial` or `downscale_ratio_temporal` keys from the input latent are removed from this output                                              |
| `denoised_output` | LATENT    | A denoised version of the output when the sampling process produces an intermediate clean prediction (x0), otherwise returns the same as the output. When available, this represents the model's best estimate of the clean latent at each step |

***

**Source fingerprint (SHA-256):** `c6217a2b89009237366109e2156e279c3a1077f28c9e8bf9808b1f04788c5370`


# SamplerDPMAdaptative - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDPMAdaptative

Complete documentation for the SamplerDPMAdaptative node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDPMAdaptative/en.md)

The SamplerDPMAdaptative node implements an adaptive DPM (Diffusion Probabilistic Model) sampler that automatically adjusts step sizes during the sampling process. It uses tolerance-based error control to determine optimal step sizes, balancing computational efficiency with sampling accuracy. This adaptive approach helps maintain quality while potentially reducing the number of steps needed.

## Inputs

| Parameter       | Data Type | Required | Range     | Description                                                   |
| --------------- | --------- | -------- | --------- | ------------------------------------------------------------- |
| `order`         | INT       | Yes      | 2-3       | The order of the sampler method (default: 3)                  |
| `rtol`          | FLOAT     | Yes      | 0.0-100.0 | Relative tolerance for error control (default: 0.05)          |
| `atol`          | FLOAT     | Yes      | 0.0-100.0 | Absolute tolerance for error control (default: 0.0078)        |
| `h_init`        | FLOAT     | Yes      | 0.0-100.0 | Initial step size (default: 0.05)                             |
| `pcoeff`        | FLOAT     | Yes      | 0.0-100.0 | Proportional coefficient for step size control (default: 0.0) |
| `icoeff`        | FLOAT     | Yes      | 0.0-100.0 | Integral coefficient for step size control (default: 1.0)     |
| `dcoeff`        | FLOAT     | Yes      | 0.0-100.0 | Derivative coefficient for step size control (default: 0.0)   |
| `accept_safety` | FLOAT     | Yes      | 0.0-100.0 | Safety factor for step acceptance (default: 0.81)             |
| `eta`           | FLOAT     | Yes      | 0.0-100.0 | Stochasticity parameter (default: 0.0)                        |
| `s_noise`       | FLOAT     | Yes      | 0.0-100.0 | Noise scaling factor (default: 1.0)                           |

## Outputs

| Output Name | Data Type | Description                                        |
| ----------- | --------- | -------------------------------------------------- |
| `sampler`   | SAMPLER   | Returns a configured DPM adaptive sampler instance |

***

**Source fingerprint (SHA-256):** `6f7bc9c02604d2645a3b33aa418c99706228ec5947722a7e45a0a519f7a42a9f`


# SamplerDPMPP_2M_SDE - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDPMPP_2M_SDE

Complete documentation for the SamplerDPMPP_2M_SDE node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDPMPP_2M_SDE/en.md)

The SamplerDPMPP\_2M\_SDE node creates a DPM++ 2M SDE sampler for diffusion models. This sampler uses second-order differential equation solvers with stochastic differential equations to generate samples. It provides different solver types and noise handling options to control the sampling process.

## Inputs

| Parameter      | Data Type | Required | Range                      | Description                                                                                                                                                                                                                  |
| -------------- | --------- | -------- | -------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `solver_type`  | STRING    | Yes      | `"midpoint"`<br />`"heun"` | The type of differential equation solver to use for the sampling process                                                                                                                                                     |
| `eta`          | FLOAT     | Yes      | 0.0 - 100.0                | Controls the stochasticity of the sampling process (default: 1.0)                                                                                                                                                            |
| `s_noise`      | FLOAT     | Yes      | 0.0 - 100.0                | Controls the amount of noise added during sampling (default: 1.0)                                                                                                                                                            |
| `noise_device` | STRING    | Yes      | `"gpu"`<br />`"cpu"`       | The device where noise calculations are performed. When set to "cpu", the sampler uses CPU-based noise generation; when set to "gpu", it uses GPU-based noise generation for potentially faster performance (default: "gpu") |

## Outputs

| Output Name | Data Type | Description                                                        |
| ----------- | --------- | ------------------------------------------------------------------ |
| `sampler`   | SAMPLER   | A configured sampler object ready for use in the sampling pipeline |

***

**Source fingerprint (SHA-256):** `1f699504ddefc6bdebee0fbad31b59aa38611f0fcdc40a15898be3db184872a6`


# SamplerDPMPP_2S_Ancestral - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDPMPP_2S_Ancestral

Complete documentation for the SamplerDPMPP_2S_Ancestral node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDPMPP_2S_Ancestral/en.md)

The SamplerDPMPP\_2S\_Ancestral node creates a sampler that uses the DPM++ 2S Ancestral sampling method for generating images. This sampler combines deterministic and stochastic elements to produce varied results while maintaining some consistency. It allows you to control the randomness and noise levels during the sampling process.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                                                    |
| --------- | --------- | -------- | ----------- | ------------------------------------------------------------------------------ |
| `eta`     | FLOAT     | Yes      | 0.0 - 100.0 | Controls the amount of stochastic noise added during sampling (default: 1.0)   |
| `s_noise` | FLOAT     | Yes      | 0.0 - 100.0 | Controls the scale of noise applied during the sampling process (default: 1.0) |

## Outputs

| Output Name | Data Type | Description                                                                   |
| ----------- | --------- | ----------------------------------------------------------------------------- |
| `sampler`   | SAMPLER   | Returns a configured sampler object that can be used in the sampling pipeline |

***

**Source fingerprint (SHA-256):** `f18f51eb960250b52e7cbe58e19ed61d9a64876368c643b83a88e80fdb821d7d`


# SamplerDPMPP_3M_SDE - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDPMPP_3M_SDE

Complete documentation for the SamplerDPMPP_3M_SDE node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDPMPP_3M_SDE/en.md)

The SamplerDPMPP\_3M\_SDE node creates a DPM++ 3M SDE sampler for use in the sampling process. This sampler uses a third-order multistep stochastic differential equation method with configurable noise parameters. The node allows you to choose whether noise calculations are performed on the GPU or CPU.

## Inputs

| Parameter      | Data Type | Required | Range            | Description                                                                   |
| -------------- | --------- | -------- | ---------------- | ----------------------------------------------------------------------------- |
| `eta`          | FLOAT     | Yes      | 0.0 - 100.0      | Controls the stochasticity of the sampling process (default: 1.0)             |
| `s_noise`      | FLOAT     | Yes      | 0.0 - 100.0      | Controls the amount of noise added during sampling (default: 1.0)             |
| `noise_device` | COMBO     | Yes      | "gpu"<br />"cpu" | Selects the device for noise calculations, either GPU or CPU (default: "gpu") |

## Outputs

| Output Name | Data Type | Description                                                       |
| ----------- | --------- | ----------------------------------------------------------------- |
| `sampler`   | SAMPLER   | Returns a configured sampler object for use in sampling workflows |

***

**Source fingerprint (SHA-256):** `d25f8f69211ebca5aca8d1925d53f90a1bee3f883239635bffc107b5fdae8b36`


# SamplerDPMPP_SDE - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDPMPP_SDE

Complete documentation for the SamplerDPMPP_SDE node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerDPMPP_SDE/en.md)

The SamplerDPMPP\_SDE node creates a DPM++ SDE (Stochastic Differential Equation) sampler for use in the sampling process. This sampler provides a stochastic sampling method with configurable noise parameters and device selection. It returns a sampler object that can be used in the sampling pipeline.

## Inputs

| Parameter      | Data Type | Required | Range            | Description                                                                |
| -------------- | --------- | -------- | ---------------- | -------------------------------------------------------------------------- |
| `eta`          | FLOAT     | Yes      | 0.0 - 100.0      | Controls the stochasticity of the sampling process (default: 1.0)          |
| `s_noise`      | FLOAT     | Yes      | 0.0 - 100.0      | Controls the amount of noise added during sampling (default: 1.0)          |
| `r`            | FLOAT     | Yes      | 0.0 - 100.0      | A parameter that influences the sampling behavior (default: 0.5)           |
| `noise_device` | COMBO     | Yes      | "gpu"<br />"cpu" | Selects the device where noise calculations are performed (default: "gpu") |

## Outputs

| Output Name | Data Type | Description                                                                 |
| ----------- | --------- | --------------------------------------------------------------------------- |
| `sampler`   | SAMPLER   | Returns a configured DPM++ SDE sampler object for use in sampling pipelines |

***

**Source fingerprint (SHA-256):** `613c129801297c6b7e993727e570476f8b3b1aef16a402cf2115922299944402`


# SamplerDpmpp2mSde - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDpmpp2mSde

Complete documentation for the SamplerDpmpp2mSde node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to generate a sampler for the DPMPP\_2M\_SDE model, allowing for the creation of samples based on specified solver types, noise levels, and computational device preferences. It abstracts the complexities of sampler configuration, providing a streamlined interface for generating samples with customized settings.

## Inputs

| Parameter      | Data Type      | Description                                                                                                                                                                                    |
| -------------- | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `solver_type`  | COMBO\[STRING] | Specifies the solver type to be used in the sampling process, offering options between 'midpoint' and 'heun'. This choice influences the numerical integration method applied during sampling. |
| `eta`          | `FLOAT`        | Determines the step size in the numerical integration, affecting the granularity of the sampling process. A higher value indicates a larger step size.                                         |
| `s_noise`      | `FLOAT`        | Controls the level of noise introduced during the sampling process, influencing the variability of the generated samples.                                                                      |
| `noise_device` | COMBO\[STRING] | Indicates the computational device ('gpu' or 'cpu') on which the noise generation process is executed, affecting performance and efficiency.                                                   |

## Outputs

| Parameter | Data Type | Description                                                                                             |
| --------- | --------- | ------------------------------------------------------------------------------------------------------- |
| `sampler` | `SAMPLER` | The output is a sampler configured according to the specified parameters, ready for generating samples. |


# SamplerDpmppSde - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerDpmppSde

Complete documentation for the SamplerDpmppSde node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to generate a sampler for the DPM++ SDE (Stochastic Differential Equation) model. It adapts to both CPU and GPU execution environments, optimizing the sampler's implementation based on the available hardware.

## Inputs

| Parameter      | Data Type      | Description                                                                                                                |
| -------------- | -------------- | -------------------------------------------------------------------------------------------------------------------------- |
| `eta`          | FLOAT          | Specifies the step size for the SDE solver, influencing the granularity of the sampling process.                           |
| `s_noise`      | FLOAT          | Determines the level of noise to be applied during the sampling process, affecting the diversity of the generated samples. |
| `r`            | FLOAT          | Controls the ratio of noise reduction in the sampling process, impacting the clarity and quality of the generated samples. |
| `noise_device` | COMBO\[STRING] | Selects the execution environment (CPU or GPU) for the sampler, optimizing performance based on available hardware.        |

## Outputs

| Parameter | Data Type | Description                                                                                           |
| --------- | --------- | ----------------------------------------------------------------------------------------------------- |
| `sampler` | SAMPLER   | The generated sampler configured with the specified parameters, ready for use in sampling operations. |


# SamplerER_SDE - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerER_SDE

Complete documentation for the SamplerER_SDE node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerER_SDE/en.md)

The SamplerER\_SDE node provides specialized sampling methods for diffusion models, offering different solver types including ER-SDE, Reverse-time SDE, and ODE approaches. It allows control over the stochastic behavior and computational stages of the sampling process. The node automatically adjusts parameters based on the selected solver type to ensure proper functionality.

## Inputs

| Parameter     | Data Type | Required | Range                                       | Description                                                                                                                                            |
| ------------- | --------- | -------- | ------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `solver_type` | COMBO     | Yes      | "ER-SDE"<br />"Reverse-time SDE"<br />"ODE" | The type of solver to use for sampling. Determines the mathematical approach for the diffusion process.                                                |
| `max_stage`   | INT       | No       | 1-3                                         | The maximum number of stages for the sampling process (default: 3). Controls the computational complexity and quality.                                 |
| `eta`         | FLOAT     | No       | 0.0-100.0                                   | Stochastic strength of reverse-time SDE (default: 1.0). When eta=0, it reduces to deterministic ODE. This setting doesn't apply to ER-SDE solver type. |
| `s_noise`     | FLOAT     | No       | 0.0-100.0                                   | Noise scaling factor for the sampling process (default: 1.0). Controls the amount of noise applied during sampling.                                    |

**Parameter Constraints:**

* When `solver_type` is set to "ODE" or when using "Reverse-time SDE" with `eta`=0, both `eta` and `s_noise` are automatically set to 0 regardless of user input values.
* The `eta` parameter only affects "Reverse-time SDE" solver type and has no effect on "ER-SDE" solver type.

## Outputs

| Output Name | Data Type | Description                                                                                               |
| ----------- | --------- | --------------------------------------------------------------------------------------------------------- |
| `sampler`   | SAMPLER   | A configured sampler object that can be used in the sampling pipeline with the specified solver settings. |

***

**Source fingerprint (SHA-256):** `7a822bd28a41e616dea9feb1826d5bc1594fe0ba7429a7de21c602fe9f84ff10`


# SamplerEulerAncestral - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerEulerAncestral

Complete documentation for the SamplerEulerAncestral node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerEulerAncestral/en.md)

The SamplerEulerAncestral node creates an Euler Ancestral sampler for generating images. This sampler uses a specific mathematical approach that combines Euler integration with ancestral sampling techniques to produce image variations. The node allows you to configure the sampling behavior by adjusting parameters that control the randomness and step size during the generation process.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                                                                                     |
| --------- | --------- | -------- | ----------- | --------------------------------------------------------------------------------------------------------------- |
| `eta`     | FLOAT     | No       | 0.0 - 100.0 | Controls the step size and stochasticity of the sampling process (default: 1.0). This is an advanced parameter. |
| `s_noise` | FLOAT     | No       | 0.0 - 100.0 | Controls the amount of noise added during sampling (default: 1.0). This is an advanced parameter.               |

## Outputs

| Output Name | Data Type | Description                                                                             |
| ----------- | --------- | --------------------------------------------------------------------------------------- |
| `sampler`   | SAMPLER   | Returns a configured Euler Ancestral sampler that can be used in the sampling pipeline. |

***

**Source fingerprint (SHA-256):** `e54d6ae421731851d54ba747063ff804b1def6024b530afdec0748d255ad1251`


# SamplerEulerAncestralCFGPP - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerEulerAncestralCFGPP

Complete documentation for the SamplerEulerAncestralCFGPP node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerEulerAncestralCFGPP/en.md)

The SamplerEulerAncestralCFGPP node creates a sampler that uses the Euler Ancestral method with classifier-free guidance (CFG++) for image generation. This sampler combines ancestral sampling techniques with guidance conditioning to produce diverse image variations while maintaining coherence, and allows fine-tuning through parameters that control noise and step size adjustments.

## Inputs

| Parameter | Data Type | Required | Range      | Description                                                                                                    |
| --------- | --------- | -------- | ---------- | -------------------------------------------------------------------------------------------------------------- |
| `eta`     | FLOAT     | Yes      | 0.0 - 1.0  | Controls the step size during sampling, with higher values resulting in more aggressive updates (default: 1.0) |
| `s_noise` | FLOAT     | Yes      | 0.0 - 10.0 | Adjusts the amount of noise added during the sampling process (default: 1.0)                                   |

## Outputs

| Output Name | Data Type | Description                                                                           |
| ----------- | --------- | ------------------------------------------------------------------------------------- |
| `sampler`   | SAMPLER   | Returns a configured sampler object that can be used in the image generation pipeline |

***

**Source fingerprint (SHA-256):** `c519c9ff857a13e3a99fc907672925747565d8f1c6456c345138b33ebeda2b17`


# SamplerLCM - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerLCM

Complete documentation for the SamplerLCM node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerLCM/en.md)

The SamplerLCM node provides an LCM (Latent Consistency Model) sampler with tunable per-step noise parameters. It allows you to control the noise applied at each sampling step, enabling fine-grained adjustment of the sampling process.

## Inputs

| Parameter        | Data Type | Required | Range                    | Description                                                                                                          |
| ---------------- | --------- | -------- | ------------------------ | -------------------------------------------------------------------------------------------------------------------- |
| `s_noise`        | FLOAT     | Yes      | 0.0 to 64.0 (step: 0.01) | Per-step noise multiplier at the first step. A value of 1.0 matches the model's training noise scale. (default: 1.0) |
| `s_noise_end`    | FLOAT     | Yes      | 0.0 to 64.0 (step: 0.01) | Per-step noise multiplier at the last step. Set equal to `s_noise` for a constant noise schedule. (default: 1.0)     |
| `noise_clip_std` | FLOAT     | Yes      | 0.0 to 10.0 (step: 0.01) | Clamps the per-step noise to within +/- N standard deviations. A value of 0 disables clamping. (default: 0.0)        |

## Outputs

| Output Name | Data Type | Description                                                                 |
| ----------- | --------- | --------------------------------------------------------------------------- |
| `SAMPLER`   | SAMPLER   | The configured LCM sampler object, ready to be used in a sampling workflow. |

***

**Source fingerprint (SHA-256):** `e6f9007f66625baeee8850018784187cf45117591c443f117c593eef547ada98`


# SamplerLCMUpscale - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerLCMUpscale

Complete documentation for the SamplerLCMUpscale node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerLCMUpscale/en.md)

The SamplerLCMUpscale node provides a specialized sampling method that combines Latent Consistency Model (LCM) sampling with image upscaling capabilities. It allows you to upscale images during the sampling process using various interpolation methods, making it useful for generating higher resolution outputs while maintaining image quality.

## Inputs

| Parameter        | Data Type | Required | Range                                                                     | Description                                                                                      |
| ---------------- | --------- | -------- | ------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------ |
| `scale_ratio`    | FLOAT     | No       | 0.1 - 20.0                                                                | The scaling factor to apply during upscaling (default: 1.0)                                      |
| `scale_steps`    | INT       | No       | -1 - 1000                                                                 | The number of steps to use for upscaling process. Use -1 for automatic calculation (default: -1) |
| `upscale_method` | COMBO     | Yes      | "bislerp"<br />"nearest-exact"<br />"bilinear"<br />"area"<br />"bicubic" | The interpolation method used for upscaling the image                                            |

## Outputs

| Output Name | Data Type | Description                                                                   |
| ----------- | --------- | ----------------------------------------------------------------------------- |
| `sampler`   | SAMPLER   | Returns a configured sampler object that can be used in the sampling pipeline |

***

**Source fingerprint (SHA-256):** `11cd4de455d8345f0008757e7402b6cba1c21cf6eeebdd41f4500e615d826920`


# SamplerLMS - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerLMS

Complete documentation for the SamplerLMS node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerLMS/en.md)

The SamplerLMS node creates a Least Mean Squares (LMS) sampler for use in diffusion models. It generates a sampler object that can be used in the sampling process, allowing you to control the order of the LMS algorithm for numerical stability and accuracy.

## Inputs

| Parameter | Data Type | Required | Range    | Description                                                                                                                  |
| --------- | --------- | -------- | -------- | ---------------------------------------------------------------------------------------------------------------------------- |
| `order`   | INT       | Yes      | 1 to 100 | The order parameter for the LMS sampler algorithm, which controls the numerical method's accuracy and stability (default: 4) |

## Outputs

| Output Name | Data Type | Description                                                               |
| ----------- | --------- | ------------------------------------------------------------------------- |
| `sampler`   | SAMPLER   | A configured LMS sampler object that can be used in the sampling pipeline |

***

**Source fingerprint (SHA-256):** `fc1f7965a2f1dc78d9ce1181fa0a1f584c2e6b5c3404c4d5463a765498e20536`


# SamplerSASolver - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerSASolver

Complete documentation for the SamplerSASolver node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerSASolver/en.md)

The SamplerSASolver node implements a custom sampling algorithm for diffusion models. It uses a predictor-corrector approach with configurable order settings and stochastic differential equation (SDE) parameters to generate samples from the input model.

## Inputs

| Parameter           | Data Type | Required | Range       | Description                                                             |
| ------------------- | --------- | -------- | ----------- | ----------------------------------------------------------------------- |
| `model`             | MODEL     | Yes      | -           | The diffusion model to use for sampling                                 |
| `eta`               | FLOAT     | No       | 0.0 - 10.0  | Controls the step size scaling factor (default: 1.0)                    |
| `sde_start_percent` | FLOAT     | No       | 0.0 - 1.0   | The starting percentage for SDE sampling (default: 0.2)                 |
| `sde_end_percent`   | FLOAT     | No       | 0.0 - 1.0   | The ending percentage for SDE sampling (default: 0.8)                   |
| `s_noise`           | FLOAT     | No       | 0.0 - 100.0 | Controls the amount of noise added during sampling (default: 1.0)       |
| `predictor_order`   | INT       | No       | 1 - 6       | The order of the predictor component in the solver (default: 3)         |
| `corrector_order`   | INT       | No       | 0 - 6       | The order of the corrector component in the solver (default: 4)         |
| `use_pece`          | BOOLEAN   | No       | -           | Enables or disables the PECE (Predict-Evaluate-Correct-Evaluate) method |
| `simple_order_2`    | BOOLEAN   | No       | -           | Enables or disables simplified second-order calculations                |

## Outputs

| Output Name | Data Type | Description                                                        |
| ----------- | --------- | ------------------------------------------------------------------ |
| `sampler`   | SAMPLER   | A configured sampler object that can be used with diffusion models |

***

**Source fingerprint (SHA-256):** `f1491a63377d4d8a5c44cb7109afba09678ef9c048786f9086a5437aacb17753`


# SamplerSEEDS2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplerSEEDS2

Complete documentation for the SamplerSEEDS2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplerSEEDS2/en.md)

This node provides a configurable sampler for generating images. It implements the SEEDS-2 algorithm, which is a stochastic differential equation (SDE) solver. By adjusting its parameters, you can configure it to behave like several specific samplers, including `seeds_2`, `exp_heun_2_x0`, and `exp_heun_2_x0_sde`.

## Inputs

| Parameter     | Data Type | Required | Range                    | Description                                                             |
| ------------- | --------- | -------- | ------------------------ | ----------------------------------------------------------------------- |
| `solver_type` | COMBO     | Yes      | `"phi_1"`<br />`"phi_2"` | Selects the underlying solver algorithm for the sampler.                |
| `eta`         | FLOAT     | No       | 0.0 - 100.0              | Stochastic strength (default: 1.0).                                     |
| `s_noise`     | FLOAT     | No       | 0.0 - 100.0              | SDE noise multiplier (default: 1.0).                                    |
| `r`           | FLOAT     | No       | 0.01 - 1.0               | Relative step size for the intermediate stage (c2 node) (default: 0.5). |

## Outputs

| Output Name | Data Type | Description                                                             |
| ----------- | --------- | ----------------------------------------------------------------------- |
| `sampler`   | SAMPLER   | A configured sampler object that can be passed to other sampling nodes. |

***

**Source fingerprint (SHA-256):** `85cd8fe647b555e32e2aae9c2300ff9d3e01fcfd8bcdff687b0dc2aa0d06b47d`


# SamplingPercentToSigma - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SamplingPercentToSigma

Complete documentation for the SamplingPercentToSigma node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SamplingPercentToSigma/en.md)

The SamplingPercentToSigma node converts a sampling percentage value to a corresponding sigma value using the model's sampling parameters. It takes a percentage value between 0.0 and 1.0 and maps it to the appropriate sigma value in the model's noise schedule, with options to return either the calculated sigma or the actual maximum/minimum sigma values at the boundaries.

## Inputs

| Parameter             | Data Type | Required | Range                     | Description                                                                                                                             |
| --------------------- | --------- | -------- | ------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
| `model`               | MODEL     | Yes      | -                         | The model containing the sampling parameters used for conversion                                                                        |
| `sampling_percent`    | FLOAT     | Yes      | 0.0 to 1.0 (step: 0.0001) | The sampling percentage to convert to sigma (default: 0.0)                                                                              |
| `return_actual_sigma` | BOOLEAN   | Yes      | -                         | Return the actual sigma value instead of the value used for interval checks. This only affects results at 0.0 and 1.0. (default: False) |

## Outputs

| Output Name   | Data Type | Description                                                              |
| ------------- | --------- | ------------------------------------------------------------------------ |
| `sigma_value` | FLOAT     | The converted sigma value corresponding to the input sampling percentage |

***

**Source fingerprint (SHA-256):** `4aa5c1efdb5c9bf8c6b2c38db58845a71a0159d6b2ff7a71449934acb05eae1a`


# SaveTrainingDataset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveTrainingDataset

Complete documentation for the SaveTrainingDataset node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveTrainingDataset/en.md)

This node saves a prepared training dataset to your computer's hard drive. It takes encoded data, which includes image latents and their corresponding text conditioning, and organizes them into multiple smaller files called shards for easier management. The node automatically creates a folder in your output directory and saves both the data files and a metadata file describing the dataset.

## Inputs

| Parameter      | Data Type    | Required | Range       | Description                                                                              |
| -------------- | ------------ | -------- | ----------- | ---------------------------------------------------------------------------------------- |
| `latents`      | LATENT       | Yes      | N/A         | List of latent dicts from MakeTrainingDataset.                                           |
| `conditioning` | CONDITIONING | Yes      | N/A         | List of conditioning lists from MakeTrainingDataset.                                     |
| `folder_name`  | STRING       | No       | N/A         | Name of folder to save dataset (inside output directory). (default: "training\_dataset") |
| `shard_size`   | INT          | No       | 1 to 100000 | Number of samples per shard file. (default: 1000)                                        |

**Note:** The number of items in the `latents` list must exactly match the number of items in the `conditioning` list. The node will raise an error if these counts do not match.

## Outputs

This node does not produce any output data. Its function is to save files to your disk.

***

**Source fingerprint (SHA-256):** `88ef66ea13cb2cc3ab2c321fc88d84d6431c3503413f651a50a40fbc541b3e54`


# SetFirstSigma - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SetFirstSigma

Complete documentation for the SetFirstSigma node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SetFirstSigma/en.md)

The SetFirstSigma node modifies a sequence of sigma values by replacing the first sigma value in the sequence with a custom value. It takes an existing sigma sequence and a new sigma value as inputs, then returns a new sigma sequence where only the first element has been changed while keeping all other sigma values unchanged.

## Inputs

| Parameter | Data Type | Required | Range          | Description                                                                      |
| --------- | --------- | -------- | -------------- | -------------------------------------------------------------------------------- |
| `sigmas`  | SIGMAS    | Yes      | -              | The input sequence of sigma values to be modified                                |
| `sigma`   | FLOAT     | Yes      | 0.0 to 20000.0 | The new sigma value to set as the first element in the sequence (default: 136.0) |

## Outputs

| Output Name | Data Type | Description                                                                           |
| ----------- | --------- | ------------------------------------------------------------------------------------- |
| `sigmas`    | SIGMAS    | The modified sigma sequence with the first element replaced by the custom sigma value |

***

**Source fingerprint (SHA-256):** `7f5a5fa4b4aaa4cf31a725df74821ad400bf951320b1ce004087d7ec53668b63`


# SplitSigmas - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplitSigmas

Complete documentation for the SplitSigmas node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The SplitSigmas node is designed for dividing a sequence of sigma values into two parts based on a specified step. This functionality is crucial for operations that require different handling or processing of the initial and subsequent parts of the sigma sequence, enabling more flexible and targeted manipulation of these values.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                                                                                                    |
| --------- | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `sigmas`  | `SIGMAS`  | The 'sigmas' parameter represents the sequence of sigma values to be split. It is essential for determining the division point and the resulting two sequences of sigma values, impacting the node's execution and results.                                    |
| `step`    | `INT`     | The 'step' parameter specifies the index at which the sigma sequence should be split. It plays a critical role in defining the boundary between the two resulting sigma sequences, influencing the node's functionality and the characteristics of the output. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                                                                                |
| --------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `sigmas`  | `SIGMAS`  | The node outputs two sequences of sigma values, each representing a part of the original sequence divided at the specified step. These outputs are crucial for subsequent operations that require differentiated handling of sigma values. |


# SplitSigmasDenoise - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SplitSigmasDenoise

Complete documentation for the SplitSigmasDenoise node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SplitSigmasDenoise/en.md)

The SplitSigmasDenoise node divides a sequence of sigma values into two parts based on a denoising strength parameter. It splits the input sigmas into high and low sigma sequences, where the split point is determined by multiplying the total steps by the denoise factor. This allows for separating the noise schedule into different intensity ranges for specialized processing.

## Inputs

| Parameter | Data Type | Required | Range     | Description                                                                                    |
| --------- | --------- | -------- | --------- | ---------------------------------------------------------------------------------------------- |
| `sigmas`  | SIGMAS    | Yes      | -         | The input sequence of sigma values representing the noise schedule                             |
| `denoise` | FLOAT     | Yes      | 0.0 - 1.0 | The denoising strength factor that determines where to split the sigma sequence (default: 1.0) |

## Outputs

| Output Name   | Data Type | Description                                                            |
| ------------- | --------- | ---------------------------------------------------------------------- |
| `high_sigmas` | SIGMAS    | The first portion of the sigma sequence containing higher sigma values |
| `low_sigmas`  | SIGMAS    | The second portion of the sigma sequence containing lower sigma values |

***

**Source fingerprint (SHA-256):** `e458c32a51534011712885aa65bfb94bed09a1886954dee07447a7adf41ed456`


# StringCompare - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringCompare

Complete documentation for the StringCompare node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringCompare/en.md)

The StringCompare node compares two text strings using different comparison methods. It can check if one string starts with another, ends with another, or if both strings are exactly equal. The comparison can be performed with or without considering letter case differences.

## Inputs

| Parameter        | Data Type | Required | Range                                       | Description                                                       |
| ---------------- | --------- | -------- | ------------------------------------------- | ----------------------------------------------------------------- |
| `string_a`       | STRING    | Yes      | -                                           | The first string to compare                                       |
| `string_b`       | STRING    | Yes      | -                                           | The second string to compare against                              |
| `mode`           | COMBO     | Yes      | "Starts With"<br />"Ends With"<br />"Equal" | The comparison method to use (default: "Starts With")             |
| `case_sensitive` | BOOLEAN   | No       | -                                           | Whether to consider letter case during comparison (default: true) |

## Outputs

| Output Name | Data Type | Description                                                      |
| ----------- | --------- | ---------------------------------------------------------------- |
| `output`    | BOOLEAN   | Returns true if the comparison condition is met, false otherwise |

***

**Source fingerprint (SHA-256):** `18599228c31543f270afde0f3b838512ee12d1998b8de42c4d3e7852b1a5d8b2`


# StringConcatenate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringConcatenate

Complete documentation for the StringConcatenate node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringConcatenate/en.md)

The StringConcatenate node combines two text strings into one by joining them with a specified delimiter. It takes two input strings and a delimiter character or string, then outputs a single string where the two inputs are connected with the delimiter placed between them.

## Inputs

| Parameter   | Data Type | Required | Range | Description                                                                             |
| ----------- | --------- | -------- | ----- | --------------------------------------------------------------------------------------- |
| `string_a`  | STRING    | Yes      | -     | The first text string to concatenate                                                    |
| `string_b`  | STRING    | Yes      | -     | The second text string to concatenate                                                   |
| `delimiter` | STRING    | No       | -     | The character or string to insert between the two input strings (default: empty string) |

## Outputs

| Output Name | Data Type | Description                                                                     |
| ----------- | --------- | ------------------------------------------------------------------------------- |
| `output`    | STRING    | The combined string with the delimiter inserted between string\_a and string\_b |

***

**Source fingerprint (SHA-256):** `ea6fa7948d07e87b7ea3aeaf4f38c4cfdbfa5c5bd56d9f2935f94f1775686d08`


# StringContains - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringContains

Complete documentation for the StringContains node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringContains/en.md)

The StringContains node checks if a given string contains a specified substring. It can perform this check with either case-sensitive or case-insensitive matching, returning a boolean result indicating whether the substring was found within the main string.

## Inputs

| Parameter        | Data Type | Required | Range | Description                                                            |
| ---------------- | --------- | -------- | ----- | ---------------------------------------------------------------------- |
| `string`         | STRING    | Yes      | -     | The main text string to search within                                  |
| `substring`      | STRING    | Yes      | -     | The text to search for within the main string                          |
| `case_sensitive` | BOOLEAN   | No       | -     | Determines whether the search should be case-sensitive (default: true) |

## Outputs

| Output Name | Data Type | Description                                                           |
| ----------- | --------- | --------------------------------------------------------------------- |
| `contains`  | BOOLEAN   | Returns true if the substring is found in the string, false otherwise |

***

**Source fingerprint (SHA-256):** `9e85e51bc32c4041a66de8d5b11475aba3120eee1e8c5a37fedfaa470746888c`


# StringFormat - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringFormat

Complete documentation for the StringFormat node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringFormat/en.md)

## Overview

This node formats text using Python's string format method. It works like a template where you define a text pattern with placeholders, and then provide values to fill those placeholders. It supports all of Python's format options and features.

## Inputs

| Parameter  | Data Type | Required | Range | Description                                                                                                                 |
| ---------- | --------- | -------- | ----- | --------------------------------------------------------------------------------------------------------------------------- |
| `f_string` | STRING    | Yes      | N/A   | The format string template with placeholders (default: `{a}`). Supports multiline input.                                    |
| `values`   | STRING    | Yes      | N/A   | Dynamic input for providing values to fill placeholders in the format string. Multiple value inputs can be added as needed. |

**Note on `values` input:** This input is dynamic and can be expanded to include multiple named values. Each value input is labeled with a letter (a, b, c, etc.) and corresponds to a placeholder in the format string (e.g., `{a}`, `{b}`, `{c}`). You can add or remove value inputs as needed.

## Outputs

| Output Name | Data Type | Description                                                                             |
| ----------- | --------- | --------------------------------------------------------------------------------------- |
| `STRING`    | STRING    | The formatted text string with all placeholders replaced by their corresponding values. |

***

**Source fingerprint (SHA-256):** `72625287533829a8087687bb47f39bc265aced3d5f43066f615326d729725122`


# StringLength - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringLength

Complete documentation for the StringLength node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringLength/en.md)

The StringLength node calculates the number of characters in a text string. It takes any text input and returns the total count of characters, including spaces and punctuation. This is useful for measuring text length or validating string size requirements.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                         |
| --------- | --------- | -------- | ----- | ------------------------------------------------------------------- |
| `string`  | STRING    | Yes      | N/A   | The text string to measure the length of. Supports multiline input. |

## Outputs

| Output Name | Data Type | Description                                                                                  |
| ----------- | --------- | -------------------------------------------------------------------------------------------- |
| `length`    | INT       | The total number of characters in the input string, including spaces and special characters. |

***

**Source fingerprint (SHA-256):** `bfb0cae513e4bd5c179b3cd0071a71a6ad7d67e71891cf1152f8ff9632e6d217`


# StringReplace - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringReplace

Complete documentation for the StringReplace node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringReplace/en.md)

The StringReplace node performs text replacement operations on input strings. It searches for a specified substring within the input text and replaces all occurrences with a different substring. This node returns the modified string with all replacements applied.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                     |
| --------- | --------- | -------- | ----- | --------------------------------------------------------------- |
| `string`  | STRING    | Yes      | -     | The input text string where replacements will be performed      |
| `find`    | STRING    | Yes      | -     | The substring to search for within the input text               |
| `replace` | STRING    | Yes      | -     | The replacement text that will substitute all found occurrences |

## Outputs

| Output Name | Data Type | Description                                                                            |
| ----------- | --------- | -------------------------------------------------------------------------------------- |
| `output`    | STRING    | The modified string with all occurrences of the find text replaced by the replace text |

***

**Source fingerprint (SHA-256):** `7f384aff132eb6919b58f04163c4611a7b5545e1af9217f9aca60dc416c06d60`


# StringSubstring - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringSubstring

Complete documentation for the StringSubstring node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringSubstring/en.md)

The StringSubstring node extracts a portion of text from a larger string. It takes a starting position and ending position to define the section you want to extract, then returns the text between those two positions.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                                             |
| --------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------------- |
| `string`  | STRING    | Yes      | -     | The input text string to extract from. Supports multi-line text.                                        |
| `start`   | INT       | Yes      | -     | The starting position index for the substring. The first character is at index 0.                       |
| `end`     | INT       | Yes      | -     | The ending position index for the substring. The character at this index is not included in the result. |

## Outputs

| Output Name | Data Type | Description                                                                                                                                    |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| `output`    | STRING    | The extracted substring from the input text, containing all characters from the `start` position up to (but not including) the `end` position. |

***

**Source fingerprint (SHA-256):** `fd3ec23bbfe3a51f5481f1b0fe8b77f66e08469bb2a4bd3e266a7607f014e544`


# StringTrim - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StringTrim

Complete documentation for the StringTrim node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StringTrim/en.md)

The StringTrim node removes whitespace characters (such as spaces, tabs, and newlines) from the beginning, end, or both sides of a text string. You can choose to trim from the left side, right side, or both sides of the string. This is useful for cleaning up text inputs by removing unwanted whitespace.

## Inputs

| Parameter | Data Type | Required | Range                           | Description                                                                                                                                                         |
| --------- | --------- | -------- | ------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `string`  | STRING    | Yes      | -                               | The text string to process. Supports multiline input.                                                                                                               |
| `mode`    | COMBO     | Yes      | "Both"<br />"Left"<br />"Right" | Specifies which side(s) of the string to trim. "Both" removes whitespace from both ends, "Left" removes from the beginning only, "Right" removes from the end only. |

## Outputs

| Output Name | Data Type | Description                                                                     |
| ----------- | --------- | ------------------------------------------------------------------------------- |
| `output`    | STRING    | The trimmed text string with whitespace removed according to the selected mode. |

***

**Source fingerprint (SHA-256):** `b7d0694b752f3017a5f8ee9a6ca1d88260f761576b5960f2cb210e34efb09d18`


# StripWhitespace - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/StripWhitespace

Complete documentation for the StripWhitespace node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/StripWhitespace/en.md)

This node removes any extra spaces, tabs, or newlines from the beginning and end of a text string. It takes a text input and returns a cleaned version with the leading and trailing whitespace trimmed off.

**Note: This node is deprecated and superseded by the Trim Text node.**

## Inputs

| Parameter | Data Type | Required | Range | Description                                                           |
| --------- | --------- | -------- | ----- | --------------------------------------------------------------------- |
| `text`    | STRING    | Yes      | N/A   | The text string from which to remove leading and trailing whitespace. |

## Outputs

| Output Name | Data Type | Description                                                                     |
| ----------- | --------- | ------------------------------------------------------------------------------- |
| `text`      | STRING    | The processed text with all leading and trailing whitespace characters removed. |

***

**Source fingerprint (SHA-256):** `182f01e15050b35cc33de7792886721873daf387a934befbe1ff37cbcd766143`


# TextGenerate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextGenerate

Complete documentation for the TextGenerate node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextGenerate/en.md)

The TextGenerate node uses a CLIP model to create text based on a user's prompt. It can optionally use images, video, or audio as additional context to guide the text generation. You can control the length of the output, enable a thinking mode for supported models, and choose whether to use random sampling with various settings or to generate text without sampling.

## Inputs

| Parameter              | Data Type | Required | Range                     | Description                                                                                                                                                                                                           |
| ---------------------- | --------- | -------- | ------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `clip`                 | CLIP      | Yes      | N/A                       | The CLIP model used for tokenizing the prompt and generating text.                                                                                                                                                    |
| `prompt`               | STRING    | Yes      | N/A                       | The text prompt that guides the generation. This field supports multiple lines and dynamic prompts. The default value is an empty string.                                                                             |
| `image`                | IMAGE     | No       | N/A                       | An optional image that can be used alongside the text prompt to influence the generated text.                                                                                                                         |
| `video`                | IMAGE     | No       | N/A                       | Video frames as an image batch. Assumed to be 24 FPS; subsampled to 1 FPS internally.                                                                                                                                 |
| `audio`                | AUDIO     | No       | N/A                       | An optional audio input that can be used alongside the text prompt to influence the generated text.                                                                                                                   |
| `max_length`           | INT       | Yes      | 1 to 2048                 | The maximum number of tokens the model will generate. The default value is 256.                                                                                                                                       |
| `sampling_mode`        | COMBO     | Yes      | `"on"`<br />`"off"`       | Controls whether random sampling is used during text generation. When set to "on", additional parameters for controlling the sampling become available. The default is "on".                                          |
| `thinking`             | BOOLEAN   | No       | True or False             | Operate in thinking mode if the model supports it. The default value is False.                                                                                                                                        |
| `use_default_template` | BOOLEAN   | No       | True or False             | Use the built-in system prompt/template if the model has one. The default value is True. This is an advanced parameter.                                                                                               |
| `temperature`          | FLOAT     | No       | 0.01 to 2.0               | Controls the randomness of the output. Lower values make the output more predictable, higher values make it more creative. This parameter is only available when `sampling_mode` is "on". The default value is 0.7.   |
| `top_k`                | INT       | No       | 0 to 1000                 | Limits the sampling pool to the top K most likely next tokens. A value of 0 disables this filter. This parameter is only available when `sampling_mode` is "on". The default value is 64.                             |
| `top_p`                | FLOAT     | No       | 0.0 to 1.0                | Uses nucleus sampling, limiting choices to tokens whose cumulative probability is less than this value. This parameter is only available when `sampling_mode` is "on". The default value is 0.95.                     |
| `min_p`                | FLOAT     | No       | 0.0 to 1.0                | Sets a minimum probability threshold for tokens to be considered. This parameter is only available when `sampling_mode` is "on". The default value is 0.05.                                                           |
| `repetition_penalty`   | FLOAT     | No       | 0.0 to 5.0                | Penalizes tokens that have already been generated to reduce repetition. A value of 1.0 applies no penalty. This parameter is only available when `sampling_mode` is "on". The default value is 1.05.                  |
| `presence_penalty`     | FLOAT     | No       | 0.0 to 5.0                | Penalizes new tokens based on whether they have appeared in the text so far, encouraging the model to talk about new topics. This parameter is only available when `sampling_mode` is "on". The default value is 0.0. |
| `seed`                 | INT       | No       | 0 to 18446744073709551615 | A number used to initialize the random number generator for reproducible results when sampling is "on". The default value is 0.                                                                                       |

**Note:** The parameters `temperature`, `top_k`, `top_p`, `min_p`, `repetition_penalty`, `presence_penalty`, and `seed` are only active and visible in the node interface when the `sampling_mode` is set to "on".

## Outputs

| Output Name      | Data Type | Description                                                                                    |
| ---------------- | --------- | ---------------------------------------------------------------------------------------------- |
| `generated_text` | STRING    | The text generated by the model based on the input prompt and optional image, video, or audio. |

***

**Source fingerprint (SHA-256):** `d2d08577e4d5aeea60f5517377730c4917df607be32f29227b07b1011b0f2c2d`


# TextGenerateLTX2Prompt - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextGenerateLTX2Prompt

Complete documentation for the TextGenerateLTX2Prompt node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextGenerateLTX2Prompt/en.md)

The TextGenerateLTX2Prompt node is a specialized version of a text generation node. It takes a user's text prompt and automatically formats it with specific system instructions before sending it to a language model for enhancement or completion. The node can operate in two modes: text-only or with an image reference, using different system prompts for each case.

## Inputs

| Parameter              | Data Type | Required | Range                                                         | Description                                                                                                                    |
| ---------------------- | --------- | -------- | ------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------ |
| `clip`                 | CLIP      | Yes      |                                                               | The CLIP model used for text encoding.                                                                                         |
| `prompt`               | STRING    | Yes      |                                                               | The raw text input from the user that will be enhanced or completed.                                                           |
| `max_length`           | INT       | Yes      |                                                               | The maximum number of tokens the language model is allowed to generate.                                                        |
| `sampling_mode`        | COMBO     | Yes      | `"greedy"`<br />`"top_k"`<br />`"top_p"`<br />`"temperature"` | The sampling strategy used to select the next token during text generation.                                                    |
| `image`                | IMAGE     | No       |                                                               | An optional input image. When provided, the node uses a different system prompt that includes a placeholder for image context. |
| `thinking`             | BOOLEAN   | No       |                                                               | When enabled, the model will output its reasoning process before the final answer.                                             |
| `use_default_template` | BOOLEAN   | No       |                                                               | When enabled, the node will use the default chat template for formatting.                                                      |
| `video`                | VIDEO     | No       |                                                               | An optional video input that can be used as additional context for generation.                                                 |
| `audio`                | AUDIO     | No       |                                                               | An optional audio input that can be used as additional context for generation.                                                 |

**Note:** The behavior of the node changes based on the presence of the `image` input. If an image is provided, the generated prompt will be formatted for an image-to-video task using a system prompt that describes how to expand the prompt based on the image's content. If no image is provided, the formatting will be for a text-to-video task using a system prompt that expands the prompt into a detailed video generation description.

## Outputs

| Output Name | Data Type | Description                                                            |
| ----------- | --------- | ---------------------------------------------------------------------- |
| `output`    | STRING    | The enhanced or completed text string generated by the language model. |

***

**Source fingerprint (SHA-256):** `c037e526efab4b4e8eeeb84b4374d33a295996632b9897259806502ca32f48e1`


# TextToLowercase - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextToLowercase

Complete documentation for the TextToLowercase node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextToLowercase/en.md)

The Text to Lowercase node takes a text string as input and converts all of its characters to lowercase. It is a simple utility for standardizing text case.

> **Note:** This node is deprecated and superseded by the Convert Text Case node.

## Inputs

| Parameter | Data Type | Required | Range           | Description                                   |
| --------- | --------- | -------- | --------------- | --------------------------------------------- |
| `text`    | STRING    | Yes      | Any text string | The text string to be converted to lowercase. |

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `text`      | STRING    | The input text with all characters converted to lowercase. |

***

**Source fingerprint (SHA-256):** `7ebafc952672510cbadf4549d37c5566bef474b8d1d159af4086cde64bcad849`


# TextToUppercase - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TextToUppercase

Complete documentation for the TextToUppercase node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextToUppercase/en.md)

The Text to Uppercase node takes a text input and converts all of its characters to uppercase. It is a simple text processing utility that modifies the case of the provided string.

**Note:** This node is deprecated and superseded by the Convert Text Case node.

## Inputs

| Parameter | Data Type | Required | Range | Description                                   |
| --------- | --------- | -------- | ----- | --------------------------------------------- |
| `text`    | STRING    | Yes      | N/A   | The text string to be converted to uppercase. |

## Outputs

| Output Name | Data Type | Description                                                    |
| ----------- | --------- | -------------------------------------------------------------- |
| `text`      | STRING    | The resulting text with all characters converted to uppercase. |

***

**Source fingerprint (SHA-256):** `b1d8c05aceda4dfd95400b40fdf01b16dccaa4e093e62d298b12753bfc0278a2`


# TrainLoraNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TrainLoraNode

Complete documentation for the TrainLoraNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TrainLoraNode/en.md)

The TrainLoraNode creates and trains a LoRA (Low-Rank Adaptation) model on a diffusion model using provided latents and conditioning data. It allows you to fine-tune a model with custom training parameters, optimizers, and loss functions. The node outputs the trained LoRA weights, a loss history map, and the total training steps completed.

## Inputs

| Parameter                 | Data Type    | Required | Range                                         | Description                                                                                                                                                                                                   |
| ------------------------- | ------------ | -------- | --------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`                   | MODEL        | Yes      | -                                             | The model to train the LoRA on.                                                                                                                                                                               |
| `latents`                 | LATENT       | Yes      | -                                             | The Latents to use for training, serve as dataset/input of the model.                                                                                                                                         |
| `positive`                | CONDITIONING | Yes      | -                                             | The positive conditioning to use for training.                                                                                                                                                                |
| `batch_size`              | INT          | Yes      | 1-10000                                       | The batch size to use for training (default: 1).                                                                                                                                                              |
| `grad_accumulation_steps` | INT          | Yes      | 1-1024                                        | The number of gradient accumulation steps to use for training (default: 1).                                                                                                                                   |
| `steps`                   | INT          | Yes      | 1-100000                                      | The number of steps to train the LoRA for (default: 16).                                                                                                                                                      |
| `learning_rate`           | FLOAT        | Yes      | 0.0000001-1.0                                 | The learning rate to use for training (default: 0.0005).                                                                                                                                                      |
| `rank`                    | INT          | Yes      | 1-128                                         | The rank of the LoRA layers (default: 8).                                                                                                                                                                     |
| `optimizer`               | COMBO        | Yes      | "AdamW"<br />"Adam"<br />"SGD"<br />"RMSprop" | The optimizer to use for training (default: "AdamW").                                                                                                                                                         |
| `loss_function`           | COMBO        | Yes      | "MSE"<br />"L1"<br />"Huber"<br />"SmoothL1"  | The loss function to use for training (default: "MSE").                                                                                                                                                       |
| `seed`                    | INT          | Yes      | 0-18446744073709551615                        | The seed to use for training (used in generator for LoRA weight initialization and noise sampling) (default: 0).                                                                                              |
| `training_dtype`          | COMBO        | Yes      | "bf16"<br />"fp32"<br />"none"                | The dtype to use for training. 'none' preserves the model's native compute dtype instead of overriding it. For fp16 models, GradScaler is automatically enabled (default: "bf16").                            |
| `lora_dtype`              | COMBO        | Yes      | "bf16"<br />"fp32"                            | The dtype to use for lora (default: "bf16").                                                                                                                                                                  |
| `quantized_backward`      | BOOLEAN      | Yes      | -                                             | When using training\_dtype 'none' and training on quantized model, doing backward with quantized matmul when enabled (default: False).                                                                        |
| `algorithm`               | COMBO        | Yes      | Multiple options available                    | The algorithm to use for training.                                                                                                                                                                            |
| `gradient_checkpointing`  | BOOLEAN      | Yes      | -                                             | Use gradient checkpointing for training (default: True).                                                                                                                                                      |
| `checkpoint_depth`        | INT          | Yes      | 1-5                                           | Depth level for gradient checkpointing (default: 1).                                                                                                                                                          |
| `offloading`              | BOOLEAN      | Yes      | -                                             | Offload model weights to CPU during training to save GPU memory (default: False).                                                                                                                             |
| `existing_lora`           | COMBO        | Yes      | Multiple options available                    | The existing LoRA to append to. Set to None for new LoRA (default: "\[None]").                                                                                                                                |
| `bucket_mode`             | BOOLEAN      | Yes      | -                                             | Enable resolution bucket mode. When enabled, expects pre-bucketed latents from ResolutionBucket node (default: False).                                                                                        |
| `bypass_mode`             | BOOLEAN      | Yes      | -                                             | Enable bypass mode for training. When enabled, adapters are applied via forward hooks instead of weight modification. Useful for quantized models where weights cannot be directly modified (default: False). |

**Note:** The number of positive conditioning inputs must match the number of latent images. If only one positive conditioning is provided with multiple images, it will be automatically repeated for all images.

**Note on `training_dtype`:** When set to "none", the model's native compute dtype is preserved. For fp16 models, GradScaler is automatically enabled to prevent underflow during gradient computation. If `fp16_accumulation` is also enabled (via `--fast` flags), this combination can be numerically unstable and may cause NaN values.

**Note on `quantized_backward`:** This parameter is only relevant when `training_dtype` is set to "none" and the model is a quantized model. It enables quantized matrix multiplication during the backward pass.

**Note on `bypass_mode`:** When enabled, adapters are applied via forward hooks instead of modifying the model weights directly. This is particularly useful for quantized models where weights cannot be directly modified.

## Outputs

| Output Name | Data Type   | Description                                                                                     |
| ----------- | ----------- | ----------------------------------------------------------------------------------------------- |
| `lora`      | LORA\_MODEL | The trained LoRA weights that can be saved or applied to other models.                          |
| `loss_map`  | LOSS\_MAP   | A dictionary containing the training loss values over time.                                     |
| `steps`     | INT         | The total number of training steps completed (including any previous steps from existing LoRA). |

***

**Source fingerprint (SHA-256):** `e145145306330099293c8b4bb344ec0a38de690040bd796b84225f54638900c3`


# TruncateText - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TruncateText

Complete documentation for the TruncateText node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TruncateText/en.md)

This node shortens text by cutting it off at a specified maximum length. It takes any input text and returns only the first part, up to the number of characters you set. It is a simple way to ensure text does not exceed a certain size.

## Inputs

| Parameter    | Data Type | Required | Range      | Description                                                                             |
| ------------ | --------- | -------- | ---------- | --------------------------------------------------------------------------------------- |
| `text`       | STRING    | Yes      | N/A        | The text string to be truncated.                                                        |
| `max_length` | INT       | Yes      | 1 to 10000 | Maximum text length. The text will be cut off after this many characters (default: 77). |

## Outputs

| Output Name | Data Type | Description                                                                           |
| ----------- | --------- | ------------------------------------------------------------------------------------- |
| `string`    | STRING    | The truncated text, containing only the first `max_length` characters from the input. |

***

**Source fingerprint (SHA-256):** `b23c92af425be8f7b15d793bbe7f321cab6f7f3137a995bb9724948ae00145e4`


# VOIDSampler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VOIDSampler

Complete documentation for the VOIDSampler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VOIDSampler/en.md)

## Overview

The VOIDSampler node provides a specialized DDIM sampling method designed specifically for VOID inpainting models. It implements the same denoising process used during VOID model training, without the noise scaling that standard KSamplers apply. This node is intended for use with SamplerCustom or SamplerCustomAdvanced nodes, and should be paired with RandomNoise or VOIDWarpedNoiseSource.

## Inputs

This node has no configurable input parameters. It is a self-contained sampler that applies a fixed DDIM sampling algorithm.

| Parameter   | Data Type | Required | Range | Description                                     |
| ----------- | --------- | -------- | ----- | ----------------------------------------------- |
| *No inputs* | -         | -        | -     | This node does not accept any input parameters. |

## Outputs

| Output Name | Data Type | Description                                                                                                                   |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------------------------- |
| `SAMPLER`   | SAMPLER   | A sampler object implementing the VOID DDIM algorithm, ready to be connected to SamplerCustom or SamplerCustomAdvanced nodes. |

***

**Source fingerprint (SHA-256):** `ca30211dc30975a1c6447afd3f6dcdb29d59d31effabe9b7fed5b90ee1cab540`


# VOIDWarpedNoiseSource - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VOIDWarpedNoiseSource

Complete documentation for the VOIDWarpedNoiseSource node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VOIDWarpedNoiseSource/en.md)

## Overview

This node converts a LATENT (such as the output from the VOIDWarpedNoise node) into a NOISE source. This allows you to use the warped noise with the SamplerCustomAdvanced node for more controlled image generation.

## Inputs

| Parameter      | Data Type | Required | Range | Description                              |
| -------------- | --------- | -------- | ----- | ---------------------------------------- |
| `warped_noise` | LATENT    | Yes      | N/A   | Warped noise latent from VOIDWarpedNoise |

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `NOISE`     | NOISE     | A noise source that can be used with SamplerCustomAdvanced |

***

**Source fingerprint (SHA-256):** `9b1eeb2df7fc0bcf0649ff2d2425938eae5fbc44ecc0f5d1678b7e227b3a098f`


# VPScheduler - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VPScheduler

Complete documentation for the VPScheduler node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The VPScheduler node is designed to generate a sequence of noise levels (sigmas) based on the Variance Preserving (VP) scheduling method. This sequence is crucial for guiding the denoising process in diffusion models, allowing for controlled generation of images or other data types.

## Inputs

| Parameter  | Data Type | Description                                                                                                      |
| ---------- | --------- | ---------------------------------------------------------------------------------------------------------------- |
| `steps`    | INT       | Specifies the number of steps in the diffusion process, affecting the granularity of the generated noise levels. |
| `beta_d`   | FLOAT     | Determines the overall noise level distribution, influencing the variance of the generated noise levels.         |
| `beta_min` | FLOAT     | Sets the minimum boundary for the noise level, ensuring the noise does not fall below a certain threshold.       |
| `eps_s`    | FLOAT     | Adjusts the starting epsilon value, fine-tuning the initial noise level in the diffusion process.                |

## Outputs

| Parameter | Data Type | Description                                                                                                                               |
| --------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------- |
| `sigmas`  | SIGMAS    | A sequence of noise levels (sigmas) generated based on the VP scheduling method, used to guide the denoising process in diffusion models. |


# VideoLinearCFGGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VideoLinearCFGGuidance

Complete documentation for the VideoLinearCFGGuidance node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The VideoLinearCFGGuidance node applies a linear conditioning guidance scale to a video model, adjusting the influence of conditioned and unconditioned components over a specified range. This enables dynamic control over the generation process, allowing for fine-tuning of the model's output based on the desired level of conditioning.

## Inputs

| Parameter | Data Type | Description                                                                                                                                                                                                                                                      |
| --------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | The model parameter represents the video model to which the linear CFG guidance will be applied. It is crucial for defining the base model that will be modified with the guidance scale.                                                                        |
| `min_cfg` | `FLOAT`   | The min\_cfg parameter specifies the minimum conditioning guidance scale to be applied, serving as the starting point for the linear scale adjustment. It plays a key role in determining the lower bound of the guidance scale, influencing the model's output. |

## Outputs

| Parameter | Data Type | Description                                                                                                                                                                                                                        |
| --------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`   | MODEL     | The output is a modified version of the input model, with the linear CFG guidance scale applied. This adjusted model is capable of generating outputs with varying degrees of conditioning, based on the specified guidance scale. |


# VideoTriangleCFGGuidance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VideoTriangleCFGGuidance

Complete documentation for the VideoTriangleCFGGuidance node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VideoTriangleCFGGuidance/en.md)

The VideoTriangleCFGGuidance node applies a triangular classifier-free guidance scaling pattern to video models. It modifies the conditioning scale over time using a triangular wave function that oscillates between the minimum CFG value and the original conditioning scale. This creates a dynamic guidance pattern that can help improve video generation consistency and quality.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                                           |
| --------- | --------- | -------- | ----------- | --------------------------------------------------------------------- |
| `model`   | MODEL     | Yes      | -           | The video model to apply triangular CFG guidance to                   |
| `min_cfg` | FLOAT     | Yes      | 0.0 - 100.0 | The minimum CFG scale value for the triangular pattern (default: 1.0) |

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `model`     | MODEL     | The modified model with triangular CFG guidance applied |

***

**Source fingerprint (SHA-256):** `10b3ad8dcfe5e44f131b2e943e6645899102f406501418906cfe06ac2d21d433`


# BatchImagesMasksLatentsNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BatchImagesMasksLatentsNode

Complete documentation for the BatchImagesMasksLatentsNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BatchImagesMasksLatentsNode/en.md)

The Batch Images/Masks/Latents node combines multiple inputs of the same type into a single batch. It automatically detects whether the inputs are images, masks, or latent representations and uses the appropriate batching method. This is useful for preparing multiple items for processing by nodes that accept batched inputs.

## Inputs

| Parameter | Data Type              | Required | Range          | Description                                                                                                                                                           |
| --------- | ---------------------- | -------- | -------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `inputs`  | IMAGE, MASK, or LATENT | Yes      | 1 to 50 inputs | A dynamic list of inputs to be combined into a batch. You can add between 1 and 50 items. All items must be of the same type (all images, all masks, or all latents). |

**Note:** The node automatically determines the data type (IMAGE, MASK, or LATENT) based on the first item in the `inputs` list. All subsequent items must match this type. The node will fail if you try to mix different data types.

**Additional behavior based on input type:**

* **Images**: When batching images, the node pads images with fewer color channels to match the maximum channel count among all inputs (padding value is 1.0). It also resizes all images to match the dimensions of the first image using bilinear interpolation.
* **Masks**: When batching masks, the node resizes all masks to match the dimensions of the first mask using bilinear interpolation.
* **Latents**: When batching latents, the node reshapes all latent tensors to match the dimensions of the first latent's samples. It also combines the `batch_index` values from each latent, extending the list with sequential indices if a latent lacks a `batch_index`.

## Outputs

| Output Name | Data Type              | Description                                                                                                     |
| ----------- | ---------------------- | --------------------------------------------------------------------------------------------------------------- |
| `output`    | IMAGE, MASK, or LATENT | A single batched output. The data type matches the input type (batched IMAGE, batched MASK, or batched LATENT). |

***

**Source fingerprint (SHA-256):** `9f82b036c99577ebcda6de647c662def572ae1f01bd78dca1a0ab32f4698e09e`


# BeebleSwitchXVideoEdit - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BeebleSwitchXVideoEdit

Complete documentation for the BeebleSwitchXVideoEdit node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BeebleSwitchXVideoEdit/en.md)

# Beeble SwitchX Video Edit

Edit a video with Beeble SwitchX. This node can switch anything in the scene (background, lighting, costume) while preserving the original subject's pixels and motion. Provide a reference image and/or text prompt to describe the new look.

## Inputs

| Parameter         | Data Type | Required | Range                                    | Description                                                                                                                                                                                                                                 |
| ----------------- | --------- | -------- | ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `video`           | VIDEO     | Yes      | N/A                                      | The input video to edit. Maximum 240 frames, maximum \~2.77 megapixels per frame.                                                                                                                                                           |
| `prompt`          | STRING    | Yes      | N/A                                      | A text description of the desired new look for the scene.                                                                                                                                                                                   |
| `alpha_mode`      | COMBO     | Yes      | `"fill"`<br />`"select"`<br />`"custom"` | The alpha matte mode. "fill" mode has no separate matte and fills the entire frame. "select" mode uses a single keyframe image to define the area to edit. "custom" mode uses a full alpha video to define the area to edit frame by frame. |
| `max_resolution`  | COMBO     | Yes      | `"720p"`<br />`"1080p"`                  | The maximum resolution for the output video (default: "1080p").                                                                                                                                                                             |
| `seed`            | INT       | Yes      | 0 to 2147483647                          | A seed value for reproducibility. Using the same seed with the same inputs will produce the same result.                                                                                                                                    |
| `reference_image` | IMAGE     | No       | N/A                                      | An optional reference image that describes the desired new look for the scene.                                                                                                                                                              |

### Alpha Mode Details

The `alpha_mode` parameter controls which parts of the video are edited:

* **fill**: The entire video frame is edited. No separate alpha matte is produced.
* **select**: You provide a single keyframe image that defines the area to edit. The node will use this to determine which parts of the video to change.
* **custom**: You provide a full alpha video that defines the area to edit frame by frame. This gives you precise control over which parts of each frame are edited.

When using `select` mode, you must provide the `alpha_keyframe` image. When using `custom` mode, you must provide the `alpha_mask` video.

## Outputs

| Output Name | Data Type | Description                                                                                 |
| ----------- | --------- | ------------------------------------------------------------------------------------------- |
| `video`     | VIDEO     | The edited video with the scene changes applied.                                            |
| `alpha`     | VIDEO     | The alpha matte used by Beeble. This is empty for "fill" mode, which has no separate matte. |

***

**Source fingerprint (SHA-256):** `e2d67b037863f024f42c97943ec0d2daf32b547b232a7dfedd6de398f4b7ba28`


# BriaRemoveVideoBackground - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/BriaRemoveVideoBackground

Complete documentation for the BriaRemoveVideoBackground node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/BriaRemoveVideoBackground/en.md)

This node removes the background from a video using the Bria AI service. It processes the input video and replaces the original background with a solid color of your choice. The operation is performed via an external API, and the result is returned as a new video file.

## Inputs

| Parameter          | Data Type | Required | Range                                                                                                                                           | Description                                                                                                                             |
| ------------------ | --------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
| `video`            | VIDEO     | Yes      | N/A                                                                                                                                             | The input video file from which the background will be removed.                                                                         |
| `background_color` | STRING    | Yes      | `"Black"`<br />`"White"`<br />`"Gray"`<br />`"Red"`<br />`"Green"`<br />`"Blue"`<br />`"Yellow"`<br />`"Cyan"`<br />`"Magenta"`<br />`"Orange"` | The solid color to use as the new background for the output video.                                                                      |
| `seed`             | INT       | No       | 0 to 2147483647                                                                                                                                 | A seed value that controls whether the node should re-run. The results are non-deterministic regardless of the seed value. (default: 0) |

**Note:** The input video must have a duration of 60 seconds or less.

## Outputs

| Output Name | Data Type | Description                                                                              |
| ----------- | --------- | ---------------------------------------------------------------------------------------- |
| `output`    | VIDEO     | The processed video file with the background removed and replaced by the selected color. |

***

**Source fingerprint (SHA-256):** `bfff6362ab9c6664b7240926c4b84c7a1c05fd5ab450cf240a46db16e70cc6f7`


# ByteDance2FirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDance2FirstLastFrameNode

Complete documentation for the ByteDance2FirstLastFrameNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDance2FirstLastFrameNode/en.md)

This node uses ByteDance's Seedance 2.0 model to generate a video. It creates the video based on a text prompt and a required first frame image. You can optionally provide a last frame image to guide the ending of the video sequence.

## Inputs

| Parameter              | Data Type | Required | Range                                       | Description                                                                                                                                                                                                                                        |
| ---------------------- | --------- | -------- | ------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`                | COMBO     | Yes      | `"Seedance 2.0"`<br />`"Seedance 2.0 Fast"` | The model to use for video generation. Seedance 2.0 is for maximum quality, while Seedance 2.0 Fast is optimized for speed. Selecting a model will reveal additional inputs for `prompt`, `resolution`, `ratio`, `duration`, and `generate_audio`. |
| `first_frame`          | IMAGE     | No       | -                                           | The image to use as the first frame of the video.                                                                                                                                                                                                  |
| `last_frame`           | IMAGE     | No       | -                                           | The image to use as the last frame of the video.                                                                                                                                                                                                   |
| `first_frame_asset_id` | STRING    | No       | -                                           | A Seedance asset\_id to use as the first frame. This cannot be used at the same time as the `first_frame` image input. Default is an empty string.                                                                                                 |
| `last_frame_asset_id`  | STRING    | No       | -                                           | A Seedance asset\_id to use as the last frame. This cannot be used at the same time as the `last_frame` image input. Default is an empty string.                                                                                                   |
| `seed`                 | INT       | No       | 0 to 2147483647                             | A seed value. Changing this seed will cause the node to re-run, but the results are non-deterministic. Default is 0.                                                                                                                               |
| `watermark`            | BOOLEAN   | No       | -                                           | Whether to add a watermark to the generated video. Default is False.                                                                                                                                                                               |

**Parameter Constraints:**

* You must provide **either** a `first_frame` image **or** a `first_frame_asset_id`. Providing both will cause an error.
* You cannot provide both a `last_frame` image and a `last_frame_asset_id` for the same frame.
* The `model` input is a dynamic combo. After selecting a model, you must also fill in the revealed `prompt` field (a text description) and configure the other revealed parameters (`resolution`, `ratio`, `duration`, `generate_audio`).

## Outputs

| Output Name | Data Type | Description          |
| ----------- | --------- | -------------------- |
| `output`    | VIDEO     | The generated video. |

***

**Source fingerprint (SHA-256):** `434d6ad8f005515677b0de73b57df916aa589adff94aad892827202e6ebcb6e1`


# ByteDance2ReferenceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDance2ReferenceNode

Complete documentation for the ByteDance2ReferenceNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDance2ReferenceNode/en.md)

The ByteDance Seedance 2.0 Reference to Video node uses the Seedance 2.0 AI model to create, edit, or extend videos based on your text prompt and provided reference materials. It can use images, videos, and audio as references to guide the generation process, supporting tasks like video editing and extension.

## Inputs

| Parameter   | Data Type | Required | Range                                       | Description                                                                                                                                                                                                                                                                                                                                                     |
| ----------- | --------- | -------- | ------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`     | COMBO     | Yes      | `"Seedance 2.0"`<br />`"Seedance 2.0 Fast"` | The AI model to use. Seedance 2.0 is for maximum quality, while Seedance 2.0 Fast is optimized for speed. Selecting a model reveals additional required inputs for `prompt`, `resolution`, `duration`, `ratio`, `generate_audio`, and optional inputs for `reference_images`, `reference_videos`, `reference_audios`, `reference_assets`, and `auto_downscale`. |
| `seed`      | INT       | No       | 0 to 2147483647                             | A number used to control whether the node should re-run. The results are non-deterministic regardless of the seed value (default: 0).                                                                                                                                                                                                                           |
| `watermark` | BOOLEAN   | No       | `True` / `False`                            | Whether to add a watermark to the generated video (default: False).                                                                                                                                                                                                                                                                                             |

**Important Constraints:**

* At least one reference image or video (provided via the `reference_images`, `reference_videos`, or `reference_assets` inputs) is required for the node to work.
* A maximum of 9 reference images can be used in total (including those from `reference_images` and `reference_assets`).
* A maximum of 3 reference videos can be used in total (including those from `reference_videos` and `reference_assets`).
* A maximum of 3 reference audio clips can be used in total (including those from `reference_audios` and `reference_assets`).
* Each reference video must be at least 1.8 seconds long. The combined duration of all reference videos cannot exceed 15.1 seconds.
* Each reference audio clip must be at least 1.8 seconds long. The combined duration of all reference audio cannot exceed 15.1 seconds.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `video`     | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `4420682a5c2773ce1b4df2f4c9537754ec90ad8411d6332fa38d48f5ea88d66f`


# ByteDance2TextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDance2TextToVideoNode

Complete documentation for the ByteDance2TextToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDance2TextToVideoNode/en.md)

This node uses ByteDance's Seedance 2.0 API to generate a video from a text description. It sends your prompt to the selected model, waits for the video to be processed, and returns the final result.

## Inputs

| Parameter   | Data Type | Required | Range                                       | Description                                                                                                                                                                                                                                                     |
| ----------- | --------- | -------- | ------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`     | COMBO     | Yes      | `"Seedance 2.0"`<br />`"Seedance 2.0 Fast"` | The model to use for video generation. Selecting a model will reveal additional required inputs for the prompt, resolution, aspect ratio, duration, and audio generation. "Seedance 2.0" is for maximum quality; "Seedance 2.0 Fast" is for speed optimization. |
| `seed`      | INT       | No       | 0 to 2147483647                             | A seed value (default: 0). The node will re-run if this value changes, but the results are non-deterministic regardless of the seed.                                                                                                                            |
| `watermark` | BOOLEAN   | No       | True / False                                | Whether to add a watermark to the video (default: False). This is an advanced setting.                                                                                                                                                                          |

**Note:** The `model` parameter is a dynamic combo. When you select a model, it will reveal several required sub-parameters that must be filled in, including the text prompt, resolution, aspect ratio, duration, and whether to generate audio. The prompt text must be at least 1 character long after removing whitespace.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `video`     | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `670a35641fa421fb67ea067cdf38aff0d0fb51056ecc26485b5594e944adbbc8`


# ByteDanceCreateVideoAsset - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceCreateVideoAsset

Complete documentation for the ByteDanceCreateVideoAsset node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceCreateVideoAsset/en.md)

This node creates a personal video asset for Seedance 2.0. It uploads your input video and registers it within a specified asset group. If you don't provide a group ID, it will guide you through a real-person verification process in your browser to create a new group first.

## Inputs

| Parameter  | Data Type | Required | Range | Description                                                                                                                                                                                                     |
| ---------- | --------- | -------- | ----- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `video`    | VIDEO     | Yes      | -     | Video to register as a personal asset.                                                                                                                                                                          |
| `group_id` | STRING    | No       | -     | Reuse an existing Seedance asset group ID to skip repeated human verification for the same person. Leave empty to run real-person authentication in the browser and create a new group. (default: empty string) |

**Video Constraints:**

* **Duration:** Must be between 2 and 15 seconds.
* **Dimensions:** Width and height must each be between 300 and 6000 pixels.
* **Aspect Ratio:** The width-to-height ratio must be between 0.4 and 2.5.
* **Total Pixels:** The total number of pixels (width × height) must be between 409,600 and 927,408.
* **Frame Rate:** Must be between 24 and 60 frames per second (FPS).

## Outputs

| Output Name | Data Type | Description                                                                                                              |
| ----------- | --------- | ------------------------------------------------------------------------------------------------------------------------ |
| `asset_id`  | STRING    | The unique identifier for the newly created video asset.                                                                 |
| `group_id`  | STRING    | The identifier of the asset group containing the new video. This will be the provided `group_id` or a newly created one. |

***

**Source fingerprint (SHA-256):** `6598a586dae18811698bd505333ec45b7d2a60aa85728a38e5de790c5bacbdb7`


# ByteDanceFirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceFirstLastFrameNode

Complete documentation for the ByteDanceFirstLastFrameNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceFirstLastFrameNode/en.md)

This node generates a video using a text prompt along with first and last frame images. It takes your description and the two key frames to create a complete video sequence that transitions between them. The node provides various options to control the video's resolution, aspect ratio, duration, and other generation parameters.

## Inputs

| Parameter        | Data Type | Required | Range                                                                                              | Description                                                                                                                                                           |
| ---------------- | --------- | -------- | -------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`          | COMBO     | Yes      | `"seedance-1-5-pro-251215"`<br />`"seedance-1-0-pro-250528"`<br />`"seedance-1-0-lite-i2v-250428"` | The model to use for video generation (default: `"seedance-1-0-lite-i2v-250428"`).                                                                                    |
| `prompt`         | STRING    | Yes      | -                                                                                                  | The text prompt used to generate the video.                                                                                                                           |
| `first_frame`    | IMAGE     | Yes      | -                                                                                                  | First frame to be used for the video. Must be between 300x300 and 6000x6000 pixels, with an aspect ratio between 0.4 and 2.5.                                         |
| `last_frame`     | IMAGE     | Yes      | -                                                                                                  | Last frame to be used for the video. Must be between 300x300 and 6000x6000 pixels, with an aspect ratio between 0.4 and 2.5.                                          |
| `resolution`     | COMBO     | Yes      | `"480p"`<br />`"720p"`<br />`"1080p"`                                                              | The resolution of the output video.                                                                                                                                   |
| `aspect_ratio`   | COMBO     | Yes      | `"adaptive"`<br />`"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"`      | The aspect ratio of the output video (default: `"adaptive"`).                                                                                                         |
| `duration`       | INT       | Yes      | 3 - 12                                                                                             | The duration of the output video in seconds (default: 5). Note: For the `seedance-1-5-pro-251215` model, the minimum supported duration is 4 seconds.                 |
| `seed`           | INT       | No       | 0 - 2147483647                                                                                     | Seed to use for generation (default: 0).                                                                                                                              |
| `camera_fixed`   | BOOLEAN   | No       | -                                                                                                  | Specifies whether to fix the camera. The platform appends an instruction to fix the camera to your prompt, but does not guarantee the actual effect (default: False). |
| `watermark`      | BOOLEAN   | No       | -                                                                                                  | Whether to add an "AI generated" watermark to the video (default: False).                                                                                             |
| `generate_audio` | BOOLEAN   | No       | -                                                                                                  | This parameter is ignored for any model except `seedance-1-5-pro-251215` (default: False).                                                                            |

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `output`    | VIDEO     | The generated video file |

***

**Source fingerprint (SHA-256):** `ac16faf3aabcb06154c6a8815cc20c8a0e0c3a6b5b21e7d49813c10dce33d7be`


# ByteDanceImageReferenceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceImageReferenceNode

Complete documentation for the ByteDanceImageReferenceNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceImageReferenceNode/en.md)

The ByteDance Image Reference Node generates videos using a text prompt and one to four reference images. It sends the images and prompt to an external API service that creates a video matching your description while incorporating the visual style and content from your reference images. The node provides various controls for video resolution, aspect ratio, duration, and other generation parameters.

## Inputs

| Parameter      | Data Type | Required | Range                                                                                         | Description                                                                                                            |
| -------------- | --------- | -------- | --------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------- |
| `model`        | STRING    | Yes      | `"seedance-1-0-pro-250528"`<br />`"seedance-1-0-lite-i2v-250428"`                             | The AI model to use for video generation (default: `"seedance-1-0-lite-i2v-250428"`).                                  |
| `prompt`       | STRING    | Yes      | -                                                                                             | The text prompt used to generate the video.                                                                            |
| `images`       | IMAGE     | Yes      | -                                                                                             | One to four images. Each image must be between 300x300 and 6000x6000 pixels, with an aspect ratio between 0.4 and 2.5. |
| `resolution`   | STRING    | Yes      | `"480p"`<br />`"720p"`                                                                        | The resolution of the output video.                                                                                    |
| `aspect_ratio` | STRING    | Yes      | `"adaptive"`<br />`"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"` | The aspect ratio of the output video (default: `"adaptive"`).                                                          |
| `duration`     | INT       | Yes      | 3 - 12                                                                                        | The duration of the output video in seconds (default: 5).                                                              |
| `seed`         | INT       | No       | 0 - 2147483647                                                                                | Seed to use for generation (default: 0).                                                                               |
| `watermark`    | BOOLEAN   | No       | -                                                                                             | Whether to add an "AI generated" watermark to the video (default: False).                                              |

**Note:** The prompt text must not contain the following parameter strings: `--resolution`, `--ratio`, `--duration`, `--seed`, or `--watermark`. These values are controlled exclusively through their dedicated input widgets.

## Outputs

| Output Name | Data Type | Description                                                              |
| ----------- | --------- | ------------------------------------------------------------------------ |
| `output`    | VIDEO     | The generated video file based on the input prompt and reference images. |

***

**Source fingerprint (SHA-256):** `5365f846cafc80333bc8db5bce9101d83e69f3aae1625f275de7a172623a54b9`


# ByteDanceImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceImageToVideoNode

Complete documentation for the ByteDanceImageToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceImageToVideoNode/en.md)

The ByteDance Image to Video node generates videos using ByteDance models through an API based on an input image and text prompt. It takes a starting image frame and creates a video sequence that follows the provided description. The node offers various customization options for video resolution, aspect ratio, duration, and other generation parameters.

## Inputs

| Parameter        | Data Type | Required | Range                                                                                                                                    | Description                                                                                                                                                           |
| ---------------- | --------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`          | STRING    | Yes      | `"seedance-1-5-pro-251215"`<br />`"seedance-1-0-pro-250528"`<br />`"seedance-1-0-lite-i2v-250428"`<br />`"seedance-1-0-pro-fast-251015"` | The ByteDance model to use for video generation (default: `"seedance-1-0-pro-fast-251015"`).                                                                          |
| `prompt`         | STRING    | Yes      | -                                                                                                                                        | The text prompt used to generate the video. Must be at least 1 character long after trimming whitespace.                                                              |
| `image`          | IMAGE     | Yes      | -                                                                                                                                        | First frame to be used for the video. Must be between 300x300 and 6000x6000 pixels, with an aspect ratio between 0.4 and 2.5.                                         |
| `resolution`     | STRING    | Yes      | `"480p"`<br />`"720p"`<br />`"1080p"`                                                                                                    | The resolution of the output video.                                                                                                                                   |
| `aspect_ratio`   | STRING    | Yes      | `"adaptive"`<br />`"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"`                                            | The aspect ratio of the output video.                                                                                                                                 |
| `duration`       | INT       | Yes      | 3 - 12                                                                                                                                   | The duration of the output video in seconds (default: 5). For the `seedance-1-5-pro-251215` model, the minimum supported duration is 4 seconds.                       |
| `seed`           | INT       | No       | 0 - 2147483647                                                                                                                           | Seed to use for generation (default: 0).                                                                                                                              |
| `camera_fixed`   | BOOLEAN   | No       | -                                                                                                                                        | Specifies whether to fix the camera. The platform appends an instruction to fix the camera to your prompt, but does not guarantee the actual effect (default: False). |
| `watermark`      | BOOLEAN   | No       | -                                                                                                                                        | Whether to add an "AI generated" watermark to the video (default: False).                                                                                             |
| `generate_audio` | BOOLEAN   | No       | -                                                                                                                                        | This parameter is ignored for any model except `seedance-1-5-pro-251215` (default: False).                                                                            |

**Note:** The prompt must not contain the following words (case-insensitive): `resolution`, `ratio`, `duration`, `seed`, `camerafixed`, `watermark`. These parameters are set via their dedicated inputs.

## Outputs

| Output Name | Data Type | Description                                                              |
| ----------- | --------- | ------------------------------------------------------------------------ |
| `output`    | VIDEO     | The generated video file based on the input image and prompt parameters. |

***

**Source fingerprint (SHA-256):** `7b77df4ab83ef41164eff80a4c02478d5480c9368aa67bcd624fe2f8375d6e07`


# ByteDanceTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ByteDanceTextToVideoNode

Complete documentation for the ByteDanceTextToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ByteDanceTextToVideoNode/en.md)

The ByteDance Text to Video node generates videos using ByteDance models through an API based on text prompts. It takes a text description and various video settings as input, then creates a video that matches the provided specifications. The node handles the API communication and returns the generated video as output.

## Inputs

| Parameter        | Data Type | Required | Range                                                                                                                                    | Description                                                                                                                                                           |
| ---------------- | --------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`          | STRING    | Yes      | `"seedance-1-5-pro-251215"`<br />`"seedance-1-0-pro-250528"`<br />`"seedance-1-0-lite-t2v-250428"`<br />`"seedance-1-0-pro-fast-251015"` | The ByteDance model to use for generation (default: `"seedance-1-0-pro-fast-251015"`).                                                                                |
| `prompt`         | STRING    | Yes      | -                                                                                                                                        | The text prompt used to generate the video.                                                                                                                           |
| `resolution`     | STRING    | Yes      | `"480p"`<br />`"720p"`<br />`"1080p"`                                                                                                    | The resolution of the output video.                                                                                                                                   |
| `aspect_ratio`   | STRING    | Yes      | `"16:9"`<br />`"4:3"`<br />`"1:1"`<br />`"3:4"`<br />`"9:16"`<br />`"21:9"`                                                              | The aspect ratio of the output video.                                                                                                                                 |
| `duration`       | INT       | Yes      | 3 to 12                                                                                                                                  | The duration of the output video in seconds (default: 5).                                                                                                             |
| `seed`           | INT       | No       | 0 to 2147483647                                                                                                                          | Seed to use for generation (default: 0).                                                                                                                              |
| `camera_fixed`   | BOOLEAN   | No       | -                                                                                                                                        | Specifies whether to fix the camera. The platform appends an instruction to fix the camera to your prompt, but does not guarantee the actual effect (default: False). |
| `watermark`      | BOOLEAN   | No       | -                                                                                                                                        | Whether to add an "AI generated" watermark to the video (default: False).                                                                                             |
| `generate_audio` | BOOLEAN   | No       | -                                                                                                                                        | This parameter is ignored for any model except `seedance-1-5-pro-251215` (default: False).                                                                            |

**Parameter Constraints:**

* The `prompt` parameter must contain at least 1 character after whitespace removal.
* The `prompt` parameter cannot contain the following text parameters: "resolution", "ratio", "duration", "seed", "camerafixed", "watermark".
* The `duration` parameter is limited to values between 3 and 12 seconds. For the `seedance-1-5-pro-251215` model, the minimum supported duration is 4 seconds.
* The `seed` parameter accepts values from 0 to 2,147,483,647.
* The `generate_audio` parameter only has an effect when the `model` is set to `seedance-1-5-pro-251215`; it is ignored for all other models.

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `output`    | VIDEO     | The generated video file |

***

**Source fingerprint (SHA-256):** `a16c07e920a0e96e3e14eec33e5b4e3393e924970528365b326ef32887d64766`


# ColorToRGBInt - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ColorToRGBInt

Complete documentation for the ColorToRGBInt node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ColorToRGBInt/en.md)

The **ColorToRGBInt** node converts a color specified in hexadecimal format (like `#FF5733`) into a single integer value. It takes the red, green, and blue components from the color string and combines them into one RGB integer.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                                              |
| --------- | --------- | -------- | ----- | -------------------------------------------------------------------------------------------------------- |
| `color`   | STRING    | Yes      | N/A   | A color value in the hexadecimal format `#RRGGBB`. Must be exactly 7 characters long and start with `#`. |

**Note:** The input `color` string must follow the format `#RRGGBB` exactly. If the string is not 7 characters long or does not start with `#`, the node will raise an error.

## Outputs

| Output Name | Data Type | Description                                                                                                 |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------- |
| `rgb_int`   | INT       | The calculated RGB integer value. This is derived from the formula: `(Red * 65536) + (Green * 256) + Blue`. |

***

**Source fingerprint (SHA-256):** `afbbdddb59eddf9e2cc8ab51765affff1676a589c2a2989ff90038ad0119dc9f`


# ComfyMathExpression - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyMathExpression

Complete documentation for the ComfyMathExpression node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyMathExpression/en.md)

The ComfyMathExpression node evaluates a mathematical formula using a set of input values. You can write an expression using variable names (like `a`, `b`, `c`), and the node will calculate the result. It supports dynamically adding as many input values as needed for your calculation.

## Inputs

| Parameter    | Data Type           | Required | Range | Description                                                                                                                                                                                                          |
| ------------ | ------------------- | -------- | ----- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `expression` | STRING              | Yes      | N/A   | The mathematical formula to evaluate. You can use variable names that correspond to the input values (default: "a + b").                                                                                             |
| `values`     | FLOAT, INT, BOOLEAN | No       | N/A   | A set of numeric or boolean inputs that can be dynamically added. Each input is assigned a letter from the alphabet (a, b, c, ...) to be used as a variable in the expression. At least one input value is required. |

**Parameter Constraints:**

* The `expression` parameter cannot be empty or contain only whitespace.
* The expression must evaluate to a finite numeric result (INT or FLOAT). Boolean or other non-numeric results will cause an error.
* The input values for the `values` parameter can be numbers (INT or FLOAT) or boolean values (TRUE/FALSE).
* At least one input value must be provided in the `values` group.

## Outputs

| Output Name | Data Type | Description                                                           |
| ----------- | --------- | --------------------------------------------------------------------- |
| `FLOAT`     | FLOAT     | The result of the mathematical expression as a floating-point number. |
| `INT`       | INT       | The result of the mathematical expression as an integer.              |
| `BOOL`      | BOOLEAN   | The result of the mathematical expression as a boolean value.         |

***

**Source fingerprint (SHA-256):** `bf6221a7e1e955bdb56482de0a86a782494b2775fdd2edfde9fd20a9df0fe1a7`


# ComfyNumberConvert - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ComfyNumberConvert

Complete documentation for the ComfyNumberConvert node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ComfyNumberConvert/en.md)

The Number Convert node transforms various input data types into numeric values. It accepts a single input of type integer, float, string, or boolean and produces two outputs: a floating-point number and an integer. This is useful for converting text or logical values into a format that can be used by other mathematical or processing nodes in your workflow.

## Inputs

| Parameter | Data Type                   | Required | Range | Description                                                                                                                          |
| --------- | --------------------------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------ |
| `value`   | INT, FLOAT, STRING, BOOLEAN | Yes      | N/A   | The value to be converted into numeric outputs. Accepts an integer, a floating-point number, a text string, or a true/false boolean. |

**Note:** When the input is a string, it must not be empty and must contain a valid representation of a number (e.g., `"123"`, `"3.14"`). The node will raise an error for empty strings, text that cannot be parsed as a number, or values that are not finite (like `"inf"` or `"nan"`). For boolean inputs, `true` converts to 1.0 (FLOAT) and 1 (INT), while `false` converts to 0.0 (FLOAT) and 0 (INT). For float inputs, the integer output is obtained by truncating the decimal portion.

## Outputs

| Output Name | Data Type | Description                                                                            |
| ----------- | --------- | -------------------------------------------------------------------------------------- |
| `FLOAT`     | FLOAT     | The input value converted to a floating-point number.                                  |
| `INT`       | INT       | The input value converted to an integer. For float inputs, this performs a truncation. |

***

**Source fingerprint (SHA-256):** `3a5501a3916df827b0376e4ba9c8b9972a91485cca38e067b683bb5f96c1d53c`


# CreateList - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateList

Complete documentation for the CreateList node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateList/en.md)

The Create List node combines multiple inputs into a single, sequential list. It takes any number of inputs of the same data type and concatenates them in the order they are connected. This node is useful for preparing batches of data, such as images or text, to be processed by other nodes in a workflow.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                                                                                                        |
| --------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `inputs`  | Varies    | Yes      | Any   | A variable number of input slots. You can add more inputs by clicking the plus (+) icon. All inputs must be of the same data type (e.g., all IMAGE or all STRING). |

**Note:** The node will automatically create new input slots as you connect items. All connected inputs must share the same data type for the node to function correctly.

## Outputs

| Output Name | Data Type | Description                                                                                                                                                       |
| ----------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `list`      | Varies    | A single list containing all the items from the connected inputs, concatenated in the order they were provided. The output data type matches the input data type. |

***

**Source fingerprint (SHA-256):** `54a099948853f76f4f9c9918e4fef8a8eff96ad66d35ab9eeefd2a419670e867`


# CurveEditor - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CurveEditor

Complete documentation for the CurveEditor node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CurveEditor/en.md)

The Curve Editor node provides a visual interface for adjusting and fine-tuning a curve. It allows you to modify the shape of an input curve and optionally visualize its distribution with a histogram. The node outputs the modified curve for use in other parts of your workflow.

## Inputs

| Parameter   | Data Type | Required | Range | Description                                                                |
| ----------- | --------- | -------- | ----- | -------------------------------------------------------------------------- |
| `curve`     | CURVE     | Yes      | N/A   | The input curve to be edited.                                              |
| `histogram` | HISTOGRAM | No       | N/A   | An optional histogram to display alongside the curve for visual reference. |

## Outputs

| Output Name | Data Type | Description                                                                |
| ----------- | --------- | -------------------------------------------------------------------------- |
| `curve`     | CURVE     | The edited curve after adjustments have been made in the node's interface. |

***

**Source fingerprint (SHA-256):** `7cd265b724f4b80bd6838b665254b54f1ca16f32ed0b4e072fabf856d769e11c`


# CustomCombo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CustomCombo

Complete documentation for the CustomCombo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CustomCombo/en.md)

The Custom Combo node allows you to create a custom dropdown menu with your own list of text options. It is a frontend-focused node that provides a backend representation to ensure compatibility within your workflow. When you select an option from the dropdown, the node outputs that text as a string and its index position.

## Inputs

| Parameter | Data Type | Required | Range        | Description                                                                                                                               |
| --------- | --------- | -------- | ------------ | ----------------------------------------------------------------------------------------------------------------------------------------- |
| `choice`  | COMBO     | Yes      | User-defined | The text option selected from the custom dropdown. The list of available options is defined by the user in the node's frontend interface. |
| `index`   | INT       | No       | 0            | An integer value that can be used to specify an index. Default: 0.                                                                        |

**Note:** The validation for this node's input is intentionally disabled. This allows you to define any custom text options you want in the frontend without the backend checking if your selection is from a predefined list.

## Outputs

| Output Name | Data Type | Description                                                       |
| ----------- | --------- | ----------------------------------------------------------------- |
| `STRING`    | STRING    | The text string of the option selected from the custom combo box. |
| `INDEX`     | INT       | The index position of the selected option in the dropdown list.   |

***

**Source fingerprint (SHA-256):** `1c68db3a71526d52d21f79abae146ffa235b4927961ff45db3aa075bba4e910a`


# GrokVideoEditNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokVideoEditNode

Complete documentation for the GrokVideoEditNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokVideoEditNode/en.md)

This node uses the Grok API to edit an existing video based on a text prompt. It uploads your video, sends a request to the AI model to modify it according to your description, and returns the newly generated video.

## Inputs

| Parameter | Data Type | Required | Range                                                   | Description                                                                                                                             |
| --------- | --------- | -------- | ------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
| `model`   | COMBO     | Yes      | `"grok-imagine-video"`<br />`"grok-imagine-video-beta"` | The AI model to use for video editing (default: `"grok-imagine-video"`).                                                                |
| `prompt`  | STRING    | Yes      | N/A                                                     | Text description of the desired video.                                                                                                  |
| `video`   | VIDEO     | Yes      | N/A                                                     | The input video to be edited. Maximum supported duration is 8.7 seconds and 50MB file size.                                             |
| `seed`    | INT       | No       | 0 to 2147483647                                         | A seed value to determine if the node should re-run. The actual results are nondeterministic regardless of the seed value (default: 0). |

**Constraints:**

* The input `video` must be between 1 and 8.7 seconds in duration.
* The input `video` file size must not exceed 50MB.
* The `prompt` must not be empty.

## Outputs

| Output Name | Data Type | Description                                 |
| ----------- | --------- | ------------------------------------------- |
| `video`     | VIDEO     | The edited video generated by the AI model. |

***

**Source fingerprint (SHA-256):** `04cdc989b48445562017cd2c2066c773473c5c241ed94ff6eca00b8aadf4c6df`


# GrokVideoExtendNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokVideoExtendNode

Complete documentation for the GrokVideoExtendNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokVideoExtendNode/en.md)

The Grok Video Extend node uses an AI model to create a seamless continuation of an existing video. You provide a short video and a text prompt describing what should happen next, and the node generates a new video clip that follows on from the original.

## Inputs

| Parameter | Data Type | Required | Range                  | Description                                                                                                   |
| --------- | --------- | -------- | ---------------------- | ------------------------------------------------------------------------------------------------------------- |
| `prompt`  | STRING    | Yes      | N/A                    | Text description of what should happen next in the video.                                                     |
| `video`   | VIDEO     | Yes      | N/A                    | Source video to extend. MP4 format, 2-15 seconds.                                                             |
| `model`   | COMBO     | Yes      | `"grok-imagine-video"` | The model to use for video extension. When selected, it reveals a nested `duration` parameter.                |
| `seed`    | INT       | No       | 0 to 2147483647        | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). |

**Parameter Constraints:**

* The `video` input must be an MP4 file between 2 and 15 seconds in length and cannot exceed 50MB in file size.
* The `prompt` must contain at least one character (whitespace is trimmed).
* The `model` parameter is a dynamic combo. Selecting the "grok-imagine-video" option reveals a nested `duration` parameter, which controls the length of the extension in seconds (default: 8, range: 2 to 10).

## Outputs

| Output Name | Data Type | Description                          |
| ----------- | --------- | ------------------------------------ |
| `output`    | VIDEO     | The newly generated video extension. |

***

**Source fingerprint (SHA-256):** `7e56ecb0cb31795b4124671e074ef274d6de61ec2cd734b6edd5e76a3cb6a7ba`


# GrokVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokVideoNode

Complete documentation for the GrokVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokVideoNode/en.md)

The Grok Video node generates a short video from a text description. It can create a video from scratch using a prompt or animate a single input image based on a prompt. The node sends a request to an external API and returns the generated video.

## Inputs

| Parameter      | Data Type | Required | Range                                                                                                 | Description                                                                                                   |
| -------------- | --------- | -------- | ----------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- |
| `model`        | COMBO     | Yes      | `"grok-imagine-video"`<br />`"grok-imagine-video-beta"`                                               | The model to use for video generation.                                                                        |
| `prompt`       | STRING    | Yes      | -                                                                                                     | Text description of the desired video.                                                                        |
| `resolution`   | COMBO     | Yes      | `"480p"`<br />`"720p"`                                                                                | The resolution of the output video.                                                                           |
| `aspect_ratio` | COMBO     | Yes      | `"auto"`<br />`"16:9"`<br />`"4:3"`<br />`"3:2"`<br />`"1:1"`<br />`"2:3"`<br />`"3:4"`<br />`"9:16"` | The aspect ratio of the output video (default: "auto").                                                       |
| `duration`     | INT       | Yes      | 1 to 15                                                                                               | The duration of the output video in seconds (default: 6).                                                     |
| `seed`         | INT       | Yes      | 0 to 2147483647                                                                                       | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). |
| `image`        | IMAGE     | No       | -                                                                                                     | An optional input image to animate.                                                                           |

**Note:** If an `image` is provided, only one image is supported. Providing multiple images will cause an error. The `prompt` must be at least 1 character long after stripping whitespace.

## Outputs

| Output Name | Data Type | Description          |
| ----------- | --------- | -------------------- |
| `output`    | VIDEO     | The generated video. |

***

**Source fingerprint (SHA-256):** `7b4bcd25cfe620b4593c16a2cb2a288e47f9791ae2c60d56b79009bc62bac6e2`


# GrokVideoReferenceNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GrokVideoReferenceNode

Complete documentation for the GrokVideoReferenceNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GrokVideoReferenceNode/en.md)

The Grok Reference-to-Video node generates a video based on a text prompt, using up to seven reference images to guide the style and content of the output. It connects to an external API to create the video, which is then downloaded and returned.

## Inputs

| Parameter                | Data Type | Required | Range                                                                                   | Description                                                                                                   |
| ------------------------ | --------- | -------- | --------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- |
| `prompt`                 | STRING    | Yes      | N/A                                                                                     | Text description of the desired video.                                                                        |
| `model`                  | COMBO     | Yes      | `"grok-imagine-video"`                                                                  | The model to use for video generation.                                                                        |
| `model.reference_images` | IMAGE     | Yes      | 1 to 7 images                                                                           | Up to 7 reference images to guide the video generation.                                                       |
| `model.resolution`       | COMBO     | Yes      | `"480p"`<br />`"720p"`                                                                  | The resolution of the output video.                                                                           |
| `model.aspect_ratio`     | COMBO     | Yes      | `"16:9"`<br />`"4:3"`<br />`"3:2"`<br />`"1:1"`<br />`"2:3"`<br />`"3:4"`<br />`"9:16"` | The aspect ratio of the output video.                                                                         |
| `model.duration`         | INT       | Yes      | 2 to 10                                                                                 | The duration of the output video in seconds (default: 6).                                                     |
| `seed`                   | INT       | No       | 0 to 2147483647                                                                         | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0). |

**Note:** The `model` parameter is a group containing `reference_images`, `resolution`, `aspect_ratio`, and `duration`. You must provide at least one reference image, and you can provide up to seven.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `video`     | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `df50e80ca403d05469881e1c456ca4777d70989d8950c5e3844271c3ff8df85a`


# HappyHorseImageToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HappyHorseImageToVideoApi

Complete documentation for the HappyHorseImageToVideoApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HappyHorseImageToVideoApi/en.md)

## Overview

This node generates a short video from a single starting image using the HappyHorse model. You provide a first frame image and a text prompt describing the desired motion and scene, and the node creates a video that continues from that image.

## Inputs

| Parameter          | Data Type | Required | Range                   | Description                                                                                     |
| ------------------ | --------- | -------- | ----------------------- | ----------------------------------------------------------------------------------------------- |
| `model`            | COMBO     | Yes      | `"happyhorse-1.0-i2v"`  | The HappyHorse model to use for video generation.                                               |
| `model.prompt`     | STRING    | No       | N/A                     | Prompt describing the elements and visual features. Supports English and Chinese. (default: "") |
| `model.resolution` | COMBO     | Yes      | `"720P"`<br />`"1080P"` | The output video resolution. (default: "720P")                                                  |
| `model.duration`   | INT       | Yes      | 3 to 15                 | The duration of the generated video in seconds. (default: 5)                                    |
| `first_frame`      | IMAGE     | Yes      | N/A                     | First frame image. The output aspect ratio is derived from this image.                          |
| `seed`             | INT       | No       | 0 to 2147483647         | Seed to use for generation. (default: 0)                                                        |
| `watermark`        | BOOLEAN   | No       | True / False            | Whether to add an AI-generated watermark to the result. (default: False)                        |

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `video`     | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `b8764d68024b7d2a526b6cc3e1e56c3240b1aa55f31a07263e7014d4f6c67509`


# HappyHorseReferenceVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HappyHorseReferenceVideoApi

Complete documentation for the HappyHorseReferenceVideoApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HappyHorseReferenceVideoApi/en.md)

## Overview

This node generates a video featuring a person or object based on reference images using the HappyHorse model. It supports creating videos with a single character or multiple characters interacting with each other.

## Inputs

| Parameter          | Data Type | Required | Range                                                         | Description                                                                                                                                    |
| ------------------ | --------- | -------- | ------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`            | COMBO     | Yes      | `"happyhorse-1.0-r2v"`                                        | The HappyHorse model to use for video generation.                                                                                              |
| `prompt`           | STRING    | Yes      | N/A                                                           | A text description of the video you want to generate. Use identifiers like 'character1' and 'character2' to refer to the reference characters. |
| `resolution`       | COMBO     | Yes      | `"720P"`<br />`"1080P"`                                       | The resolution of the generated video.                                                                                                         |
| `ratio`            | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"` | The aspect ratio of the generated video.                                                                                                       |
| `duration`         | INT       | Yes      | 3 to 15                                                       | The duration of the generated video in seconds (default: 5).                                                                                   |
| `reference_images` | IMAGE     | Yes      | 1 to 9                                                        | One or more reference images of the person or object to feature in the video. You must provide at least one image.                             |
| `seed`             | INT       | No       | 0 to 2147483647                                               | A seed value for reproducible generation (default: 0). The seed can be set to automatically change after each generation.                      |
| `watermark`        | BOOLEAN   | No       | True or False                                                 | Whether to add an AI-generated watermark to the resulting video (default: False).                                                              |

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `VIDEO`     | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `42c844db22ed2284bd16bd28fe0060652248ada0d5d31003134768ed5e44356c`


# HappyHorseTextToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HappyHorseTextToVideoApi

Complete documentation for the HappyHorseTextToVideoApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HappyHorseTextToVideoApi/en.md)

## Overview

Generates a video based on a text prompt using the HappyHorse model. This node sends your prompt and settings to the HappyHorse API, waits for the video to be generated, and then downloads the result.

## Inputs

| Parameter   | Data Type | Required | Range           | Description                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| ----------- | --------- | -------- | --------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`     | DICT      | Yes      | See Description | A dictionary containing the model selection and its associated parameters. The model must be `"happyhorse-1.0-t2v"`. This dictionary includes the following sub-parameters:<br /><br />**`prompt`** (STRING): The text description of the video you want to generate. Supports English and Chinese. (default: "").<br />**`resolution`** (COMBO): The resolution of the output video. Options: `"720P"`<br />`"1080P"`.<br />**`ratio`** (COMBO): The aspect ratio of the output video. Options: `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"`.<br />**`duration`** (INT): The length of the video in seconds. (default: 5, min: 3, max: 15, step: 1). |
| `seed`      | INT       | Yes      | 0 to 2147483647 | Seed to use for generation. Using the same seed with the same inputs will produce the same result. (default: 0).                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
| `watermark` | BOOLEAN   | No       | True / False    | Whether to add an AI-generated watermark to the result. (default: False).                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `VIDEO`     | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `8e2c0aaab2c8918079c5ec02916375e9a11b0e745d3296155f37c0128a9dbc3c`


# HappyHorseVideoEditApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HappyHorseVideoEditApi

Complete documentation for the HappyHorseVideoEditApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HappyHorseVideoEditApi/en.md)

## Overview

Edit a video using text instructions or reference images with the HappyHorse model. The output duration is 3-15 seconds and matches the input video; inputs longer than 15 seconds are truncated.

## Inputs

| Parameter   | Data Type | Required | Range           | Description                                                                                                          |
| ----------- | --------- | -------- | --------------- | -------------------------------------------------------------------------------------------------------------------- |
| `model`     | DICT      | Yes      | See below       | Model configuration containing the model selection, prompt, resolution, aspect ratio, and optional reference images. |
| `video`     | VIDEO     | Yes      | -               | The video to edit.                                                                                                   |
| `seed`      | INT       | Yes      | 0 to 2147483647 | Seed to use for generation (default: 0).                                                                             |
| `watermark` | BOOLEAN   | No       | True / False    | Whether to add an AI-generated watermark to the result (default: False).                                             |

### `model` Parameter Details

The `model` parameter is a dictionary with the following fields:

| Field              | Data Type | Required | Range                                                         | Description                                                                             |
| ------------------ | --------- | -------- | ------------------------------------------------------------- | --------------------------------------------------------------------------------------- |
| `model`            | STRING    | Yes      | `"happyhorse-1.0-video-edit"`                                 | The HappyHorse video editing model to use.                                              |
| `prompt`           | STRING    | Yes      | -                                                             | Editing instructions or style transfer requirements. Must be at least 1 character long. |
| `resolution`       | STRING    | Yes      | `"720P"`<br />`"1080P"`                                       | The output resolution.                                                                  |
| `ratio`            | STRING    | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"` | Aspect ratio. If not changed, approximates the input video ratio.                       |
| `reference_images` | DICT      | No       | 0 to 5 images                                                 | Optional reference images (image1, image2, image3, image4, image5) to guide the edit.   |

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `video`     | VIDEO     | The edited video output. |

***

**Source fingerprint (SHA-256):** `eadb446a8dbcc524a8bb6a2ee48941136f8c1ec2cb64aa9061fb1fa22e1b683d`


# HitPawVideoEnhance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/HitPawVideoEnhance

Complete documentation for the HitPawVideoEnhance node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/HitPawVideoEnhance/en.md)

The HitPaw Video Enhance node uses an external API to improve the quality of videos. It upscales low-resolution videos to a higher resolution, removes visual artifacts, and reduces noise. The processing cost is calculated per second of the input video.

## Inputs

| Parameter          | Data Type     | Required | Range                                                                                                                                                                                                                                        | Description                                                                                                                                                      |
| ------------------ | ------------- | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`            | DYNAMIC COMBO | Yes      | `"Portrait Restore Model (1x)"`<br />`"Portrait Restore Model (2x)"`<br />`"General Restore Model (1x)"`<br />`"General Restore Model (2x)"`<br />`"General Restore Model (4x)"`<br />`"Ultra HD Model (2x)"`<br />`"Generative Model (1x)"` | The AI model to use for video enhancement. Selecting a model reveals a nested `resolution` parameter. The available models and their supported resolutions vary. |
| `model.resolution` | COMBO         | Yes      | For `"Generative Model (1x)"`: `"original"`<br />`"720p"`<br />`"1080p"`<br />`"2K/QHD"`<br />`"4K/UHD"`<br /><br />For all other models: `"original"`<br />`"720p"`<br />`"1080p"`<br />`"2K/QHD"`<br />`"4K/UHD"`<br />`"8K"`              | The target resolution for the enhanced video. The `"8K"` option is only available for models other than `"Generative Model (1x)"`.                               |
| `video`            | VIDEO         | Yes      | N/A                                                                                                                                                                                                                                          | The input video file to be enhanced.                                                                                                                             |

**Constraints:**

* The input `video` must be between 0.5 seconds and 60 minutes (3600 seconds) in duration.
* The selected `resolution` must be larger than the input video's dimensions. If the video is square, the selected resolution must be larger than its width/height. For non-square videos, the selected resolution must be larger than the video's shorter dimension. If the target resolution is smaller, an error will be raised. Choose `"original"` to keep the input video's resolution.

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `video`     | VIDEO     | The enhanced video file. |

***

**Source fingerprint (SHA-256):** `49291b3c610d32cf60fb4786333cb7e3d18c9de39c15577dabbd9f27bc9eac75`


# ImageHistogram - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ImageHistogram

Complete documentation for the ImageHistogram node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ImageHistogram/en.md)

The ImageHistogram node analyzes the color distribution of an input image. It calculates and outputs several histograms, which are graphs showing how many pixels in the image have each possible intensity value. It generates separate histograms for the red, green, and blue color channels, a composite RGB histogram, and a luminance histogram based on a standard brightness formula.

## Inputs

| Parameter | Data Type | Required | Range | Description                                                                  |
| --------- | --------- | -------- | ----- | ---------------------------------------------------------------------------- |
| `image`   | IMAGE     | Yes      | N/A   | The input image to analyze. The node processes the first image in the batch. |

## Outputs

| Output Name | Data Type | Description                                                                                                    |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------------- |
| `rgb`       | HISTOGRAM | A composite histogram representing the average pixel intensity across the red, green, and blue channels.       |
| `luminance` | HISTOGRAM | A histogram of the image's perceived brightness, calculated using the ITU-R BT.709 standard luminance formula. |
| `red`       | HISTOGRAM | A histogram showing the distribution of pixel intensities in the red color channel.                            |
| `green`     | HISTOGRAM | A histogram showing the distribution of pixel intensities in the green color channel.                          |
| `blue`      | HISTOGRAM | A histogram showing the distribution of pixel intensities in the blue color channel.                           |

***

**Source fingerprint (SHA-256):** `026a470129a49794bc1ddcdd3ecd8e8ad95b43fc94db4387f0e2de365b305879`


# KlingAvatarNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingAvatarNode

Complete documentation for the KlingAvatarNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingAvatarNode/en.md)

The Kling Avatar 2.0 node generates broadcast-style digital human videos from a single reference photo and an audio file. It creates a talking avatar video with an optional text prompt to define the avatar's actions, emotions, and camera movements.

## Inputs

| Parameter    | Data Type | Required | Range                | Description                                                                                                    |
| ------------ | --------- | -------- | -------------------- | -------------------------------------------------------------------------------------------------------------- |
| `image`      | IMAGE     | Yes      | -                    | Avatar reference image. Width and height must be at least 300px. Aspect ratio must be between 1:2.5 and 2.5:1. |
| `sound_file` | AUDIO     | Yes      | -                    | Audio input. Must be between 2 and 300 seconds in duration.                                                    |
| `mode`       | COMBO     | Yes      | `"std"`<br />`"pro"` | The generation mode to use.                                                                                    |
| `prompt`     | STRING    | No       | -                    | Optional prompt to define avatar actions, emotions, and camera movements. (default: empty string)              |
| `seed`       | INT       | Yes      | 0 to 2147483647      | Seed controls whether the node should re-run; results are non-deterministic regardless of seed. (default: 0)   |

**Note:** The `image` and `sound_file` inputs have specific validation requirements. The image must be at least 300x300 pixels with an aspect ratio between 1:2.5 and 2.5:1. The audio file must be between 2 and 300 seconds long.

## Outputs

| Output Name | Data Type | Description                        |
| ----------- | --------- | ---------------------------------- |
| `output`    | VIDEO     | The generated digital human video. |

***

**Source fingerprint (SHA-256):** `d9264e250c578dcb38612c192f8567a8f48c6624e030d8765b13bb71aae2d0b8`


# KlingCameraControlI2VNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingCameraControlI2VNode

Complete documentation for the KlingCameraControlI2VNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingCameraControlI2VNode/en.md)

The Kling Image to Video Camera Control Node transforms still images into cinematic videos with professional camera movements. This specialized image-to-video node allows you to control virtual camera actions including zoom, rotation, pan, tilt, and first-person view while maintaining focus on your original image. Camera control is currently only supported in pro mode with the kling-v1-5 model at 5-second duration.

## Inputs

| Parameter         | Data Type       | Required | Range                               | Description                                                                                                                                                                                |
| ----------------- | --------------- | -------- | ----------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `start_frame`     | IMAGE           | Yes      | -                                   | Reference Image - URL or Base64 encoded string, cannot exceed 10MB, resolution not less than 300x300px, aspect ratio between 1:2.5 and 2.5:1. Base64 should not include data:image prefix. |
| `prompt`          | STRING          | Yes      | -                                   | Positive text prompt describing the desired video content. Maximum length is 500 characters.                                                                                               |
| `negative_prompt` | STRING          | Yes      | -                                   | Negative text prompt describing what to avoid in the generated video. Maximum length is 500 characters.                                                                                    |
| `cfg_scale`       | FLOAT           | No       | 0.0 to 1.0                          | Controls the strength of text guidance. Higher values make the output more closely follow the prompt (default: 0.75)                                                                       |
| `aspect_ratio`    | COMBO           | No       | `"16:9"`<br />`"9:16"`<br />`"1:1"` | The aspect ratio of the generated video (default: "16:9")                                                                                                                                  |
| `camera_control`  | CAMERA\_CONTROL | Yes      | -                                   | Can be created using the Kling Camera Controls node. Controls the camera movement and motion during the video generation.                                                                  |

## Outputs

| Output Name | Data Type | Description                               |
| ----------- | --------- | ----------------------------------------- |
| `output`    | VIDEO     | The generated video output                |
| `video_id`  | STRING    | Unique identifier for the generated video |
| `duration`  | STRING    | Duration of the generated video           |

***

**Source fingerprint (SHA-256):** `c7c0ef732a97d60b03c6942a9f026a23982ea5d86746520772cc6bf2f450865c`


# KlingCameraControlT2VNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingCameraControlT2VNode

Complete documentation for the KlingCameraControlT2VNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingCameraControlT2VNode/en.md)

Kling Text to Video Camera Control Node transforms text into cinematic videos with professional camera movements that simulate real-world cinematography. This node supports controlling virtual camera actions including zoom, rotation, pan, tilt, and first-person view while maintaining focus on your original text. The duration, mode, and model name are hard-coded because camera control is only supported in pro mode with the kling-v1-5 model at 5-second duration.

## Inputs

| Parameter         | Data Type       | Required | Range                                                           | Description                                                                                                               |
| ----------------- | --------------- | -------- | --------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------- |
| `prompt`          | STRING          | Yes      | -                                                               | Positive text prompt                                                                                                      |
| `negative_prompt` | STRING          | Yes      | -                                                               | Negative text prompt                                                                                                      |
| `cfg_scale`       | FLOAT           | No       | 0.0-1.0                                                         | Controls how closely the output follows the prompt (default: 0.75)                                                        |
| `aspect_ratio`    | COMBO           | No       | "16:9"<br />"9:16"<br />"1:1"<br />"21:9"<br />"3:4"<br />"4:3" | The aspect ratio for the generated video (default: "16:9")                                                                |
| `camera_control`  | CAMERA\_CONTROL | No       | -                                                               | Can be created using the Kling Camera Controls node. Controls the camera movement and motion during the video generation. |

## Outputs

| Output Name | Data Type | Description                                     |
| ----------- | --------- | ----------------------------------------------- |
| `output`    | VIDEO     | The generated video with camera control effects |
| `video_id`  | STRING    | The unique identifier for the generated video   |
| `duration`  | STRING    | The duration of the generated video             |

***

**Source fingerprint (SHA-256):** `c2e6ea8f136d3bb82d6627b3362a8a4dfb9cb0414f6d846e5283e49a0ba6d357`


# KlingCameraControls - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingCameraControls

Complete documentation for the KlingCameraControls node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingCameraControls/en.md)

The Kling Camera Controls node allows you to configure various camera movement and rotation parameters for creating motion control effects in video generation. It provides controls for camera positioning, rotation, and zoom to simulate different camera movements.

## Inputs

| Parameter             | Data Type | Required | Range                        | Description                                                                                                                                    |
| --------------------- | --------- | -------- | ---------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| `camera_control_type` | COMBO     | Yes      | `"simple"`<br />`"advanced"` | Specifies the type of camera control configuration to use                                                                                      |
| `horizontal_movement` | FLOAT     | No       | -10.0 to 10.0                | Controls camera's movement along horizontal axis (x-axis). Negative indicates left, positive indicates right (default: 0.0)                    |
| `vertical_movement`   | FLOAT     | No       | -10.0 to 10.0                | Controls camera's movement along vertical axis (y-axis). Negative indicates downward, positive indicates upward (default: 0.0)                 |
| `pan`                 | FLOAT     | No       | -10.0 to 10.0                | Controls camera's rotation in vertical plane (x-axis). Negative indicates downward rotation, positive indicates upward rotation (default: 0.5) |
| `tilt`                | FLOAT     | No       | -10.0 to 10.0                | Controls camera's rotation in horizontal plane (y-axis). Negative indicates left rotation, positive indicates right rotation (default: 0.0)    |
| `roll`                | FLOAT     | No       | -10.0 to 10.0                | Controls camera's rolling amount (z-axis). Negative indicates counterclockwise, positive indicates clockwise (default: 0.0)                    |
| `zoom`                | FLOAT     | No       | -10.0 to 10.0                | Controls change in camera's focal length. Negative indicates narrower field of view, positive indicates wider field of view (default: 0.0)     |

**Note:** At least one of the camera control parameters (`horizontal_movement`, `vertical_movement`, `pan`, `tilt`, `roll`, or `zoom`) must have a non-zero value for the configuration to be valid.

## Outputs

| Output Name      | Data Type       | Description                                                                |
| ---------------- | --------------- | -------------------------------------------------------------------------- |
| `camera_control` | CAMERA\_CONTROL | Returns the configured camera control settings for use in video generation |

***

**Source fingerprint (SHA-256):** `35bc9a47bb58f847e73b87156d099e821bd791546f6126dc78e47c5494a7851c`


# KlingDualCharacterVideoEffectNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingDualCharacterVideoEffectNode

Complete documentation for the KlingDualCharacterVideoEffectNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingDualCharacterVideoEffectNode/en.md)

The Kling Dual Character Video Effect Node creates videos with special effects based on the selected scene. It takes two images and positions the first image on the left side and the second image on the right side of the composite video. Different visual effects are applied depending on the chosen effect scene.

## Inputs

| Parameter      | Data Type | Required | Range                                                                                                                                     | Description                                                       |
| -------------- | --------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------- |
| `image_left`   | IMAGE     | Yes      | -                                                                                                                                         | Left side image                                                   |
| `image_right`  | IMAGE     | Yes      | -                                                                                                                                         | Right side image                                                  |
| `effect_scene` | COMBO     | Yes      | `"chat"`<br />`"dance"`<br />`"hug"`<br />`"kill"`<br />`"kiss"`<br />`"pat"`<br />`"punch"`<br />`"shrug"`<br />`"slap"`<br />`"tickle"` | The type of special effect scene to apply to the video generation |
| `model_name`   | COMBO     | No       | `"kling-v1"`<br />`"kling-v1-5"`<br />`"kling-v1-6"`                                                                                      | The model to use for character effects (default: "kling-v1")      |
| `mode`         | COMBO     | No       | `"std"`<br />`"pro"`                                                                                                                      | The video generation mode (default: "std")                        |
| `duration`     | COMBO     | Yes      | `"5"`<br />`"10"`                                                                                                                         | The duration of the generated video in seconds                    |

## Outputs

| Output Name | Data Type | Description                                     |
| ----------- | --------- | ----------------------------------------------- |
| `output`    | VIDEO     | The generated video with dual character effects |
| `duration`  | STRING    | The duration information of the generated video |

***

**Source fingerprint (SHA-256):** `995616159d0b61a5398ec93e847b04fed8133a28a37f597427f0335ca17920b9`


# KlingFirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingFirstLastFrameNode

Complete documentation for the KlingFirstLastFrameNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingFirstLastFrameNode/en.md)

This node uses the Kling 3.0 model to generate a video. It creates the video based on a text prompt, a specified duration, and two provided images: a starting frame and an ending frame. The node can also generate accompanying audio for the video.

## Inputs

| Parameter          | Data Type | Required | Range                               | Description                                                                                                                            |
| ------------------ | --------- | -------- | ----------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`           | STRING    | Yes      | N/A                                 | The text description that guides the video generation. Must be between 1 and 2500 characters long.                                     |
| `duration`         | INT       | No       | 3 to 15                             | The length of the video in seconds (default: 5).                                                                                       |
| `first_frame`      | IMAGE     | Yes      | N/A                                 | The starting image for the video. Must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1.                    |
| `end_frame`        | IMAGE     | Yes      | N/A                                 | The ending image for the video. Must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1.                      |
| `generate_audio`   | BOOLEAN   | No       | N/A                                 | Controls whether to generate audio for the video (default: True).                                                                      |
| `model`            | COMBO     | No       | `"kling-v3"`                        | Model and generation settings. Selecting this option reveals a nested `resolution` parameter.                                          |
| `model.resolution` | COMBO     | No       | `"4k"`<br />`"1080p"`<br />`"720p"` | The resolution for the generated video. This parameter is only available when the `model` is set to `"kling-v3"` (default: `"1080p"`). |
| `seed`             | INT       | No       | 0 to 2147483647                     | A number used to control whether the node should re-run. The results are non-deterministic regardless of the seed value (default: 0).  |

**Note:** The `first_frame` and `end_frame` images must meet the specified minimum size and aspect ratio requirements for the node to function correctly.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `def99b6a37962b5a28be1025ce41ae50bf7b90246c50894fcf3419365f807b2f`


# KlingImage2VideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingImage2VideoNode

Complete documentation for the KlingImage2VideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingImage2VideoNode/en.md)

The Kling Image to Video Node generates a video from a starting reference image using text prompts. It takes an image as the first frame and creates a video sequence based on positive and negative text descriptions, with configurable options for model, duration, aspect ratio, and generation mode.

## Inputs

| Parameter         | Data Type | Required | Range                                                                                                                                                                        | Description                                                                                                                                                                                                                 |
| ----------------- | --------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `start_frame`     | IMAGE     | Yes      | -                                                                                                                                                                            | The reference image used to generate the video. The image must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1.                                                                                 |
| `prompt`          | STRING    | Yes      | -                                                                                                                                                                            | Positive text prompt. Maximum 500 characters.                                                                                                                                                                               |
| `negative_prompt` | STRING    | Yes      | -                                                                                                                                                                            | Negative text prompt. Maximum 500 characters.                                                                                                                                                                               |
| `model_name`      | COMBO     | Yes      | `"kling-v2-master"`<br />`"kling-v2-1-master"`<br />`"kling-v2-5-turbo"`<br />`"kling-v2-1"`<br />`"kling-v1-6"`<br />`"kling-v1-5"`<br />`"kling-v1-4"`<br />`"kling-v1-0"` | The model used for video generation (default: `"kling-v2-master"`).                                                                                                                                                         |
| `cfg_scale`       | FLOAT     | Yes      | 0.0 to 1.0                                                                                                                                                                   | Controls how closely the video follows the prompt. Higher values mean stronger adherence (default: 0.8).                                                                                                                    |
| `mode`            | COMBO     | Yes      | `"std"`<br />`"pro"`                                                                                                                                                         | The generation mode. `"std"` is standard quality, `"pro"` is higher quality (default: `"std"`). Note: When using the `kling-v2-5-turbo` model, `"std"` mode is not supported and will be automatically switched to `"pro"`. |
| `aspect_ratio`    | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`                                                                                                                                          | The aspect ratio of the generated video (default: `"16:9"`).                                                                                                                                                                |
| `duration`        | COMBO     | Yes      | `"5"`<br />`"10"`                                                                                                                                                            | The duration of the generated video in seconds (default: `"5"`).                                                                                                                                                            |

## Outputs

| Output Name | Data Type | Description                                   |
| ----------- | --------- | --------------------------------------------- |
| `output`    | VIDEO     | The generated video output.                   |
| `video_id`  | STRING    | Unique identifier for the generated video.    |
| `duration`  | STRING    | Duration information for the generated video. |

***

**Source fingerprint (SHA-256):** `2845117c840372d457c58bfb8da077ccac32a9398e5679120104d8ee597d4855`


# KlingImageToVideoWithAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingImageToVideoWithAudio

Complete documentation for the KlingImageToVideoWithAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingImageToVideoWithAudio/en.md)

The Kling Image(First Frame) to Video with Audio node uses the Kling AI model to generate a short video from a single starting image and a text prompt. It creates a video sequence that begins with the provided image and can optionally include AI-generated audio to accompany the visuals.

## Inputs

| Parameter        | Data Type | Required | Range          | Description                                                                                                                                                      |
| ---------------- | --------- | -------- | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model_name`     | COMBO     | Yes      | `"kling-v2-6"` | The specific version of the Kling AI model to use for video generation.                                                                                          |
| `start_frame`    | IMAGE     | Yes      | -              | The image that will serve as the first frame of the generated video. The image must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1. |
| `prompt`         | STRING    | Yes      | -              | Positive text prompt. This describes the video content you want to generate. The prompt must be between 1 and 2500 characters long.                              |
| `mode`           | COMBO     | Yes      | `"pro"`        | The operational mode for the video generation.                                                                                                                   |
| `duration`       | COMBO     | Yes      | `5`<br />`10`  | The length of the video to generate, in seconds.                                                                                                                 |
| `generate_audio` | BOOLEAN   | No       | -              | When enabled, the node will generate audio to accompany the video. When disabled, the video will be silent. (default: True)                                      |

## Outputs

| Output Name | Data Type | Description                                                                                |
| ----------- | --------- | ------------------------------------------------------------------------------------------ |
| `video`     | VIDEO     | The generated video file, which may include audio depending on the `generate_audio` input. |

***

**Source fingerprint (SHA-256):** `c994748fdfa6d79f81aaf864ec174a6b608c4f05943a7e23edd345608122d9a1`


# KlingLipSyncAudioToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingLipSyncAudioToVideoNode

Complete documentation for the KlingLipSyncAudioToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingLipSyncAudioToVideoNode/en.md)

Kling Lip Sync Audio to Video Node synchronizes mouth movements in a video file to match the audio content of an audio file. This node analyzes the vocal patterns in the audio and adjusts the facial movements in the video to create realistic lip-syncing. The process requires both a video containing a distinct face and an audio file with clearly distinguishable vocals.

## Inputs

| Parameter        | Data Type | Required | Range                                                                                                                                                                                      | Description                                                 |
| ---------------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------- |
| `video`          | VIDEO     | Yes      | -                                                                                                                                                                                          | The video file containing a face to be lip-synced           |
| `audio`          | AUDIO     | Yes      | -                                                                                                                                                                                          | The audio file containing vocals to sync with the video     |
| `voice_language` | COMBO     | Yes      | `"en"`<br />`"zh"`<br />`"es"`<br />`"fr"`<br />`"de"`<br />`"it"`<br />`"pt"`<br />`"pl"`<br />`"tr"`<br />`"ru"`<br />`"nl"`<br />`"cs"`<br />`"ar"`<br />`"ja"`<br />`"hu"`<br />`"ko"` | The language of the voice in the audio file (default: "en") |

**Important Constraints:**

* The audio file should not be larger than 5MB
* The video file should not be larger than 100MB
* Video dimensions should be between 720px and 1920px in height/width
* Video duration should be between 2 seconds and 10 seconds
* The audio must contain clearly distinguishable vocals
* The video must contain a distinct face

## Outputs

| Output Name | Data Type | Description                                         |
| ----------- | --------- | --------------------------------------------------- |
| `output`    | VIDEO     | The processed video with lip-synced mouth movements |
| `video_id`  | STRING    | The unique identifier for the processed video       |
| `duration`  | STRING    | The duration of the processed video                 |

***

**Source fingerprint (SHA-256):** `bc6dcc5a1e3b873edc0c65cc156bb622992866920a4975a308d8cdb8a3c0e71a`


# KlingLipSyncTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingLipSyncTextToVideoNode

Complete documentation for the KlingLipSyncTextToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingLipSyncTextToVideoNode/en.md)

Kling Lip Sync Text to Video Node synchronizes mouth movements in a video file to match a text prompt. It takes an input video and generates a new video where the character's lip movements are aligned with the provided text. The node uses voice synthesis to create natural-looking speech synchronization.

## Inputs

| Parameter     | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              | Description                                                                                                                                                 |
| ------------- | --------- | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `video`       | VIDEO     | Yes      | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | Input video file for lip synchronization. Video must be between 720px and 1920px in height/width, between 2s and 10s in duration, and no larger than 100MB. |
| `text`        | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | Text Content for Lip-Sync Video Generation. Required when mode is text2video. Maximum length is 120 characters.                                             |
| `voice`       | COMBO     | No       | "Melody"<br />"Sunny"<br />"Sage"<br />"Ace"<br />"Blossom"<br />"Peppy"<br />"Dove"<br />"Shine"<br />"Anchor"<br />"Lyric"<br />"Tender"<br />"Siren"<br />"Zippy"<br />"Bud"<br />"Sprite"<br />"Candy"<br />"Beacon"<br />"Rock"<br />"Titan"<br />"Grace"<br />"Helen"<br />"Lore"<br />"Crag"<br />"Prattle"<br />"Hearth"<br />"The Reader"<br />"Commercial Lady"<br />"阳光少年"<br />"懂事小弟"<br />"运动少年"<br />"青春少女"<br />"温柔小妹"<br />"元气少女"<br />"阳光男生"<br />"幽默小哥"<br />"文艺小哥"<br />"甜美邻家"<br />"温柔姐姐"<br />"职场女青"<br />"活泼男童"<br />"俏皮女童"<br />"稳重老爸"<br />"温柔妈妈"<br />"严肃上司"<br />"优雅贵妇"<br />"慈祥爷爷"<br />"唠叨爷爷"<br />"唠叨奶奶"<br />"和蔼奶奶"<br />"东北老铁"<br />"重庆小伙"<br />"四川妹子"<br />"潮汕大叔"<br />"台湾男生"<br />"西安掌柜"<br />"天津姐姐"<br />"新闻播报男"<br />"译制片男"<br />"撒娇女友"<br />"刀片烟嗓"<br />"乖巧正太" | Voice selection for the lip-sync audio (default: "Melody"). Includes both English and Chinese voice options.                                                |
| `voice_speed` | FLOAT     | No       | 0.8-2.0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            | Speech Rate. Valid range: 0.8\~2.0, accurate to one decimal place. (default: 1)                                                                             |

**Video Requirements:**

* Video file should not be larger than 100MB
* Height/width should be between 720px and 1920px
* Duration should be between 2s and 10s

## Outputs

| Output Name | Data Type | Description                                  |
| ----------- | --------- | -------------------------------------------- |
| `output`    | VIDEO     | Generated video with lip-synchronized audio  |
| `video_id`  | STRING    | Unique identifier for the generated video    |
| `duration`  | STRING    | Duration information for the generated video |

***

**Source fingerprint (SHA-256):** `fb6d208be684f8fc38f692c0439bcfebafc8c448932bc54fa4730da87113f376`


# KlingMotionControl - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingMotionControl

Complete documentation for the KlingMotionControl node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingMotionControl/en.md)

The Kling Motion Control node generates a video by applying the motion, expressions, and camera movements from a reference video to a character defined by a reference image and a text prompt. It allows you to control whether the character's final orientation comes from the reference video or the reference image.

## Inputs

| Parameter               | Data Type | Required | Range                            | Description                                                                                                                                                                                                                                                                                                                                                             |
| ----------------------- | --------- | -------- | -------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`                | STRING    | Yes      | N/A                              | A text description of the desired video. Maximum length is 2500 characters.                                                                                                                                                                                                                                                                                             |
| `reference_image`       | IMAGE     | Yes      | N/A                              | An image of the character to animate. Minimum dimensions are 340x340 pixels. The aspect ratio must be between 1:2.5 and 2.5:1.                                                                                                                                                                                                                                          |
| `reference_video`       | VIDEO     | Yes      | N/A                              | A motion reference video used to drive the character's movement and expression. Minimum dimensions are 340x340 pixels, maximum dimensions are 3850x3850 pixels. Duration limits depend on the `character_orientation` setting.                                                                                                                                          |
| `keep_original_sound`   | BOOLEAN   | No       | N/A                              | Determines if the original audio from the reference video is kept in the output. Default is `True`.                                                                                                                                                                                                                                                                     |
| `character_orientation` | COMBO     | No       | `"video"`<br />`"image"`         | Controls where the character's facing/orientation comes from. `"video"`: movements, expressions, camera moves, and orientation follow the motion reference video (other details via prompt). `"image"`: movements and expressions still follow the motion reference video, but the character orientation matches the reference image (camera/other details via prompt). |
| `mode`                  | COMBO     | No       | `"pro"`<br />`"std"`             | The generation mode to use.                                                                                                                                                                                                                                                                                                                                             |
| `model`                 | COMBO     | No       | `"kling-v3"`<br />`"kling-v2-6"` | The Kling model version to use. Default is `"kling-v2-6"`.                                                                                                                                                                                                                                                                                                              |

**Constraints:**

* The `reference_video` duration must be between 3 and 30 seconds when `character_orientation` is set to `"video"`.
* The `reference_video` duration must be between 3 and 10 seconds when `character_orientation` is set to `"image"`.

## Outputs

| Output Name | Data Type | Description                                                                            |
| ----------- | --------- | -------------------------------------------------------------------------------------- |
| `output`    | VIDEO     | The generated video with the character performing the motion from the reference video. |

***

**Source fingerprint (SHA-256):** `3e350ca448a927367edfc90c5abb572be7ffa589c9e8e8734066af280233bd60`


# KlingOmniProEditVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProEditVideoNode

Complete documentation for the KlingOmniProEditVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProEditVideoNode/en.md)

The Kling Omni Edit Video (Pro) node uses an AI model to edit an existing video based on a text description. You provide a source video and a prompt, and the node generates a new video of the same length with the requested changes. It can optionally use reference images to guide the style and keep the original audio from the source video.

## Inputs

| Parameter             | Data Type | Required | Range                                     | Description                                                                                                  |
| --------------------- | --------- | -------- | ----------------------------------------- | ------------------------------------------------------------------------------------------------------------ |
| `model_name`          | COMBO     | Yes      | `"kling-v3-omni"`<br />`"kling-video-o1"` | The AI model to use for video editing (default: `"kling-v3-omni"`).                                          |
| `prompt`              | STRING    | Yes      |                                           | A text prompt describing the video content. This can include both positive and negative descriptions.        |
| `video`               | VIDEO     | Yes      |                                           | Video for editing. The output video length will be the same.                                                 |
| `keep_original_sound` | BOOLEAN   | Yes      |                                           | Determines if the original audio from the input video is kept in the output (default: True).                 |
| `reference_images`    | IMAGE     | No       |                                           | Up to 4 additional reference images.                                                                         |
| `resolution`          | COMBO     | No       | `"1080p"`<br />`"720p"`                   | The resolution for the output video (default: `"1080p"`).                                                    |
| `seed`                | INT       | No       | 0 to 2147483647                           | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0). |

**Constraints and Limitations:**

* The `prompt` must be between 1 and 2500 characters long.
* The input `video` must be between 3.0 and 10.05 seconds in duration.
* The input `video` dimensions must be between 720x720 and 2160x2160 pixels.
* A maximum of 4 `reference_images` can be provided when a video is used.
* Each `reference_image` must be at least 300x300 pixels.
* Each `reference_image` must have an aspect ratio between 1:2.5 and 2.5:1.

## Outputs

| Output Name | Data Type | Description                                 |
| ----------- | --------- | ------------------------------------------- |
| `video`     | VIDEO     | The edited video generated by the AI model. |

***

**Source fingerprint (SHA-256):** `770f1944738c06523a537a1add85340ea9264771f62e463f4985ca6bcacddf78`


# KlingOmniProFirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProFirstLastFrameNode

Complete documentation for the KlingOmniProFirstLastFrameNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProFirstLastFrameNode/en.md)

This node uses the latest Kling AI model to generate a video from a start frame, an optional end frame, or reference images. It can create a single video or a multi-shot storyboard with individual prompts and durations for each segment. The node processes these inputs to produce a video of a specified length and resolution, with optional audio generation.

## Inputs

| Parameter          | Data Type      | Required | Range                                                                                                                                                 | Description                                                                                                                                                                        |
| ------------------ | -------------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model_name`       | COMBO          | Yes      | `"kling-v3-omni"`<br />`"kling-video-o1"`                                                                                                             | The specific Kling AI model to use for video generation.                                                                                                                           |
| `prompt`           | STRING         | Yes      | -                                                                                                                                                     | A text prompt describing the video content. This can include both positive and negative descriptions. Ignored when storyboards are enabled.                                        |
| `duration`         | INT            | Yes      | 3 to 15                                                                                                                                               | The desired length of the generated video in seconds (default: 5).                                                                                                                 |
| `first_frame`      | IMAGE          | Yes      | -                                                                                                                                                     | The starting image for the video sequence.                                                                                                                                         |
| `end_frame`        | IMAGE          | No       | -                                                                                                                                                     | An optional end frame for the video. This cannot be used simultaneously with `reference_images`. Does not work with storyboards.                                                   |
| `reference_images` | IMAGE          | No       | -                                                                                                                                                     | Up to 6 additional reference images.                                                                                                                                               |
| `resolution`       | COMBO          | No       | `"4k"`<br />`"1080p"`<br />`"720p"`                                                                                                                   | The output resolution for the generated video (default: "1080p").                                                                                                                  |
| `storyboards`      | DYNAMIC\_COMBO | No       | `"disabled"`<br />`"1 storyboard"`<br />`"2 storyboards"`<br />`"3 storyboards"`<br />`"4 storyboards"`<br />`"5 storyboards"`<br />`"6 storyboards"` | Generate a series of video segments with individual prompts and durations. Only supported for `kling-v3-omni`. When enabled, each storyboard requires a prompt and duration input. |
| `generate_audio`   | BOOLEAN        | No       | True / False                                                                                                                                          | Generate audio for the video (default: False). Only supported for `kling-v3-omni`.                                                                                                 |
| `seed`             | INT            | No       | 0 to 2147483647                                                                                                                                       | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0).                                                                       |

**Important Constraints:**

* The `end_frame` input cannot be used at the same time as the `reference_images` input.
* The `end_frame` input cannot be used simultaneously with storyboards.
* The `kling-video-o1` model does not support durations greater than 10 seconds, audio generation, 4k resolution, or storyboards.
* If you do not provide an `end_frame` or any `reference_images` with the `kling-video-o1` model, the `duration` can only be set to 5 or 10 seconds.
* All input images (`first_frame`, `end_frame`, and any `reference_images`) must have a minimum dimension of 300 pixels in both width and height.
* The aspect ratio of all input images must be between 1:2.5 and 2.5:1.
* A maximum of 6 images can be provided via the `reference_images` input.
* The `prompt` text must be between 1 and 2500 characters in length (0 characters allowed when storyboards are enabled).
* When storyboards are enabled, the total duration of all storyboard segments must equal the global `duration` value.
* Each storyboard prompt must be between 1 and 512 characters in length.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `caa8c321124c70cb9cbeedee13cdde4c37c7e107c04265b4baf2dd8864a1fc65`


# KlingOmniProImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProImageToVideoNode

Complete documentation for the KlingOmniProImageToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProImageToVideoNode/en.md)

This node uses the Kling AI model to generate a video based on a text prompt and up to seven reference images. It allows you to control the video's aspect ratio, duration, resolution, and optionally use storyboards or generate audio. The node sends the request to an external API and returns the generated video.

## Inputs

| Parameter          | Data Type      | Required | Range                                                                                                                                                 | Description                                                                                                                                                                                                                                      |
| ------------------ | -------------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `model_name`       | COMBO          | Yes      | `"kling-v3-omni"`<br />`"kling-video-o1"`                                                                                                             | The specific Kling model to use for video generation (default: "kling-v3-omni").                                                                                                                                                                 |
| `prompt`           | STRING         | Yes      | -                                                                                                                                                     | A text prompt describing the video content. This can include both positive and negative descriptions. The text is automatically normalized and must be between 1 and 2500 characters. Ignored when storyboards are enabled.                      |
| `aspect_ratio`     | COMBO          | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`                                                                                                                   | The desired aspect ratio for the generated video.                                                                                                                                                                                                |
| `duration`         | INT            | Yes      | 3 to 15                                                                                                                                               | The length of the video in seconds. The value can be adjusted with a slider (default: 5).                                                                                                                                                        |
| `reference_images` | IMAGE          | Yes      | -                                                                                                                                                     | Up to 7 reference images. Each image must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1.                                                                                                                           |
| `resolution`       | COMBO          | No       | `"4k"`<br />`"1080p"`<br />`"720p"`                                                                                                                   | The output resolution of the video. This parameter is optional (default: "1080p").                                                                                                                                                               |
| `storyboards`      | DYNAMIC\_COMBO | No       | `"disabled"`<br />`"1 storyboard"`<br />`"2 storyboards"`<br />`"3 storyboards"`<br />`"4 storyboards"`<br />`"5 storyboards"`<br />`"6 storyboards"` | Generate a series of video segments with individual prompts and durations. Only supported for `kling-v3-omni`. When enabled, the global `prompt` is ignored, and the total duration of all storyboard segments must equal the global `duration`. |
| `generate_audio`   | BOOLEAN        | No       | `true`<br />`false`                                                                                                                                   | Generate audio for the video. Only supported for `kling-v3-omni` (default: false).                                                                                                                                                               |
| `seed`             | INT            | No       | 0 to 2147483647                                                                                                                                       | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0).                                                                                                                                     |

**Note:** The `reference_images` input accepts a maximum of 7 images. If more are provided, the node will raise an error. Each image is validated for minimum dimensions and aspect ratio.

**Model-specific constraints:**

* `kling-video-o1` does not support durations greater than 10 seconds.
* `kling-video-o1` does not support audio generation.
* `kling-video-o1` does not support 4k resolution.
* `kling-video-o1` does not support storyboards.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `e1fe0433a604fbc071fdd426121a1f4ff10bb0aa6d3eb2d702306b7206dae4c0`


# KlingOmniProTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProTextToVideoNode

Complete documentation for the KlingOmniProTextToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProTextToVideoNode/en.md)

This node uses the latest Kling AI model to generate a video from a text description. It sends your prompt to a remote API and returns the generated video. The node allows you to control the video's length, shape, quality, and even create multi-shot storyboards.

## Inputs

| Parameter        | Data Type      | Required | Range                                                                                                                                                 | Description                                                                                                                                 |
| ---------------- | -------------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- |
| `model_name`     | COMBO          | Yes      | `"kling-v3-omni"`<br />`"kling-video-o1"`                                                                                                             | The specific Kling model to use for video generation (default: `"kling-v3-omni"`).                                                          |
| `prompt`         | STRING         | Yes      | 0 to 2500 characters                                                                                                                                  | A text prompt describing the video content. This can include both positive and negative descriptions. Ignored when storyboards are enabled. |
| `aspect_ratio`   | COMBO          | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`                                                                                                                   | The shape or dimensions of the video to generate.                                                                                           |
| `duration`       | INT            | Yes      | 3 to 15 seconds                                                                                                                                       | The length of the video in seconds (default: 5).                                                                                            |
| `resolution`     | COMBO          | No       | `"4k"`<br />`"1080p"`<br />`"720p"`                                                                                                                   | The quality or pixel resolution of the video (default: `"1080p"`).                                                                          |
| `storyboards`    | DYNAMIC\_COMBO | No       | `"disabled"`<br />`"1 storyboard"`<br />`"2 storyboards"`<br />`"3 storyboards"`<br />`"4 storyboards"`<br />`"5 storyboards"`<br />`"6 storyboards"` | Generate a series of video segments with individual prompts and durations. Ignored for the o1 model.                                        |
| `generate_audio` | BOOLEAN        | No       | True / False                                                                                                                                          | Whether to generate audio for the video (default: False).                                                                                   |
| `seed`           | INT            | No       | 0 to 2147483647                                                                                                                                       | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0).                                |

### Parameter Constraints and Limitations

* **Model-specific limitations:**
  * The `kling-video-o1` model only supports durations of **5 or 10 seconds**.
  * The `kling-video-o1` model does **not** support audio generation.
  * The `kling-video-o1` model does **not** support 4k resolution.
  * The `kling-video-o1` model does **not** support storyboards.
* **Storyboard constraints:**
  * When storyboards are enabled, the `prompt` field is ignored.
  * Each storyboard requires its own prompt (1 to 512 characters) and duration.
  * The total duration of all storyboards must exactly equal the global `duration` parameter.
* **Prompt requirements:**
  * When storyboards are **disabled**, the `prompt` field is required (minimum 1 character).
  * When storyboards are **enabled**, the `prompt` field can be empty (0 characters).

## Outputs

| Output Name | Data Type | Description                                                         |
| ----------- | --------- | ------------------------------------------------------------------- |
| `output`    | VIDEO     | The video generated based on the provided text prompt and settings. |

***

**Source fingerprint (SHA-256):** `8789c78184356c8ca1d84e046a2c8db644b6e47822d909d95e9d7417f2311109`


# KlingOmniProVideoToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingOmniProVideoToVideoNode

Complete documentation for the KlingOmniProVideoToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingOmniProVideoToVideoNode/en.md)

This node uses the Kling AI model to generate a new video based on an input video and optional reference images. You provide a text prompt describing the desired content, and the node transforms the reference video accordingly. It can also incorporate up to four additional reference images to guide the style and content of the output.

## Inputs

| Parameter             | Data Type | Required | Range                                     | Description                                                                                                  |
| --------------------- | --------- | -------- | ----------------------------------------- | ------------------------------------------------------------------------------------------------------------ |
| `model_name`          | COMBO     | Yes      | `"kling-v3-omni"`<br />`"kling-video-o1"` | The specific Kling model to use for video generation (default: "kling-v3-omni").                             |
| `prompt`              | STRING    | Yes      | N/A                                       | A text prompt describing the video content. This can include both positive and negative descriptions.        |
| `aspect_ratio`        | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`       | The desired aspect ratio for the generated video.                                                            |
| `duration`            | INT       | Yes      | 3 to 10                                   | The length of the generated video in seconds (default: 3).                                                   |
| `reference_video`     | VIDEO     | Yes      | N/A                                       | Video to use as a reference.                                                                                 |
| `keep_original_sound` | BOOLEAN   | Yes      | N/A                                       | Determines if the audio from the reference video is kept in the output (default: True).                      |
| `reference_images`    | IMAGE     | No       | N/A                                       | Up to 4 additional reference images.                                                                         |
| `resolution`          | COMBO     | No       | `"1080p"`<br />`"720p"`                   | The resolution for the generated video (default: "1080p").                                                   |
| `seed`                | INT       | No       | 0 to 2147483647                           | Seed controls whether the node should re-run; results are non-deterministic regardless of seed (default: 0). |

**Parameter Constraints:**

* The `prompt` must be between 1 and 2500 characters long.
* The `reference_video` must be between 3.0 and 10.05 seconds in duration.
* The `reference_video` must have dimensions between 720x720 and 2160x2160 pixels.
* A maximum of 4 `reference_images` can be provided. Each image must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1.

## Outputs

| Output Name | Data Type | Description                |
| ----------- | --------- | -------------------------- |
| `output`    | VIDEO     | The newly generated video. |

***

**Source fingerprint (SHA-256):** `aa99b865ca96ec5c2d5535d3392e8dc94dd5e56ebf624f8fdff09302767ab300`


# KlingSingleImageVideoEffectNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingSingleImageVideoEffectNode

Complete documentation for the KlingSingleImageVideoEffectNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingSingleImageVideoEffectNode/en.md)

The Kling Single Image Video Effect Node creates videos with different special effects based on a single reference image. It applies various visual effects and scenes to transform static images into dynamic video content. The node supports different effect scenes, model options, and video durations to achieve the desired visual outcome.

## Inputs

| Parameter      | Data Type | Required | Range                                                                                                                          | Description                                                                                                                                                                      |
| -------------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `image`        | IMAGE     | Yes      | -                                                                                                                              | Reference Image. URL or Base64 encoded string (without data:image prefix). File size cannot exceed 10MB, resolution not less than 300x300px, aspect ratio between 1:2.5 to 2.5:1 |
| `effect_scene` | COMBO     | Yes      | `"dizzydizzy"`<br />`"bloombloom"`<br />`"neon"`<br />`"cartoon"`<br />`"sketch"`<br />`"oil"`<br />`"watercolor"`<br />`"3d"` | The type of special effect scene to apply to the video generation. Some effects may have different pricing.                                                                      |
| `model_name`   | COMBO     | Yes      | `"kling-v1-5"`<br />`"kling-v1-6"`                                                                                             | The specific model version to use for generating the video effect.                                                                                                               |
| `duration`     | COMBO     | Yes      | `"5"`<br />`"10"`                                                                                                              | The length of the generated video in seconds.                                                                                                                                    |

**Note:** The `effect_scene` parameter affects the pricing of the node. Effects `dizzydizzy` and `bloombloom` cost $0.49 USD per generation, while all other effects cost $0.28 USD per generation.

## Outputs

| Output Name | Data Type | Description                                   |
| ----------- | --------- | --------------------------------------------- |
| `output`    | VIDEO     | The generated video with applied effects      |
| `video_id`  | STRING    | The unique identifier for the generated video |
| `duration`  | STRING    | The duration of the generated video           |

***

**Source fingerprint (SHA-256):** `7e9d1e2830f16361587d3d1f082fb2536d36ca9d933aa9e2ced32eeb65a161ea`


# KlingStartEndFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingStartEndFrameNode

Complete documentation for the KlingStartEndFrameNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingStartEndFrameNode/en.md)

Kling Start-End Frame to Video node creates a video sequence that transitions between your provided start and end images. It generates all the frames in between to produce a smooth transformation from the first frame to the last frame. This node calls the image-to-video API but only supports the input options that work with the `image_tail` request field.

## Inputs

| Parameter         | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                              | Description                                                                                                                                                                                |
| ----------------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `start_frame`     | IMAGE     | Yes      | -                                                                                                                                                                                                                                                                                                                                                                  | Reference Image - URL or Base64 encoded string, cannot exceed 10MB, resolution not less than 300\*300px, aspect ratio between 1:2.5 \~ 2.5:1. Base64 should not include data:image prefix. |
| `end_frame`       | IMAGE     | Yes      | -                                                                                                                                                                                                                                                                                                                                                                  | Reference Image - End frame control. URL or Base64 encoded string, cannot exceed 10MB, resolution not less than 300\*300px. Base64 should not include data:image prefix.                   |
| `prompt`          | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                                                                  | Positive text prompt                                                                                                                                                                       |
| `negative_prompt` | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                                                                  | Negative text prompt                                                                                                                                                                       |
| `cfg_scale`       | FLOAT     | No       | 0.0-1.0                                                                                                                                                                                                                                                                                                                                                            | Controls the strength of the prompt guidance (default: 0.5)                                                                                                                                |
| `aspect_ratio`    | COMBO     | No       | "16:9"<br />"9:16"<br />"1:1"                                                                                                                                                                                                                                                                                                                                      | The aspect ratio for the generated video (default: "16:9")                                                                                                                                 |
| `mode`            | COMBO     | No       | "pro mode / 5s duration / kling-v1-5"<br />"pro mode / 10s duration / kling-v1-5"<br />"pro mode / 5s duration / kling-v1-6"<br />"pro mode / 10s duration / kling-v1-6"<br />"pro mode / 5s duration / kling-v2-1"<br />"pro mode / 10s duration / kling-v2-1"<br />"pro mode / 5s duration / kling-v2-5-turbo"<br />"pro mode / 10s duration / kling-v2-5-turbo" | The configuration to use for the video generation following the format: mode / duration / model\_name. (default: "pro mode / 5s duration / kling-v2-5-turbo")                              |

**Image Constraints:**

* Both `start_frame` and `end_frame` must be provided and cannot exceed 10MB file size
* Minimum resolution: 300×300 pixels for both images
* `start_frame` aspect ratio must be between 1:2.5 and 2.5:1
* Base64 encoded images should not include the "data:image" prefix

## Outputs

| Output Name | Data Type | Description                               |
| ----------- | --------- | ----------------------------------------- |
| `output`    | VIDEO     | The generated video sequence              |
| `video_id`  | STRING    | Unique identifier for the generated video |
| `duration`  | STRING    | Duration of the generated video           |

***

**Source fingerprint (SHA-256):** `e0bf25103e72ea3f56651adf64c0712f32c055f2b870448dcbbe82b546be8f37`


# KlingTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingTextToVideoNode

Complete documentation for the KlingTextToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingTextToVideoNode/en.md)

The Kling Text to Video Node converts text descriptions into video content. It takes text prompts and generates corresponding video sequences based on the specified configuration settings. The node supports different aspect ratios, generation modes, and model versions to produce videos of varying durations and quality.

## Inputs

| Parameter         | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | Description                                                                                                                                               |
| ----------------- | --------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt`          | STRING    | Yes      | Maximum 2500 characters                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             | Positive text prompt describing the desired video content                                                                                                 |
| `negative_prompt` | STRING    | Yes      | Maximum 2500 characters                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             | Negative text prompt describing what to avoid in the video                                                                                                |
| `cfg_scale`       | FLOAT     | No       | 0.0 to 1.0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          | Configuration scale value that controls how closely the video follows the prompt (default: 1.0)                                                           |
| `aspect_ratio`    | COMBO     | No       | `"16:9"`<br />`"9:16"`<br />`"1:1"`                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | Video aspect ratio setting (default: "16:9")                                                                                                              |
| `mode`            | COMBO     | No       | `"standard mode / 5s duration / kling-v1-6"`<br />`"standard mode / 10s duration / kling-v1-6"`<br />`"pro mode / 5s duration / kling-v2-master"`<br />`"pro mode / 10s duration / kling-v2-master"`<br />`"standard mode / 5s duration / kling-v2-master"`<br />`"standard mode / 10s duration / kling-v2-master"`<br />`"pro mode / 5s duration / kling-v2-1-master"`<br />`"pro mode / 10s duration / kling-v2-1-master"`<br />`"pro mode / 5s duration / kling-v2-5-turbo"`<br />`"pro mode / 10s duration / kling-v2-5-turbo"` | The configuration to use for video generation, following the format: mode / duration / model\_name (default: "pro mode / 5s duration / kling-v2-5-turbo") |

## Outputs

| Output Name | Data Type | Description                                  |
| ----------- | --------- | -------------------------------------------- |
| `output`    | VIDEO     | The generated video output                   |
| `video_id`  | STRING    | Unique identifier for the generated video    |
| `duration`  | STRING    | Duration information for the generated video |

***

**Source fingerprint (SHA-256):** `2ec33023f023e8e6fbef04df4f6038a95b88205dbb9d170e88a964cf1ef03a27`


# KlingTextToVideoWithAudio - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingTextToVideoWithAudio

Complete documentation for the KlingTextToVideoWithAudio node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingTextToVideoWithAudio/en.md)

The Kling Text to Video with Audio node generates a short video from a text description. It sends a request to the Kling AI service, which processes the prompt and returns a video file. The node can also generate accompanying audio for the video based on the text.

## Inputs

| Parameter        | Data Type | Required | Range                               | Description                                                                                                                      |
| ---------------- | --------- | -------- | ----------------------------------- | -------------------------------------------------------------------------------------------------------------------------------- |
| `model_name`     | COMBO     | Yes      | `"kling-v2-6"`                      | The specific AI model to use for video generation.                                                                               |
| `prompt`         | STRING    | Yes      | -                                   | Positive text prompt. The description used to generate the video. Must be between 1 and 2500 characters.                         |
| `mode`           | COMBO     | Yes      | `"pro"`                             | The operational mode for the video generation.                                                                                   |
| `aspect_ratio`   | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"` | The desired width-to-height ratio for the generated video.                                                                       |
| `duration`       | COMBO     | Yes      | `5`<br />`10`                       | The length of the video in seconds.                                                                                              |
| `generate_audio` | BOOLEAN   | No       | -                                   | Controls whether audio is generated for the video. When enabled, the AI will create sound based on the prompt. (default: `True`) |

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `60c76cc66b02552cfbf63dda35e8422349c0b6989ca07631d2d8321bb5686cca`


# KlingVideoExtendNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingVideoExtendNode

Complete documentation for the KlingVideoExtendNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingVideoExtendNode/en.md)

The Kling Video Extend Node allows you to extend videos created by other Kling nodes. It takes an existing video identified by its video ID and generates additional content based on your text prompts. The node works by sending your extension request to the Kling API and returning the extended video along with its new ID and duration.

## Inputs

| Parameter         | Data Type | Required | Range     | Description                                                                                                                                                                                      |
| ----------------- | --------- | -------- | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `prompt`          | STRING    | No       | -         | Positive text prompt for guiding the video extension                                                                                                                                             |
| `negative_prompt` | STRING    | No       | -         | Negative text prompt for elements to avoid in the extended video                                                                                                                                 |
| `cfg_scale`       | FLOAT     | No       | 0.0 - 1.0 | Controls the strength of prompt guidance (default: 0.5)                                                                                                                                          |
| `video_id`        | STRING    | Yes      | -         | The ID of the video to be extended. Supports videos generated by text-to-video, image-to-video, and previous video extension operations. Cannot exceed 3 minutes total duration after extension. |

**Note:** The `video_id` must reference a video created by other Kling nodes, and the total duration after extension cannot exceed 3 minutes. The positive prompt must not be empty and both prompts must be under 2500 characters.

## Outputs

| Output Name | Data Type | Description                                   |
| ----------- | --------- | --------------------------------------------- |
| `output`    | VIDEO     | The extended video generated by the Kling API |
| `video_id`  | STRING    | The unique identifier for the extended video  |
| `duration`  | STRING    | The duration of the extended video            |

***

**Source fingerprint (SHA-256):** `31f9d394845412d92b9e9ad7e032acea9c686fe54e32b53dac3848ab54ff9287`


# KlingVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/KlingVideoNode

Complete documentation for the KlingVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/KlingVideoNode/en.md)

This node generates videos using the Kling V3 model. It supports two primary modes: text-to-video, where a video is created from a text description, and image-to-video, where an existing image is animated. It also offers advanced features like creating multi-segment videos with different prompts for each part (storyboards) and optionally generating accompanying audio.

## Inputs

| Parameter            | Data Type | Required | Range                                                                                                                                                 | Description                                                                                                                                                                                         |
| -------------------- | --------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `multi_shot`         | COMBO     | Yes      | `"disabled"`<br />`"1 storyboard"`<br />`"2 storyboards"`<br />`"3 storyboards"`<br />`"4 storyboards"`<br />`"5 storyboards"`<br />`"6 storyboards"` | Controls whether to generate a single video or a series of segments with individual prompts and durations. When not "disabled," additional inputs for each storyboard's prompt and duration appear. |
| `generate_audio`     | BOOLEAN   | Yes      | `True` / `False`                                                                                                                                      | When enabled, the node will generate audio for the video. Default is `True`.                                                                                                                        |
| `model`              | COMBO     | Yes      | `"kling-v3"`                                                                                                                                          | The model and its associated settings. Selecting this option reveals the `resolution` and `aspect_ratio` sub-parameters.                                                                            |
| `model.resolution`   | COMBO     | Yes      | `"4k"`<br />`"1080p"`<br />`"720p"`                                                                                                                   | The resolution for the generated video. This setting is available when the `model` is set to "kling-v3".                                                                                            |
| `model.aspect_ratio` | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`                                                                                                                   | The aspect ratio for the generated video. This setting is ignored when an image is provided for `start_frame` (image-to-video mode). Available when the `model` is set to "kling-v3".               |
| `seed`               | INT       | Yes      | 0 to 2147483647                                                                                                                                       | A seed value for generation. Changing this value will cause the node to re-run, but the results are non-deterministic. Default is `0`.                                                              |
| `start_frame`        | IMAGE     | No       | -                                                                                                                                                     | An optional starting image. When connected, the node switches from text-to-video to image-to-video mode, animating the provided image.                                                              |

**Inputs for `multi_shot` mode:**

* When `multi_shot` is set to **"disabled"**, the following inputs appear:
  * `prompt` (STRING): The main text description for the video. Required. Must be between 1 and 2500 characters.
  * `negative_prompt` (STRING): Text describing what should not appear in the video. Optional.
  * `duration` (INT): The length of the video in seconds. Must be between 3 and 15. Default is `5`.
* When `multi_shot` is set to a storyboard option (e.g., `"3 storyboards"`), inputs for each storyboard segment appear (e.g., `storyboard_1_prompt`, `storyboard_1_duration`). Each prompt must be between 1 and 512 characters. The **total sum of all storyboard durations** must be between 3 and 15 seconds.

**Constraints:**

* The node operates in **text-to-video** mode when `start_frame` is not connected. It uses the `model.aspect_ratio` setting in this mode.
* The node operates in **image-to-video** mode when `start_frame` is connected. The `model.aspect_ratio` setting is ignored. The input image must be at least 300x300 pixels and have an aspect ratio between 1:2.5 and 2.5:1.
* In storyboard mode (`multi_shot` not "disabled"), the main `prompt` and `negative_prompt` inputs are hidden and not used.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `video`     | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `c329fa5a8609ccd2caec96fc23afae9ba79bdf835faa05450d4e20a7380087f5`


# LtxvApiImageToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LtxvApiImageToVideo

Complete documentation for the LtxvApiImageToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LtxvApiImageToVideo/en.md)

The LTXV Image To Video node generates a professional-quality video from a single starting image. It uses an external API to create a video sequence based on your text prompt, allowing you to customize the duration, resolution, and frame rate.

## Inputs

| Parameter        | Data Type | Required | Range                                                                    | Description                                                                                                                        |
| ---------------- | --------- | -------- | ------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------- |
| `image`          | IMAGE     | Yes      | -                                                                        | First frame to be used for the video.                                                                                              |
| `model`          | COMBO     | Yes      | `"LTX-2 (Pro)"`<br />`"LTX-2 (Fast)"`                                    | The AI model to use for video generation. The "Pro" model is optimized for quality, while the "Fast" model is optimized for speed. |
| `prompt`         | STRING    | Yes      | -                                                                        | A text description that guides the content and motion of the generated video.                                                      |
| `duration`       | COMBO     | Yes      | `6`<br />`8`<br />`10`<br />`12`<br />`14`<br />`16`<br />`18`<br />`20` | The length of the video in seconds (default: 8).                                                                                   |
| `resolution`     | COMBO     | Yes      | `"1920x1080"`<br />`"2560x1440"`<br />`"3840x2160"`                      | The output resolution of the generated video.                                                                                      |
| `fps`            | COMBO     | Yes      | `25`<br />`50`                                                           | The frames per second for the video (default: 25).                                                                                 |
| `generate_audio` | BOOLEAN   | No       | -                                                                        | When true, the generated video will include AI-generated audio matching the scene (default: False).                                |

**Important Constraints:**

* The `image` input must contain exactly one image.
* The `prompt` must be between 1 and 10,000 characters long.
* If you select a `duration` longer than 10 seconds, you must use the **"LTX-2 (Fast)"** model, a **"1920x1080"** resolution, and **25** FPS. This combination is required for longer videos.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `video`     | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `a4c6109ba8f70b0e80cf1888f940190c7a3e3994867e37f00669ae12742a94f8`


# LtxvApiTextToVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LtxvApiTextToVideo

Complete documentation for the LtxvApiTextToVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LtxvApiTextToVideo/en.md)

The LTXV Text To Video node generates professional-quality videos from a text description. It connects to an external API to create videos with customizable duration, resolution, and frame rate. You can also choose to have AI-generated audio added to the video.

## Inputs

| Parameter        | Data Type | Required | Range                                                                    | Description                                                                                                                 |
| ---------------- | --------- | -------- | ------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------- |
| `model`          | COMBO     | Yes      | `"LTX-2 (Pro)"`<br />`"LTX-2 (Fast)"`                                    | The AI model to use for video generation. "LTX-2 (Pro)" offers higher quality, while "LTX-2 (Fast)" is optimized for speed. |
| `prompt`         | STRING    | Yes      | -                                                                        | The text description that the AI will use to generate the video. This field supports multiple lines of text.                |
| `duration`       | COMBO     | Yes      | `6`<br />`8`<br />`10`<br />`12`<br />`14`<br />`16`<br />`18`<br />`20` | The length of the generated video in seconds (default: 8).                                                                  |
| `resolution`     | COMBO     | Yes      | `"1920x1080"`<br />`"2560x1440"`<br />`"3840x2160"`                      | The pixel dimensions (width x height) of the output video.                                                                  |
| `fps`            | COMBO     | Yes      | `25`<br />`50`                                                           | The frames per second for the video (default: 25).                                                                          |
| `generate_audio` | BOOLEAN   | No       | -                                                                        | When enabled, the generated video will include AI-generated audio matching the scene (default: False).                      |

**Important Constraints:**

* The `prompt` must be between 1 and 10,000 characters long.
* If you select a `duration` greater than 10 seconds, you must also use the `"LTX-2 (Fast)"` model, a resolution of `"1920x1080"`, and an `fps` of `25`. This combination is required for longer videos.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `8da5616f195dc4dea7d46d56b71dead6fb7a5dfa74bb7d8909bf6bd792540feb`


# LumaConceptsNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaConceptsNode

Complete documentation for the LumaConceptsNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaConceptsNode/en.md)

Holds one or more Camera Concepts for use with Luma Text to Video and Luma Image to Video nodes. This node allows you to select up to four camera concepts and optionally combine them with existing concept chains.

## Inputs

| Parameter       | Data Type      | Required | Range                                                  | Description                                                  |
| --------------- | -------------- | -------- | ------------------------------------------------------ | ------------------------------------------------------------ |
| `concept1`      | STRING         | Yes      | Multiple options available<br />Includes "None" option | First camera concept selection from available Luma concepts  |
| `concept2`      | STRING         | Yes      | Multiple options available<br />Includes "None" option | Second camera concept selection from available Luma concepts |
| `concept3`      | STRING         | Yes      | Multiple options available<br />Includes "None" option | Third camera concept selection from available Luma concepts  |
| `concept4`      | STRING         | Yes      | Multiple options available<br />Includes "None" option | Fourth camera concept selection from available Luma concepts |
| `luma_concepts` | LUMA\_CONCEPTS | No       | N/A                                                    | Optional Camera Concepts to add to the ones chosen here      |

**Note:** All concept parameters (`concept1` through `concept4`) can be set to "None" if you don't want to use all four concept slots. The node will merge any provided `luma_concepts` with the selected concepts to create a combined concept chain.

## Outputs

| Output Name     | Data Type      | Description                                                    |
| --------------- | -------------- | -------------------------------------------------------------- |
| `luma_concepts` | LUMA\_CONCEPTS | Combined camera concept chain containing all selected concepts |

***

**Source fingerprint (SHA-256):** `37e292aee8316e165e0069b1080479fed049d5bf754de90ef830f6400ca7e5c8`


# LumaImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaImageToVideoNode

Complete documentation for the LumaImageToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaImageToVideoNode/en.md)

Generates videos synchronously based on a text prompt and optional starting/ending images. This node uses the Luma API to create videos, allowing you to define the video's content through a prompt and optionally specify the first and/or last frame to control the video's structure.

## Inputs

| Parameter       | Data Type | Required | Range                                             | Description                                                                                                            |
| --------------- | --------- | -------- | ------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------- |
| `prompt`        | STRING    | Yes      | -                                                 | Prompt for the video generation (default: "")                                                                          |
| `model`         | COMBO     | Yes      | `"ray-1-6"`<br />`"ray-2"`                        | Selects the video generation model from available Luma models                                                          |
| `resolution`    | COMBO     | Yes      | `"540p"`<br />`"720p"<br />`"1080p"`<br />`"4k"\` | Output resolution for the generated video (default: "540p"). This parameter is ignored when using the `ray-1-6` model. |
| `duration`      | COMBO     | Yes      | `"5s"`<br />`"9s"`                                | Duration of the generated video. This parameter is ignored when using the `ray-1-6` model.                             |
| `loop`          | BOOLEAN   | Yes      | -                                                 | Whether the generated video should loop (default: False)                                                               |
| `seed`          | INT       | Yes      | 0 to 18446744073709551615                         | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed. (default: 0)          |
| `first_image`   | IMAGE     | No       | -                                                 | First frame of generated video. (optional)                                                                             |
| `last_image`    | IMAGE     | No       | -                                                 | Last frame of generated video. (optional)                                                                              |
| `luma_concepts` | CUSTOM    | No       | -                                                 | Optional Camera Concepts to dictate camera motion via the Luma Concepts node. (optional)                               |

**Note:** At least one of `first_image` or `last_image` must be provided. The node will raise an exception if both are missing. The `resolution` and `duration` parameters are ignored when the `model` is set to `ray-1-6`.

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `output`    | VIDEO     | The generated video file |

***

**Source fingerprint (SHA-256):** `0ef0e33f4822b522909a9732b333710197cd6e28ed6012c791f4268f8e995a84`


# LumaVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LumaVideoNode

Complete documentation for the LumaVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LumaVideoNode/en.md)

Generates videos synchronously based on a text prompt and output settings. This node creates video content using text descriptions and various generation parameters, producing the final video output once the generation process is complete.

## Inputs

| Parameter       | Data Type | Required | Range                                                                                     | Description                                                                                                      |
| --------------- | --------- | -------- | ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------- |
| `prompt`        | STRING    | Yes      | -                                                                                         | Prompt for the video generation (default: empty string). Must be at least 3 characters long.                     |
| `model`         | COMBO     | Yes      | `"ray_1_6"`<br />`"ray_2"`                                                                | The video generation model to use.                                                                               |
| `aspect_ratio`  | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"`<br />`"21:9"`<br />`"9:21"` | The aspect ratio for the generated video (default: "16:9").                                                      |
| `resolution`    | COMBO     | Yes      | `"540p"`<br />`"720p"`<br />`"1080p"`                                                     | The output resolution for the video (default: "540p"). This parameter is ignored when using the `ray_1_6` model. |
| `duration`      | COMBO     | Yes      | `"5s"`<br />`"9s"`                                                                        | The duration of the generated video. This parameter is ignored when using the `ray_1_6` model.                   |
| `loop`          | BOOLEAN   | Yes      | -                                                                                         | Whether the video should loop (default: False).                                                                  |
| `seed`          | INT       | Yes      | 0 to 18446744073709551615                                                                 | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0).    |
| `luma_concepts` | CUSTOM    | No       | -                                                                                         | Optional Camera Concepts to dictate camera motion via the Luma Concepts node.                                    |

**Note:** When using the `ray_1_6` model, the `duration` and `resolution` parameters are automatically ignored and do not affect the generation.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `3e7fb20aebee034e2055d87e7c1c24a995aece152b0271de48c81ce82cf2911a`


# MarkdownNote - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MarkdownNote

Complete documentation for the MarkdownNote node in ComfyUI. Learn its inputs, outputs, parameters and usage.

Node to add annotations to a workflow. It supports text formatting using Markdown syntax.

## Inputs

## Outputs

The node doesn't have outputs.


# MinimaxHailuoVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxHailuoVideoNode

Complete documentation for the MinimaxHailuoVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxHailuoVideoNode/en.md)

Generates videos from text prompts using the MiniMax Hailuo-02 model. You can optionally provide a starting image as the first frame to create a video that continues from that image.

## Inputs

| Parameter           | Data Type | Required | Range                     | Description                                                                                  |
| ------------------- | --------- | -------- | ------------------------- | -------------------------------------------------------------------------------------------- |
| `prompt_text`       | STRING    | Yes      | -                         | Text prompt to guide the video generation.                                                   |
| `seed`              | INT       | No       | 0 to 18446744073709551615 | The random seed used for creating the noise (default: 0).                                    |
| `first_frame_image` | IMAGE     | No       | -                         | Optional image to use as the first frame to generate a video.                                |
| `prompt_optimizer`  | BOOLEAN   | No       | -                         | Optimize prompt to improve generation quality when needed (default: True).                   |
| `duration`          | COMBO     | No       | `6`<br />`10`             | The length of the output video in seconds (default: 6).                                      |
| `resolution`        | COMBO     | No       | `"768P"`<br />`"1080P"`   | The dimensions of the video display. 1080p is 1920x1080, 768p is 1366x768 (default: "768P"). |

**Note:** When using the MiniMax-Hailuo-02 model with 1080P resolution, the duration is limited to 6 seconds.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `180e8d3c739e34094a12a719d3187378a4c360a5799a4b23029edf164d0c55a3`


# MinimaxImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxImageToVideoNode

Complete documentation for the MinimaxImageToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxImageToVideoNode/en.md)

Generates videos synchronously based on an image and prompt, and optional parameters using MiniMax's API. This node takes an input image and text description to create a video sequence, with various model options and configuration settings available.

## Inputs

| Parameter     | Data Type | Required | Range                                              | Description                                                       |
| ------------- | --------- | -------- | -------------------------------------------------- | ----------------------------------------------------------------- |
| `image`       | IMAGE     | Yes      | -                                                  | Image to use as first frame of video generation                   |
| `prompt_text` | STRING    | Yes      | -                                                  | Text prompt to guide the video generation (default: empty string) |
| `model`       | COMBO     | Yes      | "I2V-01-Director"<br />"I2V-01"<br />"I2V-01-live" | Model to use for video generation (default: "I2V-01")             |
| `seed`        | INT       | No       | 0 to 18446744073709551615                          | The random seed used for creating the noise (default: 0)          |

## Outputs

| Output Name | Data Type | Description                |
| ----------- | --------- | -------------------------- |
| `output`    | VIDEO     | The generated video output |

***

**Source fingerprint (SHA-256):** `8e5ae93cc214b541665f057c66d3203ef0ffdb10021fed2c05607df1b1a27844`


# MinimaxSubjectToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxSubjectToVideoNode

Complete documentation for the MinimaxSubjectToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxSubjectToVideoNode/en.md)

Generates a video synchronously based on a subject image and a text prompt using MiniMax's API. This node takes an image of a subject and a description to create a video that animates or features that subject according to the prompt.

## Inputs

| Parameter     | Data Type | Required | Range                     | Description                                                       |
| ------------- | --------- | -------- | ------------------------- | ----------------------------------------------------------------- |
| `subject`     | IMAGE     | Yes      | -                         | Image of subject to reference for video generation                |
| `prompt_text` | STRING    | Yes      | -                         | Text prompt to guide the video generation (default: empty string) |
| `model`       | COMBO     | No       | `"S2V-01"`                | Model to use for video generation (default: "S2V-01")             |
| `seed`        | INT       | No       | 0 to 18446744073709551615 | The random seed used for creating the noise (default: 0)          |

## Outputs

| Output Name | Data Type | Description                                                     |
| ----------- | --------- | --------------------------------------------------------------- |
| `output`    | VIDEO     | The generated video based on the input subject image and prompt |

***

**Source fingerprint (SHA-256):** `0dbdb1bb92850f4eac7c30017643a49ad932b2542bdf5c5c521ba875a0e341ca`


# MinimaxTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/MinimaxTextToVideoNode

Complete documentation for the MinimaxTextToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/MinimaxTextToVideoNode/en.md)

Generates videos synchronously based on a text prompt and optional parameters using MiniMax's API. This node creates video content from text descriptions by connecting to MiniMax's text-to-video service.

## Inputs

| Parameter     | Data Type | Required | Range                           | Description                                              |
| ------------- | --------- | -------- | ------------------------------- | -------------------------------------------------------- |
| `prompt_text` | STRING    | Yes      | -                               | Text prompt to guide the video generation                |
| `model`       | COMBO     | No       | "T2V-01"<br />"T2V-01-Director" | Model to use for video generation (default: "T2V-01")    |
| `seed`        | INT       | No       | 0 to 18446744073709551615       | The random seed used for creating the noise (default: 0) |

## Outputs

| Output Name | Data Type | Description                                   |
| ----------- | --------- | --------------------------------------------- |
| `output`    | VIDEO     | The generated video based on the input prompt |

***

**Source fingerprint (SHA-256):** `603b6407446f4f7c5ea9520126f960a52c498d16b59f66fe022fd439b59c39ba`


# Note - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Note

Complete documentation for the Note node in ComfyUI. Learn its inputs, outputs, parameters and usage.

Node to add annotations to a workflow.

## Inputs

## Outputs

The node doesn't have outputs.


# OpenAIVideoSora2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/OpenAIVideoSora2

Complete documentation for the OpenAIVideoSora2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/OpenAIVideoSora2/en.md)

The OpenAIVideoSora2 node generates videos using OpenAI's Sora models. It creates video content based on text prompts and optional input images, then returns the generated video output. The node supports different video durations and resolutions depending on the selected model.

**DEPRECATION NOTICE:** OpenAI will stop serving the Sora v2 API in September 2026. This node will be removed from ComfyUI at that time.

## Inputs

| Parameter  | Data Type | Required | Range                                                        | Description                                                                                                  |
| ---------- | --------- | -------- | ------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------ |
| `model`    | COMBO     | Yes      | "sora-2"<br />"sora-2-pro"                                   | The OpenAI Sora model to use for video generation (default: "sora-2")                                        |
| `prompt`   | STRING    | Yes      | -                                                            | Guiding text; may be empty if an input image is present (default: empty)                                     |
| `size`     | COMBO     | Yes      | "720x1280"<br />"1280x720"<br />"1024x1792"<br />"1792x1024" | The resolution for the generated video (default: "1280x720")                                                 |
| `duration` | COMBO     | Yes      | 4<br />8<br />12                                             | The duration of the generated video in seconds (default: 8)                                                  |
| `image`    | IMAGE     | No       | -                                                            | Optional input image for video generation                                                                    |
| `seed`     | INT       | No       | 0 to 2147483647                                              | Seed to determine if node should re-run; actual results are nondeterministic regardless of seed (default: 0) |

**Constraints and Limitations:**

* The "sora-2" model only supports "720x1280" and "1280x720" resolutions
* Only one input image is supported when using the image parameter
* Results are nondeterministic regardless of the seed value

## Outputs

| Output Name | Data Type | Description                |
| ----------- | --------- | -------------------------- |
| `output`    | VIDEO     | The generated video output |

***

**Source fingerprint (SHA-256):** `b632ef33ca5f01a7aed780a9eeea9b2fcbf4ab85ccb8f026e6175ceaafbda47b`


# PixverseImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseImageToVideoNode

Complete documentation for the PixverseImageToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseImageToVideoNode/en.md)

Generates videos based on an input image and text prompt. This node takes an image and creates an animated video by applying the specified motion and quality settings to transform the static image into a moving sequence.

## Inputs

| Parameter           | Data Type | Required | Range                                                                                                                                                                                                             | Description                                                                                  |
| ------------------- | --------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------- |
| `image`             | IMAGE     | Yes      | -                                                                                                                                                                                                                 | Input image to transform into video                                                          |
| `prompt`            | STRING    | Yes      | -                                                                                                                                                                                                                 | Prompt for the video generation                                                              |
| `quality`           | COMBO     | Yes      | `res_540p`<br />`res_1080p`                                                                                                                                                                                       | Video quality setting (default: res\_540p)                                                   |
| `duration_seconds`  | COMBO     | Yes      | `dur_2`<br />`dur_5`<br />`dur_10`                                                                                                                                                                                | Duration of the generated video in seconds                                                   |
| `motion_mode`       | COMBO     | Yes      | `normal`<br />`fast`<br />`slow`<br />`zoom_in`<br />`zoom_out`<br />`pan_left`<br />`pan_right`<br />`pan_up`<br />`pan_down`<br />`tilt_up`<br />`tilt_down`<br />`roll_clockwise`<br />`roll_counterclockwise` | Motion style applied to the video generation                                                 |
| `seed`              | INT       | Yes      | 0-2147483647                                                                                                                                                                                                      | Seed for video generation (default: 0)                                                       |
| `negative_prompt`   | STRING    | No       | -                                                                                                                                                                                                                 | An optional text description of undesired elements on an image                               |
| `pixverse_template` | CUSTOM    | No       | -                                                                                                                                                                                                                 | An optional template to influence style of generation, created by the PixVerse Template node |

**Note:** When using 1080p quality, the motion mode is automatically set to normal and duration is limited to 5 seconds. For durations other than 5 seconds, the motion mode is also automatically set to normal.

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `output`    | VIDEO     | Generated video based on the input image and parameters |

***

**Source fingerprint (SHA-256):** `4ca1624efc87e87de75c33aab850c84a0c8c786229930695fce479fe50455cb0`


# PixverseTemplateNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseTemplateNode

Complete documentation for the PixverseTemplateNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseTemplateNode/en.md)

The PixVerse Template node allows you to select from available templates for PixVerse video generation. It converts your selected template name into the corresponding template ID that the PixVerse API requires for video creation.

## Inputs

| Parameter  | Data Type | Required | Range                      | Description                                                                                                                         |
| ---------- | --------- | -------- | -------------------------- | ----------------------------------------------------------------------------------------------------------------------------------- |
| `template` | STRING    | Yes      | Multiple options available | The template to use for PixVerse video generation. The available options correspond to predefined templates in the PixVerse system. |

## Outputs

| Output Name         | Data Type | Description                                                                                                                  |
| ------------------- | --------- | ---------------------------------------------------------------------------------------------------------------------------- |
| `pixverse_template` | STRING    | The template ID corresponding to the selected template name, which can be used by other PixVerse nodes for video generation. |

***

**Source fingerprint (SHA-256):** `34daaf036f28b676b1048e8e4174ab34bf69328a94dd9e51696f6298936b4e84`


# PixverseTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseTextToVideoNode

Complete documentation for the PixverseTextToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseTextToVideoNode/en.md)

Generates videos based on a text prompt and various generation parameters. This node creates video content using the PixVerse API, allowing control over aspect ratio, quality, duration, motion style, and more.

## Inputs

| Parameter           | Data Type | Required | Range                               | Description                                                                                  |
| ------------------- | --------- | -------- | ----------------------------------- | -------------------------------------------------------------------------------------------- |
| `prompt`            | STRING    | Yes      | -                                   | Prompt for the video generation (default: "")                                                |
| `aspect_ratio`      | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"` | Aspect ratio for the generated video                                                         |
| `quality`           | COMBO     | Yes      | `"540p"`<br />`"1080p"`             | Video quality setting (default: "540p")                                                      |
| `duration_seconds`  | COMBO     | Yes      | `"5"`<br />`"10"`                   | Duration of the generated video in seconds                                                   |
| `motion_mode`       | COMBO     | Yes      | `"normal"`<br />`"fast"`            | Motion style for the video generation                                                        |
| `seed`              | INT       | Yes      | 0 to 2147483647                     | Seed for video generation (default: 0)                                                       |
| `negative_prompt`   | STRING    | No       | -                                   | An optional text description of undesired elements on an image (default: "")                 |
| `pixverse_template` | CUSTOM    | No       | -                                   | An optional template to influence style of generation, created by the PixVerse Template node |

**Note:** When using 1080p quality, the motion mode is automatically set to normal and duration is limited to 5 seconds. For non-5 second durations, the motion mode is also automatically set to normal.

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `output`    | VIDEO     | The generated video file |

***

**Source fingerprint (SHA-256):** `dd065e218e3e8ca3d70b58f4d8afdecc33094635663c87f79467452ca47881c7`


# PixverseTransitionVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PixverseTransitionVideoNode

Complete documentation for the PixverseTransitionVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PixverseTransitionVideoNode/en.md)

Generates a transition video between two input images using the PixVerse API. You provide a starting image and an ending image, and the node creates a smooth video that transitions from one to the other, guided by your text prompt and chosen settings.

## Inputs

| Parameter          | Data Type | Required | Range                                               | Description                                                                            |
| ------------------ | --------- | -------- | --------------------------------------------------- | -------------------------------------------------------------------------------------- |
| `first_frame`      | IMAGE     | Yes      | -                                                   | The starting image for the video transition                                            |
| `last_frame`       | IMAGE     | Yes      | -                                                   | The ending image for the video transition                                              |
| `prompt`           | STRING    | Yes      | -                                                   | Prompt for the video generation (default: empty string)                                |
| `quality`          | COMBO     | Yes      | `"360p"`<br />`"540p"`<br />`"720p"`<br />`"1080p"` | Video quality setting (default: `"540p"`)                                              |
| `duration_seconds` | COMBO     | Yes      | `5`<br />`8`                                        | Video duration in seconds                                                              |
| `motion_mode`      | COMBO     | Yes      | `"normal"`<br />`"fast"`                            | Motion style for the transition (default: `"normal"`)                                  |
| `seed`             | INT       | Yes      | 0 to 2147483647                                     | Seed for video generation (default: 0)                                                 |
| `negative_prompt`  | STRING    | No       | -                                                   | An optional text description of undesired elements on an image (default: empty string) |

**Note on parameter constraints:** When using 1080p quality, the motion mode is automatically set to `"normal"` and duration is limited to 5 seconds. For any non-5 second duration, the motion mode is also automatically set to `"normal"`.

## Outputs

| Output Name | Data Type | Description                    |
| ----------- | --------- | ------------------------------ |
| `output`    | VIDEO     | The generated transition video |

***

**Source fingerprint (SHA-256):** `941ba26ffdd5cc93d800066ccd75adc4ccdb9a1c9f93ae0ccd28a11ba5f3c567`


# PreviewAny - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PreviewAny

Complete documentation for the PreviewAny node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PreviewAny/en.md)

The PreviewAny node displays a preview of any input data type in text format. It accepts any data type as input and converts it to a readable string representation for viewing. The node automatically handles different data types including strings, numbers, booleans, and complex objects by attempting to serialize them to JSON format.

## Inputs

| Parameter | Data Type | Required | Range         | Description                                     |
| --------- | --------- | -------- | ------------- | ----------------------------------------------- |
| `source`  | ANY       | Yes      | Any data type | Accepts any input data type for preview display |

## Outputs

| Output Name       | Data Type | Description                                                                                                                              |
| ----------------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------- |
| `UI Text Display` | STRING    | Displays the input data converted to text format in the user interface. Also returns the text as a string output for further processing. |

***

**Source fingerprint (SHA-256):** `6011c39a31ef9a6786a1dff6e135edcf35def2f715b49301dd49a6467f859271`


# PrimitiveInt - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveInt

Complete documentation for the PrimitiveInt node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveInt/en.md)

The PrimitiveInt node provides a simple way to work with integer values in your workflow. It takes an integer input and outputs the same value, making it useful for passing integer parameters between nodes or setting specific numeric values for other operations.

## Inputs

| Parameter | Data Type | Required | Range                                       | Description                              |
| --------- | --------- | -------- | ------------------------------------------- | ---------------------------------------- |
| `value`   | INT       | Yes      | -9223372036854775807 to 9223372036854775807 | The integer value to output (default: 0) |

## Outputs

| Output Name | Data Type | Description                                      |
| ----------- | --------- | ------------------------------------------------ |
| `output`    | INT       | The input integer value passed through unchanged |

***

**Source fingerprint (SHA-256):** `79e0bad8e15fd660ee405ad34bf4f1cd76d2c37494f640be1ddf4d9fe8cbb9a0`


# PrimitiveString - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveString

Complete documentation for the PrimitiveString node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveString/en.md)

The String node provides a simple way to input and pass through text data in your workflow. It takes a text string as input and outputs the same string unchanged, making it useful for providing text inputs to other nodes that require string parameters.

## Inputs

| Parameter | Data Type | Required | Range    | Description                                   |
| --------- | --------- | -------- | -------- | --------------------------------------------- |
| `value`   | STRING    | Yes      | Any text | The text string to be passed through the node |

## Outputs

| Output Name | Data Type | Description                                     |
| ----------- | --------- | ----------------------------------------------- |
| `output`    | STRING    | The same text string that was provided as input |

***

**Source fingerprint (SHA-256):** `4e7b3a07572480f9138b7c77268581875b91599964382c11a8f5fbcd7f76f213`


# PrimitiveStringMultiline - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/PrimitiveStringMultiline

Complete documentation for the PrimitiveStringMultiline node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/PrimitiveStringMultiline/en.md)

The PrimitiveStringMultiline node provides a multiline text input field for entering and passing string values through your workflow. It accepts text input with multiple lines and outputs the same string value unchanged. This node is useful when you need to input longer text content or formatted text that spans multiple lines.

## Inputs

| Parameter | Data Type | Required | Range | Description                                       |
| --------- | --------- | -------- | ----- | ------------------------------------------------- |
| `value`   | STRING    | Yes      | N/A   | The text input value that can span multiple lines |

## Outputs

| Output Name | Data Type | Description                                      |
| ----------- | --------- | ------------------------------------------------ |
| `output`    | STRING    | The same string value that was provided as input |

***

**Source fingerprint (SHA-256):** `cc3e3f09f71f91721c338649699ffb8822de5109a2892e93eb9746ba3c9b22fb`


# Reroute - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Reroute

Complete documentation for the Reroute node in ComfyUI. Learn its inputs, outputs, parameters and usage.

Node Name: Reroute Node
Node Purpose: Mainly used to organize the logic of overly long connection lines in the ComfyUI workflow.

## How to Use Reroute Nodes

| Menu Options         | Description                                   |
| -------------------- | --------------------------------------------- |
| Show Type            | Display the node's type property              |
| Hide Type By Default | Hide the node's type property by default      |
| Set Vertical         | Set the node's wiring direction to vertical   |
| Set Horizontal       | Set the node's wiring direction to horizontal |

When your wiring logic is too long and complex, and you want to tidy up the interface, you can insert a `Reroute` node between two connection points. The input and output of this node are not type-restricted, and the default style is horizontal. You can change the wiring direction to vertical through the right-click menu.


# ResolutionSelector - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ResolutionSelector

Complete documentation for the ResolutionSelector node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ResolutionSelector/en.md)

The Resolution Selector node calculates the pixel width and height for an image based on a chosen aspect ratio and a target total resolution in megapixels. It is useful for generating consistent dimensions for other nodes, such as the Empty Latent Image node. The output dimensions are always rounded to the nearest multiple of 8.

## Inputs

| Parameter      | Data Type | Required | Range                                                                                                                                                                                                                 | Description                                                                           |
| -------------- | --------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- |
| `aspect_ratio` | COMBO     | Yes      | `"1:1 (Square)"`<br />`"3:2 (Photo)"`<br />`"4:3 (Standard)"`<br />`"16:9 (Widescreen)"`<br />`"21:9 (Ultrawide)"`<br />`"2:3 (Portrait Photo)"`<br />`"3:4 (Portrait Standard)"`<br />`"9:16 (Portrait Widescreen)"` | The aspect ratio for the output dimensions (default: `"1:1 (Square)"`).               |
| `megapixels`   | FLOAT     | Yes      | 0.1 - 16.0                                                                                                                                                                                                            | Target total megapixels. 1.0 MP ≈ 1024×1024 for a square aspect ratio (default: 1.0). |

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `width`     | INT       | The calculated width in pixels, which is a multiple of 8.  |
| `height`    | INT       | The calculated height in pixels, which is a multiple of 8. |

***

**Source fingerprint (SHA-256):** `7b27f0ffaaa1740a6371e53f10fa6a0ead3237ecec656b9148a2ecd11de7aaa5`


# RunwayFirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RunwayFirstLastFrameNode

Complete documentation for the RunwayFirstLastFrameNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RunwayFirstLastFrameNode/en.md)

The Runway First-Last-Frame to Video node generates videos by uploading first and last keyframes along with a text prompt. It creates smooth transitions between the provided start and end frames using Runway's Gen-3 model. This is particularly useful for complex transitions where the end frame differs significantly from the start frame.

## Inputs

| Parameter     | Data Type | Required | Range                          | Description                                                          |
| ------------- | --------- | -------- | ------------------------------ | -------------------------------------------------------------------- |
| `prompt`      | STRING    | Yes      | N/A                            | Text prompt for the generation (default: empty string)               |
| `start_frame` | IMAGE     | Yes      | N/A                            | Start frame to be used for the video                                 |
| `end_frame`   | IMAGE     | Yes      | N/A                            | End frame to be used for the video. Supported for gen3a\_turbo only. |
| `duration`    | COMBO     | Yes      | `"5"`<br />`"10"`              | Video duration in seconds (default: "5")                             |
| `ratio`       | COMBO     | Yes      | `"768:1280"`<br />`"1280:768"` | Aspect ratio for the generated video (default: "768:1280")           |
| `seed`        | INT       | No       | 0 to 4294967295                | Random seed for generation. Set to 0 for random seed (default: 0).   |

**Parameter Constraints:**

* The `prompt` must contain at least 1 character
* Both `start_frame` and `end_frame` must have maximum dimensions of 7999x7999 pixels
* Both `start_frame` and `end_frame` must have aspect ratios between 0.5 and 2.0
* The `end_frame` parameter is only supported when using the gen3a\_turbo model

## Outputs

| Output Name | Data Type | Description                                                        |
| ----------- | --------- | ------------------------------------------------------------------ |
| `output`    | VIDEO     | The generated video transitioning between the start and end frames |

***

**Source fingerprint (SHA-256):** `a2d4839bf30bff3e3199a18129eb32c8495b8ea0c9ce209e9b3d00574de35399`


# RunwayImageToVideoNodeGen3a - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RunwayImageToVideoNodeGen3a

Complete documentation for the RunwayImageToVideoNodeGen3a node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RunwayImageToVideoNodeGen3a/en.md)

The Runway Image to Video (Gen3a Turbo) node generates a video from a single starting frame using Runway's Gen3a Turbo model. It takes a text prompt and an initial image frame, then creates a video sequence based on the specified duration and aspect ratio. This node connects to Runway's API to process the generation remotely.

## Inputs

| Parameter     | Data Type | Required | Range                          | Description                                               |
| ------------- | --------- | -------- | ------------------------------ | --------------------------------------------------------- |
| `prompt`      | STRING    | Yes      | N/A                            | Text prompt for the generation (default: "")              |
| `start_frame` | IMAGE     | Yes      | N/A                            | Start frame to be used for the video                      |
| `duration`    | COMBO     | Yes      | `"5"`<br />`"10"`              | Video duration in seconds (default: "5")                  |
| `ratio`       | COMBO     | Yes      | `"768:1280"`<br />`"1280:768"` | Aspect ratio of the generated video (default: "768:1280") |
| `seed`        | INT       | No       | 0 to 4294967295                | Random seed for generation (default: 0)                   |

**Parameter Constraints:**

* The `start_frame` must have dimensions not exceeding 7999x7999 pixels.
* The `start_frame` must have an aspect ratio between 0.5 and 2.0.
* The `prompt` must contain at least one character (cannot be empty).

## Outputs

| Output Name | Data Type | Description                  |
| ----------- | --------- | ---------------------------- |
| `output`    | VIDEO     | The generated video sequence |

***

**Source fingerprint (SHA-256):** `ff88d2486746ab3ddf1b7a0c3184c54abd6bcb01e9743bc04c93e9c3a9e8d9ff`


# RunwayImageToVideoNodeGen4 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/RunwayImageToVideoNodeGen4

Complete documentation for the RunwayImageToVideoNodeGen4 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RunwayImageToVideoNodeGen4/en.md)

The Runway Image to Video (Gen4 Turbo) node generates a video from a single starting frame using Runway's Gen4 Turbo model. It takes a text prompt and an initial image frame, then creates a video sequence based on the provided duration and aspect ratio settings. The node handles uploading the starting frame to Runway's API and returns the generated video.

## Inputs

| Parameter     | Data Type | Required | Range                                                                                                 | Description                                                |
| ------------- | --------- | -------- | ----------------------------------------------------------------------------------------------------- | ---------------------------------------------------------- |
| `prompt`      | STRING    | Yes      | -                                                                                                     | Text prompt for the generation (default: empty string)     |
| `start_frame` | IMAGE     | Yes      | -                                                                                                     | Start frame to be used for the video                       |
| `duration`    | COMBO     | Yes      | `"5"`<br />`"10"`                                                                                     | Video duration in seconds (default: "5")                   |
| `ratio`       | COMBO     | Yes      | `"1280:720"`<br />`"720:1280"`<br />`"1104:832"`<br />`"832:1104"`<br />`"960:960"`<br />`"1584:672"` | Aspect ratio for the generated video (default: "1280:720") |
| `seed`        | INT       | No       | 0 to 4294967295                                                                                       | Random seed for generation (default: 0)                    |

**Parameter Constraints:**

* The `start_frame` image must have dimensions not exceeding 7999x7999 pixels
* The `start_frame` image must have an aspect ratio between 0.5 and 2.0
* The `prompt` must contain at least one character

## Outputs

| Output Name | Data Type | Description                                             |
| ----------- | --------- | ------------------------------------------------------- |
| `output`    | VIDEO     | The generated video based on the input frame and prompt |

***

**Source fingerprint (SHA-256):** `0b5a2c351277b8c2247b4625fd030dd6f4de8dafd92f59a969575db1ba2f7fe9`


# TerminalLog - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TerminalLog

Complete documentation for the TerminalLog node in ComfyUI. Learn its inputs, outputs, parameters and usage.

Terminal Log (Manager) node is primarily used to display the running information of ComfyUI in the terminal within the ComfyUI interface. To use it, you need to set the `mode` to **logging** mode. This will allow it to record corresponding log information during the image generation task. If the `mode` is set to **stop** mode, it will not record log information.
When you access and use ComfyUI via remote connections or local area network connections, Terminal Log (Manager) node becomes particularly useful. It allows you to directly view error messages from the CMD within the ComfyUI interface, making it easier to understand the current status of ComfyUI's operation.


# TopazVideoEnhance - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TopazVideoEnhance

Complete documentation for the TopazVideoEnhance node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TopazVideoEnhance/en.md)

The Topaz Video Enhance node uses an external API to improve video quality. It can upscale video resolution, increase frame rate through interpolation, and apply compression. The node processes an input MP4 video and returns an enhanced version based on the selected settings.

## Inputs

| Parameter                           | Data Type | Required | Range                                                                                         | Description                                                                                                                         |
| ----------------------------------- | --------- | -------- | --------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------- |
| `video`                             | VIDEO     | Yes      | -                                                                                             | The input video file to be enhanced.                                                                                                |
| `upscaler_enabled`                  | BOOLEAN   | Yes      | -                                                                                             | Enables or disables the video upscaling feature (default: True).                                                                    |
| `upscaler_model`                    | COMBO     | Yes      | `"Starlight (Astra) Fast"`<br />`"Starlight (Astra) Creative"`<br />`"Starlight Precise 2.5"` | The AI model used for upscaling the video.                                                                                          |
| `upscaler_resolution`               | COMBO     | Yes      | `"FullHD (1080p)"`<br />`"4K (2160p)"`                                                        | The target resolution for the upscaled video.                                                                                       |
| `upscaler_creativity`               | COMBO     | No       | `"low"`<br />`"middle"`<br />`"high"`                                                         | Creativity level (applies only to Starlight (Astra) Creative). (default: "low")                                                     |
| `interpolation_enabled`             | BOOLEAN   | No       | -                                                                                             | Enables or disables the frame interpolation feature (default: False).                                                               |
| `interpolation_model`               | COMBO     | No       | `"apo-8"`                                                                                     | The model used for frame interpolation (default: "apo-8").                                                                          |
| `interpolation_slowmo`              | INT       | No       | 1 to 16                                                                                       | Slow-motion factor applied to the input video. For example, 2 makes the output twice as slow and doubles the duration. (default: 1) |
| `interpolation_frame_rate`          | INT       | No       | 15 to 240                                                                                     | Output frame rate. (default: 60)                                                                                                    |
| `interpolation_duplicate`           | BOOLEAN   | No       | -                                                                                             | Analyze the input for duplicate frames and remove them. (default: False)                                                            |
| `interpolation_duplicate_threshold` | FLOAT     | No       | 0.001 to 0.1                                                                                  | Detection sensitivity for duplicate frames. (default: 0.01)                                                                         |
| `dynamic_compression_level`         | COMBO     | No       | `"Low"`<br />`"Mid"`<br />`"High"`                                                            | CQP level. (default: "Low")                                                                                                         |

**Note:** At least one enhancement feature must be enabled. The node will raise an error if both `upscaler_enabled` and `interpolation_enabled` are set to `False`. The input video must be in MP4 format.

## Outputs

| Output Name | Data Type | Description                     |
| ----------- | --------- | ------------------------------- |
| `video`     | VIDEO     | The enhanced output video file. |

***

**Source fingerprint (SHA-256):** `ef2d1e62c0000f4d9a99014317db2f1c4e0b8a77334024cf614ec0376058a2f7`


# TopazVideoEnhanceV2 - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/TopazVideoEnhanceV2

Complete documentation for the TopazVideoEnhanceV2 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TopazVideoEnhanceV2/en.md)

# Topaz Video Enhance V2

The **Topaz Video Enhance V2** node allows you to upscale and enhance video using Topaz Labs' AI models. It can increase resolution, adjust frame rate through interpolation, and apply creative or realistic enhancements to breathe new life into your video footage.

## Inputs

| Parameter                                               | Data Type     | Required    | Range                                                                                                                            | Description                                                                                                                                                                                               |
| ------------------------------------------------------- | ------------- | ----------- | -------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `video`                                                 | VIDEO         | Yes         | -                                                                                                                                | The input video to be processed. Must be in MP4 container format.                                                                                                                                         |
| `upscaler_model`                                        | COMBO         | Yes         | `"Astra 2"`<br />`"Starlight (Astra) Fast"`<br />`"Starlight (Astra) Creative"`<br />`"Starlight Precise 2.5"`<br />`"Disabled"` | The AI model used for upscaling the video. Selecting "Disabled" means no upscaling will be applied.                                                                                                       |
| `upscaler_model.upscaler_resolution`                    | COMBO         | Conditional | `"FullHD (1080p)"`<br />`"4K (2160p)"`                                                                                           | The target output resolution for the upscaler. This parameter is required when an upscaler model is selected (not "Disabled").                                                                            |
| `upscaler_model.creativity`                             | FLOAT / COMBO | Conditional | Astra 2: 0.0 to 1.0 (step 0.1)<br />Starlight Creative: `"low"`<br />`"middle"`<br />`"high"`                                    | Creative strength of the upscale. Available only for "Astra 2" and "Starlight (Astra) Creative" models. For Astra 2, it's a slider (default: 0.5). For Starlight Creative, it's a combo (default: "low"). |
| `upscaler_model.prompt`                                 | STRING        | No          | -                                                                                                                                | Optional descriptive (not instructive) scene prompt. Only available for the "Astra 2" model. Capped at 450 input frames (\~15s @ 30fps) when set. Default: empty.                                         |
| `upscaler_model.sharp`                                  | FLOAT         | No          | 0.0 to 1.0 (step 0.01)                                                                                                           | Pre-enhance sharpness: 0.0=Gaussian blur, 0.5=passthrough (default), 1.0=USM sharpening. Only available for the "Astra 2" model. Default: 0.5.                                                            |
| `upscaler_model.realism`                                | FLOAT         | No          | 0.0 to 1.0 (step 0.01)                                                                                                           | Pulls output toward photographic realism. Leave at 0 for the model default. Only available for the "Astra 2" model. Default: 0.0.                                                                         |
| `interpolation_model`                                   | COMBO         | Yes         | `"Disabled"`<br />`"apo-8"`                                                                                                      | The AI model used for frame interpolation. Selecting "Disabled" means no interpolation will be applied.                                                                                                   |
| `interpolation_model.interpolation_frame_rate`          | INT           | Conditional | 15 to 240                                                                                                                        | Output frame rate. Required when interpolation model is "apo-8". Default: 60.                                                                                                                             |
| `interpolation_model.interpolation_slowmo`              | INT           | No          | 1 to 16                                                                                                                          | Slow-motion factor applied to the input video. For example, 2 makes the output twice as slow and doubles the duration. Default: 1.                                                                        |
| `interpolation_model.interpolation_duplicate`           | BOOLEAN       | No          | True/False                                                                                                                       | Analyze the input for duplicate frames and remove them. Default: False.                                                                                                                                   |
| `interpolation_model.interpolation_duplicate_threshold` | FLOAT         | No          | 0.001 to 0.1 (step 0.001)                                                                                                        | Detection sensitivity for duplicate frames. Default: 0.01.                                                                                                                                                |
| `dynamic_compression_level`                             | COMBO         | No          | `"Low"`<br />`"Mid"`<br />`"High"`                                                                                               | CQP level for video compression. Default: "Low".                                                                                                                                                          |

**Important Constraints:**

* At least one of `upscaler_model` or `interpolation_model` must be enabled (not "Disabled"), otherwise an error is raised.
* The input video must be in MP4 container format.
* The "Astra 2" model with a prompt is limited to 450 input frames (\~15 seconds at 30fps). Without a prompt, it is limited to 9000 input frames.
* When `upscaler_model` is not "Disabled", the `upscaler_resolution` sub-parameter is required.
* When `interpolation_model` is not "Disabled", the `interpolation_frame_rate` sub-parameter is required.

## Outputs

| Output Name | Data Type | Description                                                                                   |
| ----------- | --------- | --------------------------------------------------------------------------------------------- |
| `video`     | VIDEO     | The enhanced video output after applying the selected upscaling and/or interpolation filters. |

***

**Source fingerprint (SHA-256):** `3b3df144ecd7de6e0c141cffa30fc7b303e0edc991e714c2f0aaf0e4be903166`


# Veo3FirstLastFrameNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Veo3FirstLastFrameNode

Complete documentation for the Veo3FirstLastFrameNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Veo3FirstLastFrameNode/en.md)

The Veo3FirstLastFrameNode uses Google's Veo 3 model to generate a video based on a text prompt, with a provided first and last frame that define the start and end of the video sequence.

## Inputs

| Parameter         | Data Type | Required | Range                                                                     | Description                                                                       |
| ----------------- | --------- | -------- | ------------------------------------------------------------------------- | --------------------------------------------------------------------------------- |
| `prompt`          | STRING    | Yes      | N/A                                                                       | Text description of the video (default: empty string).                            |
| `negative_prompt` | STRING    | No       | N/A                                                                       | Negative text prompt to guide what to avoid in the video (default: empty string). |
| `resolution`      | COMBO     | Yes      | `"720p"`<br />`"1080p"`<br />`"4k"`                                       | The resolution of the output video.                                               |
| `aspect_ratio`    | COMBO     | No       | `"16:9"`<br />`"9:16"`                                                    | Aspect ratio of the output video (default: "16:9").                               |
| `duration`        | INT       | No       | 4 to 8                                                                    | Duration of the output video in seconds (default: 8, step: 2).                    |
| `seed`            | INT       | No       | 0 to 4294967295                                                           | Seed for video generation (default: 0).                                           |
| `first_frame`     | IMAGE     | Yes      | N/A                                                                       | The start frame for the video.                                                    |
| `last_frame`      | IMAGE     | Yes      | N/A                                                                       | The end frame for the video.                                                      |
| `model`           | COMBO     | No       | `"veo-3.1-generate"`<br />`"veo-3.1-fast-generate"`<br />`"veo-3.1-lite"` | The specific Veo 3 model to use for generation (default: "veo-3.1-generate").     |
| `generate_audio`  | BOOLEAN   | No       | N/A                                                                       | Generate audio for the video (default: True).                                     |

**Note:** The `veo-3.1-lite` model does not support 4K resolution. If you select `veo-3.1-lite` and `4k` resolution, an error will occur.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `63d2cf6b636bff6e8bc4efc8b795cb63f6cd775e040323e290986266029109b3`


# Veo3VideoGenerationNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Veo3VideoGenerationNode

Complete documentation for the Veo3VideoGenerationNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Veo3VideoGenerationNode/en.md)

Generates videos from text prompts using Google's Veo 3 API. This node supports multiple Veo 3 models, including fast and lite variants, and allows you to specify video resolution, duration, and audio generation.

## Inputs

| Parameter           | Data Type | Required | Range                                                                                                                            | Description                                                                                         |
| ------------------- | --------- | -------- | -------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------- |
| `prompt`            | STRING    | Yes      | -                                                                                                                                | Text description of the video (default: "")                                                         |
| `aspect_ratio`      | COMBO     | Yes      | "16:9"<br />"9:16"                                                                                                               | Aspect ratio of the output video (default: "16:9")                                                  |
| `resolution`        | COMBO     | No       | "720p"<br />"1080p"<br />"4k"                                                                                                    | Output video resolution. 4K is not available for veo-3.1-lite and veo-3.0 models. (default: "720p") |
| `negative_prompt`   | STRING    | No       | -                                                                                                                                | Negative text prompt to guide what to avoid in the video (default: "")                              |
| `duration_seconds`  | INT       | No       | 4-8                                                                                                                              | Duration of the output video in seconds, in steps of 2 (default: 8)                                 |
| `enhance_prompt`    | BOOLEAN   | No       | -                                                                                                                                | This parameter is deprecated and ignored. (default: True)                                           |
| `person_generation` | COMBO     | No       | "ALLOW"<br />"BLOCK"                                                                                                             | Whether to allow generating people in the video (default: "ALLOW")                                  |
| `seed`              | INT       | No       | 0-4294967295                                                                                                                     | Seed for video generation (0 for random) (default: 0)                                               |
| `image`             | IMAGE     | No       | -                                                                                                                                | Optional reference image to guide video generation                                                  |
| `model`             | COMBO     | No       | "veo-3.1-generate"<br />"veo-3.1-fast-generate"<br />"veo-3.1-lite"<br />"veo-3.0-generate-001"<br />"veo-3.0-fast-generate-001" | Veo 3 model to use for video generation (default: "veo-3.0-generate-001")                           |
| `generate_audio`    | BOOLEAN   | No       | -                                                                                                                                | Generate audio for the video. Supported by all Veo 3 models. (default: False)                       |

**Note:** The `enhance_prompt` parameter is deprecated and its value is ignored. The node always enhances the prompt internally. Additionally, the `resolution` parameter is only applied when using a veo-3.1 model; it is ignored for veo-3.0 models. If you select "4k" resolution with a veo-3.1-lite or veo-3.0 model, the node will raise an error.

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `output`    | VIDEO     | The generated video file |

***

**Source fingerprint (SHA-256):** `d19071ba853a846c797bc88d4a803357563f144ea9071fc79fc4203ea40f1a81`


# VeoVideoGenerationNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/VeoVideoGenerationNode

Complete documentation for the VeoVideoGenerationNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/VeoVideoGenerationNode/en.md)

Generates videos from text prompts using Google's Veo API. This node can create videos from text descriptions and optional image inputs, with control over parameters like aspect ratio, duration, and more.

## Inputs

| Parameter           | Data Type | Required | Range                                                                                                                                                        | Description                                                                                        |
| ------------------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------- |
| `prompt`            | STRING    | Yes      | -                                                                                                                                                            | Text description of the video (default: empty)                                                     |
| `aspect_ratio`      | COMBO     | Yes      | "16:9"<br />"9:16"                                                                                                                                           | Aspect ratio of the output video (default: "16:9")                                                 |
| `negative_prompt`   | STRING    | No       | -                                                                                                                                                            | Negative text prompt to guide what to avoid in the video (default: empty)                          |
| `duration_seconds`  | INT       | No       | 5-8                                                                                                                                                          | Duration of the output video in seconds (default: 5)                                               |
| `enhance_prompt`    | BOOLEAN   | No       | -                                                                                                                                                            | Whether to enhance the prompt with AI assistance (default: True). This is an advanced parameter.   |
| `person_generation` | COMBO     | No       | "ALLOW"<br />"BLOCK"                                                                                                                                         | Whether to allow generating people in the video (default: "ALLOW"). This is an advanced parameter. |
| `seed`              | INT       | No       | 0-4294967295                                                                                                                                                 | Seed for video generation (0 for random) (default: 0). This is an advanced parameter.              |
| `image`             | IMAGE     | No       | -                                                                                                                                                            | Optional reference image to guide video generation                                                 |
| `model`             | COMBO     | No       | "veo-2.0-generate-001"<br />"veo-3.1-generate"<br />"veo-3.1-fast-generate"<br />"veo-3.1-lite"<br />"veo-3.0-generate-001"<br />"veo-3.0-fast-generate-001" | Veo model to use for video generation (default: "veo-2.0-generate-001")                            |

**Note:** The `generate_audio` parameter is only available for Veo 3.0 and Veo 3.1 models and is automatically handled by the node based on the selected model. When using Veo 3.0 or Veo 3.1 models, the `enhance_prompt` parameter is forced to True.

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `output`    | VIDEO     | The generated video file |

***

**Source fingerprint (SHA-256):** `abb403ceddb16511988e4ac98ae126c7d6de3bf2f25789189fc05d72f475ca95`


# Vidu2ImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu2ImageToVideoNode

Complete documentation for the Vidu2ImageToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu2ImageToVideoNode/en.md)

The Vidu2 Image-to-Video Generation node creates a video sequence starting from a single input image. It uses a specified Vidu2 model to animate the scene based on an optional text prompt, controlling the video's length, resolution, and the intensity of motion.

## Inputs

| Parameter            | Data Type | Required | Range                                                         | Description                                                                                               |
| -------------------- | --------- | -------- | ------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- |
| `model`              | COMBO     | Yes      | `"viduq2-pro-fast"`<br />`"viduq2-pro"`<br />`"viduq2-turbo"` | The Vidu2 model to use for video generation. Different models offer varying speed and quality trade-offs. |
| `image`              | IMAGE     | Yes      | -                                                             | An image to be used as the start frame of the generated video. Only one image is allowed.                 |
| `prompt`             | STRING    | No       | -                                                             | An optional text prompt for video generation (max 2000 characters). Default is an empty string.           |
| `duration`           | INT       | Yes      | 1 to 10                                                       | The length of the generated video in seconds. Default is 5.                                               |
| `seed`               | INT       | No       | 0 to 2147483647                                               | A seed value for random number generation to ensure reproducible results. Default is 1.                   |
| `resolution`         | COMBO     | Yes      | `"720p"`<br />`"1080p"`                                       | The output resolution of the generated video. This parameter is advanced.                                 |
| `movement_amplitude` | COMBO     | Yes      | `"auto"`<br />`"small"`<br />`"medium"`<br />`"large"`        | The movement amplitude of objects in the frame. This parameter is advanced.                               |

**Constraints:**

* The `image` input must contain exactly one image.
* The input image's aspect ratio must be between 1:4 and 4:1.
* The `prompt` text is limited to a maximum of 2000 characters.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `5311b64380bf089b846d5ac0c32330e021b79754cf2f3cac41f71ca1da3ffdda`


# Vidu2ReferenceVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu2ReferenceVideoNode

Complete documentation for the Vidu2ReferenceVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu2ReferenceVideoNode/en.md)

The Vidu2 Reference-to-Video Generation node creates a video from a text prompt and multiple reference images. You can define up to seven subjects, each with its own set of reference images, and reference them in the prompt using `@subject{subject_id}`. The node generates a video with configurable duration, aspect ratio, and movement.

## Inputs

| Parameter            | Data Type | Required | Range                                                         | Description                                                                                                                                                                        |
| -------------------- | --------- | -------- | ------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`              | COMBO     | Yes      | `"viduq2"`                                                    | The AI model to use for video generation.                                                                                                                                          |
| `subjects`           | AUTOGROW  | Yes      | N/A                                                           | For each subject, provide up to 3 reference images (7 images total across all subjects). Reference them in prompts via `@subject{subject_id}`.                                     |
| `prompt`             | STRING    | Yes      | N/A                                                           | The text description used to guide the video generation. When the `audio` parameter is enabled, the video will include generated speech and background music based on this prompt. |
| `audio`              | BOOLEAN   | No       | N/A                                                           | When enabled, the video will contain generated speech and background music based on the prompt (default: `False`).                                                                 |
| `duration`           | INT       | No       | 1 to 10                                                       | The length of the generated video in seconds (default: `5`).                                                                                                                       |
| `seed`               | INT       | No       | 0 to 2147483647                                               | A number used to control the randomness of the generation for reproducible results (default: `1`).                                                                                 |
| `aspect_ratio`       | COMBO     | No       | `"16:9"`<br />`"9:16"`<br />`"4:3"`<br />`"3:4"`<br />`"1:1"` | The shape of the video frame.                                                                                                                                                      |
| `resolution`         | COMBO     | No       | `"720p"`<br />`"1080p"`                                       | The pixel resolution of the output video (default: `"720p"`).                                                                                                                      |
| `movement_amplitude` | COMBO     | No       | `"auto"`<br />`"small"`<br />`"medium"`<br />`"large"`        | Controls the movement amplitude of objects in the frame (default: `"auto"`).                                                                                                       |

**Constraints:**

* The `prompt` must be between 1 and 2000 characters long.
* You can define multiple subjects, but the total number of reference images across all subjects must not exceed 7.
* Each individual subject can have a maximum of 3 reference images.
* Each reference image must have a width-to-height ratio between 1:4 and 4:1.
* Each reference image must be at least 128 pixels in both width and height.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `73366d1ae9d64428141a7f9de3f9632f12e41918f85771a9a41619564c88ed38`


# Vidu2StartEndToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu2StartEndToVideoNode

Complete documentation for the Vidu2StartEndToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu2StartEndToVideoNode/en.md)

This node generates a video by interpolating between a provided start frame and an end frame, guided by a text prompt. It uses a specified Vidu model to create a smooth transition between the two images over a set duration.

## Inputs

| Parameter            | Data Type | Required | Range                                                         | Description                                                                              |
| -------------------- | --------- | -------- | ------------------------------------------------------------- | ---------------------------------------------------------------------------------------- |
| `model`              | COMBO     | Yes      | `"viduq2-pro-fast"`<br />`"viduq2-pro"`<br />`"viduq2-turbo"` | The Vidu model to use for video generation.                                              |
| `first_frame`        | IMAGE     | Yes      | -                                                             | The starting image for the video sequence. Only a single image is allowed.               |
| `end_frame`          | IMAGE     | Yes      | -                                                             | The ending image for the video sequence. Only a single image is allowed.                 |
| `prompt`             | STRING    | Yes      | -                                                             | A text description guiding the video generation (maximum 2000 characters).               |
| `duration`           | INT       | No       | 2 to 8                                                        | The length of the generated video in seconds (default: 5).                               |
| `seed`               | INT       | No       | 0 to 2147483647                                               | A number used to initialize the random generation for reproducible results (default: 1). |
| `resolution`         | COMBO     | No       | `"720p"`<br />`"1080p"`                                       | The output resolution of the generated video.                                            |
| `movement_amplitude` | COMBO     | No       | `"auto"`<br />`"small"`<br />`"medium"`<br />`"large"`        | The movement amplitude of objects in the frame.                                          |

**Note:** The `first_frame` and `end_frame` images must have similar aspect ratios. The node will validate that their aspect ratios are within a relative range of 0.8 to 1.25.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `4d4caf53387132c420fe0bb0eea581e6784bdc59243607c6440d6548f70f859b`


# Vidu2TextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu2TextToVideoNode

Complete documentation for the Vidu2TextToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu2TextToVideoNode/en.md)

The Vidu2 Text-to-Video Generation node creates a video from a text description. It connects to an external API to generate video content based on your prompt, allowing you to control the video's length, visual style, and format.

## Inputs

| Parameter          | Data Type | Required | Range                                                         | Description                                                                                                                                       |
| ------------------ | --------- | -------- | ------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`            | COMBO     | Yes      | `"viduq2"`                                                    | The AI model to use for video generation. Currently, only one model is available.                                                                 |
| `prompt`           | STRING    | Yes      | -                                                             | A textual description for video generation, with a maximum length of 2000 characters.                                                             |
| `duration`         | INT       | No       | 1 to 10                                                       | The length of the generated video in seconds. The value can be adjusted using a slider (default: 5).                                              |
| `seed`             | INT       | No       | 0 to 2147483647                                               | A number used to control the randomness of the generation, allowing for reproducible results. It can be controlled after generation (default: 1). |
| `aspect_ratio`     | COMBO     | No       | `"16:9"`<br />`"9:16"`<br />`"3:4"`<br />`"4:3"`<br />`"1:1"` | The proportional relationship between the video's width and height.                                                                               |
| `resolution`       | COMBO     | No       | `"720p"`<br />`"1080p"`                                       | The pixel dimensions of the generated video. This is an advanced parameter.                                                                       |
| `background_music` | BOOLEAN   | No       | -                                                             | Whether to add background music to the generated video (default: False). This is an advanced parameter.                                           |

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `eec93de5d781474f919001a4d78525d80478852424506fae245f445d1ef3b0ee`


# Vidu3ImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu3ImageToVideoNode

Complete documentation for the Vidu3ImageToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu3ImageToVideoNode/en.md)

The Vidu Q3 Image-to-Video Generation node creates a video sequence starting from an input image. It uses a Vidu Q3 model to animate the image, optionally guided by a text prompt, and outputs a video file.

## Inputs

| Parameter          | Data Type | Required | Range                                                 | Description                                                                                     |
| ------------------ | --------- | -------- | ----------------------------------------------------- | ----------------------------------------------------------------------------------------------- |
| `model`            | COMBO     | Yes      | `"viduq3-pro"`<br />`"viduq3-turbo"`                  | Model to use for video generation.                                                              |
| `model.resolution` | COMBO     | Yes      | `"720p"`<br />`"1080p"`<br />`"2K"` (viduq3-pro only) | Resolution of the output video. The available options depend on the selected model.             |
| `model.duration`   | INT       | Yes      | 1 to 16                                               | Duration of the output video in seconds (default: 5).                                           |
| `model.audio`      | BOOLEAN   | Yes      | `True` / `False`                                      | When enabled, outputs video with sound (including dialogue and sound effects) (default: False). |
| `image`            | IMAGE     | Yes      | -                                                     | An image to be used as the start frame of the generated video.                                  |
| `prompt`           | STRING    | No       | -                                                     | An optional text prompt for video generation (max 2000 characters) (default: empty).            |
| `seed`             | INT       | No       | 0 to 2147483647                                       | A seed value for controlling the randomness of the generation (default: 1).                     |

**Note:** The `image` must have an aspect ratio between 1:4 and 4:1 (portrait to landscape). The `prompt` is optional but cannot exceed 2000 characters. The `model.resolution` options depend on the selected `model`: `"viduq3-pro"` supports `"720p"`, `"1080p"`, and `"2K"`; `"viduq3-turbo"` supports `"720p"` and `"1080p"`.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `5081dcbad3e9203c7a1b5ddc0d041d51e1961a2e0a0672c2e14cba2f839f562d`


# Vidu3StartEndToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu3StartEndToVideoNode

Complete documentation for the Vidu3StartEndToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu3StartEndToVideoNode/en.md)

This node generates a video by interpolating between a provided start frame and an end frame, guided by a text prompt. It uses the Vidu Q3 model to create a seamless transition between the two images, producing a video of a specified duration and resolution.

## Inputs

| Parameter          | Data Type | Required | Range                                | Description                                                                                                                                           |
| ------------------ | --------- | -------- | ------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`            | COMBO     | Yes      | `"viduq3-pro"`<br />`"viduq3-turbo"` | The model to use for video generation. Selecting an option reveals additional configuration parameters for `resolution`, `duration`, and `audio`.     |
| `model.resolution` | COMBO     | Yes      | `"720p"`<br />`"1080p"`              | Resolution of the output video. This parameter is revealed after selecting a `model`.                                                                 |
| `model.duration`   | INT       | Yes      | 1 to 16                              | Duration of the output video in seconds (default: 5). This parameter is revealed after selecting a `model`.                                           |
| `model.audio`      | BOOLEAN   | Yes      | `True` / `False`                     | When enabled, outputs video with sound (including dialogue and sound effects) (default: False). This parameter is revealed after selecting a `model`. |
| `first_frame`      | IMAGE     | Yes      | -                                    | The starting image for the video sequence.                                                                                                            |
| `end_frame`        | IMAGE     | Yes      | -                                    | The ending image for the video sequence.                                                                                                              |
| `prompt`           | STRING    | Yes      | -                                    | A text description guiding the video generation (maximum 2000 characters).                                                                            |
| `seed`             | INT       | No       | 0 to 2147483647                      | A seed value for controlling the randomness of the generation (default: 1).                                                                           |

**Note:** The `first_frame` and `end_frame` images should have similar aspect ratios for optimal results. The aspect ratio of the two images must be within 80% to 125% of each other (a relative closeness between 0.8 and 1.25).

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `video`     | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `a3a1befd61a011ccc9912972d07506c2e851ca94cda3f83fcc1faa8a1dc3905c`


# Vidu3TextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Vidu3TextToVideoNode

Complete documentation for the Vidu3TextToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Vidu3TextToVideoNode/en.md)

The Vidu Q3 Text-to-Video Generation node creates a video from a text description. It uses the Vidu Q3 Pro or Q3 Turbo model to generate video content based on your prompt, allowing you to control the video's length, resolution, aspect ratio, and whether it includes audio.

## Inputs

| Parameter            | Data Type | Required | Range                                                         | Description                                                                                                                                            |
| -------------------- | --------- | -------- | ------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `model`              | COMBO     | Yes      | `"viduq3-pro"`<br />`"viduq3-turbo"`                          | Model to use for video generation. Selecting a model reveals additional configuration parameters for aspect ratio, resolution, duration, and audio.    |
| `model.aspect_ratio` | COMBO     | Yes\*    | `"16:9"`<br />`"9:16"`<br />`"3:4"`<br />`"4:3"`<br />`"1:1"` | The aspect ratio of the output video. This parameter is revealed when a `model` is selected.                                                           |
| `model.resolution`   | COMBO     | Yes\*    | `"720p"`<br />`"1080p"`                                       | Resolution of the output video. This parameter is revealed when a `model` is selected.                                                                 |
| `model.duration`     | INT       | Yes\*    | 1 to 16                                                       | Duration of the output video in seconds (default: 5). This parameter is revealed when a `model` is selected.                                           |
| `model.audio`        | BOOLEAN   | Yes\*    | True/False                                                    | When enabled, outputs video with sound (including dialogue and sound effects) (default: False). This parameter is revealed when a `model` is selected. |
| `prompt`             | STRING    | Yes      | N/A                                                           | A textual description for video generation, with a maximum length of 2000 characters.                                                                  |
| `seed`               | INT       | No       | 0 to 2147483647                                               | A seed value for controlling the randomness of the generation (default: 1).                                                                            |

\*Note: The parameters `aspect_ratio`, `resolution`, `duration`, and `audio` are required once a `model` is selected, as they are part of its configuration.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `video`     | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `d135d453159d113f9198b7510838c5ce5feefbf3cb7b318a55df95e6d26aa7a9`


# ViduExtendVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduExtendVideoNode

Complete documentation for the ViduExtendVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduExtendVideoNode/en.md)

The ViduExtendVideoNode generates additional frames to extend the length of an existing video. It uses a specified AI model to create a seamless continuation based on the source video and an optional text prompt.

## Inputs

| Parameter          | Data Type | Required | Range                                | Description                                                                                                                                                                        |
| ------------------ | --------- | -------- | ------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`            | COMBO     | Yes      | `"viduq2-pro"`<br />`"viduq2-turbo"` | The AI model to use for video extension. Selecting a model reveals its specific duration and resolution settings.                                                                  |
| `model.duration`   | INT       | Yes      | 1 to 7                               | The duration of the extended video in seconds (default: 4). This setting appears after selecting a model.                                                                          |
| `model.resolution` | COMBO     | Yes      | `"720p"`<br />`"1080p"`              | The resolution of the output video. This setting appears after selecting a model.                                                                                                  |
| `video`            | VIDEO     | Yes      | -                                    | The source video to extend.                                                                                                                                                        |
| `prompt`           | STRING    | No       | -                                    | An optional text prompt to guide the content of the extended video (max 2000 characters, default: empty).                                                                          |
| `seed`             | INT       | No       | 0 to 2147483647                      | A seed value for controlling the randomness of the generation (default: 1).                                                                                                        |
| `end_frame`        | IMAGE     | No       | -                                    | An optional image to use as the target end frame for the extension. If provided, its aspect ratio must be between 1:4 and 4:1, and its dimensions must be at least 128x128 pixels. |

**Note:** The source `video` must have a duration between 4 and 55 seconds.

## Outputs

| Output Name | Data Type | Description                                                     |
| ----------- | --------- | --------------------------------------------------------------- |
| `output`    | VIDEO     | The newly generated video file containing the extended footage. |

***

**Source fingerprint (SHA-256):** `067eda95bf7738fec1b68fb496b6309dab5f56c57ab4d7d92a3a5e50239c17c8`


# ViduImageToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduImageToVideoNode

Complete documentation for the ViduImageToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduImageToVideoNode/en.md)

The Vidu Image To Video Generation node creates a short video from a starting image and an optional text description. It uses an AI model to generate video content that continues from the provided image frame, and returns the resulting video.

## Inputs

| Parameter            | Data Type | Required | Range                                          | Description                                                              |
| -------------------- | --------- | -------- | ---------------------------------------------- | ------------------------------------------------------------------------ |
| `model`              | COMBO     | Yes      | `viduq1`                                       | Model name (default: viduq1)                                             |
| `image`              | IMAGE     | Yes      | -                                              | An image to be used as the start frame of the generated video            |
| `prompt`             | STRING    | No       | -                                              | A textual description for video generation (default: empty)              |
| `duration`           | INT       | No       | 5-5                                            | Duration of the output video in seconds (default: 5, fixed at 5 seconds) |
| `seed`               | INT       | No       | 0-2147483647                                   | Seed for video generation (0 for random) (default: 0)                    |
| `resolution`         | COMBO     | No       | `1080p`                                        | Supported values may vary by model & duration (default: 1080p)           |
| `movement_amplitude` | COMBO     | No       | `auto`<br />`small`<br />`medium`<br />`large` | The movement amplitude of objects in the frame (default: auto)           |

**Constraints:**

* Only one input image is allowed (cannot process multiple images).
* The input image must have an aspect ratio between 1:4 and 4:1.

## Outputs

| Output Name | Data Type | Description                |
| ----------- | --------- | -------------------------- |
| `output`    | VIDEO     | The generated video output |

***

**Source fingerprint (SHA-256):** `2364ee527cbc37905e973ae1870499040eea4ed94ab8ed789d3c85af857f5488`


# ViduMultiFrameVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduMultiFrameVideoNode

Complete documentation for the ViduMultiFrameVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduMultiFrameVideoNode/en.md)

This node generates a video by creating transitions between multiple keyframes. It starts from an initial image and animates through a sequence of user-defined end images and prompts, producing a single video file as output.

## Inputs

| Parameter     | Data Type    | Required | Range                                                                              | Description                                                                                                     |
| :------------ | :----------- | :------- | :--------------------------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------- |
| `model`       | COMBO        | Yes      | `"viduq2-pro"`<br />`"viduq2-turbo"`                                               | The Vidu model to use for video generation.                                                                     |
| `start_image` | IMAGE        | Yes      | -                                                                                  | The starting frame image. Aspect ratio must be between 1:4 and 4:1.                                             |
| `seed`        | INT          | No       | 0 to 2147483647                                                                    | A seed value for random number generation to ensure reproducible results (default: 1).                          |
| `resolution`  | COMBO        | Yes      | `"720p"`<br />`"1080p"`                                                            | The resolution of the output video.                                                                             |
| `frames`      | DYNAMICCOMBO | Yes      | `"2"`<br />`"3"`<br />`"4"`<br />`"5"`<br />`"6"`<br />`"7"`<br />`"8"`<br />`"9"` | Number of keyframe transitions (2-9). Selecting a value dynamically reveals the required inputs for each frame. |

**Frame Inputs (Dynamically Revealed):**
When you select a value for `frames` (e.g., "3"), the node will show a corresponding set of required inputs for each transition. For each frame `i` from 1 to the selected number, you must provide:

* `end_image{i}` (IMAGE): The target image for this transition. Aspect ratio must be between 1:4 and 4:1.
* `prompt{i}` (STRING): A text description guiding the transition to this frame (maximum 2000 characters).
* `duration{i}` (INT): The duration in seconds for this specific transition segment.

## Outputs

| Output Name | Data Type | Description                                                       |
| :---------- | :-------- | :---------------------------------------------------------------- |
| `output`    | VIDEO     | The generated video file containing all the animated transitions. |

***

**Source fingerprint (SHA-256):** `06c3236589dd6067c5dd0a430e062686adb3e878542f8382e022a3fafe81507b`


# ViduReferenceVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduReferenceVideoNode

Complete documentation for the ViduReferenceVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduReferenceVideoNode/en.md)

The Vidu Reference Video Node generates videos from multiple reference images and a text prompt. It uses AI models to create consistent video content based on the provided images and description. The node supports various video settings including duration, aspect ratio, resolution, and movement control.

## Inputs

| Parameter            | Data Type | Required | Range                                                  | Description                                                                                 |
| -------------------- | --------- | -------- | ------------------------------------------------------ | ------------------------------------------------------------------------------------------- |
| `model`              | COMBO     | Yes      | `"viduq1"`                                             | Model name for video generation (default: "viduq1")                                         |
| `images`             | IMAGE     | Yes      | -                                                      | Images to use as references to generate a video with consistent subjects (maximum 7 images) |
| `prompt`             | STRING    | Yes      | -                                                      | A textual description for video generation                                                  |
| `duration`           | INT       | No       | 5-5                                                    | Duration of the output video in seconds (default: 5)                                        |
| `seed`               | INT       | No       | 0-2147483647                                           | Seed for video generation (0 for random) (default: 0)                                       |
| `aspect_ratio`       | COMBO     | No       | `"16:9"`<br />`"9:16"`<br />`"1:1"`                    | The aspect ratio of the output video                                                        |
| `resolution`         | COMBO     | No       | `"1080p"`                                              | Supported values may vary by model & duration (default: "1080p")                            |
| `movement_amplitude` | COMBO     | No       | `"auto"`<br />`"small"`<br />`"medium"`<br />`"large"` | The movement amplitude of objects in the frame (default: "auto")                            |

**Constraints and Limitations:**

* The `prompt` field is required and cannot be empty
* Maximum of 7 images allowed for reference
* Each image must have an aspect ratio between 1:4 and 4:1
* Each image must have minimum dimensions of 128x128 pixels
* Duration is fixed at 5 seconds

## Outputs

| Output Name | Data Type | Description                                                  |
| ----------- | --------- | ------------------------------------------------------------ |
| `output`    | VIDEO     | The generated video based on the reference images and prompt |

***

**Source fingerprint (SHA-256):** `ac86287d93257105446a5af42efd7d7fc07738fb7fcd0b260b8049a98552f193`


# ViduStartEndToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduStartEndToVideoNode

Complete documentation for the ViduStartEndToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduStartEndToVideoNode/en.md)

The Vidu Start End To Video Generation node creates a video by generating frames between a starting frame and an ending frame. It uses a text prompt to guide the video generation process and supports various video models with different resolution and movement settings. The node validates that the start and end frames have compatible aspect ratios before processing.

## Inputs

| Parameter            | Data Type | Required | Range                                                  | Description                                                              |
| -------------------- | --------- | -------- | ------------------------------------------------------ | ------------------------------------------------------------------------ |
| `model`              | COMBO     | Yes      | `"viduq1"`                                             | Model name                                                               |
| `first_frame`        | IMAGE     | Yes      | -                                                      | Start frame                                                              |
| `end_frame`          | IMAGE     | Yes      | -                                                      | End frame                                                                |
| `prompt`             | STRING    | No       | -                                                      | A textual description for video generation                               |
| `duration`           | INT       | No       | 5-5                                                    | Duration of the output video in seconds (default: 5, fixed at 5 seconds) |
| `seed`               | INT       | No       | 0-2147483647                                           | Seed for video generation (0 for random) (default: 0)                    |
| `resolution`         | COMBO     | No       | `"1080p"`                                              | Supported values may vary by model & duration (default: "1080p")         |
| `movement_amplitude` | COMBO     | No       | `"auto"`<br />`"small"`<br />`"medium"`<br />`"large"` | The movement amplitude of objects in the frame (default: "auto")         |

**Note:** The start and end frames must have compatible aspect ratios (validated with min\_rel=0.8, max\_rel=1.25 ratio tolerance).

## Outputs

| Output Name | Data Type | Description              |
| ----------- | --------- | ------------------------ |
| `output`    | VIDEO     | The generated video file |

***

**Source fingerprint (SHA-256):** `bffb4d3e90b1c6a1a3a7cc864a44ab96bac0be90411be791f9ffb15b9a50c6b6`


# ViduTextToVideoNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/ViduTextToVideoNode

Complete documentation for the ViduTextToVideoNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/ViduTextToVideoNode/en.md)

The Vidu Text To Video Generation node creates videos from text descriptions. It uses the Vidu video generation model to transform your text prompts into video content with customizable settings for duration, aspect ratio, and visual style.

## Inputs

| Parameter            | Data Type | Required | Range                                          | Description                                           |
| -------------------- | --------- | -------- | ---------------------------------------------- | ----------------------------------------------------- |
| `model`              | COMBO     | Yes      | `viduq1`                                       | Model name                                            |
| `prompt`             | STRING    | Yes      | -                                              | A textual description for video generation            |
| `duration`           | INT       | No       | 5-5                                            | Duration of the output video in seconds (default: 5)  |
| `seed`               | INT       | No       | 0-2147483647                                   | Seed for video generation (0 for random) (default: 0) |
| `aspect_ratio`       | COMBO     | No       | `16:9`<br />`9:16`<br />`1:1`                  | The aspect ratio of the output video                  |
| `resolution`         | COMBO     | No       | `1080p`                                        | Supported values may vary by model & duration         |
| `movement_amplitude` | COMBO     | No       | `auto`<br />`small`<br />`medium`<br />`large` | The movement amplitude of objects in the frame        |

**Note:** The `prompt` field is required and cannot be empty. The `duration` parameter is currently fixed at 5 seconds.

## Outputs

| Output Name | Data Type | Description                                  |
| ----------- | --------- | -------------------------------------------- |
| `output`    | VIDEO     | The generated video based on the text prompt |

***

**Source fingerprint (SHA-256):** `33ca2a60d7914e7b9ab65fbf166e1ba5388d53134cd56ef59acdcbfada5f999d`


# Wan2ImageToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan2ImageToVideoApi

Complete documentation for the Wan2ImageToVideoApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan2ImageToVideoApi/en.md)

The Wan 2.7 Image to Video node generates a video starting from a first-frame image. You can optionally provide a last-frame image to create a transition between the two, or provide an audio file to guide the video's motion and timing. The node uses an AI model to animate the scene based on your text description.

## Inputs

| Parameter               | Data Type | Required | Range                   | Description                                                                                                                                                                                                                          |
| ----------------------- | --------- | -------- | ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `model`                 | COMBO     | Yes      | `"wan2.7-i2v"`          | The AI model to use for video generation.                                                                                                                                                                                            |
| `model.prompt`          | STRING    | Yes      | -                       | A text description of the elements and visual features you want in the video. Supports English and Chinese.                                                                                                                          |
| `model.negative_prompt` | STRING    | Yes      | -                       | A text description of elements or features you want the model to avoid.                                                                                                                                                              |
| `model.resolution`      | COMBO     | Yes      | `"720P"`<br />`"1080P"` | The resolution of the output video.                                                                                                                                                                                                  |
| `model.duration`        | INT       | Yes      | 2 to 15                 | The length of the generated video in seconds (default: 5).                                                                                                                                                                           |
| `first_frame`           | IMAGE     | Yes      | -                       | The image to use as the first frame of the video. The output video's aspect ratio is derived from this image.                                                                                                                        |
| `last_frame`            | IMAGE     | No       | -                       | An optional image to use as the last frame. When provided, the model generates a video that transitions from the first frame to this last frame.                                                                                     |
| `audio`                 | AUDIO     | No       | -                       | An optional audio file to drive the video generation, useful for lip-syncing or beat-matched motion. Duration must be between 2 and 30 seconds. If not provided, the model will generate matching background music or sound effects. |
| `seed`                  | INT       | Yes      | 0 to 2147483647         | A seed value to control the randomness of the generation (default: 0).                                                                                                                                                               |
| `prompt_extend`         | BOOLEAN   | Yes      | -                       | When enabled, the node will use AI assistance to enhance your text prompt (default: True). This is an advanced setting.                                                                                                              |
| `watermark`             | BOOLEAN   | Yes      | -                       | When enabled, an AI-generated watermark will be added to the final video (default: False). This is an advanced setting.                                                                                                              |

**Note:** The `audio` input has a duration constraint. If provided, the audio file must be between 2 and 30 seconds long.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `db5e4e26a407c71e2b79179d32cdad926db5af16461f2aa565eab544295df7ff`


# Wan2ReferenceVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan2ReferenceVideoApi

Complete documentation for the Wan2ReferenceVideoApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan2ReferenceVideoApi/en.md)

This node generates a video featuring a person or object based on provided reference materials. It uses the Wan 2.7 model to create videos from a text prompt, supporting single-character performances and multi-character interactions. You must provide at least one reference video or image for the generation to work.

## Inputs

| Parameter                | Data Type | Required | Range                                                         | Description                                                                                                              |
| ------------------------ | --------- | -------- | ------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------ |
| `model`                  | COMBO     | Yes      | `"wan2.7-r2v"`                                                | The specific model to use for video generation.                                                                          |
| `model.prompt`           | STRING    | Yes      | -                                                             | Prompt describing the video. Use identifiers such as 'character1' and 'character2' to refer to the reference characters. |
| `model.negative_prompt`  | STRING    | No       | -                                                             | Negative prompt describing what to avoid in the generated video (default: empty).                                        |
| `model.resolution`       | COMBO     | Yes      | `"720P"`<br />`"1080P"`                                       | The resolution of the output video.                                                                                      |
| `model.ratio`            | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"` | The aspect ratio of the output video.                                                                                    |
| `model.duration`         | INT       | Yes      | 2 to 10                                                       | The length of the generated video in seconds (default: 5).                                                               |
| `model.reference_videos` | VIDEO     | No       | -                                                             | A list of reference videos. You can add up to 3 videos.                                                                  |
| `model.reference_images` | IMAGE     | No       | -                                                             | A list of reference images. You can add up to 5 images.                                                                  |
| `seed`                   | INT       | No       | 0 to 2147483647                                               | Seed to use for generation, which helps control the randomness of the output (default: 0).                               |
| `watermark`              | BOOLEAN   | No       | -                                                             | Whether to add an AI-generated watermark to the result (default: False). This is an advanced setting.                    |

**Important Constraints:**

* You must provide at least one reference video or reference image in the `model.reference_videos` or `model.reference_images` inputs.
* The total combined number of reference videos and images cannot exceed 5.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `83550e1193a13c3686506a279c0a8469be93be564dd27867e31b8b2724e7025d`


# Wan2TextToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan2TextToVideoApi

Complete documentation for the Wan2TextToVideoApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan2TextToVideoApi/en.md)

This node generates a video from a text description using the Wan 2.7 model. It sends your request to an external API, which processes the prompt and returns a video file. You can optionally provide an audio clip to influence the video's motion and timing.

## Inputs

| Parameter               | Data Type | Required | Range                                                         | Description                                                                                                                                                                                                                               |
| ----------------------- | --------- | -------- | ------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`                 | COMBO     | Yes      | `"wan2.7-t2v"`                                                | The specific model to use for video generation.                                                                                                                                                                                           |
| `model.prompt`          | STRING    | Yes      | -                                                             | A description of the elements and visual features you want in the video. Supports English and Chinese.                                                                                                                                    |
| `model.negative_prompt` | STRING    | No       | -                                                             | A description of elements or features you want to avoid in the generated video.                                                                                                                                                           |
| `model.resolution`      | COMBO     | Yes      | `"720P"`<br />`"1080P"`                                       | The resolution of the output video.                                                                                                                                                                                                       |
| `model.ratio`           | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"` | The aspect ratio of the output video.                                                                                                                                                                                                     |
| `model.duration`        | INT       | Yes      | 2 to 15                                                       | The length of the video in seconds (default: 5).                                                                                                                                                                                          |
| `audio`                 | AUDIO     | No       | -                                                             | An audio file to drive video generation, such as for lip-syncing or motion matching the beat. If not provided, the model will generate matching background music or sound effects. The audio duration must be between 1.5 and 60 seconds. |
| `seed`                  | INT       | No       | 0 to 2147483647                                               | A number used to control the randomness of the generation, ensuring reproducible results (default: 0).                                                                                                                                    |
| `prompt_extend`         | BOOLEAN   | No       | -                                                             | When enabled, the prompt will be enhanced with AI assistance (default: True).                                                                                                                                                             |
| `watermark`             | BOOLEAN   | No       | -                                                             | When enabled, an AI-generated watermark will be added to the result (default: False).                                                                                                                                                     |

**Note:** The `audio` parameter is optional. If provided, its duration must be between 1.5 and 60 seconds. If omitted, the model will automatically generate audio.

## Outputs

| Output Name | Data Type | Description               |
| ----------- | --------- | ------------------------- |
| `output`    | VIDEO     | The generated video file. |

***

**Source fingerprint (SHA-256):** `1eb775421209047ad06ffc210c6588c64fd39a8828a69d6fcc2b79360df311e3`


# Wan2VideoContinuationApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan2VideoContinuationApi

Complete documentation for the Wan2VideoContinuationApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan2VideoContinuationApi/en.md)

The Wan 2.7 Video Continuation node generates a new video segment that continues seamlessly from the end of an input video clip. It uses the Wan 2.7 model to synthesize the continuation based on a text prompt and can optionally guide the ending towards a specific target frame.

## Inputs

| Parameter               | Data Type | Required | Range                   | Description                                                                                                                      |
| :---------------------- | :-------- | :------- | :---------------------- | :------------------------------------------------------------------------------------------------------------------------------- |
| `model`                 | COMBO     | Yes      | `"wan2.7-i2v"`          | The video generation model to use.                                                                                               |
| `model.prompt`          | STRING    | Yes      | -                       | Prompt describing the elements and visual features. Supports English and Chinese. (default: empty string)                        |
| `model.negative_prompt` | STRING    | Yes      | -                       | Negative prompt describing what to avoid. (default: empty string)                                                                |
| `model.resolution`      | COMBO     | Yes      | `"720P"`<br />`"1080P"` | The resolution for the output video.                                                                                             |
| `model.duration`        | INT       | Yes      | 2 to 15                 | Total output duration in seconds. The model generates continuation to fill the remaining time after the input clip. (default: 5) |
| `first_clip`            | VIDEO     | Yes      | -                       | Input video to continue from. Duration: 2s-10s. The output aspect ratio is derived from this video.                              |
| `last_frame`            | IMAGE     | No       | -                       | Last frame image. The continuation will transition towards this frame.                                                           |
| `seed`                  | INT       | Yes      | 0 to 2147483647         | Seed to use for generation. (default: 0)                                                                                         |
| `prompt_extend`         | BOOLEAN   | Yes      | -                       | Whether to enhance the prompt with AI assistance. (default: True)                                                                |
| `watermark`             | BOOLEAN   | Yes      | -                       | Whether to add an AI-generated watermark to the result. (default: False)                                                         |

**Note:** The `first_clip` input video must be between 2 and 10 seconds in duration.

## Outputs

| Output Name | Data Type | Description                       |
| :---------- | :-------- | :-------------------------------- |
| `output`    | VIDEO     | The generated video continuation. |

***

**Source fingerprint (SHA-256):** `44f71824f1289351fe44ff0f830ee391d2387146444f50ba50309ecba2e54456`


# Wan2VideoEditApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Wan2VideoEditApi

Complete documentation for the Wan2VideoEditApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Wan2VideoEditApi/en.md)

The Wan2VideoEditApi node uses the Wan 2.7 model to edit a video based on text instructions, reference images, or style transfer. It processes the input video and generates a new video according to the specified parameters like resolution, duration, and aspect ratio.

## Inputs

| Parameter                | Data Type | Required | Range                                                                                                        | Description                                                                                                                                          |
| ------------------------ | --------- | -------- | ------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`                  | COMBO     | Yes      | `"wan2.7-videoedit"`                                                                                         | The model to use for video editing.                                                                                                                  |
| `model.prompt`           | STRING    | Yes      | -                                                                                                            | Editing instructions or style transfer requirements. (default: empty string)                                                                         |
| `model.resolution`       | COMBO     | Yes      | `"720P"`<br />`"1080P"`                                                                                      | The resolution for the output video.                                                                                                                 |
| `model.ratio`            | COMBO     | Yes      | `"16:9"`<br />`"9:16"`<br />`"1:1"`<br />`"4:3"`<br />`"3:4"`                                                | The aspect ratio for the output video. If not changed, it approximates the input video's ratio.                                                      |
| `model.duration`         | COMBO     | Yes      | `"auto"`<br />`"2"`<br />`"3"`<br />`"4"`<br />`"5"`<br />`"6"`<br />`"7"`<br />`"8"`<br />`"9"`<br />`"10"` | The output duration in seconds. 'auto' matches the input video duration. A specific value truncates from the start of the video. (default: "auto")   |
| `model.reference_images` | IMAGE     | No       | -                                                                                                            | A list of up to 4 reference images to guide the edit.                                                                                                |
| `video`                  | VIDEO     | Yes      | -                                                                                                            | The video to edit.                                                                                                                                   |
| `seed`                   | INT       | No       | 0 to 2147483647                                                                                              | The seed to use for generation. (default: 0)                                                                                                         |
| `audio_setting`          | COMBO     | No       | `"auto"`<br />`"origin"`                                                                                     | 'auto': model decides whether to regenerate audio based on the prompt. 'origin': preserve the original audio from the input video. (default: "auto") |
| `watermark`              | BOOLEAN   | No       | -                                                                                                            | Whether to add an AI-generated watermark to the result. (default: False)                                                                             |

**Constraints:**

* The `model.prompt` must be at least 1 character long.
* The input `video` must be between 2 and 10 seconds in duration.
* The `model.reference_images` input can accept a maximum of 4 images.

## Outputs

| Output Name | Data Type | Description                              |
| ----------- | --------- | ---------------------------------------- |
| `output`    | VIDEO     | The edited video generated by the model. |

***

**Source fingerprint (SHA-256):** `1ea6cacbf8f5b6666e164c4806d931d21ddd44568e5c9f6d44f389288f5ce84f`


# WanImageToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanImageToVideoApi

Complete documentation for the WanImageToVideoApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanImageToVideoApi/en.md)

The Wan Image to Video node generates a video from a single input image and a text prompt. It uses the provided image as the first frame and creates a video sequence based on the description, with options for resolution, duration, audio, and other advanced settings.

## Inputs

| Parameter         | Data Type | Required | Range                                  | Description                                                                                                                                                                                                            |
| ----------------- | --------- | -------- | -------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`           | COMBO     | Yes      | "wan2.5-i2v-preview"<br />"wan2.6-i2v" | Model to use (default: "wan2.6-i2v")                                                                                                                                                                                   |
| `image`           | IMAGE     | Yes      | -                                      | Input image that serves as the first frame for video generation. Exactly one image is required.                                                                                                                        |
| `prompt`          | STRING    | Yes      | -                                      | Prompt describing the elements and visual features. Supports English and Chinese (default: empty).                                                                                                                     |
| `negative_prompt` | STRING    | No       | -                                      | Negative prompt describing what to avoid (default: empty).                                                                                                                                                             |
| `resolution`      | COMBO     | No       | "480P"<br />"720P"<br />"1080P"        | Video resolution quality (default: "720P"). The Wan 2.6 model does not support 480P.                                                                                                                                   |
| `duration`        | INT       | No       | 5-15 (step: 5)                         | Duration of the generated video in seconds. A 15-second duration is supported only by the Wan 2.6 model (default: 5).                                                                                                  |
| `audio`           | AUDIO     | No       | -                                      | Audio must contain a clear, loud voice, without extraneous noise or background music. When provided, audio duration must be between 3.0 and 29.0 seconds.                                                              |
| `seed`            | INT       | No       | 0-2147483647                           | Seed to use for generation (default: 0).                                                                                                                                                                               |
| `generate_audio`  | BOOLEAN   | No       | -                                      | If no audio input is provided, generate audio automatically (default: False).                                                                                                                                          |
| `prompt_extend`   | BOOLEAN   | No       | -                                      | Whether to enhance the prompt with AI assistance (default: True).                                                                                                                                                      |
| `watermark`       | BOOLEAN   | No       | -                                      | Whether to add an AI-generated watermark to the result (default: False).                                                                                                                                               |
| `shot_type`       | COMBO     | No       | "single"<br />"multi"                  | Specifies the shot type for the generated video, that is, whether the video is a single continuous shot or multiple shots with cuts. This parameter takes effect only when prompt\_extend is True (default: "single"). |

**Constraints:**

* Exactly one input image is required for video generation.
* The Wan 2.6 model (`wan2.6-i2v`) does not support 480P resolution.
* A 15-second duration is supported only by the Wan 2.6 model (`wan2.6-i2v`).
* When audio is provided, it must be between 3.0 and 29.0 seconds in duration.

## Outputs

| Output Name | Data Type | Description                                          |
| ----------- | --------- | ---------------------------------------------------- |
| `output`    | VIDEO     | Generated video based on the input image and prompt. |

***

**Source fingerprint (SHA-256):** `b8a75e324f7436e8a376e4a058b0a32556cafbe8e7975148cbc6302638f52058`


# wanBlockSwap - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/wanBlockSwap

Complete documentation for the wanBlockSwap node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/wanBlockSwap/en.md)

This node is deprecated and serves no function. It accepts a model as input and returns the same model unchanged. The description "NOP" indicates it performs no operation.

## Inputs

| Parameter | Data Type | Required | Range | Description                         |
| --------- | --------- | -------- | ----- | ----------------------------------- |
| `model`   | MODEL     | Yes      |       | The model to pass through the node. |

## Outputs

| Output Name | Data Type | Description                                           |
| ----------- | --------- | ----------------------------------------------------- |
| `model`     | MODEL     | The same model that was provided as input, unchanged. |

***

**Source fingerprint (SHA-256):** `7acf88d1c42d90e645bb557c7fdc93e659182927ee7b3e3ef15b0ccf7c3f471a`


# Create a Comfy account
Source: https://docs.comfy.org/account/create-account

Learn how to create a new Comfy account for ComfyUI to access all features and services.

Your Comfy account gives you access to [partner nodes (Partner Node)](/tutorials/partner-nodes/overview) and [cloud subscriptions](https://www.comfy.org/cloud), enabling you to use premium features and services across the ComfyUI platform.

## Creating a Comfy account on Comfy Cloud

You can create a Comfy account for ComfyUI directly on Comfy Cloud:

1. Navigate to [Comfy Cloud](https://www.comfy.org)
2. Click **Sign up** or **Create account**
3. Choose one of the following login methods:
   * **Email**: Enter your email address and create a password
   * **Google**: Sign up with your Google account
   * **GitHub**: Sign up with your GitHub account
4. Complete the registration process
5. Verify your email if using email registration

## Creating a Comfy account locally

If you have ComfyUI installed locally, you can create a Comfy account through the application:

1. Open ComfyUI on your local machine
2. Navigate to **Settings** in the interface
3. Go to the **User** section (see [User settings](/interface/user) for details)
4. Click **Create account** or **Sign up**
5. Choose one of the following login methods:
   * **Email**: Enter your email address and create a password
   * **Google**: Sign up with your Google account
   * **GitHub**: Sign up with your GitHub account
6. Complete the registration process

<img alt="User settings interface" />

## Next steps

Once your account is created and verified:

* [Log in to your account](/account/login)
* Set up your profile preferences
* Start using ComfyUI features
* Explore tutorials and documentation

## Troubleshooting

If you encounter issues during account creation:

* Ensure your email address is valid and not already registered
* Check that your password meets the minimum requirements
* Clear your browser cache and try again
* Contact [support](/support/contact-support) if problems persist


# Delete your Comfy account
Source: https://docs.comfy.org/account/delete-account

Learn how to permanently delete your Comfy account for ComfyUI and associated data.

<Warning>
  Account deletion is permanent and cannot be undone. All your data, workflows, and settings will be permanently removed.
</Warning>

## Before you delete

Before proceeding with account deletion, consider:

* **Backup your data**: For Comfy Cloud users, your assets are stored under your account, so back up any data you want to keep. If you don't use Comfy Cloud, your API usage can be found at [https://platform.comfy.org/](https://platform.comfy.org/)
* **Cancel subscriptions**: Ensure all active subscriptions are cancelled to avoid future charges
* **Download invoices**: Save copies of any payment history or invoices you may need
* **Alternative options**: Consider deactivating your account temporarily instead of permanent deletion

## Deleting your Comfy account

To permanently delete your Comfy account for ComfyUI, send a deletion request to [support@comfy.org](mailto:support@comfy.org).

Include the following in your email:

* The email address associated with your account
* A clear statement requesting account deletion (e.g., "I request the deletion of my account and all associated personal data")

Under GDPR and similar data protection regulations, you have the right to request deletion of your personal data. We will process your request within 30 days and send you a confirmation once your account and data have been permanently deleted.

<Note>
  Older versions of the application may still display a "Delete account" button in the account settings. This button is no longer functional. Please use the email process described above.
</Note>

## What gets deleted

When you delete your account, the following data is permanently removed:

* Your user profile and account information
* All saved workflows and projects
* Generated images and outputs
* Custom settings and preferences
* Payment history and billing information
* API keys and access tokens


# Log in to your Comfy account
Source: https://docs.comfy.org/account/login

Access your Comfy account for ComfyUI to use all platform features and services.

Your Comfy account gives you access to [partner nodes (Partner Node)](/tutorials/partner-nodes/overview) and [cloud subscriptions](https://www.comfy.org/cloud), enabling you to use premium features and services across the ComfyUI platform.

## Supported login methods

ComfyUI supports the following login methods:

* **Email**: Log in with your email address and password
* **Google**: Log in with your Google account
* **GitHub**: Log in with your GitHub account

## Logging in on Comfy Cloud

To access your Comfy account for ComfyUI on Comfy Cloud:

1. Navigate to [Comfy Cloud](https://www.comfy.org)
2. Click **Log in** or **Sign in**
3. Choose your login method:
   * **Email**: Enter your email address and password, then click **Log in**
   * **Google**: Click the Google login button and authenticate
   * **GitHub**: Click the GitHub login button and authenticate

## Logging in locally

If you have ComfyUI installed locally:

1. Open ComfyUI on your local machine
2. Navigate to **Settings** in the interface
3. Go to the **User** section (see [User settings](/interface/user) for details)
4. Choose your login method:
   * **Email**: Enter your email address and password
   * **Google**: Click the Google login button and authenticate
   * **GitHub**: Click the GitHub login button and authenticate
   * **API Key**: Use an API Key for non-whitelisted deployments (see below)

<img alt="User settings interface" />

### Logging in with an API Key

Since not all ComfyUI deployments are on our domain authorization whitelist, we have provided API Key login in a recent update (2025-05-10) for logging in through non-whitelisted sites. Below are the steps for logging in with an API Key:

<video />

<Tabs>
  <Tab title="Have an API Key">
    <Steps>
      <Step title="Select Comfy API Key Login on the Login Screen">
        Select `Comfy API Key` login in the login popup

        <img alt="Select Comfy API Key Login" />
      </Step>

      <Step title="Enter Your API Key">
        <img alt="Enter API Key" />

        1. Enter your API Key and save it
        2. If you don't have an API Key, click the `Get one here` link to go to [https://platform.comfy.org/login](https://platform.comfy.org/login) and log in to obtain it.
      </Step>

      <Step title="Login Successful">
        After a successful login, you can see the corresponding API Key login information in the settings menu

        <img alt="Logged In" />
      </Step>
    </Steps>
  </Tab>

  <Tab title="No API Key, Apply for an API Key First">
    Please refer to the following steps to apply for and obtain an API Key:

    <Steps>
      <Step title="Visit https://platform.comfy.org/login and Log In">
        Please visit [https://platform.comfy.org/login](https://platform.comfy.org/login) and log in with the corresponding account

        <img alt="Visit Platform Login Page" />
      </Step>

      <Step title="Click `+ New` in API Keys to Create an API Key">
        Click `+ New` in API Keys to create an API Key

        <img alt="Create API Key" />
      </Step>

      <Step title="Enter API Key Name">
        <img alt="Enter API Key Name" />

        1. (Required) Enter the API Key name,
        2. Click `Generate` to create
      </Step>

      <Step title="Save the Obtained API Key">
        <img alt="Obtain API Key" />

        <Warning>
          Since the API Key is only visible upon first creation, please save it immediately after creation. It cannot be viewed later, so please keep it safe.
          Please note that you should not share your API Key with others. Once it leaked, you can delete it and create a new one.
        </Warning>
      </Step>
    </Steps>

    <Steps>
      <Step title="API Key Management">
        <img alt="API Key Management" />

        For unused API Keys or those at risk of being leaked, you can click `Delete` to remove them to prevent unnecessary losses.
      </Step>

      <Step title="(Optional) Log Out">
        <img alt="Log Out" />

        If you have obtained an API Key and are logged in on a public device, please log out promptly.
      </Step>
    </Steps>
  </Tab>
</Tabs>

## Forgot your password

If you can't remember your password (for email login):

1. Click the **Forgot password?** link on the login page
2. Enter your registered email address
3. Check your email for password reset instructions
4. Click the reset link in the email
5. Create a new password
6. Log in with your new password

## Troubleshooting login issues

If you're having trouble logging in:

* Verify your email address is correct
* Check that Caps Lock is not enabled when entering your password
* Clear your browser cookies and cache
* Try using a different browser or incognito mode
* Ensure your account email has been verified
* Contact [support](/support/contact-support) if issues persist

## Security tips

To keep your account secure:

* Use a strong, unique password
* Don't share your login credentials
* Log out when using shared devices
* Regularly update your password


# Generate a short-lived JWT admin token
Source: https://docs.comfy.org/api-reference/admin/generate-a-short-lived-jwt-admin-token

https://api.comfy.org/openapi post /admin/generate-token
Generates a short-lived JWT admin token for browser-based admin operations.
The user must already be authenticated with Firebase and have admin privileges.
The generated token expires after 1 hour.




# Get server feature flags
Source: https://docs.comfy.org/api-reference/registry/get-server-feature-flags

https://api.comfy.org/openapi get /features
Returns the server's feature capabilities



# list all comfy-nodes
Source: https://docs.comfy.org/api-reference/registry/list-all-comfy-nodes

https://api.comfy.org/openapi get /comfy-nodes



# Retrieve a node by ComfyUI node name
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-node-by-comfyui-node-name

https://api.comfy.org/openapi get /comfy-nodes/{comfyNodeName}/node
Returns the node that contains a ComfyUI node with the specified name



# Retrieve a specific node by ID
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-specific-node-by-id

https://api.comfy.org/openapi get /nodes/{nodeId}
Returns the details of a specific node.



# Retrieve multiple node versions in a single request
Source: https://docs.comfy.org/api-reference/registry/retrieve-multiple-node-versions-in-a-single-request

https://api.comfy.org/openapi post /bulk/nodes/versions



# Retrieves a list of nodes
Source: https://docs.comfy.org/api-reference/registry/retrieves-a-list-of-nodes

https://api.comfy.org/openapi get /nodes
Returns a paginated list of nodes across all publishers.



# Retrieves a list of nodes
Source: https://docs.comfy.org/api-reference/registry/retrieves-a-list-of-nodes-1

https://api.comfy.org/openapi get /nodes/search
Returns a paginated list of nodes across all publishers.



# Returns a node version to be installed.
Source: https://docs.comfy.org/api-reference/registry/returns-a-node-version-to-be-installed

https://api.comfy.org/openapi get /nodes/{nodeId}/install
Retrieves the node data for installation, either the latest or a specific version.



# CreateVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/CreateVideo

Complete documentation for the CreateVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/CreateVideo/en.md)

The Create Video node generates a video file from a sequence of images. You can specify the playback speed using frames per second and optionally add audio to the video. The node combines your images into a video format that can be played back with the specified frame rate.

## Inputs

| Parameter | Data Type | Required | Range       | Description                                                         |
| --------- | --------- | -------- | ----------- | ------------------------------------------------------------------- |
| `images`  | IMAGE     | Yes      | -           | The images to create a video from.                                  |
| `fps`     | FLOAT     | Yes      | 1.0 - 120.0 | The frames per second for the video playback speed (default: 30.0). |
| `audio`   | AUDIO     | No       | -           | The audio to add to the video.                                      |

## Outputs

| Output Name | Data Type | Description                                                              |
| ----------- | --------- | ------------------------------------------------------------------------ |
| `output`    | VIDEO     | The generated video file containing the input images and optional audio. |

***

**Source fingerprint (SHA-256):** `b3effbbc380a3841ffbedd3c9561e783bc9f9a7887edc8965c38992cb370a812`


# FrameInterpolate - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/FrameInterpolate

Complete documentation for the FrameInterpolate node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/FrameInterpolate/en.md)

## Overview

The Frame Interpolate node creates new frames between existing ones in a sequence of images, effectively increasing the frame rate. It uses an AI model to predict what the intermediate frames should look like, which can be used to create smooth slow-motion effects or to increase the smoothness of a video.

## Inputs

| Parameter      | Data Type | Required | Range   | Description                                                                                                                |
| -------------- | --------- | -------- | ------- | -------------------------------------------------------------------------------------------------------------------------- |
| `interp_model` | MODEL     | Yes      | -       | The frame interpolation model to use for generating intermediate frames                                                    |
| `images`       | IMAGE     | Yes      | -       | A batch of consecutive images (frames) to interpolate between. Requires at least 2 images.                                 |
| `multiplier`   | INT       | Yes      | 2 to 16 | The number of times to multiply the frame count. For example, a multiplier of 2 doubles the number of frames. (default: 2) |

## Outputs

| Output Name | Data Type | Description                                                                                                                                                                                                      |
| ----------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `IMAGE`     | IMAGE     | A new batch of images with the interpolated frames inserted between the original frames, resulting in a smoother sequence. The total number of output frames is `(number of input frames - 1) * multiplier + 1`. |

***

**Source fingerprint (SHA-256):** `54e1956bf249004315587328e8671d43739659cc00ad26f870214b704566a68b`


# GetVideoComponents - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/GetVideoComponents

Complete documentation for the GetVideoComponents node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/GetVideoComponents/en.md)

The Get Video Components node extracts all the main elements from a video file. It separates the video into individual frames, extracts the audio track, and provides the video's framerate information. This allows you to work with each component independently for further processing or analysis.

## Inputs

| Parameter | Data Type | Required | Range | Description                           |
| --------- | --------- | -------- | ----- | ------------------------------------- |
| `video`   | VIDEO     | Yes      | -     | The video to extract components from. |

## Outputs

| Output Name | Data Type | Description                                                        |
| ----------- | --------- | ------------------------------------------------------------------ |
| `images`    | IMAGE     | The individual frames extracted from the video as separate images. |
| `audio`     | AUDIO     | The audio track extracted from the video.                          |
| `fps`       | FLOAT     | The framerate of the video in frames per second.                   |

***

**Source fingerprint (SHA-256):** `de129130ed4b82d875c4e8c660209b88172e3cdd41fed8c822fb7e807c92ed47`


# LTXVPreprocess - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LTXVPreprocess

Complete documentation for the LTXVPreprocess node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LTXVPreprocess/en.md)

The LTXVPreprocess node applies video compression preprocessing to images. It simulates the quality loss of video compression by encoding an image as a single-frame MP4 video and then decoding it back, allowing you to control the compression level.

## Inputs

| Parameter         | Data Type | Required | Range | Description                                                                                       |
| ----------------- | --------- | -------- | ----- | ------------------------------------------------------------------------------------------------- |
| `image`           | IMAGE     | Yes      | -     | The input image to be processed                                                                   |
| `img_compression` | INT       | No       | 0-100 | Amount of compression to apply on image. A value of 0 disables compression entirely (default: 35) |

## Outputs

| Output Name    | Data Type | Description                                                   |
| -------------- | --------- | ------------------------------------------------------------- |
| `output_image` | IMAGE     | The processed output image with applied compression artifacts |

***

**Source fingerprint (SHA-256):** `4381837f2778948e6d8b710cf1857ce9e579b3cc630223d97266162b9799342b`


# LoadVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/LoadVideo

Complete documentation for the LoadVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadVideo/en.md)

The Load Video node loads video files from the input directory and makes them available for processing in the workflow. It reads video files from the designated input folder and outputs them as video data that can be connected to other video processing nodes.

## Inputs

| Parameter | Data Type | Required | Range                      | Description                                                                                                                                         |
| --------- | --------- | -------- | -------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- |
| `file`    | STRING    | Yes      | Multiple options available | The video file to load from the input directory. The dropdown list is dynamically populated with all video files found in the ComfyUI input folder. |

**Note:** The available options for the `file` parameter are dynamically populated from the video files present in the input directory. Only video files with supported content types are displayed. You can also upload a new video file directly through the node's file picker interface.

## Outputs

| Output Name | Data Type | Description                                                                                                    |
| ----------- | --------- | -------------------------------------------------------------------------------------------------------------- |
| `video`     | VIDEO     | The loaded video data that can be passed to other video processing nodes for further manipulation or analysis. |

***

**Source fingerprint (SHA-256):** `7cdd0ed301e4545e38fb706231a18510088b76af4e843ccdfb3ae3cf8a912f49`


# SaveVideo - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveVideo

Complete documentation for the SaveVideo node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveVideo/en.md)

The SaveVideo node saves input video content to your ComfyUI output directory. It allows you to specify the filename prefix, video format, and codec for the saved file. The node automatically handles file naming with counter increments and can include workflow metadata in the saved video.

## Inputs

| Parameter         | Data Type | Required | Range                                                                          | Description                                                                                                                                                                                   |
| ----------------- | --------- | -------- | ------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `video`           | VIDEO     | Yes      | -                                                                              | The video to save.                                                                                                                                                                            |
| `filename_prefix` | STRING    | No       | -                                                                              | The prefix for the file to save. This may include formatting information such as `%date:yyyy-MM-dd%` or `%Empty Latent Image.width%` to include values from nodes (default: "video/ComfyUI"). |
| `format`          | STRING    | No       | `"auto"`<br />`"mp4"`<br />`"webm"`<br />`"mkv"`<br />`"gif"`                  | The format to save the video as (default: "auto").                                                                                                                                            |
| `codec`           | STRING    | No       | `"auto"`<br />`"h264"`<br />`"h265"`<br />`"vp9"`<br />`"av1"`<br />`"prores"` | The codec to use for the video (default: "auto").                                                                                                                                             |

## Outputs

| Output Name | Data Type      | Description                                                                                                 |
| ----------- | -------------- | ----------------------------------------------------------------------------------------------------------- |
| `ui`        | PREVIEW\_VIDEO | A preview of the saved video file, including the file path and subfolder information for display in the UI. |

***

**Source fingerprint (SHA-256):** `099472641a2bd0125a8b9e416f9b2e15e3d4f999109b159ee298231e36de8432`


# SaveWEBM - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/SaveWEBM

Complete documentation for the SaveWEBM node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/SaveWEBM/en.md)

The SaveWEBM node saves a sequence of images as a WEBM video file. It takes multiple input images and encodes them into a video using either VP9 or AV1 codec with configurable quality settings and frame rate. The resulting video file is saved to the output directory with metadata including prompt information.

## Inputs

| Parameter         | Data Type | Required | Range            | Description                                                                                                                                       |
| ----------------- | --------- | -------- | ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------- |
| `images`          | IMAGE     | Yes      | -                | Sequence of input images to encode as video frames                                                                                                |
| `filename_prefix` | STRING    | No       | -                | Prefix for the output filename (default: "ComfyUI")                                                                                               |
| `codec`           | COMBO     | Yes      | "vp9"<br />"av1" | Video codec to use for encoding                                                                                                                   |
| `fps`             | FLOAT     | No       | 0.01-1000.0      | Frame rate for the output video (default: 24.0)                                                                                                   |
| `crf`             | FLOAT     | No       | 0-63.0           | Quality setting where higher crf means lower quality with smaller file size, lower crf means higher quality with larger file size (default: 32.0) |

## Outputs

| Output Name | Data Type | Description                               |
| ----------- | --------- | ----------------------------------------- |
| `ui`        | PREVIEW   | Video preview showing the saved WEBM file |

***

**Source fingerprint (SHA-256):** `7ed734af0f4af835c5b52a91389666ec1e0101458aa0f639ef5eeabf1968bfcc`


# Video Slice - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/Video Slice

Complete documentation for the Video Slice node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! \[Edit on GitHub]\([https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui\_embedded\_docs/docs/Video](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/Video) Slice/en.md)

The Video Slice node allows you to extract a specific segment from a video. You can define a start time and a duration to trim the video, or simply skip the beginning frames. If the requested duration is longer than the remaining video, the node can either return what's available or raise an error.

## Inputs

| Parameter         | Data Type | Required | Range         | Description                                                                                     |
| ----------------- | --------- | -------- | ------------- | ----------------------------------------------------------------------------------------------- |
| `video`           | VIDEO     | Yes      | -             | The input video to be sliced.                                                                   |
| `start_time`      | FLOAT     | No       | -1e5 to 1e5   | Start time in seconds (default: 0.0).                                                           |
| `duration`        | FLOAT     | No       | 0.0 and above | Duration in seconds, or 0 for unlimited duration (default: 0.0).                                |
| `strict_duration` | BOOLEAN   | No       | -             | If True, when the specified duration is not possible, an error will be raised (default: False). |

## Outputs

| Output Name | Data Type | Description                |
| ----------- | --------- | -------------------------- |
| `video`     | VIDEO     | The trimmed video segment. |

***

**Source fingerprint (SHA-256):** `077fadd65af9d546155d2bbb736148ce2c87810a16a76d9259b38f1b6ab6a1a3`


# WanReferenceVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanReferenceVideoApi

Complete documentation for the WanReferenceVideoApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanReferenceVideoApi/en.md)

The Wan Reference to Video node uses the visual appearance and voice from one or more input reference videos, along with a text prompt, to generate a new video. It maintains consistency with the characters from the reference material while creating new content based on your description.

## Inputs

| Parameter          | Data Type | Required | Range                                                                                                                                                                                                                                                                                                               | Description                                                                                                                                                                                                 |
| ------------------ | --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`            | COMBO     | Yes      | `"wan2.6-r2v"`                                                                                                                                                                                                                                                                                                      | The specific AI model to use for video generation.                                                                                                                                                          |
| `prompt`           | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                   | A description of the elements and visual features for the new video. Supports English and Chinese. Use identifiers like `character1` and `character2` to refer to the characters from the reference videos. |
| `negative_prompt`  | STRING    | No       | -                                                                                                                                                                                                                                                                                                                   | A description of elements or features to avoid in the generated video.                                                                                                                                      |
| `reference_videos` | AUTOGROW  | Yes      | -                                                                                                                                                                                                                                                                                                                   | A list of video inputs used as references for character appearance and voice. You must provide at least one video. Each video can be assigned a name like `character1`, `character2`, or `character3`.      |
| `size`             | COMBO     | Yes      | `"720p: 1:1 (960x960)"`<br />`"720p: 16:9 (1280x720)"`<br />`"720p: 9:16 (720x1280)"`<br />`"720p: 4:3 (1088x832)"`<br />`"720p: 3:4 (832x1088)"`<br />`"1080p: 1:1 (1440x1440)"`<br />`"1080p: 16:9 (1920x1080)"`<br />`"1080p: 9:16 (1080x1920)"`<br />`"1080p: 4:3 (1632x1248)"`<br />`"1080p: 3:4 (1248x1632)"` | The resolution and aspect ratio for the output video.                                                                                                                                                       |
| `duration`         | INT       | Yes      | 5 to 10                                                                                                                                                                                                                                                                                                             | The length of the generated video in seconds. The value must be a multiple of 5 (default: 5).                                                                                                               |
| `seed`             | INT       | No       | 0 to 2147483647                                                                                                                                                                                                                                                                                                     | A random seed value for reproducible results. A value of 0 will generate a random seed.                                                                                                                     |
| `shot_type`        | COMBO     | Yes      | `"single"`<br />`"multi"`                                                                                                                                                                                                                                                                                           | Specifies whether the generated video is a single continuous shot or contains multiple shots with cuts.                                                                                                     |
| `watermark`        | BOOLEAN   | No       | -                                                                                                                                                                                                                                                                                                                   | When enabled, an AI-generated watermark is added to the final video (default: False).                                                                                                                       |

**Constraints:**

* Each video provided in `reference_videos` must be between 2 and 30 seconds in duration.
* The `duration` parameter is limited to specific values (5 or 10 seconds).

## Outputs

| Output Name | Data Type | Description                     |
| ----------- | --------- | ------------------------------- |
| `output`    | VIDEO     | The newly generated video file. |

***

**Source fingerprint (SHA-256):** `948976c64337299217616d60200ffed7e24cce32655960c525bb068c38cc6406`


# WanTextToVideoApi - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WanTextToVideoApi

Complete documentation for the WanTextToVideoApi node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WanTextToVideoApi/en.md)

The Wan Text to Video node generates video content based on text descriptions. It uses AI models to create videos from prompts and supports various video sizes, durations, and optional audio inputs. The node can automatically generate audio when needed and provides options for prompt enhancement and watermarking.

## Inputs

| Parameter         | Data Type | Required | Range                                                                                                                                                                                                                                                                                                                                                                              | Description                                                                                                                                                                                                           |
| ----------------- | --------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `model`           | COMBO     | Yes      | "wan2.5-t2v-preview"<br />"wan2.6-t2v"                                                                                                                                                                                                                                                                                                                                             | Model to use (default: "wan2.6-t2v")                                                                                                                                                                                  |
| `prompt`          | STRING    | Yes      | -                                                                                                                                                                                                                                                                                                                                                                                  | Prompt describing the elements and visual features. Supports English and Chinese (default: "")                                                                                                                        |
| `negative_prompt` | STRING    | No       | -                                                                                                                                                                                                                                                                                                                                                                                  | Negative prompt describing what to avoid (default: "")                                                                                                                                                                |
| `size`            | COMBO     | No       | "480p: 1:1 (624x624)"<br />"480p: 16:9 (832x480)"<br />"480p: 9:16 (480x832)"<br />"720p: 1:1 (960x960)"<br />"720p: 16:9 (1280x720)"<br />"720p: 9:16 (720x1280)"<br />"720p: 4:3 (1088x832)"<br />"720p: 3:4 (832x1088)"<br />"1080p: 1:1 (1440x1440)"<br />"1080p: 16:9 (1920x1080)"<br />"1080p: 9:16 (1080x1920)"<br />"1080p: 4:3 (1632x1248)"<br />"1080p: 3:4 (1248x1632)" | Video resolution and aspect ratio (default: "720p: 1:1 (960x960)")                                                                                                                                                    |
| `duration`        | INT       | No       | 5-15 (in steps of 5)                                                                                                                                                                                                                                                                                                                                                               | Duration of the video in seconds. A 15-second duration is available only for the Wan 2.6 model (default: 5)                                                                                                           |
| `audio`           | AUDIO     | No       | -                                                                                                                                                                                                                                                                                                                                                                                  | Audio must contain a clear, loud voice, without extraneous noise or background music                                                                                                                                  |
| `seed`            | INT       | No       | 0-2147483647                                                                                                                                                                                                                                                                                                                                                                       | Seed to use for generation (default: 0)                                                                                                                                                                               |
| `generate_audio`  | BOOLEAN   | No       | -                                                                                                                                                                                                                                                                                                                                                                                  | If no audio input is provided, generate audio automatically (default: False)                                                                                                                                          |
| `prompt_extend`   | BOOLEAN   | No       | -                                                                                                                                                                                                                                                                                                                                                                                  | Whether to enhance the prompt with AI assistance (default: True)                                                                                                                                                      |
| `watermark`       | BOOLEAN   | No       | -                                                                                                                                                                                                                                                                                                                                                                                  | Whether to add an AI-generated watermark to the result (default: False)                                                                                                                                               |
| `shot_type`       | COMBO     | No       | "single"<br />"multi"                                                                                                                                                                                                                                                                                                                                                              | Specifies the shot type for the generated video, that is, whether the video is a single continuous shot or multiple shots with cuts. This parameter takes effect only when prompt\_extend is True (default: "single") |

**Note:** The Wan 2.6 model does not support 480p resolutions. A 15-second duration is only supported by the Wan 2.6 model. When providing audio input, it must be between 3.0 and 29.0 seconds in duration and contain clear voice without background noise or music.

## Outputs

| Output Name | Data Type | Description                                       |
| ----------- | --------- | ------------------------------------------------- |
| `output`    | VIDEO     | The generated video based on the input parameters |

***

**Source fingerprint (SHA-256):** `4fbdb2e06ff15849684de860ca3fdf4eb43e6af1803483b4baa7229e584f6e25`


# WavespeedFlashVSRNode - ComfyUI Built-in Node Documentation
Source: https://docs.comfy.org/built-in-nodes/WavespeedFlashVSRNode

Complete documentation for the WavespeedFlashVSRNode node in ComfyUI. Learn its inputs, outputs, parameters and usage.

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/WavespeedFlashVSRNode/en.md)

The WavespeedFlashVSRNode is a fast, high-quality video upscaler that boosts the resolution and restores clarity for low-resolution or blurry footage. It processes a video input and outputs a new video at a user-selected higher resolution.

## Inputs

| Parameter           | Data Type | Required | Range                                           | Description                                                                                                            |
| ------------------- | --------- | -------- | ----------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------- |
| `video`             | VIDEO     | Yes      | N/A                                             | The input video file to be upscaled. Must be in MP4 container format with a duration between 5 seconds and 10 minutes. |
| `target_resolution` | STRING    | Yes      | `"720p"`<br />`"1080p"`<br />`"2K"`<br />`"4K"` | The desired resolution for the upscaled output video.                                                                  |

**Input Constraints:**

* The input `video` file must be in the MP4 container format.
* The duration of the input `video` must be between 5 seconds and 10 minutes (600 seconds).

## Outputs

| Output Name | Data Type | Description                                                |
| ----------- | --------- | ---------------------------------------------------------- |
| `output`    | VIDEO     | The upscaled video file at the selected target resolution. |

***

**Source fingerprint (SHA-256):** `61381d911521ccb8848ef3512749d5cb9e047cd0c1c2bdfc000c5d3ef3360918`


# Getting Started
Source: https://docs.comfy.org/comfy-cli/getting-started



### Overview

`comfy-cli` is a [command line tool](https://github.com/Comfy-Org/comfy-cli) that makes it easier to install and manage Comfy.

It does two things:

1. **Manage a local ComfyUI install** — install, launch, update, snapshot, and bisect ComfyUI and its custom nodes.
2. **Call hosted partner nodes directly** — generate images and video from Seedance, Nano Banana (Gemini), Grok, Flux, Ideogram, DALL·E, Recraft, Stability, Kling, Luma, Runway, Pika, Vidu, Hailuo, Moonvalley, and more, with a single command. No local ComfyUI or workflow JSON required.

### Install CLI

<CodeGroup>
  ```bash pip theme={null}
  pip install comfy-cli
  ```

  ```bash homebrew theme={null}
  brew tap Comfy-Org/comfy-cli
  brew install comfy-org/comfy-cli/comfy-cli
  ```
</CodeGroup>

To get shell completion hints:

```bash theme={null}
comfy --install-completion
```

### Install ComfyUI

Create a virtual environment with any Python version greater than 3.9.

<CodeGroup>
  ```bash conda theme={null}
  conda create -n comfy-env python=3.11
  conda activate comfy-env
  ```

  ```bash venv theme={null}
  python3 -m venv comfy-env
  source comfy-env/bin/activate
  ```
</CodeGroup>

Install ComfyUI

```bash theme={null}
comfy install
```

<Warning>You still need to install CUDA, or ROCm depending on your GPU.</Warning>

### Run ComfyUI

```bash theme={null}
comfy launch
```

## Call partner nodes directly with `comfy generate` (Beta)

<Info>
  **`comfy generate` is in beta.** Flag names, model aliases, and output formats may change while we iron things out based on feedback. The underlying partner endpoints are stable — the CLI ergonomics on top of them are what's still evolving. File feedback or issues on the [comfy-cli GitHub repo](https://github.com/Comfy-Org/comfy-cli/issues).
</Info>

<Tip>
  `comfy generate` is the fastest way to call Comfy's [partner nodes](/tutorials/partner-nodes/overview) from a terminal or a script. It hits the same hosted endpoints you'd otherwise wire into a ComfyUI workflow, but as one-shot CLI calls — perfect for batch jobs, quick experiments, and automation pipelines where standing up a full ComfyUI graph is overkill.
</Tip>

### Prerequisites

* [Create a Comfy API key](/development/comfyui-server/api-key-integration)
* [Add credits to your account](/interface/credits)
* Optional: [Browse partner nodes and per-call pricing](/tutorials/partner-nodes/overview)

Set the key once, then go:

```bash theme={null}
export COMFY_API_KEY=comfyui-...   # or pass --api-key on each call
```

### Your first generation

```bash theme={null}
comfy generate flux-pro \
    --prompt "a cat on the moon, cinematic lighting" \
    --width 1024 --height 1024 \
    --download cat.png
```

That's it — the CLI uploads any local file inputs, submits the job, polls until it's ready, and saves the result to `cat.png`.

### Popular models

A few of the most-used partner models, callable with one line:

```bash theme={null}
# Nano Banana (Google Gemini Flash Image) — text-to-image and prompt-driven edits
comfy generate nano-banana \
    --prompt "a watercolor of a sleeping fox" \
    --download fox.png

# Same alias, now an image edit — pass a reference with --image (repeatable):
comfy generate nano-banana \
    --prompt "add a top hat" \
    --image ./cat.png \
    --download edited.png

# Pick a Gemini variant:
comfy generate nano-banana \
    --prompt "neon city skyline" \
    --model gemini-3-pro-image-preview \
    --download city.png

# Seedance (ByteDance) — text-to-video, up to 1080p / 12s clips
comfy generate seedance \
    --prompt "a hummingbird hovering over a flower" \
    --resolution 1080p --duration 5 \
    --download hummingbird.mp4

# Seedance image-to-video — pick a lite/i2v variant and pass a first frame
comfy generate seedance \
    --model seedance-1-0-lite-i2v-250428 \
    --prompt "the wave crests and crashes" \
    --image ./still.jpg \
    --download wave.mp4

# Grok (xAI) — image generation and editing
comfy generate grok --prompt "a cyberpunk street market at night" --download street.png
comfy generate grok-edit --prompt "swap the umbrella for a parasol" --image ./photo.jpg --download out.png

# Grok video
comfy generate grok-video --prompt "a paper plane gliding through a cathedral" --download flight.mp4
```

### Discover models

```bash theme={null}
comfy generate list                            # all available models
comfy generate list --category text-to-video   # filter by category
comfy generate list --partner kling            # filter by partner
comfy generate schema flux-kontext             # see the params for one model
```

### Image editing with a reference image

Pass local file paths directly — the CLI uploads them through Comfy's storage endpoint (or base64-encodes inline, depending on what each partner expects):

```bash theme={null}
comfy generate flux-kontext \
    --prompt "add a top hat and a monocle" \
    --input_image ./photo.jpg \
    --download out.png

comfy generate ideogram-edit \
    --image cat.png --mask mask.png \
    --prompt "add sunglasses" \
    --rendering_speed TURBO \
    --download edited.png
```

If you'd rather upload once and reuse the signed URL across many calls:

```bash theme={null}
comfy generate upload ./photo.jpg
# → prints a signed URL you can pass as --input_image
```

<Note>
  Uploaded reference assets are auto-deleted after **24 hours**. They're stored in a Comfy-managed GCS bucket and served via signed URLs. For most workflows (upload → use → done) this is transparent; for long-running pipelines, plan to re-upload before each job. See the [reference](/comfy-cli/reference#upload) for details.
</Note>

### Video generation (async jobs)

Video jobs are async — the CLI blocks and polls until ready by default:

```bash theme={null}
comfy generate kling \
    --prompt "a paper boat drifting on a river at dusk" \
    --duration 5 \
    --download boat.mp4
```

Pass `--async` to return immediately with a job id, then resume later:

```bash theme={null}
comfy generate luma --prompt "neon koi swimming through clouds" --aspect_ratio 16:9 --async
# → prints a job id; resume with:
comfy generate resume luma <job_id> --download out.mp4
```

### Scripting with JSON output

For pipelines, `--json` emits the raw API response:

```bash theme={null}
comfy generate dalle --prompt "a watercolor whale" --json | jq '.data[0].url'
```

See the [reference](/comfy-cli/reference) for the full list of commands, flags, and model aliases.

## Manage Custom Nodes

```bash theme={null}
comfy node install <NODE_NAME>
```

We use `cm-cli` for installing custom nodes. See the [docs](https://github.com/Comfy-Org/ComfyUI-Manager/blob/main/docs/en/cm-cli.md) for more information.

## Manage Models

Downloading models with `comfy-cli` is easy. Just run:

```bash theme={null}
comfy model download --url <url> --relative-path models/checkpoints
```

## Contributing

We encourage contributions to comfy-cli! If you have suggestions, ideas, or bug reports, please open an issue on our [GitHub repository](https://github.com/Comfy-Org/comfy-cli/issues). If you want to contribute code, fork the repository and submit a pull request.

Refer to the [Dev Guide](https://github.com/Comfy-Org/comfy-cli/blob/main/DEV_README.md) for further details.

## Analytics

We track usage of the CLI to improve the user experience. You can disable this by running:

```bash theme={null}
comfy tracking disable
```

To re-enable tracking, run:

```bash theme={null}
comfy tracking enable
```


# Reference
Source: https://docs.comfy.org/comfy-cli/reference



# CLI

## Generate (partner nodes) — Beta

<Info>
  **`comfy generate` is in beta.** Flag names, model aliases, and output formats may change. The underlying partner endpoints are stable; the CLI surface is still evolving. File feedback on the [comfy-cli GitHub repo](https://github.com/Comfy-Org/comfy-cli/issues).
</Info>

**Usage**:

```console theme={null}
$ comfy generate [OPTIONS] <MODEL_OR_ACTION> [--<param> value]...
```

`<MODEL_OR_ACTION>` is either:

* A **model alias** (e.g. `flux-pro`, `ideogram-edit`, `kling`, `dalle`) — calls that partner model directly.
* A **reserved action**: `list`, `schema`, `refresh`, `upload`, `resume`.

Anything not in the reserved set is treated as a model alias and the request is dispatched to that partner endpoint.

**Auth**:

Set the `COMFY_API_KEY` environment variable, or pass `--api-key <KEY>` on each call. Get a key at [platform.comfy.org](https://platform.comfy.org).

**Run-level flags** (work with any model):

* `--download PATH`: Save the result image/video to `PATH`.
* `--async`: Submit and return a job id immediately instead of polling to completion. Resume later with `comfy generate resume <model> <job_id>`.
* `--json`: Emit the raw API response as JSON (useful for scripting).
* `--timeout SECONDS`: Override the default 300s polling timeout.
* `--api-key KEY`: Inline API key (overrides `COMFY_API_KEY`).

**Examples**:

```bash theme={null}
comfy generate flux-pro --prompt "a cat on the moon" --width 1024 --height 1024 --download cat.png
comfy generate ideogram-edit --image cat.png --mask m.png --prompt "add sunglasses" --rendering_speed TURBO
comfy generate kling --prompt "a paper boat drifting at dusk" --duration 5 --download boat.mp4
```

### `list`

List available partner models with their short aliases.

**Usage**:

```console theme={null}
$ comfy generate list [OPTIONS]
```

**Options**:

* `--partner TEXT` / `-p TEXT`: Filter by partner (e.g. `bfl`, `kling`, `ideogram`, `openai`).
* `--category TEXT` / `--style TEXT` / `-c TEXT`: Filter by category (e.g. `text-to-image`, `image-edit`, `inpaint`, `upscale`, `text-to-video`, `image-to-video`).
* `--query TEXT` / `-q TEXT`: Substring match against model id/summary.

### `schema`

Show the parameters for a specific model, including required/optional flags, types, defaults, and an example invocation.

**Usage**:

```console theme={null}
$ comfy generate schema <MODEL>
```

**Example**:

```bash theme={null}
comfy generate schema flux-pro
comfy generate schema kling-i2v
```

### `refresh`

Refresh the local cached model catalog from the cloud OpenAPI spec. Useful when new partner models are added.

**Usage**:

```console theme={null}
$ comfy generate refresh
```

### `upload`

Upload a local file (or rehost a remote URL) to Comfy's storage and print the signed URL. Most models accept local file paths directly — this is for cases where you want the URL explicitly (e.g. to reuse the same asset across multiple calls).

**Usage**:

```console theme={null}
$ comfy generate upload <FILE_OR_URL> [--json]
```

**Example**:

```bash theme={null}
comfy generate upload ./photo.jpg
comfy generate upload ./photo.jpg --json
```

<Note>
  **Reference assets are auto-deleted after 24 hours.** Uploaded files (whether via `comfy generate upload` or implicitly when you pass a local file path to a model) are stored in a Comfy-managed GCS bucket (`api-nodes-prod`) and reachable only via a signed URL. Objects are automatically deleted **1 day after upload** by a bucket lifecycle rule. If you need an asset to persist across long-running async jobs, re-upload it before each job, or host it yourself and pass the URL directly.
</Note>

### `resume`

Resume a previously submitted async job (typically a video job submitted with `--async`). Polls until the result is ready and optionally downloads it.

**Usage**:

```console theme={null}
$ comfy generate resume <MODEL> <JOB_ID> [--download PATH] [--json]
```

**Example**:

```bash theme={null}
comfy generate resume luma 7c3f9e2a --download out.mp4
```

### Model aliases (selected)

The following short aliases are accepted as `<MODEL>`. Run `comfy generate list` for the full, up-to-date catalog.

**Popular**:

| Alias               | Partner                     | Category                               |
| ------------------- | --------------------------- | -------------------------------------- |
| `nano-banana`       | Google (Gemini Flash Image) | text-to-image / image-edit             |
| `seedance`          | ByteDance                   | text-to-video / image-to-video (async) |
| `grok`, `grok-edit` | xAI                         | text-to-image / image-edit             |
| `grok-video`        | xAI                         | text-to-video (async)                  |

**Everything else**:

| Alias                                                                                                                                                 | Partner    | Category                                                        |
| ----------------------------------------------------------------------------------------------------------------------------------------------------- | ---------- | --------------------------------------------------------------- |
| `flux-pro`, `flux-ultra`, `flux-2`                                                                                                                    | BFL        | text-to-image (async)                                           |
| `flux-kontext`, `flux-kontext-max`                                                                                                                    | BFL        | image-edit (async)                                              |
| `flux-fill`, `flux-expand`, `flux-canny`, `flux-depth`                                                                                                | BFL        | inpaint / outpaint / controlnet                                 |
| `ideogram`, `ideogram-edit`, `ideogram-remix`, `ideogram-reframe`, `ideogram-bg`                                                                      | Ideogram   | text-to-image / image-edit                                      |
| `dalle`, `dalle-edit`                                                                                                                                 | OpenAI     | text-to-image / image-edit                                      |
| `stability-ultra`, `stability-sd3`, `stability-upscale`, `stability-upscale-creative`, `stability-upscale-fast`                                       | Stability  | text-to-image / upscale                                         |
| `recraft`, `recraft-vectorize`, `recraft-rmbg`, `recraft-replace-bg`, `recraft-i2i`, `recraft-inpaint`, `recraft-upscale`, `recraft-upscale-creative` | Recraft    | text-to-image / image-edit                                      |
| `reve`, `reve-edit`                                                                                                                                   | Reve       | text-to-image / image-edit                                      |
| `runway`                                                                                                                                              | Runway     | text-to-image                                                   |
| `kling`, `kling-i2v`, `kling-extend`, `kling-lipsync`                                                                                                 | Kling      | text-to-video / image-to-video / video-extend / lipsync (async) |
| `luma`, `luma-i2v`                                                                                                                                    | Luma       | text-to-video / image-to-video (async)                          |
| `hailuo`                                                                                                                                              | MiniMax    | text-to-video (async)                                           |
| `runway-i2v`                                                                                                                                          | Runway     | image-to-video (async)                                          |
| `moonvalley-t2v`, `moonvalley-i2v`                                                                                                                    | Moonvalley | text-to-video / image-to-video (async)                          |
| `pika`, `pika-i2v`                                                                                                                                    | Pika       | text-to-video / image-to-video (async)                          |
| `vidu`, `vidu-i2v`, `vidu-extend`                                                                                                                     | Vidu       | text-to-video / image-to-video / video-extend (async)           |

## Nodes

**Usage**:

```console theme={null}
$ comfy node [OPTIONS] COMMAND [ARGS]...
```

**Options**:

* `--install-completion`: Install completion for the current shell.
* `--show-completion`: Show completion for the current shell, to copy it or customize the installation.
* `--help`: Show this message and exit.

**Commands**:

* `deps-in-workflow`
* `disable`
* `enable`
* `fix`
* `install`
* `install-deps`
* `reinstall`
* `restore-dependencies`
* `restore-snapshot`
* `save-snapshot`: Save a snapshot of the current ComfyUI...
* `show`
* `simple-show`
* `uninstall`
* `update`

### `deps-in-workflow`

**Usage**:

```console theme={null}
$ deps-in-workflow [OPTIONS]
```

**Options**:

* `--workflow TEXT`: Workflow file (.json/.png)  \[required]
* `--output TEXT`: Workflow file (.json/.png)  \[required]
* `--channel TEXT`: Specify the operation mode
* `--mode TEXT`: \[remote|local|cache]
* `--help`: Show this message and exit.

### `disable`

**Usage**:

```console theme={null}
$ disable [OPTIONS] ARGS...
```

**Arguments**:

* `ARGS...`: disable custom nodes  \[required]

**Options**:

* `--channel TEXT`: Specify the operation mode
* `--mode TEXT`: \[remote|local|cache]
* `--help`: Show this message and exit.

### `enable`

**Usage**:

```console theme={null}
$ enable [OPTIONS] ARGS...
```

**Arguments**:

* `ARGS...`: enable custom nodes  \[required]

**Options**:

* `--channel TEXT`: Specify the operation mode
* `--mode TEXT`: \[remote|local|cache]
* `--help`: Show this message and exit.

### `fix`

**Usage**:

```console theme={null}
$ fix [OPTIONS] ARGS...
```

**Arguments**:

* `ARGS...`: fix dependencies for specified custom nodes  \[required]

**Options**:

* `--channel TEXT`: Specify the operation mode
* `--mode TEXT`: \[remote|local|cache]
* `--help`: Show this message and exit.

### `install`

**Usage**:

```console theme={null}
$ install [OPTIONS] ARGS...
```

**Arguments**:

* `ARGS...`: install custom nodes  \[required]

**Options**:

* `--channel TEXT`: Specify the operation mode
* `--mode TEXT`: \[remote|local|cache]
* `--help`: Show this message and exit.

### `install-deps`

**Usage**:

```console theme={null}
$ install-deps [OPTIONS]
```

**Options**:

* `--deps TEXT`: Dependency spec file (.json)
* `--workflow TEXT`: Workflow file (.json/.png)
* `--channel TEXT`: Specify the operation mode
* `--mode TEXT`: \[remote|local|cache]
* `--help`: Show this message and exit.

### `reinstall`

**Usage**:

```console theme={null}
$ reinstall [OPTIONS] ARGS...
```

**Arguments**:

* `ARGS...`: reinstall custom nodes  \[required]

**Options**:

* `--channel TEXT`: Specify the operation mode
* `--mode TEXT`: \[remote|local|cache]
* `--help`: Show this message and exit.

### `restore-dependencies`

**Usage**:

```console theme={null}
$ restore-dependencies [OPTIONS]
```

**Options**:

* `--help`: Show this message and exit.

### `restore-snapshot`

**Usage**:

```console theme={null}
$ restore-snapshot [OPTIONS] PATH
```

**Arguments**:

* `PATH`: \[required]

**Options**:

* `--help`: Show this message and exit.

### `save-snapshot`

Save a snapshot of the current ComfyUI environment

**Usage**:

```console theme={null}
$ save-snapshot [OPTIONS]
```

**Options**:

* `--output TEXT`: Specify the output file path. (.json/.yaml)
* `--help`: Show this message and exit.

### `show`

**Usage**:

```console theme={null}
$ show [OPTIONS] ARGS...
```

**Arguments**:

* `ARGS...`: \[installed|enabled|not-installed|disabled|all|snapshot|snapshot-list]  \[required]

**Options**:

* `--channel TEXT`: Specify the operation mode
* `--mode TEXT`: \[remote|local|cache]
* `--help`: Show this message and exit.

### `simple-show`

**Usage**:

```console theme={null}
$ simple-show [OPTIONS] ARGS...
```

**Arguments**:

* `ARGS...`: \[installed|enabled|not-installed|disabled|all|snapshot|snapshot-list]  \[required]

**Options**:

* `--channel TEXT`: Specify the operation mode
* `--mode TEXT`: \[remote|local|cache]
* `--help`: Show this message and exit.

### `uninstall`

**Usage**:

```console theme={null}
$ uninstall [OPTIONS] ARGS...
```

**Arguments**:

* `ARGS...`: uninstall custom nodes  \[required]

**Options**:

* `--channel TEXT`: Specify the operation mode
* `--mode TEXT`: \[remote|local|cache]
* `--help`: Show this message and exit.

### `update`

**Usage**:

```console theme={null}
$ update [OPTIONS] ARGS...
```

**Arguments**:

* `ARGS...`: update custom nodes  \[required]

**Options**:

* `--channel TEXT`: Specify the operation mode
* `--mode TEXT`: \[remote|local|cache]
* `--help`: Show this message and exit.

## Models

**Usage**:

```console theme={null}
$ comfy model [OPTIONS] COMMAND [ARGS]...
```

**Options**:

* `--install-completion`: Install completion for the current shell.
* `--show-completion`: Show completion for the current shell, to copy it or customize the installation.
* `--help`: Show this message and exit.

**Commands**:

* `download`: Download a model to a specified relative...
* `list`: Display a list of all models currently...
* `remove`: Remove one or more downloaded models,...

### `download`

Download a model to a specified relative path if it is not already downloaded.

**Usage**:

```console theme={null}
$ download [OPTIONS]
```

**Options**:

* `--url TEXT`: The URL from which to download the model  \[required]
* `--relative-path TEXT`: The relative path from the current workspace to install the model.  \[default: models/checkpoints]
* `--help`: Show this message and exit.

### `list`

Display a list of all models currently downloaded in a table format.

**Usage**:

```console theme={null}
$ list [OPTIONS]
```

**Options**:

* `--relative-path TEXT`: The relative path from the current workspace where the models are stored.  \[default: models/checkpoints]
* `--help`: Show this message and exit.

### `remove`

Remove one or more downloaded models, either by specifying them directly or through an interactive selection.

**Usage**:

```console theme={null}
$ remove [OPTIONS]
```

**Options**:

* `--relative-path TEXT`: The relative path from the current workspace where the models are stored.  \[default: models/checkpoints]
* `--model-names TEXT`: List of model filenames to delete, separated by spaces
* `--help`: Show this message and exit.


# Getting Started
Source: https://docs.comfy.org/comfy-cli/troubleshooting



### Prerequisites

You need to have git installed on your system. Install it [here](https://git-scm.com/downloads).


# Contributing
Source: https://docs.comfy.org/community/contributing



### How to contribute

We welcome contributions of all kinds. Check out the various repositories we support on our [Github organization](https://github.com/Comfy-Org).

You can also contribute by sharing workflows or developing [custom nodes](/custom-nodes/overview).


# Community links
Source: https://docs.comfy.org/community/links

Connect with the ComfyUI community through various platforms

Join the ComfyUI community and get help, share your work, and stay updated with the latest developments.

<CardGroup>
  <Card title="Discord" icon="discord" href="https://discord.gg/comfyorg">
    Join our Discord community
  </Card>

  <Card title="Support Portal" icon="life-ring" href="https://support.comfy.org/">
    Get help and support
  </Card>

  <Card title="Forum" icon="comments" href="https://forum.comfy.org/">
    Join community discussions
  </Card>

  <Card title="Matrix" icon="hashtag" href="https://app.element.io/#/room/%23comfyui_space%3Amatrix.org">
    Chat on Matrix
  </Card>

  <Card title="GitHub" icon="github" href="https://github.com/Comfy-Org/ComfyUI/">
    View source code
  </Card>

  <Card title="YouTube" icon="youtube" href="https://www.youtube.com/@comfyorg">
    Watch tutorials
  </Card>

  <Card title="X (Twitter)" icon="x-twitter" href="https://x.com/ComfyUI">
    Follow us on X
  </Card>

  <Card title="LinkedIn" icon="linkedin" href="https://www.linkedin.com/company/comfyui/">
    Connect on LinkedIn
  </Card>

  <Card title="Reddit" icon="reddit" href="https://www.reddit.com/r/comfyui/">
    Join our subreddit
  </Card>
</CardGroup>


# Datatypes
Source: https://docs.comfy.org/custom-nodes/backend/datatypes



These are the most important built in datatypes. You can also [define your own](./more_on_inputs#custom-datatypes).

Datatypes are used on the client side to prevent a workflow from passing the wrong form of data into a node - a bit like strong typing.
The JavaScript client side code will generally not allow a node output to be connected to an input of a different datatype,
although a few exceptions are noted below.

## Comfy datatypes

### COMBO

* No additional parameters in `INPUT_TYPES`

* Python datatype: defined as `list[str]`, output value is `str`

Represents a dropdown menu widget.
Unlike other datatypes, `COMBO` it is not specified in `INPUT_TYPES` by a `str`, but by a `list[str]`
corresponding to the options in the dropdown list, with the first option selected by default.

`COMBO` inputs are often dynamically generated at run time. For instance, in the built-in `CheckpointLoaderSimple` node, you find

```
"ckpt_name": (folder_paths.get_filename_list("checkpoints"), )
```

or they might just be a fixed list of options,

```
"play_sound": (["no","yes"], {}),
```

### Primitive and reroute

Primitive and reroute nodes only exist on the client side. They do not have an intrinsic datatype, but when connected they take on
the datatype of the input or output to which they have been connected (which is why they can't connect to a `*` input...)

## Python datatypes

### INT

* Additional parameters in `INPUT_TYPES`:

  * `default` is required

  * `min` and `max` are optional

* Python datatype `int`

### FLOAT

* Additional parameters in `INPUT_TYPES`:

  * `default` is required

  * `min`, `max`, `step` are optional

* Python datatype `float`

### STRING

* Additional parameters in `INPUT_TYPES`:

  * `default` is required

* Python datatype `str`

### BOOLEAN

* Additional parameters in `INPUT_TYPES`:

  * `default` is required

* Python datatype `bool`

## Tensor datatypes

### IMAGE

* No additional parameters in `INPUT_TYPES`

* Python datatype `torch.Tensor` with *shape* \[B,H,W,C]

A batch of `B` images, height `H`, width `W`, with `C` channels (generally `C=3` for `RGB`).

### LATENT

* No additional parameters in `INPUT_TYPES`

* Python datatype `dict`, containing a `torch.Tensor` with *shape* \[B,C,H,W]

The `dict` passed contains the key `samples`, which is a `torch.Tensor` with *shape* \[B,C,H,W] representing
a batch of `B` latents, with `C` channels (generally `C=4` for existing stable diffusion models), height `H`, width `W`.

The height and width are 1/8 of the corresponding image size (which is the value you set in the Empty Latent Image node).

Other entries in the dictionary contain things like latent masks.

### MASK

* No additional parameters in `INPUT_TYPES`

* Python datatype `torch.Tensor` with *shape* \[H,W] or \[B,C,H,W]

### AUDIO

* No additional parameters in `INPUT_TYPES`

* Python datatype `dict`, containing a `torch.Tensor` with *shape* \[B, C, T] and a sample rate.

The `dict` passed contains the key `waveform`, which is a `torch.Tensor` with *shape* \[B, C, T] representing a batch of `B` audio samples, with `C` channels (`C=2` for stereo and `C=1` for mono), and `T` time steps (i.e., the number of audio samples).

The `dict` contains another key `sample_rate`, which indicates the sampling rate of the audio.

## Custom Sampling datatypes

### Noise

The `NOISE` datatype represents a *source* of noise (not the actual noise itself). It can be represented by any Python object
that provides a method to generate noise, with the signature `generate_noise(self, input_latent:Tensor) -> Tensor`, and a
property, `seed:Optional[int]`.

<Tip>The `seed` is passed into `sample` guider in the `SamplerCustomAdvanced`, but does not appear to be used in any of the standard guiders.
It is Optional, so you can generally set it to None.</Tip>

When noise is to be added, the latent is passed into this method, which should return a `Tensor` of the same shape containing the noise.

See the [noise mixing example](./snippets#creating-noise-variations)

### Sampler

The `SAMPLER` datatype represents a sampler, which is represented as a Python object providing a `sample` method.
Stable diffusion sampling is beyond the scope of this guide; see `comfy/samplers.py` if you want to dig into this part of the code.

### Sigmas

The `SIGMAS` datatypes represents the values of sigma before and after each step in the sampling process, as produced by a scheduler.
This is represented as a one-dimensional tensor, of length `steps+1`, where each element represents the noise expected to be present
before the corresponding step, with the final value representing the noise present after the final step.

A `normal` scheduler, with 20 steps and denoise of 1, for an SDXL model, produces:

```
tensor([14.6146, 10.7468,  8.0815,  6.2049,  4.8557,  
         3.8654,  3.1238,  2.5572,  2.1157,  1.7648,  
         1.4806,  1.2458,  1.0481,  0.8784,  0.7297,  
         0.5964,  0.4736,  0.3555,  0.2322,  0.0292,  0.0000])
```

<Tip>The starting value of sigma depends on the model, which is why a scheduler node requires a `MODEL` input to produce a SIGMAS output</Tip>

### Guider

A `GUIDER` is a generalisation of the denoising process, as 'guided' by a prompt or any other form of conditioning. In Comfy the guider is
represented by a `callable` Python object providing a `__call__(*args, **kwargs)` method which is called by the sample.

The `__call__` method takes (in `args[0]`) a batch of noisy latents (tensor `[B,C,H,W]`), and returns a prediction of the noise (a tensor of the same shape).

## Model datatypes

There are a number of more technical datatypes for stable diffusion models. The most significant ones are `MODEL`, `CLIP`, `VAE` and `CONDITIONING`.
Working with these is (for the time being) beyond the scope of this guide!&#x20;

## Additional Parameters

Below is a list of officially supported keys that can be used in the 'extra options' portion of an input definition.

<Warning>You can use additional keys for your own custom widgets, but should *not* reuse any of the keys below for other purposes.</Warning>

| Key              | Description                                                                                                                                                                                      |
| ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `default`        | The default value of the widget                                                                                                                                                                  |
| `min`            | The minimum value of a number (`FLOAT` or `INT`)                                                                                                                                                 |
| `max`            | The maximum value of a number (`FLOAT` or `INT`)                                                                                                                                                 |
| `step`           | The amount to increment or decrement a widget                                                                                                                                                    |
| `label_on`       | The label to use in the UI when the bool is `True` (`BOOL`)                                                                                                                                      |
| `label_off`      | The label to use in the UI when the bool is `False` (`BOOL`)                                                                                                                                     |
| `defaultInput`   | Defaults to an input socket rather than a supported widget                                                                                                                                       |
| `forceInput`     | `defaultInput` and also don't allow converting to a widget                                                                                                                                       |
| `multiline`      | Use a multiline text box (`STRING`)                                                                                                                                                              |
| `placeholder`    | Placeholder text to display in the UI when empty (`STRING`)                                                                                                                                      |
| `dynamicPrompts` | Causes the front-end to evaluate dynamic prompts                                                                                                                                                 |
| `lazy`           | Declares that this input uses [Lazy Evaluation](./lazy_evaluation)                                                                                                                               |
| `rawLink`        | When a link exists, rather than receiving the evaluated value, you will receive the link (i.e. `["nodeId", <outputIndex>]`). Primarily useful when your node uses [Node Expansion](./expansion). |


# Node Expansion
Source: https://docs.comfy.org/custom-nodes/backend/expansion



## Node Expansion

Normally, when a node is executed, that execution function immediately returns the output results of that node. "Node Expansion" is a relatively advanced technique that allows nodes to return a new subgraph of nodes that should take its place in the graph. This technique is what allows custom nodes to implement loops.

### A Simple Example

First, here's a simple example of what node expansion looks like:

<Tip>We highly recommend using the `GraphBuilder` class when creating subgraphs. It isn't mandatory, but it prevents you from making many easy mistakes.</Tip>

```python theme={null}
def load_and_merge_checkpoints(self, checkpoint_path1, checkpoint_path2, ratio):
    from comfy_execution.graph_utils import GraphBuilder # Usually at the top of the file
    graph = GraphBuilder()
    checkpoint_node1 = graph.node("CheckpointLoaderSimple", checkpoint_path=checkpoint_path1)
    checkpoint_node2 = graph.node("CheckpointLoaderSimple", checkpoint_path=checkpoint_path2)
    merge_model_node = graph.node("ModelMergeSimple", model1=checkpoint_node1.out(0), model2=checkpoint_node2.out(0), ratio=ratio)
    merge_clip_node = graph.node("ClipMergeSimple", clip1=checkpoint_node1.out(1), clip2=checkpoint_node2.out(1), ratio=ratio)
    return {
        # Returning (MODEL, CLIP, VAE) outputs
        "result": (merge_model_node.out(0), merge_clip_node.out(0), checkpoint_node1.out(2)),
        "expand": graph.finalize(),
    }
```

While this same node could previously be implemented by manually calling into ComfyUI internals, using expansion means that each subnode will be cached separately (so if you change `model2`, you don't have to reload `model1`).

### Requirements

In order to perform node expansion, a node must return a dictionary with the following keys:

1. `result`: A tuple of the outputs of the node. This may be a mix of finalized values (like you would return from a normal node) and node outputs.
2. `expand`: The finalized graph to perform expansion on. See below if you are not using the `GraphBuilder`.

#### Additional Requirements if not using GraphBuilder

The format expected from the `expand` key is the same as the ComfyUI API format. The following requirements are handled by the `GraphBuilder`, but must be handled manually if you choose to forego it:

1. Node IDs must be unique across the entire graph. (This includes between multiple executions of the same node due to the use of lists.)
2. Node IDs must be deterministic and consistent between multiple executions of the graph (including partial executions due to caching).

Even if you don't want to use the `GraphBuilder` for actually building the graph (e.g. because you're loading the raw json of the graph from a file), you can use the `GraphBuilder.alloc_prefix()` function to generate a prefix and `comfy.graph_utils.add_graph_prefix` to fix existing graphs to meet these requirements.

### Efficient Subgraph Caching

While you can pass non-literal inputs to nodes within the subgraph (like torch tensors), this can inhibit caching *within* the subgraph. When possible, you should pass links to subgraph objects rather than the node itself. (You can declare an input as a `rawLink` within the input's [Additional Parameters](./datatypes#additional-parameters) to do this easily.)

## See Also

* [Subgraphs (Developer Guide)](/custom-nodes/js/subgraphs) — Frontend guide for extension authors


# Images, Latents, and Masks
Source: https://docs.comfy.org/custom-nodes/backend/images_and_masks



When working with these datatypes, you will need to know about the `torch.Tensor` class.
Complete documentation is [here](https://pytorch.org/docs/stable/tensors.html), or
an introduction to the key concepts required for Comfy [here](./tensors).

<Warning>If your node has a single output which is a tensor, remember to return `(image,)` not `(image)`</Warning>

Most of the concepts below are illustrated in the [example code snippets](./snippets).

## Images

An IMAGE is a `torch.Tensor` with shape `[B,H,W,C]`, `C=3`. If you are going to save or load images, you will
need to convert to and from `PIL.Image` format - see the code snippets below! Note that some `pytorch` operations
offer (or expect) `[B,C,H,W]`, known as 'channel first', for reasons of computational efficiency. Just be careful.

### Working with PIL.Image

If you want to load and save images, you'll want to use PIL:

```python theme={null}
from PIL import Image, ImageOps
```

## Masks

A MASK is a `torch.Tensor` with shape `[B,H,W]`.
In many contexts, masks have binary values (0 or 1), which are used to indicate which pixels should undergo specific operations.
In some cases values between 0 and 1 are used indicate an extent of masking, (for instance, to alter transparency, adjust filters, or composite layers).

### Masks from the Load Image Node

The `LoadImage` node uses an image's alpha channel (the "A" in "RGBA") to create MASKs.
The values from the alpha channel are normalized to the range \[0,1] (torch.float32) and then inverted.
The `LoadImage` node always produces a MASK output when loading an image. Many images (like JPEGs) don't have an alpha channel.
In these cases, `LoadImage` creates a default mask with the shape `[1, 64, 64]`.

### Understanding Mask Shapes

In libraries like `numpy`, `PIL`, and many others, single-channel images (like masks) are typically represented as 2D arrays, shape `[H,W]`.
This means the `C` (channel) dimension is implicit, and thus unlike IMAGE types, batches of MASKs have only three dimensions: `[B, H, W]`.
It is not uncommon to encounter a mask which has had the `B` dimension implicitly squeezed, giving a tensor `[H,W]`.

To use a MASK, you will often have to match shapes by unsqueezing to produce a shape `[B,H,W,C]` with `C=1`
To unsqueezing the `C` dimension, so you should `unsqueeze(-1)`, to unsqueeze `B`, you `unsqueeze(0)`.
If your node receives a MASK as input, you would be wise to always check `len(mask.shape)`.

## Latents

A LATENT is a `dict`; the latent sample is referenced by the key `samples` and has shape `[B,C,H,W]`, with `C=4`.

<Tip>LATENT is channel first, IMAGE is channel last</Tip>


# Lazy Evaluation
Source: https://docs.comfy.org/custom-nodes/backend/lazy_evaluation



## Lazy Evaluation

By default, all `required` and `optional` inputs are evaluated before a node can be run. Sometimes, however, an
input won't necessarily be used and evaluating it would result in unnecessary processing. Here are some examples
of nodes where lazy evaluation may be beneficial:

1. A `ModelMergeSimple` node where the ratio is either `0.0` (in which case the first model doesn't need to be loaded)
   or `1.0` (in which case the second model doesn't need to be loaded).
2. Interpolation between two images where the ratio (or mask) is either entirely `0.0` or entirely `1.0`.
3. A Switch node where one input determines which of the other inputs will be passed through.

<Tip>There is very little cost in making an input lazy. If it's something you can do, you generally should.</Tip>

### Creating Lazy Inputs

There are two steps to making an input a "lazy" input. They are:

1. Mark the input as lazy in the dictionary returned by `INPUT_TYPES`
2. Define a method named `check_lazy_status` (note: *not* a class method) that will be called prior to evaluation to determine if any more inputs are necessary.

To demonstrate these, we'll make a "MixImages" node that interpolates between two images according to a mask. If the entire mask is `0.0`, we don't need to evaluate any part of the tree leading up to the second image. If the entire mask is `1.0`, we can skip evaluating the first image.

#### Defining `INPUT_TYPES`

Declaring that an input is lazy is as simple as adding a `lazy: True` key-value pair to the input's options dictionary.

```python theme={null}
@classmethod
def INPUT_TYPES(cls):
    return {
        "required": {
            "image1": ("IMAGE",{"lazy": True}),
            "image2": ("IMAGE",{"lazy": True}),
            "mask": ("MASK",),
        },
    }
```

In this example, `image1` and `image2` are both marked as lazy inputs, but `mask` will always be evaluated.

#### Defining `check_lazy_status`

A `check_lazy_status` method is called if there are one or more lazy inputs that are not yet available. This method receives the same arguments as the standard execution function. All available inputs are passed in with their final values while unavailable lazy inputs have a value of `None`.

The responsibility of the `check_lazy_status` function is to return a list of the names of any lazy inputs that are needed to proceed. If all lazy inputs are available, the function should return an empty list.

Note that `check_lazy_status` may be called multiple times. (For example, you might find after evaluating one lazy input that you need to evaluate another.)

<Tip>Note that because the function uses actual input values, it is *not* a class method.</Tip>

```python theme={null}
def check_lazy_status(self, mask, image1, image2):
    mask_min = mask.min()
    mask_max = mask.max()
    needed = []
    if image1 is None and (mask_min != 1.0 or mask_max != 1.0):
        needed.append("image1")
    if image2 is None and (mask_min != 0.0 or mask_max != 0.0):
        needed.append("image2")
    return needed
```

### Full Example

```python theme={null}
class LazyMixImages:
    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "image1": ("IMAGE",{"lazy": True}),
                "image2": ("IMAGE",{"lazy": True}),
                "mask": ("MASK",),
            },
        }

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "mix"

    CATEGORY = "Examples"

    def check_lazy_status(self, mask, image1, image2):
        mask_min = mask.min()
        mask_max = mask.max()
        needed = []
        if image1 is None and (mask_min != 1.0 or mask_max != 1.0):
            needed.append("image1")
        if image2 is None and (mask_min != 0.0 or mask_max != 0.0):
            needed.append("image2")
        return needed

    # Not trying to handle different batch sizes here just to keep the demo simple
    def mix(self, mask, image1, image2):
        mask_min = mask.min()
        mask_max = mask.max()
        if mask_min == 0.0 and mask_max == 0.0:
            return (image1,)
        elif mask_min == 1.0 and mask_max == 1.0:
            return (image2,)

        result = image1 * (1. - mask) + image2 * mask,
        return (result[0],)
```

## Execution Blocking

While Lazy Evaluation is the recommended way to "disable" part of a graph, there are times when you want to disable an `OUTPUT` node that doesn't implement lazy evaluation itself. If it's an output node that you developed yourself, you should just add lazy evaluation as follows:

1. Add a required (if this is a new node) or optional (if you care about backward compatibility) input for `enabled` that defaults to `True`
2. Make all other inputs `lazy` inputs
3. Only evaluate the other inputs if `enabled` is `True`

If it's not a node you control, you can make use of a `comfy_execution.graph.ExecutionBlocker`. This special object can be returned as an output from any socket. Any nodes which receive an `ExecutionBlocker` as input will skip execution and return that `ExecutionBlocker` for any outputs.

<Tip>**There is intentionally no way to stop an ExecutionBlocker from propagating forward.** If you think you want this, you should really be using Lazy Evaluation.</Tip>

### Usage

There are two ways to construct and use an `ExecutionBlocker`

1. Pass `None` into the constructor to silently block execution. This is useful for cases where blocking execution is part of a successful run -- like disabling an output.

```python theme={null}
def silent_passthrough(self, passthrough, blocked):
    if blocked:
        return (ExecutionBlocker(None),)
    else:
        return (passthrough,)
```

2. Pass a string into the constructor to display an error message when a node is blocked due to receiving the object. This can be useful if you want to display a meaningful error message if someone uses a meaningless output -- for example, the `VAE` output when loading a model that doesn't contain VAEs.

```python theme={null}
def load_checkpoint(self, ckpt_name):
    ckpt_path = folder_paths.get_full_path("checkpoints", ckpt_name)
    model, clip, vae = load_checkpoint(ckpt_path)
    if vae is None:
        # This error is more useful than a "'NoneType' has no attribute" error
        # in a later node
        vae = ExecutionBlocker(f"No VAE contained in the loaded model {ckpt_name}")
    return (model, clip, vae)
```


# Lifecycle
Source: https://docs.comfy.org/custom-nodes/backend/lifecycle



## How Comfy loads custom nodes

When Comfy starts, it scans the directory `custom_nodes` for Python modules, and attempts to load them.
If the module exports `NODE_CLASS_MAPPINGS`, it will be treated as a custom node.
<Tip>A python module is a directory containing an `__init__.py` file.
The module exports whatever is listed in the `__all__` attribute defined in `__init__.py`.</Tip>

### **init**.py

`__init__.py` is executed when Comfy attempts to import the module. For a module to be recognized as containing
custom node definitions, it needs to export `NODE_CLASS_MAPPINGS`. If it does (and if nothing goes wrong in the import),
the nodes defined in the module will be available in Comfy. If there is an error in your code,
Comfy will continue, but will report the module as having failed to load. So check the Python console!

A very simple `__init__.py` file would look like this:

```python theme={null}
from .python_file import MyCustomNode
NODE_CLASS_MAPPINGS = { "My Custom Node" : MyCustomNode }
__all__ = ["NODE_CLASS_MAPPINGS"]
```

#### NODE\_CLASS\_MAPPINGS

`NODE_CLASS_MAPPINGS` must be a `dict` mapping custom node names (unique across the Comfy install)
to the corresponding node class.

#### NODE\_DISPLAY\_NAME\_MAPPINGS

`__init__.py` may also export `NODE_DISPLAY_NAME_MAPPINGS`, which maps the same unique name to a display name for the node.
If `NODE_DISPLAY_NAME_MAPPINGS` is not provided, Comfy will use the unique name as the display name.

#### WEB\_DIRECTORY

If you are deploying client side code, you will also need to export the path, relative to the module, in which the
JavaScript files are to be found. It is conventional to place these in a subdirectory of your custom node named `js`.
<Tip>*Only* `.js` files will be served; you can't deploy `.css` or other types in this way</Tip>

<Warning>In previous versions of Comfy, `__init__.py` was required to copy the JavaScript files into the main Comfy web
subdirectory. You will still see code that does this. Don't.</Warning>


# Data lists
Source: https://docs.comfy.org/custom-nodes/backend/lists



## Length one processing

Internally, the Comfy server represents data flowing from one node to the next as a Python `list`, normally length 1, of the relevant datatype.
In normal operation, when a node returns an output, each element in the output `tuple` is separately wrapped in a list (length 1); then when the
next node is called, the data is unwrapped and passed to the main function.

<Tip>You generally don't need to worry about this, since Comfy does the wrapping and unwrapping.</Tip>

<Tip>This isn't about batches. A batch (of, for instance, latents, or images) is a *single entry* in the list (see [tensor datatypes](./images_and_masks))</Tip>

## List processing

In some circumstance, multiple data instances are processed in a single workflow, in which case the internal data will be a list containing the data instances.
An example of this might be processing a series of images one at a time to avoid running out of VRAM, or handling images of different sizes.

By default, Comfy will process the values in the list sequentially:

* if the inputs are `list`s of different lengths, the shorter ones are padded by repeating the last value
* the main method is called once for each value in the input lists
* the outputs are `list`s, each of which is the same length as the longest input

The relevant code can be found in the method `map_node_over_list` in `execution.py`.

However, as Comfy wraps node outputs into a `list` of length one, if the `tuple` returned by
a custom node contains a `list`, that `list` will be wrapped, and treated as a single piece of data.
In order to tell Comfy that the list being returned should not be wrapped, but treated as a series of data for sequential processing,
the node should provide a class attribute `OUTPUT_IS_LIST`, which is a `tuple[bool]`, of the same length as `RETURN_TYPES`, specifying
which outputs which should be so treated.

A node can also override the default input behaviour and receive the whole list in a single call. This is done by setting a class attribute
`INPUT_IS_LIST` to `True`.

Here's a (lightly annotated) example from the built in nodes - `ImageRebatch` takes one or more batches of images (received as a list, because `INPUT_IS_LIST - True`)
and rebatches them into batches of the requested size.

<Tip>`INPUT_IS_LIST` is node level - all inputs get the same treatment. So the value of the `batch_size` widget is given by `batch_size[0]`.</Tip>

```Python theme={null}

class ImageRebatch:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": { "images": ("IMAGE",),
                              "batch_size": ("INT", {"default": 1, "min": 1, "max": 4096}) }}
    RETURN_TYPES = ("IMAGE",)
    INPUT_IS_LIST = True
    OUTPUT_IS_LIST = (True, )
    FUNCTION = "rebatch"
    CATEGORY = "image/batch"

    def rebatch(self, images, batch_size):
        batch_size = batch_size[0]    # everything comes as a list, so batch_size is list[int]

        output_list = []
        all_images = []
        for img in images:                    # each img is a batch of images
            for i in range(img.shape[0]):     # each i is a single image
                all_images.append(img[i:i+1])

        for i in range(0, len(all_images), batch_size): # take batch_size chunks and turn each into a new batch
            output_list.append(torch.cat(all_images[i:i+batch_size], dim=0))  # will die horribly if the image batches had different width or height!

        return (output_list,)
```

#### INPUT\_IS\_LIST


# Hidden and Flexible inputs
Source: https://docs.comfy.org/custom-nodes/backend/more_on_inputs



## Hidden inputs

Alongside the `required` and `optional` inputs, which create corresponding inputs or widgets on the client-side,
there are three `hidden` input options which allow the custom node to request certain information from the server.

These are accessed by returning a value for `hidden` in the `INPUT_TYPES` `dict`, with the signature `dict[str,str]`,
containing one or more of `PROMPT`, `EXTRA_PNGINFO`, or `UNIQUE_ID`

```python theme={null}
@classmethod
def INPUT_TYPES(s):
    return {
        "required": {...},
        "optional": {...},
        "hidden": {
            "unique_id": "UNIQUE_ID",
            "prompt": "PROMPT", 
            "extra_pnginfo": "EXTRA_PNGINFO",
        }
    }
```

### UNIQUE\_ID

`UNIQUE_ID` is the unique identifier of the node, and matches the `id` property of the node on the client side.
It is commonly used in client-server communications (see [messages](/development/comfyui-server/comms_messages#getting-node-id)).

### PROMPT

`PROMPT` is the complete prompt sent by the client to the server.
See [the prompt object](/custom-nodes/js/javascript_objects_and_hijacking#prompt) for a full description.

### EXTRA\_PNGINFO

`EXTRA_PNGINFO` is a dictionary that will be copied into the metadata of any `.png` files saved. Custom nodes can store additional
information in this dictionary for saving (or as a way to communicate with a downstream node).

<Tip>Note that if Comfy is started with the `disable_metadata` option, this data won't be saved.</Tip>

### DYNPROMPT

`DYNPROMPT` is an instance of `comfy_execution.graph.DynamicPrompt`. It differs from `PROMPT` in that it may mutate during the course of execution in response to [Node Expansion](/custom-nodes/backend/expansion).
<Tip>`DYNPROMPT` should only be used for advanced cases (like implementing loops in custom nodes).</Tip>

## Flexible inputs

### Custom datatypes

If you want to pass data between your own custom nodes, you may find it helpful to define a custom datatype. This is (almost) as simple as
just choosing a name for the datatype, which should be a unique string in upper case, such as `CHEESE`.

You can then use `CHEESE` in your node `INPUT_TYPES` and `RETURN_TYPES`, and the Comfy client will only allow `CHEESE` outputs to connect to a `CHEESE` input.
`CHEESE` can be any python object.

The only point to note is that because the Comfy client doesn't know about `CHEESE` you need (unless you define a custom widget for `CHEESE`,
which is a topic for another day), to force it to be an input rather than a widget. This can be done with the `forceInput` option in the input options dictionary:

```python theme={null}
@classmethod
def INPUT_TYPES(s):
    return {
        "required": { "my_cheese": ("CHEESE", {"forceInput":True}) }
    }
```

### Wildcard inputs

```python theme={null}
@classmethod
def INPUT_TYPES(s):
    return {
        "required": { "anything": ("*",{})},
    }

@classmethod
def VALIDATE_INPUTS(s, input_types):
    return True
```

The frontend allows `*` to indicate that an input can be connected to any source. Because this is not officially supported by the backend, you can skip the backend validation of types by accepting a parameter named `input_types` in your `VALIDATE_INPUTS` function. (See [VALIDATE\_INPUTS](./server_overview#validate-inputs) for more information.)
It's up to the node to make sense of the data that is passed.

### Dynamically created inputs

If inputs are dynamically created on the client side, they can't be defined in the Python source code.
In order to access this data we need an `optional` dictionary that allows Comfy to pass data with
arbitrary names. Since the Comfy server

```python theme={null}
class ContainsAnyDict(dict):
    def __contains__(self, key):
        return True
...

@classmethod
def INPUT_TYPES(s):
    return {
        "required": {},
        "optional": ContainsAnyDict()
    }
...

def main_method(self, **kwargs):
    # the dynamically created input data will be in the dictionary kwargs

```

<Tip>Hat tip to rgthree for this pythonic trick!</Tip>


# Node replacement
Source: https://docs.comfy.org/custom-nodes/backend/node-replacement

Register node replacements to help users migrate from deprecated nodes

The Node Replacement API allows custom node developers to define migration paths from deprecated nodes to their newer equivalents. When you update or rename nodes, users can automatically upgrade their workflows.

## When to use

* **Changing node class names**: You changed a node's class name (use `DISPLAY_NAME` for display name changes instead)
* **Merging nodes**: Multiple nodes consolidated into one (e.g., `Load3DAnimation` merged into `Load3D`)
* **Refactoring inputs**: Input names or types changed between versions
* **Fixing typos**: Correcting node names without breaking existing workflows

## Where to register replacements

Register replacements during your extension's `on_load` lifecycle hook. Create a dedicated file (e.g., `node_replacements.py`) in your custom node package:

```
my_custom_nodes/
├── __init__.py
├── nodes.py
└── node_replacements.py   # Register replacements here
```

## Complete example

Here's a full example showing how to structure node replacements in a custom node package:

```python theme={null}
# node_replacements.py
from comfy_api.latest import ComfyExtension, io, ComfyAPI

api = ComfyAPI()


async def register_my_replacements():
    """Register all node replacements for this package."""
    
    # Simple rename - no input changes needed
    await api.node_replacement.register(io.NodeReplace(
        new_node_id="MyNewNode",
        old_node_id="MyOldNode",
    ))
    
    # Complex replacement with input mapping
    await api.node_replacement.register(io.NodeReplace(
        new_node_id="MyImprovedSampler",
        old_node_id="MyOldSampler",
        old_widget_ids=["steps", "cfg"],
        input_mapping=[
            {"new_id": "model", "old_id": "model"},
            {"new_id": "num_steps", "old_id": "steps"},
            {"new_id": "guidance", "old_id": "cfg"},
            {"new_id": "scheduler", "set_value": "normal"},  # New input with default
        ],
        output_mapping=[
            {"new_idx": 0, "old_idx": 0},
        ],
    ))


class MyExtension(ComfyExtension):
    async def on_load(self) -> None:
        await register_my_replacements()

    async def get_node_list(self) -> list[type[io.ComfyNode]]:
        return []  # No nodes defined here, just replacements


async def comfy_entrypoint() -> MyExtension:
    return MyExtension()
```

## Core examples

ComfyUI core uses node replacements for built-in node migrations. Here are real examples from [`comfy_extras/nodes_replacements.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/comfy_extras/nodes_replacements.py):

### Simple node merge

When `Load3DAnimation` was merged into `Load3D`:

```python theme={null}
await api.node_replacement.register(io.NodeReplace(
    new_node_id="Load3D",
    old_node_id="Load3DAnimation",
))
```

### Typo fix

Correcting a typo in `SDV_img2vid_Conditioning` → `SVD_img2vid_Conditioning`:

```python theme={null}
await api.node_replacement.register(io.NodeReplace(
    new_node_id="SVD_img2vid_Conditioning",
    old_node_id="SDV_img2vid_Conditioning",
))
```

### Input renaming with defaults

Replacing `ImageScaleBy` with `ResizeImageMaskNode`:

```python theme={null}
await api.node_replacement.register(io.NodeReplace(
    new_node_id="ResizeImageMaskNode",
    old_node_id="ImageScaleBy",
    old_widget_ids=["upscale_method", "scale_by"],
    input_mapping=[
        {"new_id": "input", "old_id": "image"},
        {"new_id": "resize_type", "set_value": "scale by multiplier"},
        {"new_id": "resize_type.multiplier", "old_id": "scale_by"},
        {"new_id": "scale_method", "old_id": "upscale_method"},
    ],
))
```

### Autogrow input mapping

For nodes using Autogrow (dynamic inputs), use dot notation:

```python theme={null}
await api.node_replacement.register(io.NodeReplace(
    new_node_id="BatchImagesNode",
    old_node_id="ImageBatch",
    input_mapping=[
        {"new_id": "images.image0", "old_id": "image1"},
        {"new_id": "images.image1", "old_id": "image2"},
    ],
))
```

## NodeReplace parameters

| Parameter        | Type               | Description                                               |
| ---------------- | ------------------ | --------------------------------------------------------- |
| `new_node_id`    | str                | Class name of the replacement node                        |
| `old_node_id`    | str                | Class name of the deprecated node                         |
| `old_widget_ids` | list\[str] \| None | Ordered list binding widget IDs to their relative indexes |
| `input_mapping`  | list \| None       | How to map inputs from old to new node                    |
| `output_mapping` | list \| None       | How to map outputs from old to new node                   |

## Input mapping

Each input mapping entry defines how an input transfers from the old node to the new one.

**Map from old input:**

```python theme={null}
{"new_id": "model", "old_id": "model"}
```

**Set a fixed value:**

```python theme={null}
{"new_id": "scheduler", "set_value": "normal"}
```

**Map dynamic/autogrow inputs (use dot notation):**

```python theme={null}
{"new_id": "images.image0", "old_id": "image1"}
```

## Output mapping

Output mappings use index-based references:

```python theme={null}
{"new_idx": 0, "old_idx": 0}  # Map first output
{"new_idx": 1, "old_idx": 0}  # Old output 0 -> new output 1
```

## Widget ID binding

The `old_widget_ids` field maps widget IDs to their positional indexes. This is required because workflow JSON stores widget values by position, not ID.

```python theme={null}
old_widget_ids=["steps", "cfg", "sampler"]
# Widget at index 0 = "steps"
# Widget at index 1 = "cfg"
# Widget at index 2 = "sampler"
```

## REST API

Retrieve all registered replacements:

```
GET /api/node_replacements
```

**Response:**

```json theme={null}
{
  "OldSamplerNode": [
    {
      "new_node_id": "NewSamplerNode",
      "old_node_id": "OldSamplerNode",
      "old_widget_ids": ["num_steps", "cfg_scale", "sampler_name"],
      "input_mapping": [
        {"new_id": "model", "old_id": "model"},
        {"new_id": "steps", "old_id": "num_steps"},
        {"new_id": "scheduler", "set_value": "normal"}
      ],
      "output_mapping": [
        {"new_idx": 0, "old_idx": 0}
      ]
    }
  ]
}
```

## Frontend behavior

When a workflow contains a deprecated node, the frontend:

1. Fetches replacements from `GET /api/node_replacements`
2. Detects nodes matching `old_node_id`
3. Prompts the user to upgrade
4. Applies input/output mappings automatically
5. Preserves connections and widget values

See the frontend implementation:

* [Business logic PR #8364](https://github.com/Comfy-Org/ComfyUI_frontend/pull/8364)
* [Additional logic PR #8483](https://github.com/Comfy-Org/ComfyUI_frontend/pull/8483)
* [UI views PR #8604](https://github.com/Comfy-Org/ComfyUI_frontend/pull/8604)


# Properties
Source: https://docs.comfy.org/custom-nodes/backend/server_overview

Properties of a custom node

### Simple Example

Here's the code for the Invert Image Node, which gives an overview of the key concepts in custom node development.

```python theme={null}
class InvertImageNode:
    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": { "image_in" : ("IMAGE", {}) },
        }

    RETURN_TYPES = ("IMAGE",)
    RETURN_NAMES = ("image_out",)
    CATEGORY = "examples"
    FUNCTION = "invert"

    def invert(self, image_in):
        image_out = 1 - image_in
        return (image_out,)
```

### Main properties

Every custom node is a Python class, with the following key properties:

#### INPUT\_TYPES

`INPUT_TYPES`, as the name suggests, defines the inputs for the node. The method returns a `dict`
which *must* contain the key `required`, and *may* also include the keys `optional` and/or `hidden`. The only difference
between `required` and `optional` inputs is that `optional` inputs can be left unconnected.
For more information on `hidden` inputs, see [Hidden Inputs](./more_on_inputs#hidden-inputs).

Each key has, as its value, another `dict`, in which key-value pairs specify the names and types of the inputs.
The types are defined by a `tuple`, the first element of which defines the data type,
and the second element of which is a `dict` of additional parameters.

Here we have just one required input, named `image_in`, of type `IMAGE`, with no additional parameters.

Note that unlike the next few attributes, this `INPUT_TYPES` is a `@classmethod`. This is so
that the options in dropdown widgets (like the name of the checkpoint to be loaded) can be
computed by Comfy at run time. We'll go into this more later.&#x20;

#### RETURN\_TYPES

A `tuple` of `str` defining the data types returned by the node.
If the node has no outputs this must still be provided `RETURN_TYPES = ()`
<Warning>If you have exactly one output, remember the trailing comma: `RETURN_TYPES = ("IMAGE",)`.
This is required for Python to make it a `tuple`</Warning>

#### RETURN\_NAMES

The names to be used to label the outputs. This is optional; if omitted, the names are simply the `RETURN_TYPES` in lowercase.

#### CATEGORY

Where the node will be found in the ComfyUI **Add Node** menu. Submenus can be specified as a path, eg. `examples/trivial`.

#### FUNCTION

The name of the Python function in the class that should be called when the node is executed.

The function is called with named arguments. All `required` (and `hidden`) inputs will be included;
`optional` inputs will be included only if they are connected, so you should provide default values for them in the function
definition (or capture them with `**kwargs`).

The function returns a tuple corresponding to the `RETURN_TYPES`. This is required even if nothing is returned (`return ()`).
Again, if you only have one output, remember that trailing comma `return (image_out,)`!

### Execution Control Extras

A great feature of Comfy is that it caches outputs,
and only executes nodes that might produce a different result than the previous run.
This can greatly speed up lots of workflows.

In essence this works by identifying which nodes produce an output (these, notably the Image Preview and Save Image nodes, are always executed), and then working
backwards to identify which nodes provide data that might have changed since the last run.

Two optional features of a custom node assist in this process.

#### OUTPUT\_NODE

By default, a node is not considered an output. Set `OUTPUT_NODE = True` to specify that it is.

#### IS\_CHANGED

By default, Comfy considers that a node has changed if any of its inputs or widgets have changed.
This is normally correct, but you may need to override this if, for instance, the node uses a random
number (and does not specify a seed - it's best practice to have a seed input in this case so that
the user can control reproducibility and avoid unnecessary execution), or loads an input that may have
changed externally, or sometimes ignores inputs (so doesn't need to execute just because those inputs changed).

<Warning>Despite the name, IS\_CHANGED should not return a `bool`</Warning>

`IS_CHANGED` is passed the same arguments as the main function defined by `FUNCTION`, and can return any
Python object. This object is compared with the one returned in the previous run (if any) and the node
will be considered to have changed if `is_changed != is_changed_old` (this code is in `execution.py` if you need to dig).

Since `True == True`, a node that returns `True` to say it has changed will be considered not to have! I'm sure this would
be changed in the Comfy code if it wasn't for the fact that it might break existing nodes to do so.

To specify that your node should always be considered to have changed (which you should avoid if possible, since it
stops Comfy optimising what gets run), `return float("NaN")`. This returns a `NaN` value, which is not equal
to anything, even another `NaN`.

A good example of actually checking for changes is the code from the built-in LoadImage node, which loads the image and returns a hash

```python theme={null}
    @classmethod
    def IS_CHANGED(s, image):
        image_path = folder_paths.get_annotated_filepath(image)
        m = hashlib.sha256()
        with open(image_path, 'rb') as f:
            m.update(f.read())
        return m.digest().hex()
```

#### SEARCH\_ALIASES

Optional. A list of alternative names users might search for when looking for this node.
This is included in the `/object_info` API response as `search_aliases`.

```python theme={null}
SEARCH_ALIASES = ["text concat", "join text", "merge strings"]
```

### Other attributes

There are three other attributes that can be used to modify the default Comfy treatment of a node.

#### INPUT\_IS\_LIST, OUTPUT\_IS\_LIST

These are used to control sequential processing of data, and are described [later](./lists).

### VALIDATE\_INPUTS

If a class method `VALIDATE_INPUTS` is defined, it will be called before the workflow begins execution.
`VALIDATE_INPUTS` should return `True` if the inputs are valid, or a message (as a `str`) describing the error (which will prevent execution).

#### Validating Constants

<Warning>Note that `VALIDATE_INPUTS` will only receive inputs that are defined as constants within the workflow. Any inputs that are received from other nodes will *not* be available in `VALIDATE_INPUTS`.</Warning>

`VALIDATE_INPUTS` is called with only the inputs that its signature requests (those returned by `inspect.getfullargspec(obj_class.VALIDATE_INPUTS).args`). Any inputs which are received in this way will *not* run through the default validation rules. For example, in the following snippet, the front-end will use the specified `min` and `max` values of the `foo` input, but the back-end will not enforce it.

```python theme={null}
class CustomNode:
    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": { "foo" : ("INT", {"min": 0, "max": 10}) },
        }

    @classmethod
    def VALIDATE_INPUTS(cls, foo):
        # YOLO, anything goes!
        return True
```

Additionally, if the function takes a `**kwargs` input, it will receive *all* available inputs and all of them will skip validation as if specified explicitly.

#### Validating Types

If the `VALIDATE_INPUTS` method receives an argument named `input_types`, it will be passed a dictionary in which the key is the name of each input which is connected to an output from another node and the value is the type of that output.

When this argument is present, all default validation of input types is skipped. Here's an example making use of the fact that the front-end allows for the specification of multiple types:

```python theme={null}
class AddNumbers:
    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "input1" : ("INT,FLOAT", {"min": 0, "max": 1000})
                "input2" : ("INT,FLOAT", {"min": 0, "max": 1000})
            },
        }

    @classmethod
    def VALIDATE_INPUTS(cls, input_types):
        # The min and max of input1 and input2 are still validated because
        # we didn't take `input1` or `input2` as arguments
        if input_types["input1"] not in ("INT", "FLOAT"):
            return "input1 must be an INT or FLOAT type"
        if input_types["input2"] not in ("INT", "FLOAT"):
            return "input2 must be an INT or FLOAT type"
        return True
```


# Annotated Examples
Source: https://docs.comfy.org/custom-nodes/backend/snippets



A growing collection of fragments of example code...

## Images and Masks

### Load an image

Load an image into a batch of size 1 (based on `LoadImage` source code in `nodes.py`)

```python theme={null}
i = Image.open(image_path)
i = ImageOps.exif_transpose(i)
if i.mode == 'I':
    i = i.point(lambda i: i * (1 / 255))
image = i.convert("RGB")
image = np.array(image).astype(np.float32) / 255.0
image = torch.from_numpy(image)[None,]
```

### Save an image batch

Save a batch of images (based on `SaveImage` source code in `nodes.py`)

```python theme={null}
for (batch_number, image) in enumerate(images):
    i = 255. * image.cpu().numpy()
    img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
    filepath = # some path that takes the batch number into account
    img.save(filepath)
```

### Invert a mask

Inverting a mask is a straightforward process. Since masks are normalised to the range \[0,1]:

```python theme={null}
mask = 1.0 - mask
```

### Convert a mask to Image shape

```Python theme={null}
# We want [B,H,W,C] with C = 1
if len(mask.shape)==2: # we have [H,W], so insert B and C as dimension 1
    mask = mask[None,:,:,None]
elif len(mask.shape)==3 and mask.shape[2]==1: # we have [H,W,C]
    mask = mask[None,:,:,:]
elif len(mask.shape)==3:                      # we have [B,H,W]
    mask = mask[:,:,:,None]
```

### Using Masks as Transparency Layers

When used for tasks like inpainting or segmentation, the MASK's values will eventually be rounded to the nearest integer so that they are binary — 0 indicating regions to be ignored and 1 indicating regions to be targeted. However, this doesn't happen until the MASK is passed to those nodes. This flexibility allows you to use MASKs as you would in digital photography contexts as a transparency layer:

```python theme={null}
# Invert mask back to original transparency layer
mask = 1.0 - mask

# Unsqueeze the `C` (channels) dimension
mask = mask.unsqueeze(-1)

# Concatenate ("cat") along the `C` dimension
rgba_image = torch.cat((rgb_image, mask), dim=-1)
```

## Noise

### Creating noise variations

Here's an example of creating a noise object which mixes the noise from two sources. This could be used to create slight noise variations by varying `weight2`.

```python theme={null}
class Noise_MixedNoise:
    def __init__(self, nosie1, noise2, weight2):
        self.noise1  = noise1
        self.noise2  = noise2
        self.weight2 = weight2

    @property
    def seed(self): return self.noise1.seed

    def generate_noise(self, input_latent:torch.Tensor) -> torch.Tensor:
        noise1 = self.noise1.generate_noise(input_latent)
        noise2 = self.noise2.generate_noise(input_latent)
        return noise1 * (1.0-self.weight2) + noise2 * (self.weight2)
```


# Working with torch.Tensor
Source: https://docs.comfy.org/custom-nodes/backend/tensors



## pytorch, tensors, and torch.Tensor

All the core number crunching in Comfy is done by [pytorch](https://pytorch.org/). If your custom nodes are going
to get into the guts of stable diffusion you will need to become familiar with this library, which is way beyond
the scope of this introduction.

However, many custom nodes will need to manipulate images, latents and masks, each of which are represented internally
as `torch.Tensor`, so you'll want to bookmark the
[documentation for torch.Tensor](https://pytorch.org/docs/stable/tensors.html).

### What is a Tensor?

`torch.Tensor` represents a tensor, which is the mathematical generalization of a vector or matrix to any number of dimensions.
A tensor's *rank* is the number of dimensions it has (so a vector has *rank* 1, a matrix *rank* 2); its *shape* describes the
size of each dimension.

So an RGB image (of height H and width W) might be thought of as three arrays (one for each color channel), each measuring H x W,
which could be represented as a tensor with *shape* `[H,W,3]`. In Comfy images almost always come in a batch (even if the batch
only contains a single image). `torch` always places the batch dimension first, so Comfy images have *shape* `[B,H,W,3]`, generally
written as `[B,H,W,C]` where C stands for Channels.

### squeeze, unsqueeze, and reshape

If a tensor has a dimension of size 1 (known as a collapsed dimension), it is equivalent to the same tensor with that dimension removed
(a batch with 1 image is just an image). Removing such a collapsed dimension is referred to as squeezing, and
inserting one is known as unsqueezing.

<Warning>Some torch code, and some custom node authors, will return a squeezed tensor when a dimension is collapsed - such
as when a batch has only one member. This is a common cause of bugs!</Warning>

To represent the same data in a different shape is referred to as reshaping. This often requires you to know
the underlying data structure, so handle with care!

### Important notation

`torch.Tensor` supports most Python slice notation, iteration, and other common list-like operations. A tensor
also has a `.shape` attribute which returns its size as a `torch.Size` (which is a subclass of `tuple` and can
be treated as such).

There are some other important bits of notation you'll often see (several of these are less common
standard Python notation, seen much more frequently when dealing with tensors)

* `torch.Tensor` supports the use of `None` in slice notation
  to indicate the insertion of a dimension of size 1.

* `:` is frequently used when slicing a tensor; this simply means 'keep the whole dimension'.
  It's like using `a[start:end]` in Python, but omitting the start point and end point.

* `...` represents 'the whole of an unspecified number of dimensions'. So `a[0, ...]` would extract the first
  item from a batch regardless of the number of dimensions.

* in methods which require a shape to be passed, it is often passed as a `tuple` of the dimensions, in
  which a single dimension can be given the size `-1`, indicating that the size of this dimension should
  be calculated based on the total size of the data.

```python theme={null}
>>> a = torch.Tensor((1,2))
>>> a.shape
torch.Size([2])
>>> a[:,None].shape 
torch.Size([2, 1])
>>> a.reshape((1,-1)).shape
torch.Size([1, 2])
```

### Elementwise operations

Many binary on `torch.Tensor` (including '+', '-', '\*', '/' and '==') are applied elementwise (independently applied to each element).
The operands must be *either* two tensors of the same shape, *or* a tensor and a scalar. So:

```python theme={null}
>>> import torch
>>> a = torch.Tensor((1,2))
>>> b = torch.Tensor((3,2))
>>> a*b
tensor([3., 4.])
>>> a/b
tensor([0.3333, 1.0000])
>>> a==b
tensor([False,  True])
>>> a==1
tensor([ True, False])
>>> c = torch.Tensor((3,2,1)) 
>>> a==c
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
RuntimeError: The size of tensor a (2) must match the size of tensor b (3) at non-singleton dimension 0
```

### Tensor truthiness

<Warning>The 'truthiness' value of a Tensor is not the same as that of Python lists.</Warning>

You may be familiar with the truthy value of a Python list as `True` for any non-empty list, and `False` for `None` or `[]`.
By contrast A `torch.Tensor` (with more than one elements) does not have a defined truthy value. Instead you need to use
`.all()` or `.any()` to combine the elementwise truthiness:

```python theme={null}
>>> a = torch.Tensor((1,2))
>>> print("yes" if a else "no")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
RuntimeError: Boolean value of Tensor with more than one value is ambiguous
>>> a.all()
tensor(False)
>>> a.any()
tensor(True)
```

This also means that you need to use `if a is not None:` not `if a:` to determine if a tensor variable has been set.


# Add node docs for your ComfyUI custom node
Source: https://docs.comfy.org/custom-nodes/help_page

How to create rich documentation for your custom nodes

## Node Documentation with Markdown

Custom nodes can include rich markdown documentation that will be displayed in the UI instead of the generic node description. This provides users with detailed information about your node's functionality, parameters, and usage examples.

If you have already added tooltips for each parameter in the node definition, this basic information can be directly accessed via the node documentation panel.
No additional node documentation needs to be added, and you can refer to the related implementation of [ContextWindowsManualNode](https://github.com/Comfy-Org/ComfyUI/blob/master/comfy_extras/nodes_context_windows.py#L7)

## Setup

To add documentation for your custom nodes or multi-language support documentation:

1. Create a `docs` folder inside your `WEB_DIRECTORY`
2. Add markdown files named after your nodes (the names of your nodes are the dictionary keys in the `NODE_CLASS_MAPPINGS` dictionary used to register the nodes):
   * `WEB_DIRECTORY/docs/NodeName.md` - Default documentation
   * `WEB_DIRECTORY/docs/NodeName/en.md` - English documentation
   * `WEB_DIRECTORY/docs/NodeName/zh.md` - Chinese documentation
   * Add other locales as needed (e.g., `fr.md`, `de.md`, etc.)

The system will automatically load the appropriate documentation based on the user's locale, falling back to `NodeName.md` if a localized version is not available.

## Supported Markdown Features

* Standard markdown syntax (headings, lists, code blocks, etc.)
* Images using markdown syntax: `![alt text](image.png)`
* HTML media elements with specific attributes:
  * `<video>` and `<source>` tags
  * Allowed attributes: `controls`, `autoplay`, `loop`, `muted`, `preload`, `poster`

## Example Structure

```
my-custom-node/
├── __init__.py
├── web/              # WEB_DIRECTORY
│   ├── js/
│   │   └── my-node.js
│   └── docs/
│       ├── MyNode.md           # Fallback documentation
│       └── MyNode/
│           ├── en.md           # English version
│           └── zh.md           # Chinese version
```

## Example Markdown File

```markdown theme={null}
# My Custom Node

This node processes images using advanced algorithms.

## Parameters

- **image**: Input image to process
- **strength**: Processing strength (0.0 - 1.0)

## Usage

![example usage](example.png)

<video controls loop muted>
  <source src="demo.mp4" type="video/mp4">
</video>
```


# ComfyUI Custom Nodes i18n Support
Source: https://docs.comfy.org/custom-nodes/i18n

Learn how to add multi-language support for ComfyUI custom nodes

If you want to add support for multiple languages, you can refer to this document to learn how to implement multi-language support.

Currently, ComfyUI supports the following languages:

* English（en）
* Chinese (Simplified)（zh）
* Chinese (Traditional)（zh-TW）
* French（fr）
* Korean（ko）
* Russian（ru）
* Spanish（es）
* Japanese（ja）
* Arabic（ar）

Custom node i18n demo: [comfyui-wiki/ComfyUI-i18n-demo](https://github.com/comfyui-wiki/ComfyUI-i18n-demo)

## Directory Structure

Create a `locales` folder under your custom node, which supports multiple types of translation files:

```bash theme={null}
your_custom_node/
├── __init__.py
├── your_node.py
└── locales/                   # i18n support folder
    ├── en/                    # English translations (recommended as the base)
    │   ├── main.json          # General English translation content
    │   ├── nodeDefs.json      # English node definition translations
    │   ├── settings.json      # Optional: settings interface translations
    │   └── commands.json      # Optional: command translations
    ├── zh/                    # Chinese translation files
    │   ├── nodeDefs.json      # Chinese node definition translations
    │   ├── main.json          # General Chinese translation content
    │   ├── settings.json      # Chinese settings interface translations
    │   └── commands.json      # Chinese command translations
    ├──...

```

## nodeDefs.json - Node Definition Translation

For example, here is a Python definition example of an [i18n-demo](https://github.com/comfyui-wiki/ComfyUI-i18n-demo) node:

```python theme={null}
class I18nTextProcessor:
    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "text": ("STRING", {
                    "multiline": True,
                    "default": "Hello World!",
                    "tooltip": "The original text content to be processed"
                }),
                "operation": (["uppercase", "lowercase", "reverse", "add_prefix"], {
                    "default": "uppercase",
                    "tooltip": "The text processing operation to be executed"
                }),
                "count": ("INT", {
                    "default": 1,
                    "min": 1,
                    "max": 10,
                    "step": 1,
                    "tooltip": "The number of times to repeat the operation"
                }),
            },
            "optional": {
                "prefix": ("STRING", {
                    "default": "[I18N] ",
                    "multiline": False,
                    "tooltip": "The prefix to add to the text"
                }),
            }
        }

    RETURN_TYPES = ("STRING",)
    RETURN_NAMES = ("processed_text",)
    FUNCTION = "process_text"
    CATEGORY = "I18n Demo"
    DESCRIPTION = "A simple i18n demo node that demonstrates text processing with internationalization support"

    def process_text(self, text, operation, count, prefix=""):
        try:
            result = text
            
            for _ in range(count):
                if operation == "uppercase":
                    result = result.upper()
                elif operation == "lowercase":
                    result = result.lower()
                elif operation == "reverse":
                    result = result[::-1]
                elif operation == "add_prefix":
                    result = prefix + result
            
            return (result,)
        except Exception as e:
            print(f"I18nTextProcessor error: {e}")
            return (f"Error: {str(e)}",)
```

Then the corresponding localized support nodeDefs.json file content should include:

```json theme={null}
{
  "I18nTextProcessor": {
    "display_name": "I18n Text Processor",
    "description": "A simple i18n demo node that demonstrates text processing with internationalization support",
    "inputs": {
      "text": {
        "name": "Text Input",
        "tooltip": "The original text content to be processed"
      },
      "operation": {
        "name": "Operation Type",
        "tooltip": "The text processing operation to be executed",
        "options": {
          "uppercase": "To Uppercase",
          "lowercase": "To Lowercase",
          "reverse": "Reverse Text",
          "add_prefix": "Add Prefix"
        }
      },
      "count": {
        "name": "Repeat Count",
        "tooltip": "The number of times to repeat the operation"
      },
      "prefix": {
        "name": "Prefix Text",
        "tooltip": "The prefix to add to the text"
      }
    },
    "outputs": {
      "0": {
        "name": "Processed Text",
        "tooltip": "The final processed text result"
      }
    }
  }
}
```

For the node output part, the corresponding output index is used instead of the output name, for example, the first output should be `0`, the second output should be `1`, and so on.

## Menu Settings

For example, in the i18n-demo custom node, we registered the following two menu settings:

```javascript theme={null}
app.registerExtension({
    name: "I18nDemo",
    settings: [
        {
            id: "I18nDemo.EnableDebugMode",
            category: ["I18nDemo","DebugMode"], // This matches the settingsCategories key in main.json
            name: "Enable Debug Mode", // Will be overridden by translation
            tooltip: "Show debug information in console for i18n demo nodes", // Will be overridden by translation
            type: "boolean",
            defaultValue: false,
            experimental: true,
            onChange: (value) => {
                console.log("I18n Demo:", value ? "Debug mode enabled" : "Debug mode disabled");
            }
        },
        {
            id: "I18nDemo.DefaultTextOperation",
            category: ["I18nDemo","DefaultTextOperation"], // This matches the settingsCategories key in main.json
            name: "Default Text Operation", // Will be overridden by translation
            tooltip: "Default operation for text processor node", // Will be overridden by translation
            type: "combo",
            options: ["uppercase", "lowercase", "reverse", "add_prefix"],
            defaultValue: "uppercase",
            experimental: true
        }
    ],
    })
```

If you need to add corresponding internationalization support, for the menu category, you need to add it in the `main.json` file:

```json theme={null}
{
  "settingsCategories": {
    "I18nDemo": "I18n Demo",
    "DebugMode": "Debug Mode",
    "DefaultTextOperation": "Default Text Operation"
  }
}
```

For the translation of the corresponding setting items, it is recommended to update them separately in the `settings.json` file, for example:

```json theme={null}
{
  "I18nDemo_EnableDebugMode": {
    "name": "Enable Debug Mode",
    "tooltip": "Show debug information in console for i18n demo nodes"
  },
  "I18nDemo_DefaultTextOperation": {
    "name": "Default Text Operation",
    "tooltip": "Default operation for text processor node",
    "options": {
      "uppercase": "Uppercase",
      "lowercase": "Lowercase",
      "reverse": "Reverse",
      "add_prefix": "Add Prefix"
    }
  }
}
```

Note that the name of the corresponding translation key should replace the `.` in the original id with `_`, for example:

```
"I18nDemo.EnableDebugMode" -> "I18nDemo_EnableDebugMode"
```

## Custom Frontend Component Localization Support

\[To be updated]


# Context Menu Migration Guide
Source: https://docs.comfy.org/custom-nodes/js/context-menu-migration



This guide helps you migrate from the deprecated monkey-patching approach to the new context menu extension API.

The old approach of monkey-patching `LGraphCanvas.prototype.getCanvasMenuOptions` and `nodeType.prototype.getExtraMenuOptions` is deprecated:

<Tip>If you see deprecation warnings in your browser console, your extension is using the old API and should be migrated.</Tip>

## Migrating Canvas Menus

### Old Approach (Deprecated)

The old approach modified the prototype during extension setup:

```javascript theme={null}
import { app } from "../../scripts/app.js"

app.registerExtension({
  name: "MyExtension",
  async setup() {
    // ❌ OLD: Monkey-patching the prototype
    const original = LGraphCanvas.prototype.getCanvasMenuOptions
    LGraphCanvas.prototype.getCanvasMenuOptions = function() {
      const options = original.apply(this, arguments)

      options.push(null) // separator
      options.push({
        content: "My Custom Action",
        callback: () => {
          console.log("Action triggered")
        }
      })

      return options
    }
  }
})
```

### New Approach (Recommended)

The new approach uses a dedicated extension hook:

```javascript theme={null}
import { app } from "../../scripts/app.js"

app.registerExtension({
  name: "MyExtension",
  // ✅ NEW: Use the getCanvasMenuItems hook
  getCanvasMenuItems(canvas) {
    return [
      null, // separator
      {
        content: "My Custom Action",
        callback: () => {
          console.log("Action triggered")
        }
      }
    ]
  }
})
```

### Key Differences

| Old Approach               | New Approach                     |
| -------------------------- | -------------------------------- |
| Modified in `setup()`      | Uses `getCanvasMenuItems()` hook |
| Wraps existing function    | Returns menu items directly      |
| Modifies `options` array   | Returns new array                |
| Canvas accessed via `this` | Canvas passed as parameter       |

## Migrating Node Menus

### Old Approach (Deprecated)

The old approach modified the node type prototype:

```javascript theme={null}
import { app } from "../../scripts/app.js"

app.registerExtension({
  name: "MyExtension",
  async beforeRegisterNodeDef(nodeType, nodeData, app) {
    if (nodeType.comfyClass === "KSampler") {
      // ❌ OLD: Monkey-patching the node prototype
      const original = nodeType.prototype.getExtraMenuOptions
      nodeType.prototype.getExtraMenuOptions = function(canvas, options) {
        original?.apply(this, arguments)

        options.push({
          content: "Randomize Seed",
          callback: () => {
            const seedWidget = this.widgets.find(w => w.name === "seed")
            if (seedWidget) {
              seedWidget.value = Math.floor(Math.random() * 1000000)
            }
          }
        })
      }
    }
  }
})
```

### New Approach (Recommended)

The new approach uses a dedicated extension hook:

```javascript theme={null}
import { app } from "../../scripts/app.js"

app.registerExtension({
  name: "MyExtension",
  // ✅ NEW: Use the getNodeMenuItems hook
  getNodeMenuItems(node) {
    const items = []

    // Add items only for specific node types
    if (node.comfyClass === "KSampler") {
      items.push({
        content: "Randomize Seed",
        callback: () => {
          const seedWidget = node.widgets.find(w => w.name === "seed")
          if (seedWidget) {
            seedWidget.value = Math.floor(Math.random() * 1000000)
          }
        }
      })
    }

    return items
  }
})
```

### Key Differences

| Old Approach                          | New Approach                         |
| ------------------------------------- | ------------------------------------ |
| Modified in `beforeRegisterNodeDef()` | Uses `getNodeMenuItems()` hook       |
| Type-specific via `if` check          | Type-specific via `if` check in hook |
| Modifies `options` array              | Returns new array                    |
| Node accessed via `this`              | Node passed as parameter             |

## Common Patterns

### Conditional Menu Items

Both approaches support conditional items, but the new API is cleaner:

```javascript theme={null}
// ✅ NEW: Clean conditional logic
getCanvasMenuItems(canvas) {
  const items = []

  if (canvas.selectedItems.size > 0) {
    items.push({
      content: `Process ${canvas.selectedItems.size} Selected Nodes`,
      callback: () => {
        // Process nodes
      }
    })
  }

  return items
}
```

### Adding Separators

Separators are added the same way in both approaches:

```javascript theme={null}
getCanvasMenuItems(canvas) {
  return [
    null, // Separator (horizontal line)
    {
      content: "My Action",
      callback: () => {}
    }
  ]
}
```

### Creating Submenus

The recommended way to create submenus is using the declarative `submenu` property:

```javascript theme={null}
getNodeMenuItems(node) {
  return [
    {
      content: "Advanced Options",
      submenu: {
        options: [
          { content: "Option 1", callback: () => {} },
          { content: "Option 2", callback: () => {} }
        ]
      }
    }
  ]
}
```

This declarative approach is cleaner and matches the patterns used throughout the ComfyUI codebase.

<Tip>While a callback-based approach with `has_submenu: true` and `new LiteGraph.ContextMenu()` is also supported, the declarative `submenu` property is preferred for better maintainability.</Tip>

### Accessing State

```javascript theme={null}
// ✅ NEW: State access is clearer
getCanvasMenuItems(canvas) {
  // Access canvas properties
  const selectedCount = canvas.selectedItems.size
  const graphMousePos = canvas.graph_mouse

  return [/* menu items */]
}

getNodeMenuItems(node) {
  // Access node properties
  const nodeType = node.comfyClass
  const isDisabled = node.mode === 2
  const widgets = node.widgets

  return [/* menu items */]
}
```

## Troubleshooting

### How to Identify Old API Usage

Look for these patterns in your code:

```javascript theme={null}
// ❌ Signs of old API:
LGraphCanvas.prototype.getCanvasMenuOptions = function() { /* ... */ }
nodeType.prototype.getExtraMenuOptions = function() { /* ... */ }
```

### Understanding Deprecation Warnings

If you see this warning in the console:

```
[DEPRECATED] Monkey-patching getCanvasMenuOptions is deprecated. (Extension: "MyExtension")
Please use the new context menu API instead.
See: https://docs.comfy.org/custom-nodes/js/context-menu-migration
```

Your extension is using the old approach and should be migrated.

### Verifying Migration Success

After migration:

1. Remove all prototype modifications from `setup()` and `beforeRegisterNodeDef()`
2. Add `getCanvasMenuItems()` and/or `getNodeMenuItems()` hooks
3. Test that your menu items still appear correctly
4. Verify no deprecation warnings appear in the console

### Complete Migration Example

**Before:**

```javascript theme={null}
app.registerExtension({
  name: "MyExtension",
  async setup() {
    const original = LGraphCanvas.prototype.getCanvasMenuOptions
    LGraphCanvas.prototype.getCanvasMenuOptions = function() {
      const options = original.apply(this, arguments)
      options.push({ content: "Action", callback: () => {} })
      return options
    }
  },
  async beforeRegisterNodeDef(nodeType) {
    if (nodeType.comfyClass === "KSampler") {
      const original = nodeType.prototype.getExtraMenuOptions
      nodeType.prototype.getExtraMenuOptions = function(_, options) {
        original?.apply(this, arguments)
        options.push({ content: "Node Action", callback: () => {} })
      }
    }
  }
})
```

**After:**

```javascript theme={null}
app.registerExtension({
  name: "MyExtension",
  getCanvasMenuItems(canvas) {
    return [
      { content: "Action", callback: () => {} }
    ]
  },
  getNodeMenuItems(node) {
    if (node.comfyClass === "KSampler") {
      return [
        { content: "Node Action", callback: () => {} }
      ]
    }
    return []
  }
})
```

## Additional Resources

* [Annotated Examples](./javascript_examples) - More examples using the new API
* [Extension Hooks](./javascript_hooks) - Complete list of available extension hooks
* [Commands and Keybindings](./javascript_commands_keybindings) - Add keyboard shortcuts to your menu actions


# About Panel Badges
Source: https://docs.comfy.org/custom-nodes/js/javascript_about_panel_badges



The About Panel Badges API allows extensions to add custom badges to the ComfyUI about page. These badges can display information about your extension and contain links to documentation, source code, or other resources.

## Basic Usage

```javascript theme={null}
app.registerExtension({
  name: "MyExtension",
  aboutPageBadges: [
    {
      label: "Documentation",
      url: "https://example.com/docs",
      icon: "pi pi-file"
    },
    {
      label: "GitHub",
      url: "https://github.com/username/repo",
      icon: "pi pi-github"
    }
  ]
});
```

## Badge Configuration

Each badge requires all of these properties:

```javascript theme={null}
{
  label: string,           // Text to display on the badge
  url: string,             // URL to open when badge is clicked
  icon: string             // Icon class (e.g., PrimeVue icon)
}
```

## Icon Options

Badge icons use PrimeVue's icon set. Here are some commonly used icons:

* Documentation: `pi pi-file` or `pi pi-book`
* GitHub: `pi pi-github`
* External link: `pi pi-external-link`
* Information: `pi pi-info-circle`
* Download: `pi pi-download`
* Website: `pi pi-globe`
* Discord: `pi pi-discord`

For a complete list of available icons, refer to the [PrimeVue Icons documentation](https://primevue.org/icons/).

## Example

```javascript theme={null}
app.registerExtension({
  name: "BadgeExample",
  aboutPageBadges: [
    {
      label: "Website",
      url: "https://example.com",
      icon: "pi pi-home"
    },
    {
      label: "Donate",
      url: "https://example.com/donate",
      icon: "pi pi-heart"
    },
    {
      label: "Documentation",
      url: "https://example.com/docs",
      icon: "pi pi-book"
    }
  ]
});
```

Badges appear in the About panel of the Settings dialog, which can be accessed via the gear icon in the top-right corner of the ComfyUI interface.


# Bottom Panel Tabs
Source: https://docs.comfy.org/custom-nodes/js/javascript_bottom_panel_tabs



The Bottom Panel Tabs API allows extensions to add custom tabs to the bottom panel of the ComfyUI interface. This is useful for adding features like logs, debugging tools, or custom panels.

## Basic Usage

```javascript theme={null}
app.registerExtension({
  name: "MyExtension",
  bottomPanelTabs: [
    {
      id: "customTab",
      title: "Custom Tab",
      type: "custom",
      render: (el) => {
        el.innerHTML = '<div>This is my custom tab content</div>';
      }
    }
  ]
});
```

## Tab Configuration

Each tab requires an `id`, `title`, and `type`, along with a render function:

```javascript theme={null}
{
  id: string,              // Unique identifier for the tab
  title: string,           // Display title shown on the tab
  type: string,            // Tab type (usually "custom")
  icon?: string,           // Icon class (optional)
  render: (element) => void // Function that populates the tab content
}
```

The `render` function receives a DOM element where you should insert your tab's content.

## Interactive Elements

You can add interactive elements like buttons:

```javascript theme={null}
app.registerExtension({
  name: "InteractiveTabExample",
  bottomPanelTabs: [
    {
      id: "controlsTab",
      title: "Controls",
      type: "custom",
      render: (el) => {
        el.innerHTML = `
          <div style="padding: 10px;">
            <button id="runBtn">Run Workflow</button>
          </div>
        `;
        
        // Add event listeners
        el.querySelector('#runBtn').addEventListener('click', () => {
          app.queuePrompt();
        });
      }
    }
  ]
});
```

## Using React Components

You can mount React components in bottom panel tabs:

```javascript theme={null}
// Import React dependencies in your extension
import React from "react";
import ReactDOM from "react-dom/client";

// Simple React component
function TabContent() {
  const [count, setCount] = React.useState(0);
  
  return (
    <div style={{ padding: "10px" }}>
      <h3>React Component</h3>
      <p>Count: {count}</p>
      <button onClick={() => setCount(count + 1)}>Increment</button>
    </div>
  );
}

// Register the extension with React content
app.registerExtension({
  name: "ReactTabExample",
  bottomPanelTabs: [
    {
      id: "reactTab",
      title: "React Tab",
      type: "custom",
      render: (el) => {
        const container = document.createElement("div");
        container.id = "react-tab-container";
        el.appendChild(container);
        
        // Mount React component
        ReactDOM.createRoot(container).render(
          <React.StrictMode>
            <TabContent />
          </React.StrictMode>
        );
      }
    }
  ]
});
```

## Standalone Registration

You can also register tabs outside of `registerExtension`:

```javascript theme={null}
app.extensionManager.registerBottomPanelTab({
  id: "standAloneTab",
  title: "Stand-Alone Tab",
  type: "custom",
  render: (el) => {
    el.innerHTML = '<div>This tab was registered independently</div>';
  }
});
```


# Commands and Keybindings
Source: https://docs.comfy.org/custom-nodes/js/javascript_commands_keybindings



The Commands and Keybindings API allows extensions to register custom commands and associate them with keyboard shortcuts. This enables users to quickly trigger actions without using the mouse.

## Basic Usage

```javascript theme={null}
app.registerExtension({
  name: "MyExtension",
  // Register commands
  commands: [
    {
      id: "myCommand",
      label: "My Command",
      function: () => {
        console.log("Command executed!");
      }
    }
  ],
  // Associate keybindings with commands
  keybindings: [
    {
      combo: { key: "k", ctrl: true },
      commandId: "myCommand"
    }
  ]
});
```

## Command Configuration

Each command requires an `id`, `label`, and `function`:

```javascript theme={null}
{
  id: string,              // Unique identifier for the command
  label: string,           // Display name for the command
  function: () => void     // Function to execute when command is triggered
}
```

## Keybinding Configuration

Each keybinding requires a `combo` and `commandId`:

```javascript theme={null}
{
  combo: {                 // Key combination
    key: string,           // The main key (single character or special key)
    ctrl?: boolean,        // Require Ctrl key (optional)
    shift?: boolean,       // Require Shift key (optional)
    alt?: boolean,         // Require Alt key (optional)
    meta?: boolean         // Require Meta/Command key (optional)
  },
  commandId: string        // ID of the command to trigger
}
```

### Special Keys

For non-character keys, use one of these values:

* Arrow keys: `"ArrowUp"`, `"ArrowDown"`, `"ArrowLeft"`, `"ArrowRight"`
* Function keys: `"F1"` through `"F12"`
* Other special keys: `"Escape"`, `"Tab"`, `"Enter"`, `"Backspace"`, `"Delete"`, `"Home"`, `"End"`, `"PageUp"`, `"PageDown"`

## Command Examples

```javascript theme={null}
app.registerExtension({
  name: "CommandExamples",
  commands: [
    {
      id: "runWorkflow",
      label: "Run Workflow",
      function: () => {
        app.queuePrompt();
      }
    },
    {
      id: "clearWorkflow",
      label: "Clear Workflow",
      function: () => {
        if (confirm("Clear the workflow?")) {
          app.graph.clear();
        }
      }
    },
    {
      id: "saveWorkflow",
      label: "Save Workflow",
      function: () => {
        app.graphToPrompt().then(workflow => {
          const blob = new Blob([JSON.stringify(workflow)], {type: "application/json"});
          const url = URL.createObjectURL(blob);
          const a = document.createElement("a");
          a.href = url;
          a.download = "workflow.json";
          a.click();
          URL.revokeObjectURL(url);
        });
      }
    }
  ]
});
```

## Keybinding Examples

```javascript theme={null}
app.registerExtension({
  name: "KeybindingExamples",
  commands: [
    /* Commands defined above */
  ],
  keybindings: [
    // Ctrl+R to run workflow
    {
      combo: { key: "r", ctrl: true },
      commandId: "runWorkflow"
    },
    // Ctrl+Shift+C to clear workflow
    {
      combo: { key: "c", ctrl: true, shift: true },
      commandId: "clearWorkflow"
    },
    // Ctrl+S to save workflow
    {
      combo: { key: "s", ctrl: true },
      commandId: "saveWorkflow"
    },
    // F5 to run workflow (alternative)
    {
      combo: { key: "F5" },
      commandId: "runWorkflow"
    }
  ]
});
```

## Notes and Limitations

* Keybindings defined in the ComfyUI core cannot be overwritten by extensions. Check the core keybindings in these source files:
  * [Core Commands](https://github.com/Comfy-Org/ComfyUI_frontend/blob/e76e9ec61a068fd2d89797762f08ee551e6d84a0/src/composables/useCoreCommands.ts)
  * [Core Menu Commands](https://github.com/Comfy-Org/ComfyUI_frontend/blob/e76e9ec61a068fd2d89797762f08ee551e6d84a0/src/constants/coreMenuCommands.ts)
  * [Core Keybindings](https://github.com/Comfy-Org/ComfyUI_frontend/blob/e76e9ec61a068fd2d89797762f08ee551e6d84a0/src/constants/coreKeybindings.ts)
  * [Reserved Key Combos](https://github.com/Comfy-Org/ComfyUI_frontend/blob/e76e9ec61a068fd2d89797762f08ee551e6d84a0/src/constants/reservedKeyCombos.ts)

* Some key combinations are reserved by the browser (like Ctrl+F for search) and cannot be overridden

* If multiple extensions register the same keybinding, the behavior is undefined


# Dialog API
Source: https://docs.comfy.org/custom-nodes/js/javascript_dialog



The Dialog API provides standardized dialogs that work consistently across desktop and web environments. Extension authors will find the prompt and confirm methods most useful.

## Basic Usage

### Prompt Dialog

```javascript theme={null}
// Show a prompt dialog
app.extensionManager.dialog.prompt({
  title: "User Input",
  message: "Please enter your name:",
  defaultValue: "User"
}).then(result => {
  if (result !== null) {
    console.log(`Input: ${result}`);
  }
});
```

### Confirm Dialog

```javascript theme={null}
// Show a confirmation dialog
app.extensionManager.dialog.confirm({
  title: "Confirm Action",
  message: "Are you sure you want to continue?",
  type: "default"
}).then(result => {
  console.log(result ? "User confirmed" : "User cancelled");
});
```

## API Reference

### Prompt

```javascript theme={null}
app.extensionManager.dialog.prompt({
  title: string,             // Dialog title
  message: string,           // Message/question to display
  defaultValue?: string      // Initial value in the input field (optional)
}).then((result: string | null) => {
  // result is the entered text, or null if cancelled
});
```

### Confirm

```javascript theme={null}
app.extensionManager.dialog.confirm({
  title: string,             // Dialog title
  message: string,           // Message to display
  type?: "default" | "overwrite" | "delete" | "dirtyClose" | "reinstall", // Dialog type (optional)
  itemList?: string[],       // List of items to display (optional)
  hint?: string              // Hint text to display (optional)
}).then((result: boolean | null) => {
  // result is true if confirmed, false if denied, null if cancelled
});
```

For other specialized dialogs available in ComfyUI, extension authors can refer to the `dialogService.ts` file in the source code.


# Annotated Examples
Source: https://docs.comfy.org/custom-nodes/js/javascript_examples



A growing collection of fragments of example code...

## Right click menus

### Background menu

The main background menu (right-click on the canvas) is generated by a call to
`LGraphCanvas.getCanvasMenuOptions`. The standard way of editing this is to implement the `getCanvasMenuItems` method on your extension:

```javascript theme={null}
app.registerExtension({
  name: "MyExtension",
  getCanvasMenuItems(canvas) {
    const items = []
    items.push(null) // inserts a divider
    items.push({
      content: "The text for the menu",
      callback: async () => {
        // do whatever
      }
    })
    return items
  }
});
```

### Node menu

When you right click on a node, the menu is similarly generated by `node.getExtraMenuOptions`.
The standard way is to implement the `getNodeMenuItems` method on your extension:

```javascript theme={null}
app.registerExtension({
  name: "MyExtension",
  getNodeMenuItems(node) {
    const items = []

    // You can filter by node type if needed
    if (node.comfyClass === "MyNodeClass") {
      items.push({
        content: "Do something fun",
        callback: async () => {
          // fun thing
        }
      })
    }

    return items
  }
});
```

### Submenus

If you want a submenu, use the `submenu` property with an `options` array:

```javascript theme={null}
app.registerExtension({
  name: "MyExtension",
  getCanvasMenuItems(canvas) {
    const items = []
    items.push({
      content: "Menu with options",
      submenu: {
        options: [
          {
            content: "option 1",
            callback: (v) => {
              // do something with v
            }
          },
          {
            content: "option 2",
            callback: (v) => {
              // do something with v
            }
          },
          {
            content: "option 3",
            callback: (v) => {
              // do something with v
            }
          }
        ]
      }
    })
    return items
  }
});
```

## Capture UI events

This works just like you'd expect - find the UI element in the DOM and
add an eventListener. `setup()` is a good place to do this, since the page
has fully loaded. For instance, to detect a click on the 'Queue' button:

```Javascript theme={null}
function queue_button_pressed() { console.log("Queue button was pressed!") }
document.getElementById("queue-button").addEventListener("click", queue_button_pressed);
```

## Detect when a workflow starts

This is one of many `api` events:

```javascript theme={null}
import { api } from "../../scripts/api.js";
/* in setup() */
    function on_execution_start() { 
        /* do whatever */
    }
    api.addEventListener("execution_start", on_execution_start);
```

## Detect an interrupted workflow

<Note>
  **Deprecated:** The API hijacking pattern shown below is deprecated and subject to change at any point in the near future. Use the official [extension hooks](/custom-nodes/js/javascript_hooks) and API event listeners where available.
</Note>

A simple example of hijacking the api:

```Javascript theme={null}
import { api } from "../../scripts/api.js";
/* in setup() */
    const original_api_interrupt = api.interrupt;
    api.interrupt = function () {
        /* Do something before the original method is called */
        original_api_interrupt.apply(this, arguments);
        /* Or after */
    }
```

## Catch clicks on your node

<Note>
  **Deprecated:** The node method hijacking pattern shown below is deprecated and subject to change at any point in the near future. Use the official [extension hooks](/custom-nodes/js/javascript_hooks) where available.
</Note>

`node` has a mouseDown method you can hijack.
This time we're careful to pass on any return value.

```javascript theme={null}
async nodeCreated(node) {
    if (node?.comfyClass === "My Node Name") {
        const original_onMouseDown = node.onMouseDown;
        node.onMouseDown = function( e, pos, canvas ) {
            alert("ouch!");
            return original_onMouseDown?.apply(this, arguments);
        }        
    }
}
```


# Comfy Hooks
Source: https://docs.comfy.org/custom-nodes/js/javascript_hooks



## Extension hooks

At various points during Comfy execution, the application calls
`#invokeExtensionsAsync` or `#invokeExtensions` with the name of a hook.
These invoke, on all registered extensions, the appropriately named method (if present), such as `setup`
in the example above.

Comfy provides a variety of hooks for custom extension code to use to modify client behavior.

<Tip>These hooks are called during creation and modification of the Comfy client side elements.
<br />Events during workflow execution are handled by
the `apiUpdateHandlers`</Tip>&#x20;

A few of the most significant hooks are described below.
As Comfy is being actively developed, from time to time additional hooks are added, so
search for `#invokeExtensions` in `app.js` to find all available hooks.

See also the [sequence](#call-sequences) in which hooks are invoked.

### Commonly used hooks

Start with `beforeRegisterNodeDef`, which is used by the majority of extensions, and is often the only one needed.

#### beforeRegisterNodeDef()

Called once for each node type (the list of nodes available in the `AddNode` menu), and is used to
modify the behaviour of the node.

```Javascript theme={null}
async beforeRegisterNodeDef(nodeType, nodeData, app) 
```

The object passed in the `nodeType` parameter essentially serves as a template
for all nodes that will be created of this type, so modifications made to `nodeType.prototype` will apply
to all nodes of this type. `nodeData` is an encapsulation of aspects of the node defined in the Python code,
such as its category, inputs, and outputs. `app` is a reference to the main Comfy app object (which you
have already imported anyway!)

<Tip>This method is called, on each registered extension, for *every* node type, not just the ones added by that extension.</Tip>

The usual idiom is to check `nodeType.ComfyClass`, which holds the Python class name corresponding to this node,
to see if you need to modify the node. Often this means modifying the custom nodes that you have added,
although you may sometimes need to modify the behavior of other nodes (or other custom nodes
might modify yours!), in which case care should be taken to ensure interoperability.

<Tip>Since other extensions may also modify nodes, aim to write code that makes as few assumptions as possible.
And play nicely - isolate your changes wherever possible.</Tip>

A very common idiom in `beforeRegisterNodeDef` is to 'hijack' an existing method:

<Note>
  **Deprecated:** The prototype hijacking pattern shown below is deprecated and subject to change at any point in the near future. For context menus, use the official [Context Menu API](/custom-nodes/js/context-menu-migration) instead. For other use cases, prefer using the official [extension hooks](/custom-nodes/js/javascript_hooks) where available.
</Note>

```Javascript theme={null}
async beforeRegisterNodeDef(nodeType, nodeData, app) {
	if (nodeType.comfyClass=="MyNodeClass") { 
		const onConnectionsChange = nodeType.prototype.onConnectionsChange;
		nodeType.prototype.onConnectionsChange = function (side,slot,connect,link_info,output) {     
			const r = onConnectionsChange?.apply(this, arguments);   
			console.log("Someone changed my connection!");
			return r;
		}
	}
}
```

In this idiom the existing prototype method is stored, and then replaced. The replacement calls the
original method (the `?.apply` ensures that if there wasn't one this is still safe) and then
performs additional operations. Depending on your code logic, you may need to place the `apply` elsewhere in your replacement code,
or even make calling it conditional.

When hijacking a method in this way, you will want to look at the core comfy code (breakpoints are your friend) to check
and conform with the method signature.

<Warning>This approach is fragile and may break with future ComfyUI updates. Use official APIs whenever possible.</Warning>

#### nodeCreated()

```Javascript theme={null}
async nodeCreated(node)
```

Called when a specific instance of a node gets created
(right at the end of the `ComfyNode()` function on `nodeType` which serves as a constructor).
In this hook you can make modifications to individual instances of your node.

<Tip>Changes that apply to all instances are better added to the prototype in `beforeRegisterNodeDef` as described above.</Tip>

#### init()

```Javascript theme={null}
async init()
```

Called when the Comfy webpage is loaded (or reloaded). The call is made after the graph object has been created, but before any
nodes are registered or created. It can be used to modify core Comfy behavior by hijacking methods of the app, or of the
graph (a `LiteGraph` object). This is discussed further in [Comfy Objects](./javascript_objects_and_hijacking).

<Warning>With great power comes great responsibility. Hijacking core behavior makes it more likely your nodes
will be incompatible with other custom nodes, or future Comfy updates</Warning>

#### setup()

```Javascript theme={null}
async setup()
```

Called at the end of the startup process. A good place to add event listeners (either for Comfy events, or DOM events),
or adding to the global menus, both of which are discussed elsewhere.&#x20;

<Tip>To do something when a workflow has loaded, use `afterConfigureGraph`, not `setup`</Tip>

### Call sequences

These sequences were obtained by insert logging code into the Comfy `app.js` file. You may find similar code helpful
in understanding the execution flow.

```Javascript theme={null}
/* approx line 220 at time of writing: */
	#invokeExtensions(method, ...args) {
		console.log(`invokeExtensions      ${method}`) // this line added
		// ...
	}
/* approx line 250 at time of writing: */
	async #invokeExtensionsAsync(method, ...args) {
		console.log(`invokeExtensionsAsync ${method}`) // this line added
		// ...
	}
```

#### Web page load

```
invokeExtensionsAsync init
invokeExtensionsAsync addCustomNodeDefs
invokeExtensionsAsync getCustomWidgets
invokeExtensionsAsync beforeRegisterNodeDef    [repeated multiple times]
invokeExtensionsAsync registerCustomNodes
invokeExtensionsAsync beforeConfigureGraph
invokeExtensionsAsync nodeCreated
invokeExtensions      loadedGraphNode
invokeExtensionsAsync afterConfigureGraph
invokeExtensionsAsync setup
```

#### Loading workflow

```
invokeExtensionsAsync beforeConfigureGraph
invokeExtensionsAsync beforeRegisterNodeDef   [zero, one, or multiple times]
invokeExtensionsAsync nodeCreated             [repeated multiple times]
invokeExtensions      loadedGraphNode         [repeated multiple times]
invokeExtensionsAsync afterConfigureGraph
```

#### Adding new node

```
invokeExtensionsAsync nodeCreated
```


# Comfy Objects
Source: https://docs.comfy.org/custom-nodes/js/javascript_objects_and_hijacking



## LiteGraph

The Comfy UI is built on top of [LiteGraph](https://github.com/jagenjo/litegraph.js).
Much of the Comfy functionality is provided by LiteGraph, so if developing more complex
nodes you will probably find it helpful to clone that repository and browse the documentation,
which can be found at `doc/index.html`.

## ComfyApp

The `app` object (always accessible by `import { app } from "../../scripts/app.js";`) represents the Comfy application running in the browser,
and contains a number of useful properties and functions, some of which are listed below.

<Note>
  **Deprecated:** Hijacking/monkey-patching functions on `app` or prototypes is deprecated and subject to change at any point in the near future. Use the official [extension hooks](/custom-nodes/js/javascript_hooks) and [Context Menu API](/custom-nodes/js/context-menu-migration) instead.
</Note>

<Warning>Hijacking functions on `app` is not recommended, as Comfy is under constant development, and core behavior may change.</Warning>

### Properties

Important properties of `app` include (this is not an exhaustive list):

| property        | contents                                                                                                                                                        |
| --------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `canvas`        | An LGraphCanvas object, representing the current user interface. It contains some potentially interesting properties, such as `node_over` and `selected_nodes`. |
| `canvasEl`      | The DOM `<canvas>` element                                                                                                                                      |
| `graph`         | A reference to the LGraph object describing the current graph                                                                                                   |
| `runningNodeId` | During execution, the node currently being executed                                                                                                             |
| `ui`            | Provides access to some UI elements, such as the queue, menu, and dialogs                                                                                       |

`canvas` (for graphical elements) and `graph` (for logical connections) are probably the ones you are most likely to want to access.

### Functions

Again, there are many. A few significant ones are:

| function          | notes                                                                 |
| ----------------- | --------------------------------------------------------------------- |
| graphToPrompt     | Convert the graph into a prompt that can be sent to the Python server |
| loadGraphData     | Load a graph                                                          |
| queuePrompt       | Submit a prompt to the queue                                          |
| registerExtension | You've seen this one - used to add an extension                       |

## LGraph

The `LGraph` object is part of the LiteGraph framework, and represents the current logical state of the graph (nodes and links).
If you want to manipulate the graph, the LiteGraph documentation (at `doc/index.html` if you clone `https://github.com/jagenjo/litegraph.js`)
describes the functions you will need.

You can use `graph` to obtain details of nodes and links, for example:

```Javascript theme={null}
const ComfyNode_object_for_my_node = app.graph._nodes_by_id(my_node_id) 
ComfyNode_object_for_my_node.inputs.forEach(input => {
    const link_id = input.link;
    if (link_id) {
        const LLink_object = app.graph.links[link_id]
        const id_of_upstream_node = LLink_object.origin_id
        // etc
    }
});
```

## LLink

The `LLink` object, accessible through `graph.links`, represents a single link in the graph, from node `link.origin_id` output slot `link.origin_slot`
to node `link.target_id` slot `link.target_slot`. It also has a string representing the data type, in `link.type`, and `link.id`.

`LLink`s are created in the `connect` method of a `LGraphNode` (of which `ComfyNode` is a subclass).

<Tip>Avoid creating your own LLink objects - use the LiteGraph functions instead.</Tip>

## ComfyNode

`ComfyNode` is a subclass of `LGraphNode`, and the LiteGraph documentation is therefore helpful for more generic
operations. However, Comfy has significantly extended the LiteGraph core behavior, and also does not make
use of all LiteGraph functionality.

<Tip>The description that follows applies to a normal node.
Group nodes, primitive nodes, notes, and redirect nodes have different properties.</Tip>

A `ComfyNode` object represents a node in the current workflow. It has a number of important properties
that you may wish to make use of, a very large number of functions that you may wish to use, or hijack to
modify behavior.

<Note>
  **Deprecated:** Hijacking prototype methods on `ComfyNode` or `LGraphNode` is deprecated and subject to change at any point in the near future. Use the official [extension hooks](/custom-nodes/js/javascript_hooks) where available, such as `getNodeMenuItems` for context menus. See the [Context Menu Migration Guide](/custom-nodes/js/context-menu-migration) for examples.
</Note>

To get a more complete sense of the node object, you may find it helpful to insert the following
code into your extension and place a breakpoint on the `console.log` command. When you then create a new node
you can use your favorite debugger to interrogate the node.

```Javascript theme={null}
async nodeCreated(node) {
    console.log("nodeCreated")
}
```

### Properties

| property          | contents                                                                                                                            |
| ----------------- | ----------------------------------------------------------------------------------------------------------------------------------- |
| `bgcolor`         | The background color of the node, or undefined for the default                                                                      |
| `comfyClass`      | The Python class representing the node                                                                                              |
| `flags`           | A dictionary that may contain flags related to the state of the node. In particular, `flags.collapsed` is true for collapsed nodes. |
| `graph`           | A reference to the LGraph object                                                                                                    |
| `id`              | A unique id                                                                                                                         |
| `input_type`      | A list of the input types (eg "STRING", "MODEL", "CLIP" etc). Generally matches the Python INPUT\_TYPES                             |
| `inputs`          | A list of inputs (discussed below)                                                                                                  |
| `mode`            | Normally 0, set to 2 if the node is muted and 4 if the node is bypassed. Values of 1 and 3 are not used by Comfy                    |
| `order`           | The node's position in the execution order. Set by `LGraph.computeExecutionOrder()` when the prompt is submitted                    |
| `pos`             | The \[x,y] position of the node on the canvas                                                                                       |
| `properties`      | A dictionary containing `"Node name for S&R"`, used by LiteGraph                                                                    |
| `properties_info` | The type and default value of entries in `properties`                                                                               |
| `size`            | The width and height of the node on the canvas                                                                                      |
| `title`           | Display Title                                                                                                                       |
| `type`            | The unique name (from Python) of the node class                                                                                     |
| `widgets`         | A list of widgets (discussed below)                                                                                                 |
| `widgets_values`  | A list of the current values of widgets                                                                                             |

### Functions

There are a very large number of functions (85, last time I counted). A selection are listed below.
Most of these functions are unmodified from the LiteGraph core code.

#### Inputs, Outputs, Widgets

| function               | notes                                                                                              |
| ---------------------- | -------------------------------------------------------------------------------------------------- |
| Inputs / Outputs       | Most have output methods with the equivalent names: s/In/Out/                                      |
| `addInput`             | Create a new input, defined by name and type                                                       |
| `addInputs`            | Array version of `addInput`                                                                        |
| `findInputSlot`        | Find the slot index from the input name                                                            |
| `findInputSlotByType`  | Find an input matching the type. Options to prefer, or only use, free slots                        |
| `removeInput`          | By slot index                                                                                      |
| `getInputNode`         | Get the node connected to this input. The output equivalent is `getOutputNodes` and returns a list |
| `getInputLink`         | Get the LLink connected to this input. No output equivalent                                        |
| Widgets                |                                                                                                    |
| `addWidget`            | Add a standard Comfy widget                                                                        |
| `addCustomWidget`      | Add a custom widget (defined in the `getComfyWidgets` hook)                                        |
| `addDOMWidget`         | Add a widget defined by a DOM element                                                              |
| `convertWidgetToInput` | Convert a widget to an input if allowed by `isConvertableWidget` (in `widgetInputs.js`)            |

#### Connections

| function              | notes                                                                                             |
| --------------------- | ------------------------------------------------------------------------------------------------- |
| `connect`             | Connect this node's output to another node's input                                                |
| `connectByType`       | Connect output to another node by specifying the type - connects to first available matching slot |
| `connectByTypeOutput` | Connect input to another node output by type                                                      |
| `disconnectInput`     | Remove any link into the input (specified by name or index)                                       |
| `disconnectOutput`    | Disconnect an output from a specified node's input                                                |
| `onConnectionChange`  | Called on each node. `side==1` if it's an input on this node                                      |
| `onConnectInput`      | Called *before* a connection is made. If this returns `false`, the connection is refused          |

#### Display

| function           | notes                                                                                                  |
| ------------------ | ------------------------------------------------------------------------------------------------------ |
| `setDirtyCanvas`   | Specify that the foreground (nodes) and/or background (links and images) need to be redrawn            |
| `onDrawBackground` | Called with a `CanvasRenderingContext2D` object to draw the background. Used by Comfy to render images |
| `onDrawForeground` | Called with a `CanvasRenderingContext2D` object to draw the node.                                      |
| `getTitle`         | The title to be displayed.                                                                             |
| `collapse`         | Toggles the collapsed state of the node.                                                               |

<Warning>`collapse` is badly named; it *toggles* the collapsed state.
It takes a boolean parameter, which can be used to override
`node.collapsable === false`.</Warning>

#### Other

| function     | notes                                                              |
| ------------ | ------------------------------------------------------------------ |
| `changeMode` | Use to set the node to bypassed (`mode == 4`) or not (`mode == 0`) |

## Inputs and Widgets

Inputs and Widgets represent the two ways that data can be fed into a node. In general a widget can be
converted to an input, but not all inputs can be converted to a widget (as many datatypes can't be
entered through a UI element).

`node.inputs` is a list of the current inputs (colored dots on the left hand side of the node),
specifying their `.name`, `.type`, and `.link` (a reference to the connected `LLink` in `app.graph.links`).

If an input is a widget which has been converted, it also holds a reference to the, now inactive, widget in `.widget`.

`node.widgets` is a list of all widgets, whether or not they have been converted to an input. A widget has:

| property/function | notes                                                                     |
| ----------------- | ------------------------------------------------------------------------- |
| `callback`        | A function called when the widget value is changed                        |
| `last_y`          | The vertical position of the widget in the node                           |
| `name`            | The (unique within a node) widget name                                    |
| `options`         | As specified in the Python code (such as default, min, and max)           |
| `type`            | The name of the widget type (see below) in lowercase                      |
| `value`           | The current widget value. This is a property with `get` and `set` methods |

### Widget Types

`app.widgets` is a dictionary of currently registered widget types, keyed in the UPPER CASE version of the name of the type.
Build in Comfy widgets types include the self explanatory `BOOLEAN`, `INT`, and `FLOAT`,
as well as `STRING` (which comes in two flavours, single line and multiline),
`COMBO` for dropdown selection from a list, and `IMAGEUPLOAD`, used in Load Image nodes.

Custom widget types can be added by providing a `getCustomWidgets` method in your extension.

### Linked widgets

Widgets can also be linked - the built in behavior of `seed` and `control_after_generate`, for example.
A linked widget has `.type = 'base_widget_type:base_widget_name'`; so `control_after_generate` may have
type `int:seed`.

## Prompt

When you press the `Queue Prompt` button in Comfy, the `app.graphToPrompt()` method is called to convert the
current graph into a prompt that can be sent to the server.

`app.graphToPrompt` returns an object (referred to herein as `prompt`) with two properties, `output` and `workflow`.

### output

`prompt.output` maps from the `node_id` of each node in the graph to an object with two properties.

* `prompt.output[node_id].class_type`, the unique name of the custom node class, as defined in the Python code
* `prompt.output[node_id].inputs`, which contains the value of each input (or widget) as a map from the input name to:
  * the selected value, if it is a widget, or
  * an array containing (`upstream_node_id`, `upstream_node_output_slot`) if there is a link connected to the input, or
  * undefined, if it is a widget that has been converted to an input and is not connected
  * other unconnected inputs are not included in `.inputs`

<Tip>Note that the `upstream_node_id` in the array describing a connected input is represented as a string, not an integer.</Tip>

### workflow

`prompt.workflow` contains the following properties:

* `config` - a dictionary of additional configuration options (empty by default)
* `extra` - a dictionary containing extra information about the workflow. By default it contains:
  * `extra.ds` - describes the current view of the graph (`scale` and `offset`)
* `groups` - all groups in the workflow
* `last_link_id` - the id of the last link added
* `last_node_id` - the id of the last node added
* `links` - a list of all links in the graph. Each entry is an array of five integers and one string:
  * (`link_id`, `upstream_node_id`, `upstream_node_output_slot`, `downstream_node_id`, `downstream_node_input_slot`, `data type`)
* `nodes` - a list of all nodes in the graph. Each entry is a map of a subset of the properties of the node as described [above](#comfynode)
  * The following properties are included: `flags`, `id`, `inputs`, `mode`, `order`, `pos`, `properties`, `size`, `type`, `widgets_values`
  * In addition, unless a node has no outputs, there is an `outputs` property, which is a list of the outputs of the node, each of which contains:
    * `name` - the name of the output
    * `type` - the data type of the output
    * `links` - a list of the `link_id` of all links from this output (if there are no connections, may be an empty list, or null),
    * `shape` - the shape used to draw the output (default 3 for a dot)
    * `slot_index` - the slot number of the output
* `version` - the LiteGraph version number (at time of writing, `0.4`)

<Tip>`nodes.output` is absent for nodes with no outputs, not an empty list.</Tip>


# Javascript Extensions
Source: https://docs.comfy.org/custom-nodes/js/javascript_overview



## Extending the Comfy Client

Comfy can be modified through an extensions mechanism. To add an extension you need to:

* Export `WEB_DIRECTORY` from your Python module,
* Place one or more `.js` files into that directory,
* Use `app.registerExtension` to register your extension.

These three steps are below. Once you know how to add an extension, look
through the [hooks](/custom-nodes/js/javascript_hooks) available to get your code called,
a description of various [Comfy objects](/custom-nodes/js/javascript_objects_and_hijacking) you might need,
or jump straight to some [example code snippets](/custom-nodes/js/javascript_examples).

### Exporting `WEB_DIRECTORY`

The Comfy web client can be extended by creating a subdirectory in your custom node directory, conventionally called `js`, and
exporting `WEB_DIRECTORY` - so your `__init_.py` will include something like:

```python theme={null}
WEB_DIRECTORY = "./js"
__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS", "WEB_DIRECTORY"]
```

### Including `.js` files

<Tip>All Javascript `.js` files will be loaded by the browser as the Comfy webpage loads. You don't need to specify the file
your extension is in.</Tip>

*Only* `.js` files will be added to the webpage. Other resources (such as `.css` files) can be accessed
at `extensions/custom_node_subfolder/the_file.css` and added programmatically.

<Warning>That path does *not* include the name of the subfolder. The value of `WEB_DIRECTORY` is inserted by the server.</Warning>

### Registering an extension

The basic structure of an extension follows is to import the main Comfy `app` object, and call `app.registerExtension`,
passing a dictionary that contains a unique `name`,
and one or more functions to be called by hooks in the Comfy code.

A complete, trivial, and annoying, extension might look like this:

```Javascript theme={null}
import { app } from "../../scripts/app.js";
app.registerExtension({ 
	name: "a.unique.name.for.a.useless.extension",
	async setup() { 
		alert("Setup complete!")
	},
})
```


# Selection Toolbox
Source: https://docs.comfy.org/custom-nodes/js/javascript_selection_toolbox



The Selection Toolbox API allows extensions to add custom action buttons that appear when nodes are selected on the canvas. This provides quick access to context-sensitive commands for selected items (nodes, groups, etc.).

## Basic Usage

To add commands to the selection toolbox, your extension needs to:

1. Define commands with the standard [command interface](https://docs.comfy.org/custom-nodes/js/javascript_commands_keybindings)
2. Implement the `getSelectionToolboxCommands` method to specify which commands appear in the toolbox

Note: The `getSelectionToolboxCommands` method is called for each item in the selection set whenever a new selection is made.

```javascript theme={null}
app.registerExtension({
  name: "MyExtension",
  commands: [
    {
      id: "my-extension.duplicate-special",
      label: "Duplicate Special",
      icon: "pi pi-copy",
      function: (selectedItem) => {
        // Your command logic here
        console.log("Duplicating selected nodes with special behavior");
      }
    }
  ],
  getSelectionToolboxCommands: (selectedItem) => {
    // Return array of command IDs to show in the toolbox
    return ["my-extension.duplicate-special"];
  }
});
```

## Command Definition

Commands for the selection toolbox use the standard ComfyUI command interface:

```javascript theme={null}
{
  id: string,          // Unique identifier for the command
  label: string,       // Display text for the button tooltip
  icon?: string,       // Icon class for the button (optional)
  function: (selectedItem) => void  // Function executed when clicked
}
```

The `function` receives the selected item(s) as a parameter, allowing you to perform actions on the current selection.

## Icon Options

Selection toolbox buttons support the same icon libraries as other UI elements:

* PrimeVue icons: `pi pi-[icon-name]` (e.g., `pi pi-star`)
* Material Design icons: `mdi mdi-[icon-name]` (e.g., `mdi mdi-content-copy`)

## Dynamic Command Visibility

The `getSelectionToolboxCommands` method is called each time the selection changes, allowing you to show different commands based on what's selected:

```javascript theme={null}
app.registerExtension({
  name: "ContextualCommands",
  commands: [
    {
      id: "my-ext.align-nodes",
      label: "Align Nodes",
      icon: "pi pi-align-left",
      function: () => {
        // Align multiple nodes
      }
    },
    {
      id: "my-ext.configure-single",
      label: "Configure",
      icon: "pi pi-cog",
      function: () => {
        // Configure single node
      }
    }
  ],
  getSelectionToolboxCommands: (selectedItem) => {
    const selectedItems = app.canvas.selectedItems;
    const itemCount = selectedItems ? selectedItems.size : 0;
    
    if (itemCount > 1) {
      // Show alignment command for multiple items
      return ["my-ext.align-nodes"];
    } else if (itemCount === 1) {
      // Show configuration for single item
      return ["my-ext.configure-single"];
    }
    
    return [];
  }
});
```

## Working with Selected Items

Access information about selected items through the app's canvas object. The `selectedItems` property is a Set that includes nodes, groups, and other canvas elements:

```javascript theme={null}
app.registerExtension({
  name: "SelectionInfo",
  commands: [
    {
      id: "my-ext.show-info",
      label: "Show Selection Info",
      icon: "pi pi-info-circle",
      function: () => {
        const selectedItems = app.canvas.selectedItems;
        
        if (selectedItems && selectedItems.size > 0) {
          console.log(`Selected ${selectedItems.size} items`);
          
          // Iterate through selected items
          selectedItems.forEach(item => {
            if (item.type) {
              console.log(`Item: ${item.type} (ID: ${item.id})`);
            }
          });
        }
      }
    }
  ],
  getSelectionToolboxCommands: () => ["my-ext.show-info"]
});
```

## Complete Example

Here's a simple example showing various selection toolbox features:

```javascript theme={null}
app.registerExtension({
  name: "SelectionTools",
  commands: [
    {
      id: "selection-tools.count",
      label: "Count Selection",
      icon: "pi pi-hashtag",
      function: () => {
        const count = app.canvas.selectedItems?.size || 0;
        app.extensionManager.toast.add({
          severity: "info",
          summary: "Selection Count",
          detail: `You have ${count} item${count !== 1 ? 's' : ''} selected`,
          life: 3000
        });
      }
    },
    {
      id: "selection-tools.copy-ids",
      label: "Copy IDs",
      icon: "pi pi-copy",
      function: () => {
        const items = Array.from(app.canvas.selectedItems || []);
        const ids = items.map(item => item.id).filter(id => id !== undefined);
        
        if (ids.length > 0) {
          navigator.clipboard.writeText(ids.join(', '));
          app.extensionManager.toast.add({
            severity: "success",
            summary: "Copied",
            detail: `Copied ${ids.length} IDs to clipboard`,
            life: 2000
          });
        }
      }
    },
    {
      id: "selection-tools.log-types",
      label: "Log Types",
      icon: "pi pi-info-circle",
      function: () => {
        const items = Array.from(app.canvas.selectedItems || []);
        const typeCount = {};
        
        items.forEach(item => {
          const type = item.type || 'unknown';
          typeCount[type] = (typeCount[type] || 0) + 1;
        });
        
        console.log("Selection types:", typeCount);
      }
    }
  ],
  
  getSelectionToolboxCommands: (selectedItem) => {
    const selectedItems = app.canvas.selectedItems;
    const itemCount = selectedItems ? selectedItems.size : 0;
    
    if (itemCount === 0) return [];
    
    const commands = ["selection-tools.count", "selection-tools.log-types"];
    
    // Only show copy command if items have IDs
    const hasIds = Array.from(selectedItems).some(item => item.id !== undefined);
    if (hasIds) {
      commands.push("selection-tools.copy-ids");
    }
    
    return commands;
  }
});
```

## Notes

* The selection toolbox must be enabled in settings: `Comfy.Canvas.SelectionToolbox`
* Commands must be defined in the `commands` array before being referenced in `getSelectionToolboxCommands`
* The toolbox automatically updates when the selection changes
* The `getSelectionToolboxCommands` method is called for each item in the selection set whenever a new selection is made
* Use `app.canvas.selectedItems` (a Set) to access all selected items including nodes, groups, and other canvas elements
* For backward compatibility, `app.canvas.selected_nodes` still exists but only contains nodes


# Settings
Source: https://docs.comfy.org/custom-nodes/js/javascript_settings



You can provide a settings object to ComfyUI that will show up when the user
opens the ComfyUI settings panel.

## Basic operation

### Add a setting

```javascript theme={null}
import { app } from "../../scripts/app.js";

app.registerExtension({
    name: "My Extension",
    settings: [
        {
            id: "example.boolean",
            name: "Example boolean setting",
            type: "boolean",
            defaultValue: false,
        },
    ],
});
```

The `id` must be unique across all extensions and will be used to fetch values.

If you do not [provide a category](#categories), then the `id` will be split by
`.` to determine where it appears in the settings panel.

* If your `id` doesn't contain any `.` then it will appear in the "Other"
  category and your `id` will be used as the section heading.
* If your `id` contains at least one `.` then the leftmost part will be used
  as the setting category and the second part will be used as the section
  heading. Any further parts are ignored.

### Read a setting

```javascript theme={null}
import { app } from "../../scripts/app.js";

if (app.extensionManager.setting.get('example.boolean')) {
    console.log("Setting is enabled.");
} else {
    console.log("Setting is disabled.");
}
```

### React to changes

The `onChange()` event handler will be called as soon as the user changes the
setting in the settings panel.

This will also be called when the extension is registered, on every page load.

```javascript theme={null}
{
    id: "example.boolean",
    name: "Example boolean setting",
    type: "boolean",
    defaultValue: false,
    onChange: (newVal, oldVal) => {
        console.log(`Setting was changed from ${oldVal} to ${newVal}`);
    },
}
```

### Write a setting

```javascript theme={null}
import { app } from "../../scripts/app.js";

try {
    await app.extensionManager.setting.set("example.boolean", true);
} catch (error) {
    console.error(`Error changing setting: ${error}`);
}
```

### Extra configuration

The setting types are based on [PrimeVue](https://primevue.org/) components.
Props described in the PrimeVue documentation can be defined for ComfyUI
settings by adding them in an `attrs` field.

For instance, this adds increment/decrement buttons to a number input:

```javascript theme={null}
{
    id: "example.number",
    name: "Example number setting",
    type: "number",
    defaultValue: 0,
    attrs: {
        showButtons: true,
    },
    onChange: (newVal, oldVal) => {
        console.log(`Setting was changed from ${oldVal} to ${newVal}`);
    },
}
```

## Types

### Boolean

This shows an on/off toggle.

Based on the [ToggleSwitch PrimeVue
component](https://primevue.org/toggleswitch/).

```javascript theme={null}
{
    id: "example.boolean",
    name: "Example boolean setting",
    type: "boolean",
    defaultValue: false,
    onChange: (newVal, oldVal) => {
        console.log(`Setting was changed from ${oldVal} to ${newVal}`);
    },
}
```

### Text

This is freeform text.

Based on the [InputText PrimeVue component](https://primevue.org/inputtext/).

```javascript theme={null}
{
    id: "example.text",
    name: "Example text setting",
    type: "text",
    defaultValue: "Foo",
    onChange: (newVal, oldVal) => {
        console.log(`Setting was changed from ${oldVal} to ${newVal}`);
    },
}
```

### Number

This for entering numbers.

To allow decimal places, set the `maxFractionDigits` attribute to a number greater than zero.

Based on the [InputNumber PrimeVue
component](https://primevue.org/inputnumber/).

```javascript theme={null}
{
    id: "example.number",
    name: "Example number setting",
    type: "number",
    defaultValue: 42,
    attrs: {
        showButtons: true,
        maxFractionDigits: 1,
    },
    onChange: (newVal, oldVal) => {
        console.log(`Setting was changed from ${oldVal} to ${newVal}`);
    },
}
```

### Slider

This lets the user enter a number directly or via a slider.

Based on the [Slider PrimeVue component](https://primevue.org/slider/). Ranges
are not supported.

```javascript theme={null}
{
    id: "example.slider",
    name: "Example slider setting",
    type: "slider",
    attrs: {
        min: -10,
        max: 10,
        step: 0.5,
    },
    defaultValue: 0,
    onChange: (newVal, oldVal) => {
        console.log(`Setting was changed from ${oldVal} to ${newVal}`);
    },
}
```

### Combo

This lets the user pick from a drop-down list of values.

You can provide options either as a plain string or as an object with `text`
and `value` fields. If you only provide a plain string, then it will be used
for both.

You can let the user enter freeform text by supplying the `editable: true`
attribute, or search by supplying the `filter: true` attribute.

Based on the [Select PrimeVue component](https://primevue.org/select/). Groups
are not supported.

```javascript theme={null}
{
    id: "example.combo",
    name: "Example combo setting",
    type: "combo",
    defaultValue: "first",
    options: [
        { text: "My first option", value: "first" },
        "My second option",
    ],
    attrs: {
        editable: true,
        filter: true,
    },
    onChange: (newVal, oldVal) => {
        console.log(`Setting was changed from ${oldVal} to ${newVal}`);
    },
}
```

### Color

This lets the user select a color from a color picker or type in a hex
reference.

Note that the format requires six full hex digits - three digit shorthand does
not work.

Based on the [ColorPicker PrimeVue
component](https://primevue.org/colorpicker/).

```javascript theme={null}
{
    id: "example.color",
    name: "Example color setting",
    type: "color",
    defaultValue: "ff0000",
    onChange: (newVal, oldVal) => {
        console.log(`Setting was changed from ${oldVal} to ${newVal}`);
    },
}
```

### Image

This lets the user upload an image.

The setting will be saved as a [data
URL](https://developer.mozilla.org/en-US/docs/Web/URI/Schemes/data).

Based on the [FileUpload PrimeVue
component](https://primevue.org/fileupload/).

```javascript theme={null}
{
    id: "example.image",
    name: "Example image setting",
    type: "image",
    onChange: (newVal, oldVal) => {
        console.log(`Setting was changed from ${oldVal} to ${newVal}`);
    },
}
```

### Hidden

Hidden settings aren't displayed in the settings panel, but you can read and
write to them from your code.

```javascript theme={null}
{
    id: "example.hidden",
    name: "Example hidden setting",
    type: "hidden",
}
```

## Other

### Categories

You can specify the categorisation of your setting separately to the `id`.
This means you can change the categorisation and naming without changing the
`id` and losing the values that have already been set by users.

```javascript theme={null}
{
    id: "example.boolean",
    name: "Example boolean setting",
    type: "boolean",
    defaultValue: false,
    category: ["Category name", "Section heading", "Setting label"],
}
```

### Tooltips

You can add extra contextual help with the `tooltip` field. This adds a small ℹ︎
icon after the field name that will show the help text when the user hovers
over it.

```javascript theme={null}
{
    id: "example.boolean",
    name: "Example boolean setting",
    type: "boolean",
    defaultValue: false,
    tooltip: "This is some helpful information",
}
```


# Sidebar Tabs
Source: https://docs.comfy.org/custom-nodes/js/javascript_sidebar_tabs



The Sidebar Tabs API allows extensions to add custom tabs to the sidebar of the ComfyUI interface. This is useful for adding features that require persistent visibility and quick access.

## Basic Usage

```javascript theme={null}
app.extensionManager.registerSidebarTab({
  id: "customSidebar",
  icon: "pi pi-compass",
  title: "Custom Tab",
  tooltip: "My Custom Sidebar Tab",
  type: "custom",
  render: (el) => {
    el.innerHTML = '<div>This is my custom sidebar content</div>';
  }
});
```

## Tab Configuration

Each tab requires several properties:

```javascript theme={null}
{
  id: string,              // Unique identifier for the tab
  icon: string,            // Icon class for the tab button
  title: string,           // Title text for the tab
  tooltip?: string,        // Tooltip text on hover (optional)
  type: string,            // Tab type (usually "custom")
  render: (element) => void // Function that populates the tab content
}
```

The `render` function receives a DOM element where you should insert your tab's content.

## Icon Options

Sidebar tab icons can use various icon sets:

* PrimeVue icons: `pi pi-[icon-name]` (e.g., `pi pi-home`)
* Material Design icons: `mdi mdi-[icon-name]` (e.g., `mdi mdi-robot`)
* Font Awesome icons: `fa-[style] fa-[icon-name]` (e.g., `fa-solid fa-star`)

Ensure the corresponding icon library is loaded before using these icons.

## Stateful Tab Example

You can create tabs that maintain state:

```javascript theme={null}
app.extensionManager.registerSidebarTab({
  id: "statefulTab",
  icon: "pi pi-list",
  title: "Notes",
  type: "custom",
  render: (el) => {
    // Create elements
    const container = document.createElement('div');
    container.style.padding = '10px';
    
    const notepad = document.createElement('textarea');
    notepad.style.width = '100%';
    notepad.style.height = '200px';
    notepad.style.marginBottom = '10px';
    
    // Load saved content if available
    const savedContent = localStorage.getItem('comfyui-notes');
    if (savedContent) {
      notepad.value = savedContent;
    }
    
    // Auto-save content
    notepad.addEventListener('input', () => {
      localStorage.setItem('comfyui-notes', notepad.value);
    });
    
    // Assemble the UI
    container.appendChild(notepad);
    el.appendChild(container);
  }
});
```

## Using React Components

You can mount React components in sidebar tabs:

```javascript theme={null}
// Import React dependencies in your extension
import React from "react";
import ReactDOM from "react-dom/client";

// Register sidebar tab with React content
app.extensionManager.registerSidebarTab({
  id: "reactSidebar",
  icon: "mdi mdi-react",
  title: "React Tab",
  type: "custom",
  render: (el) => {
    const container = document.createElement("div");
    container.id = "react-sidebar-container";
    el.appendChild(container);
    
    // Define a simple React component
    function SidebarContent() {
      const [count, setCount] = React.useState(0);
      
      return (
        <div style={{ padding: "10px" }}>
          <h3>React Sidebar</h3>
          <p>Count: {count}</p>
          <button onClick={() => setCount(count + 1)}>
            Increment
          </button>
        </div>
      );
    }
    
    // Mount React component
    ReactDOM.createRoot(container).render(
      <React.StrictMode>
        <SidebarContent />
      </React.StrictMode>
    );
  }
});
```

For a real-world example of a React application integrated as a sidebar tab, check out the [ComfyUI-Copilot project on GitHub](https://github.com/AIDC-AI/ComfyUI-Copilot).

## Dynamic Content Updates

You can update sidebar content in response to graph changes:

```javascript theme={null}
app.extensionManager.registerSidebarTab({
  id: "dynamicSidebar",
  icon: "pi pi-chart-line",
  title: "Stats",
  type: "custom",
  render: (el) => {
    const container = document.createElement('div');
    container.style.padding = '10px';
    el.appendChild(container);
    
    // Function to update stats
    function updateStats() {
      const stats = {
        nodes: app.graph._nodes.length,
        connections: Object.keys(app.graph.links).length
      };
      
      container.innerHTML = `
        <h3>Workflow Stats</h3>
        <ul>
          <li>Nodes: ${stats.nodes}</li>
          <li>Connections: ${stats.connections}</li>
        </ul>
      `;
    }
    
    // Initial update
    updateStats();
    
    // Listen for graph changes
    const api = app.api;
    api.addEventListener("graphChanged", updateStats);
    
    // Clean up listeners when tab is destroyed
    return () => {
      api.removeEventListener("graphChanged", updateStats);
    };
  }
});
```


# Toast API
Source: https://docs.comfy.org/custom-nodes/js/javascript_toast



The Toast API provides a way to display non-blocking notification messages to users. These are useful for providing feedback without interrupting workflow.

## Basic Usage

### Simple Toast

```javascript theme={null}
// Display a simple info toast
app.extensionManager.toast.add({
  severity: "info",
  summary: "Information",
  detail: "Operation completed successfully",
  life: 3000
});
```

### Toast Types

```javascript theme={null}
// Success toast
app.extensionManager.toast.add({
  severity: "success",
  summary: "Success",
  detail: "Data saved successfully",
  life: 3000
});

// Warning toast
app.extensionManager.toast.add({
  severity: "warn",
  summary: "Warning",
  detail: "This action may cause problems",
  life: 5000
});

// Error toast
app.extensionManager.toast.add({
  severity: "error",
  summary: "Error",
  detail: "Failed to process request",
  life: 5000
});
```

### Alert Helper

```javascript theme={null}
// Shorthand for creating an alert toast
app.extensionManager.toast.addAlert("This is an important message");
```

## API Reference

### Toast Message

```javascript theme={null}
app.extensionManager.toast.add({
  severity?: "success" | "info" | "warn" | "error" | "secondary" | "contrast", // Message severity level (default: "info")
  summary?: string,         // Short title for the toast
  detail?: any,             // Detailed message content
  closable?: boolean,       // Whether user can close the toast (default: true)
  life?: number,            // Duration in milliseconds before auto-closing
  group?: string,           // Group identifier for managing related toasts
  styleClass?: any,         // Style class of the message
  contentStyleClass?: any   // Style class of the content
});
```

### Alert Helper

```javascript theme={null}
app.extensionManager.toast.addAlert(message: string);
```

### Additional Methods

```javascript theme={null}
// Remove a specific toast
app.extensionManager.toast.remove(toastMessage);

// Remove all toasts
app.extensionManager.toast.removeAll();
```


# Topbar Menu
Source: https://docs.comfy.org/custom-nodes/js/javascript_topbar_menu



The Topbar Menu API allows extensions to add custom menu items to the ComfyUI's top menu bar. This is useful for providing access to advanced features or less frequently used commands.

## Basic Usage

```javascript theme={null}
app.registerExtension({
  name: "MyExtension",
  // Define commands
  commands: [
    { 
      id: "myCommand", 
      label: "My Command", 
      function: () => { alert("Command executed!"); } 
    }
  ],
  // Add commands to menu
  menuCommands: [
    { 
      path: ["Extensions", "My Extension"], 
      commands: ["myCommand"] 
    }
  ]
});
```

Command definitions follow the same pattern as in the [Commands and Keybindings API](./javascript_commands_keybindings). See that page for more detailed information about defining commands.

## Command Configuration

Each command requires an `id`, `label`, and `function`:

```javascript theme={null}
{
  id: string,              // Unique identifier for the command
  label: string,           // Display name for the command
  function: () => void     // Function to execute when command is triggered
}
```

## Menu Configuration

The `menuCommands` array defines where to place commands in the menu structure:

```javascript theme={null}
{
  path: string[],          // Array representing menu hierarchy
  commands: string[]       // Array of command IDs to add at this location
}
```

The `path` array specifies the menu hierarchy. For example, `["File", "Export"]` would add commands to the "Export" submenu under the "File" menu.

## Menu Examples

### Adding to Existing Menus

```javascript theme={null}
app.registerExtension({
  name: "MenuExamples",
  commands: [
    { 
      id: "saveAsImage", 
      label: "Save as Image", 
      function: () => { 
        // Code to save canvas as image
      } 
    },
    { 
      id: "exportWorkflow", 
      label: "Export Workflow", 
      function: () => { 
        // Code to export workflow
      } 
    }
  ],
  menuCommands: [
    // Add to File menu
    { 
      path: ["File"], 
      commands: ["saveAsImage", "exportWorkflow"] 
    }
  ]
});
```

### Creating Submenu Structure

```javascript theme={null}
app.registerExtension({
  name: "SubmenuExample",
  commands: [
    { 
      id: "option1", 
      label: "Option 1", 
      function: () => { console.log("Option 1"); } 
    },
    { 
      id: "option2", 
      label: "Option 2", 
      function: () => { console.log("Option 2"); } 
    },
    { 
      id: "suboption1", 
      label: "Sub-option 1", 
      function: () => { console.log("Sub-option 1"); } 
    }
  ],
  menuCommands: [
    // Create a nested menu structure
    { 
      path: ["Extensions", "My Tools"], 
      commands: ["option1", "option2"] 
    },
    { 
      path: ["Extensions", "My Tools", "Advanced"], 
      commands: ["suboption1"] 
    }
  ]
});
```

### Multiple Menu Locations

You can add the same command to multiple menu locations:

```javascript theme={null}
app.registerExtension({
  name: "MultiLocationExample",
  commands: [
    { 
      id: "helpCommand", 
      label: "Get Help", 
      function: () => { window.open("https://docs.example.com", "_blank"); } 
    }
  ],
  menuCommands: [
    // Add to Help menu
    { 
      path: ["Help"], 
      commands: ["helpCommand"] 
    },
    // Also add to Extensions menu
    { 
      path: ["Extensions"], 
      commands: ["helpCommand"] 
    }
  ]
});
```

Commands can work with other ComfyUI APIs like settings. For more information about the Settings API, see the [Settings API](./javascript_settings) documentation.


# Subgraphs
Source: https://docs.comfy.org/custom-nodes/js/subgraphs

Working with subgraphs in ComfyUI extensions: node IDs, graph traversal, events, widget promotion, and cleanup.

## Overview

Subgraphs let users group nodes into reusable, nestable components. Each subgraph is its own `LGraph` with a UUID. For the user-facing guide, see [Subgraphs](/interface/features/subgraph).

## Node Identifiers

ComfyUI uses three distinct node identifier types. Using the wrong one causes silent failures.

| Type         | Format                                | Used for                                                    |
| ------------ | ------------------------------------- | ----------------------------------------------------------- |
| `node.id`    | `42` (number)                         | Local to its immediate graph level. `graph.getNodeById(id)` |
| Execution ID | `"1:2:3"` (colon-separated string)    | Backend progress messages, `UNIQUE_ID`                      |
| Locator ID   | `"<uuid>:<localId>"` or `"<localId>"` | UI state: badges, errors, images                            |

To construct a node's locator ID from within an extension:

```javascript theme={null}
function getLocatorId(node) {
  const graphId = node.graph?.id
  return graphId ? `${graphId}:${node.id}` : String(node.id)
}
```

## Traversing Nodes

### Current layer only

```javascript theme={null}
for (const node of app.graph.nodes) {
  console.log(node.id, node.type)
}
```

### All nodes recursively

To walk into nested subgraphs, use a recursive helper that calls a callback on every node:

```javascript theme={null}
function walkGraph(graph, callback) {
  for (const node of graph.nodes ?? []) {
    callback(node, graph)
    if (node.subgraph) walkGraph(node.subgraph, callback)
  }
}
```

Full example:

```javascript theme={null}
import { app } from "../../scripts/app.js"

function walkGraph(graph, callback) {
  for (const node of graph.nodes ?? []) {
    callback(node, graph)
    if (node.subgraph) walkGraph(node.subgraph, callback)
  }
}

app.registerExtension({
  name: "MyExtension.SubgraphWalker",
  async afterConfigureGraph() {
    walkGraph(app.graph, (node, graph) => {
      console.log(`[${graph.id ?? "root"}] node ${node.id}: ${node.type}`)
    })
  }
})
```

## Root vs Active Graph

| You want to...                       | Use                 |
| ------------------------------------ | ------------------- |
| Operate on all nodes in the workflow | `app.graph` (root)  |
| Operate on only the visible layer    | `app.canvas?.graph` |
| Access a specific subgraph           | `someNode.subgraph` |

```javascript theme={null}
// All nodes (including nested subgraphs)
walkGraph(app.graph, (node) => { /* ... */ })

// Only nodes the user currently sees
for (const node of app.canvas?.graph?.nodes ?? []) { /* ... */ }
```

## Events

### Subgraph-level events

Dispatched on `subgraph.events`:

| Event             | Payload                               | When                            |
| ----------------- | ------------------------------------- | ------------------------------- |
| `widget-promoted` | `{ widget, subgraphNode }`            | Widget promoted to parent node  |
| `widget-demoted`  | `{ widget, subgraphNode }`            | Widget removed from parent node |
| `input-added`     | `{ input }`                           | Input slot added                |
| `removing-input`  | `{ input, index }`                    | Input slot being removed        |
| `output-added`    | `{ output }`                          | Output slot added               |
| `removing-output` | `{ output, index }`                   | Output slot being removed       |
| `renaming-input`  | `{ input, index, oldName, newName }`  | Input slot renamed              |
| `renaming-output` | `{ output, index, oldName, newName }` | Output slot renamed             |

### Canvas-level events

Dispatched on `app.canvas.canvas` (the HTML canvas element):

| Event                | Payload                                | When                              |
| -------------------- | -------------------------------------- | --------------------------------- |
| `subgraph-opened`    | `{ subgraph, closingGraph, fromNode }` | User navigates into a subgraph    |
| `subgraph-converted` | `{ subgraphNode }`                     | Selection converted to a subgraph |

### Listening pattern

```javascript theme={null}
import { app } from "../../scripts/app.js"

app.registerExtension({
  name: "MyExtension.SubgraphEvents",
  async setup() {
    app.canvas.canvas.addEventListener("subgraph-opened", (e) => {
      const { subgraph, fromNode } = e.detail
      console.log(`Opened subgraph from node ${fromNode.id}`)
    })
  }
})
```

## Widget Promotion

When a `SubgraphInput` connects to a widget inside a subgraph, a copy of that widget appears on the parent subgraph node. This fires `widget-promoted`. Removing the connection fires `widget-demoted`.

<Warning>
  Widget promotion behavior is still evolving and may change in future releases.
</Warning>

```javascript theme={null}
import { app } from "../../scripts/app.js"

function walkGraph(graph, callback) {
  for (const node of graph.nodes ?? []) {
    callback(node, graph)
    if (node.subgraph) walkGraph(node.subgraph, callback)
  }
}

app.registerExtension({
  name: "MyExtension.WidgetPromotion",
  async afterConfigureGraph() {
    walkGraph(app.graph, (node) => {
      if (!node.subgraph) return
      if (node._promCleanup) node._promCleanup.abort()
      const controller = new AbortController()
      node._promCleanup = controller
      const { signal } = controller

      node.subgraph.events.addEventListener("widget-promoted", (e) => {
        console.log(`Widget "${e.detail.widget.name}" promoted`)
      }, { signal })

      node.subgraph.events.addEventListener("widget-demoted", (e) => {
        console.log(`Widget "${e.detail.widget.name}" demoted`)
      }, { signal })

      const origRemoved = node.onRemoved
      node.onRemoved = function () {
        controller.abort()
        origRemoved?.apply(this, arguments)
      }
    })
  }
})
```

## Cleanup

Use an `AbortController` to clean up all event listeners when a node is removed.

```javascript theme={null}
import { app } from "../../scripts/app.js"

app.registerExtension({
  name: "MyExtension.Cleanup",
  async nodeCreated(node) {
    if (!node.subgraph) return

    const controller = new AbortController()
    const { signal } = controller

    node.subgraph.events.addEventListener("input-added", (e) => {
      console.log(`Input added: ${e.detail.input.name}`)
    }, { signal })

    node.subgraph.events.addEventListener("removing-input", (e) => {
      console.log(`Input removing: ${e.detail.input.name}`)
    }, { signal })

    const origRemoved = node.onRemoved
    node.onRemoved = function () {
      controller.abort()
      origRemoved?.apply(this, arguments)
    }
  }
})
```

<Tip>
  `onRemoved` can also fire during subgraph conversion, not just deletion. Guard teardown logic if you need to preserve state across restructuring.
</Tip>

## See Also

* [Subgraphs (User Guide)](/interface/features/subgraph)
* [Extension Hooks](/custom-nodes/js/javascript_hooks)


# Overview
Source: https://docs.comfy.org/custom-nodes/overview



Custom nodes allow you to implement new features and share them with the wider community.

A custom node is like any Comfy node: it takes input, does something to it, and produces an output.
While some custom nodes perform highly complex tasks, many just do one thing. Here's an example of a
simple node that takes an image and inverts it.

<img alt="Unique Images Node" />

Custom node examples：

* [cookiecutter-comfy-extension](https://github.com/Comfy-Org/cookiecutter-comfy-extension)
* [ComfyUI-React-Extension-Template](https://github.com/Comfy-Org/ComfyUI-React-Extension-Template)
* [ComfyUI\_frontend\_vue\_basic](https://github.com/jtydhr88/ComfyUI_frontend_vue_basic)

## Client-Server Model

Comfy runs in a client-server model. The server, written in Python, handles all the real work: data-processing, models, image diffusion etc. The client, written in Javascript, handles the user interface.

Comfy can also be used in API mode, in which a workflow is sent to the server by a non-Comfy client (such as another UI, or a command line script).

Custom nodes can be placed into one of four categories:

### Server side only

The majority of Custom Nodes run purely on the server side, by defining a Python class that specifies the input and output types, and provides a function that can be called to process inputs and produce an output.

### Client side only

A few Custom Nodes provide a modification to the client UI, but do not add core functionality. Despite the name, they may not even add new nodes to the system.

### Independent Client and Server

Custom nodes may provide additional server features, and additional (related) UI features (such as a new widget to deal with a new data type). In most cases, communication between the client and server can be handled by the Comfy data flow control.

### Connected Client and Server

In a small number of cases, the UI features and the server need to interact with each other directly.

<Warning>Any node that requires Client-Server communication will not be compatible with use through the API.</Warning>


# Subgraph blueprints
Source: https://docs.comfy.org/custom-nodes/subgraph_blueprints



If you have reusable subgraph components associated with your custom nodes, ComfyUI can make these available to users as global subgraph blueprints. Subgraph blueprints allow users to quickly add pre-built node groups from the subgraph menu.

All you have to do as a node developer is create a `subgraphs` folder in your custom node directory and place the `.json` files there.

Under the hood, ComfyUI scans all custom node directories for subgraph files and serves them via the `/global_subgraphs` API endpoint.

## Example

Under `ComfyUI-MyCustomNodeModule/subgraphs/` directory:

* `My_upscale_subgraph.json`
* `My_effects_subgraph.json`

In this example, ComfyUI's subgraph browser shows blueprints from `ComfyUI-MyCustomNodeModule` that users can add to their workflows.

## Creating a subgraph JSON file

Subgraph JSON files use the same format as workflow JSON files. The easiest way to create one:

1. Build your subgraph in ComfyUI
2. Select the nodes you want to include
3. Convert them to a subgraph
4. Export the subgraph as JSON
5. Place the JSON file in your `subgraphs/` folder

## See also

* [Subgraphs (User Guide)](/interface/features/subgraph) - How users interact with subgraphs
* [Subgraph Developer Guide](/custom-nodes/js/subgraphs) - Frontend extension development for subgraphs
* [Workflow templates](/custom-nodes/workflow_templates) - Adding example workflows to your custom nodes


# V3 Migration
Source: https://docs.comfy.org/custom-nodes/v3_migration

How to migrate your existing V1 nodes to the new V3 schema.

## Overview

The ComfyUI V3 schema introduces a more organized way of defining nodes, and future extensions to node features will only be added to V3 schema. You can use this guide to help you migrate your existing V1 nodes to the new V3 schema.

## Core Concepts

The V3 schema is kept on the new versioned Comfy API, meaning future revisions to the schema will be backwards compatible. `comfy_api.latest` will point to the latest numbered API that is still under development; the version before latest is what can be considered 'stable'. Version `v0_0_2` is the current (and first) API version so more changes will be made to it without warning. Once it is considered stable, a new version `v0_0_3` will be created for `latest` to point at.

```python theme={null}
# use latest ComfyUI API
from comfy_api.latest import ComfyExtension, io, ui

# use a specific version of ComfyUI API
from comfy_api.v0_0_2 import ComfyExtension, io, ui
```

### V1 vs V3 Architecture

The biggest changes in V3 schema are:

* Inputs and Outputs defined by objects instead of a dictionary.
* The execution method is fixed to the name 'execute' and is a class method.
* `def comfy_entrypoint()` function that returns a ComfyExtension object defines exposed nodes instead of NODE\_CLASS\_MAPPINGS/NODE\_DISPLAY\_NAME\_MAPPINGS
* Node objects do not expose 'state' - `def __init__(self)` will have no effect on what is exposed in the node's functions, as all of them are class methods. The node class is sanitized before execution as well.

#### V1 (Legacy)

```python theme={null}
class MyNode:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": {...}}

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "execute"
    CATEGORY = "my_category"

    def execute(self, ...):
        return (result,)

NODE_CLASS_MAPPINGS = {"MyNode": MyNode}
```

#### V3 (Modern)

```python theme={null}
from comfy_api.latest import ComfyExtension, io

class MyNode(io.ComfyNode):
    @classmethod
    def define_schema(cls) -> io.Schema:
        return io.Schema(
            node_id="MyNode",
            display_name="My Node",
            category="my_category",
            inputs=[...],
            outputs=[...]
        )

    @classmethod
    def execute(cls, ...) -> io.NodeOutput:
        return io.NodeOutput(result)

class MyExtension(ComfyExtension):
    async def get_node_list(self) -> list[type[io.ComfyNode]]:
        return [MyNode]

async def comfy_entrypoint() -> ComfyExtension:
    return MyExtension()
```

## Migration Steps

Going from V1 to V3 should be simple in most cases and is simply a syntax change.

### Step 1: Change Base Class

All V3 Schema nodes should inherit from `ComfyNode`. Multiple layers of inheritance are okay as long as at the top of the chain there is a `ComfyNode` parent.

**V1:**

```python theme={null}
class Example:
    def __init__(self):
        pass
```

**V3:**

```python theme={null}
from comfy_api.latest import io

class Example(io.ComfyNode):
    # No __init__ needed
```

### Step 2: Convert INPUT\_TYPES to define\_schema

Node properties like node id, display name, category, etc. that were assigned in different places in code such as dictionaries and class properties are now kept together via the `Schema` class.

The `define_schema(cls)` function is expected to return a `Schema` object in much the same way INPUT\_TYPES(s) worked in V1.

Supported core Input/Output types are stored and documented in `comfy_api/{version}` in `_io.py`, which is namespaced as `io` by default. Since Inputs/Outputs are defined by classes now instead of dictionaries or strings, custom types are supported by either defining your own class or using the helper function `Custom` in `io`.

Custom types are elaborated on in a section further below.

A type class has the following properties:

* `class Input` for Inputs (i.e. `Model.Input(...)`)
* `class Output` for Outputs (i.e. `Model.Output(...)`). Note that all types may not support being an output.
* `Type` for getting a typehint of the type (i.e. `Model.Type`). Note that some typehints are just `any`, which may be updated in the future. These typehints are not enforced and just act as useful documentation.

**V1:**

```python theme={null}
@classmethod
def INPUT_TYPES(s):
    return {
        "required": {
            "image": ("IMAGE",),
            "int_field": ("INT", {
                "default": 0,
                "min": 0,
                "max": 4096,
                "step": 64,
                "display": "number"
            }),
            "string_field": ("STRING", {
                "multiline": False,
                "default": "Hello"
            }),
            # V1 handling of arbitrary types
            "custom_field": ("MY_CUSTOM_TYPE",),
        },
        "optional": {
            "mask": ("MASK",)
        }
    }
```

**V3:**

```python theme={null}
@classmethod
def define_schema(cls) -> io.Schema:
    return io.Schema(
        node_id="Example",
        display_name="Example Node",
        category="examples",
        description="Node description here",
        inputs=[
            io.Image.Input("image"),
            io.Int.Input("int_field",
                default=0,
                min=0,
                max=4096,
                step=64,
                display_mode=io.NumberDisplay.number
            ),
            io.String.Input("string_field",
                default="Hello",
                multiline=False
            ),
            # V3 handling of arbitrary types
            io.Custom("my_custom_type").Input("custom_input"),
            io.Mask.Input("mask", optional=True)
        ],
        outputs=[
            io.Image.Output()
        ]
    )
```

### Step 3: Update Execute Method

All execution functions in v3 are named `execute` and are class methods.

**V1:**

```python theme={null}
def test(self, image, string_field, int_field):
    # Process
    image = 1.0 - image
    return (image,)
```

**V3:**

```python theme={null}
@classmethod
def execute(cls, image, string_field, int_field) -> io.NodeOutput:
    # Process
    image = 1.0 - image

    # Return with optional UI preview
    return io.NodeOutput(image, ui=ui.PreviewImage(image, cls=cls))
```

### Step 4: Convert Node Properties

Here are some examples of property names; see the source code in `comfy_api.latest._io` for more details.

| V1 Property    | V3 Schema Field             | Notes                       |
| -------------- | --------------------------- | --------------------------- |
| `RETURN_TYPES` | `outputs` in Schema         | List of Output objects      |
| `RETURN_NAMES` | `display_name` in Output    | Per-output display names    |
| `FUNCTION`     | Always `execute`            | Method name is standardized |
| `CATEGORY`     | `category` in Schema        | String value                |
| `OUTPUT_NODE`  | `is_output_node` in Schema  | Boolean flag                |
| `DEPRECATED`   | `is_deprecated` in Schema   | Boolean flag                |
| `EXPERIMENTAL` | `is_experimental` in Schema | Boolean flag                |

### Step 5: Handle Special Methods

The same special methods are supported as in v1, but either lowercased or renamed entirely to be more clear. Their usage remains the same.

#### Validation (V1 → V3)

The input validation function was renamed to `validate_inputs`.

**V1:**

```python theme={null}
@classmethod
def VALIDATE_INPUTS(s, **kwargs):
    # Validation logic
    return True
```

**V3:**

```python theme={null}
@classmethod
def validate_inputs(cls, **kwargs) -> bool | str:
    # Return True if valid, error string if not
    if error_condition:
        return "Error message"
    return True
```

#### Lazy Evaluation (V1 → V3)

The `check_lazy_status` function is class method, remains the same otherwise.

**V1:**

```python theme={null}
def check_lazy_status(self, image, string_field, ...):
    if condition:
        return ["string_field"]
    return []
```

**V3:**

```python theme={null}
@classmethod
def check_lazy_status(cls, image, string_field, ...):
    if condition:
        return ["string_field"]
    return []
```

#### Cache Control (V1 → V3)

The functionality of cache control remains the same as in V1, but the original name was very misleading as to how it operated.

V1's `IS_CHANGED` function signals execution not to trigger rerunning the node if the return value is the SAME as the last time the node was ran.

Thus, the function `IS_CHANGED` was renamed to `fingerprint_inputs`. One of the most common mistakes by developers was thinking if you return `True`, the node would always re-run. Because `True` would always be returned, it would have the opposite effect of only making the node run once and reuse cached values.

An example of using this function is the LoadImage node. It returns the hash of the selected file, so that if the file changes, the node will be forced to rerun.

**V1:**

```python theme={null}
@classmethod
def IS_CHANGED(s, **kwargs):
    return "unique_value"
```

**V3:**

```python theme={null}
@classmethod
def fingerprint_inputs(cls, **kwargs):
    return "unique_value"
```

### Step 6: Create Extension and Entry Point

Instead of defining dictionaries to link node id to node class/display name, there is now a `ComfyExtension` class and an expected `comfy_entrypoint` function to be defined.

In the future, more functions may be added to ComfyExtension to register more than just nodes via `get_node_list`.

`comfy_entrypoint` can be either async or not, but `get_node_list` must be defined as async.

**V1:**

```python theme={null}
NODE_CLASS_MAPPINGS = {
    "Example": Example
}

NODE_DISPLAY_NAME_MAPPINGS = {
    "Example": "Example Node"
}
```

**V3:**

```python theme={null}
from comfy_api.latest import ComfyExtension

class MyExtension(ComfyExtension):
    # must be declared as async
    async def get_node_list(self) -> list[type[io.ComfyNode]]:
        return [
            Example,
            # Add more nodes here
        ]

# can be declared async or not, both will work
async def comfy_entrypoint() -> MyExtension:
    return MyExtension()
```

## Input Type Reference

Already explained in step 2, but here are some type reference comparisons in V1 vs V3. See `comfy_api.latest._io` for the full type declarations.

### Basic Types

| V1 Type     | V3 Type              | Example                                                      |
| ----------- | -------------------- | ------------------------------------------------------------ |
| `"INT"`     | `io.Int.Input()`     | `io.Int.Input("count", default=1, min=0, max=100)`           |
| `"FLOAT"`   | `io.Float.Input()`   | `io.Float.Input("strength", default=1.0, min=0.0, max=10.0)` |
| `"STRING"`  | `io.String.Input()`  | `io.String.Input("text", multiline=True)`                    |
| `"BOOLEAN"` | `io.Boolean.Input()` | `io.Boolean.Input("enabled", default=True)`                  |

#### control\_after\_generate

Int and Combo inputs support a `control_after_generate` parameter that adds a control widget for automatically changing the value after each generation. In V1 this was a plain `bool`; in V3 you can use the `io.ControlAfterGenerate` enum for explicit control. Passing `True` is equivalent to `io.ControlAfterGenerate.randomize`.

| Value                               | Behavior                                            |
| ----------------------------------- | --------------------------------------------------- |
| `io.ControlAfterGenerate.fixed`     | Value stays the same after each generation.         |
| `io.ControlAfterGenerate.increment` | Value increments by the step after each generation. |
| `io.ControlAfterGenerate.decrement` | Value decrements by the step after each generation. |
| `io.ControlAfterGenerate.randomize` | Value is randomized after each generation.          |

```python theme={null}
# Enable the control widget (user picks the mode in the UI)
io.Int.Input("seed", default=0, min=0, max=0xFFFFFFFFFFFFFFFF, control_after_generate=True)

# Set a specific default mode
io.Int.Input("seed", default=0, min=0, max=0xFFFFFFFFFFFFFFFF,
    control_after_generate=io.ControlAfterGenerate.randomize)
```

### ComfyUI Types

| V1 Type          | V3 Type                   | Example                                          |
| ---------------- | ------------------------- | ------------------------------------------------ |
| `"IMAGE"`        | `io.Image.Input()`        | `io.Image.Input("image", tooltip="Input image")` |
| `"MASK"`         | `io.Mask.Input()`         | `io.Mask.Input("mask", optional=True)`           |
| `"LATENT"`       | `io.Latent.Input()`       | `io.Latent.Input("latent")`                      |
| `"CONDITIONING"` | `io.Conditioning.Input()` | `io.Conditioning.Input("positive")`              |
| `"MODEL"`        | `io.Model.Input()`        | `io.Model.Input("model")`                        |
| `"VAE"`          | `io.VAE.Input()`          | `io.VAE.Input("vae")`                            |
| `"CLIP"`         | `io.CLIP.Input()`         | `io.CLIP.Input("clip")`                          |

### Combo (Dropdowns/Selection Lists)

Combo types in V3 require explicit class definition.

**V1:**

```python theme={null}
"mode": (["option1", "option2", "option3"],)
```

**V3:**

```python theme={null}
io.Combo.Input("mode", options=["option1", "option2", "option3"])
```

## Schema Reference

The `Schema` dataclass defines all properties of a V3 node. Here is a complete reference of all available fields:

| Field               | Type           | Default    | Description                                                                                                         |
| ------------------- | -------------- | ---------- | ------------------------------------------------------------------------------------------------------------------- |
| `node_id`           | `str`          | *required* | Globally unique ID of the node. Custom nodes should add a prefix/postfix to avoid clashes.                          |
| `display_name`      | `str`          | `None`     | Display name shown in the UI. Falls back to `node_id` if not set.                                                   |
| `category`          | `str`          | `"sd"`     | Category in the "Add Node" menu (e.g. `"image/transform"`).                                                         |
| `description`       | `str`          | `""`       | Tooltip shown when hovering over the node.                                                                          |
| `inputs`            | `list[Input]`  | `[]`       | List of input definitions.                                                                                          |
| `outputs`           | `list[Output]` | `[]`       | List of output definitions.                                                                                         |
| `hidden`            | `list[Hidden]` | `[]`       | List of hidden inputs to request (see [Hidden Inputs](#hidden-inputs)).                                             |
| `search_aliases`    | `list[str]`    | `[]`       | Alternative names for search. Useful for synonyms or old names after renaming.                                      |
| `is_output_node`    | `bool`         | `False`    | Marks the node as an output node, causing it and its dependencies to be executed.                                   |
| `is_input_list`     | `bool`         | `False`    | When True, all inputs become `list[type]` regardless of how many items are passed in.                               |
| `is_deprecated`     | `bool`         | `False`    | Flags the node as deprecated, signaling users to find alternatives.                                                 |
| `is_experimental`   | `bool`         | `False`    | Flags the node as experimental, warning users it may change.                                                        |
| `is_dev_only`       | `bool`         | `False`    | Hides the node from search/menus unless dev mode is enabled.                                                        |
| `is_api_node`       | `bool`         | `False`    | Flags the node as an API node for Comfy API services.                                                               |
| `not_idempotent`    | `bool`         | `False`    | When True, the node will always re-run and never reuse cached outputs from a different identical node in the graph. |
| `enable_expand`     | `bool`         | `False`    | Allows `NodeOutput` to include an `expand` property for node expansion.                                             |
| `accept_all_inputs` | `bool`         | `False`    | When True, all inputs from the prompt are passed as kwargs, even if not defined in the schema.                      |

### Common Input Parameters

All input types share these base parameters:

| Parameter      | Type   | Default    | Description                                                                       |
| -------------- | ------ | ---------- | --------------------------------------------------------------------------------- |
| `id`           | `str`  | *required* | Unique identifier for the input, used as the kwarg name in `execute`.             |
| `display_name` | `str`  | `None`     | Label shown in the UI. Defaults to `id`.                                          |
| `optional`     | `bool` | `False`    | Whether the input is optional.                                                    |
| `tooltip`      | `str`  | `None`     | Hover tooltip text.                                                               |
| `lazy`         | `bool` | `None`     | Marks input for lazy evaluation (see [Lazy Evaluation](#lazy-evaluation-v1--v3)). |
| `raw_link`     | `bool` | `None`     | When True, passes the raw link info instead of the resolved value.                |
| `advanced`     | `bool` | `None`     | When True, the input is hidden behind an "Advanced" toggle in the UI.             |

Widget inputs (Int, Float, String, Boolean, Combo) additionally support:

| Parameter     | Type   | Default | Description                                                               |
| ------------- | ------ | ------- | ------------------------------------------------------------------------- |
| `default`     | varies | `None`  | Default value for the widget.                                             |
| `socketless`  | `bool` | `None`  | When True, hides the input socket (widget only, no incoming connections). |
| `force_input` | `bool` | `None`  | When True, forces the widget to display as a socket input instead.        |

## Advanced Features

### Hidden Inputs

Hidden inputs provide access to execution context like the prompt metadata, node ID, and other internal values. They are not visible in the UI.

In V1, hidden inputs were declared as a `"hidden"` key in `INPUT_TYPES`. In V3, they are declared via the `hidden` parameter on the Schema, and their values are accessed via `cls.hidden`.

**V1:**

```python theme={null}
@classmethod
def INPUT_TYPES(s):
    return {
        "required": {...},
        "hidden": {
            "unique_id": "UNIQUE_ID",
            "prompt": "PROMPT",
            "extra_pnginfo": "EXTRA_PNGINFO",
        }
    }

def execute(self, unique_id, prompt, extra_pnginfo, ...):
    # hidden values passed as regular arguments
    print(unique_id)
```

**V3:**

```python theme={null}
@classmethod
def define_schema(cls) -> io.Schema:
    return io.Schema(
        node_id="MyNode",
        inputs=[...],
        hidden=[io.Hidden.unique_id, io.Hidden.prompt, io.Hidden.extra_pnginfo],
    )

@classmethod
def execute(cls, ...) -> io.NodeOutput:
    # hidden values accessed via cls.hidden
    print(cls.hidden.unique_id)
    print(cls.hidden.prompt)
    print(cls.hidden.extra_pnginfo)
```

Available hidden values:

| Hidden Enum                      | Description                                                            |
| -------------------------------- | ---------------------------------------------------------------------- |
| `io.Hidden.unique_id`            | The unique identifier of the node, matching the id on the client side. |
| `io.Hidden.prompt`               | The complete prompt sent by the client.                                |
| `io.Hidden.extra_pnginfo`        | Dictionary copied into metadata of saved `.png` files.                 |
| `io.Hidden.dynprompt`            | Instance of `DynamicPrompt` that may mutate during execution.          |
| `io.Hidden.auth_token_comfy_org` | Token acquired from signing into a ComfyOrg account on the frontend.   |
| `io.Hidden.api_key_comfy_org`    | API key generated by ComfyOrg, allows skipping frontend sign-in.       |

<Note>
  Some hidden values are automatically added based on Schema flags. Output nodes (`is_output_node=True`) automatically receive `prompt` and `extra_pnginfo`. API nodes (`is_api_node=True`) automatically receive auth tokens.
</Note>

### UI Helpers

V3 provides built-in UI helpers in the `ui` module to handle common patterns like previewing and saving files. Pass them to `io.NodeOutput` via the `ui` parameter.

#### Preview Helpers

Preview helpers save temporary files and return UI data for in-node display.

```python theme={null}
from comfy_api.latest import ui

# Preview an image in the node
return io.NodeOutput(images, ui=ui.PreviewImage(images, cls=cls))

# Preview a mask (automatically converts to 3-channel for display)
return io.NodeOutput(mask, ui=ui.PreviewMask(mask, cls=cls))

# Preview audio
return io.NodeOutput(audio, ui=ui.PreviewAudio(audio, cls=cls))

# Preview text
return io.NodeOutput(ui=ui.PreviewText("Some text value"))

# Preview 3D model
return io.NodeOutput(ui=ui.PreviewUI3D(model_file, camera_info))
```

#### Save Helpers

Save helpers provide methods for saving files to the output directory with proper metadata embedding. They are typically used in output nodes.

```python theme={null}
from comfy_api.latest import ui, io

# Save images and return UI data (most common pattern)
return io.NodeOutput(
    ui=ui.ImageSaveHelper.get_save_images_ui(
        images=images,
        filename_prefix=filename_prefix,
        cls=cls,  # passes hidden prompt/extra_pnginfo for metadata
    )
)

# Save animated PNG
return io.NodeOutput(
    ui=ui.ImageSaveHelper.get_save_animated_png_ui(
        images=images,
        filename_prefix=filename_prefix,
        cls=cls,
        fps=6.0,
        compress_level=4,
    )
)

# Save animated WebP
return io.NodeOutput(
    ui=ui.ImageSaveHelper.get_save_animated_webp_ui(
        images=images,
        filename_prefix=filename_prefix,
        cls=cls,
        fps=6.0,
        lossless=True,
        quality=80,
        method=4,
    )
)

# Save audio (supports flac, mp3, opus)
return io.NodeOutput(
    ui=ui.AudioSaveHelper.get_save_audio_ui(
        audio=audio,
        filename_prefix=filename_prefix,
        cls=cls,
        format="flac",
    )
)
```

<Tip>
  Passing `cls=cls` to save/preview helpers allows them to automatically embed workflow metadata (prompt, extra\_pnginfo) in the saved files. Make sure to include `io.Hidden.prompt` and `io.Hidden.extra_pnginfo` in your schema's hidden list, or set `is_output_node=True` which adds them automatically.
</Tip>

#### Returning Raw UI Dicts

If you need to return UI data that doesn't have a helper, you can pass a dict directly:

```python theme={null}
return io.NodeOutput(ui={"images": results})
```

### Output Nodes

For nodes that produce side effects (like saving files). Same as in V1, marking a node as output will display a `run` play button in the node's context window, allowing for partial execution of the graph.

```python theme={null}
@classmethod
def define_schema(cls) -> io.Schema:
    return io.Schema(
        node_id="SaveNode",
        inputs=[...],
        outputs=[],  # Does not need to be empty.
        is_output_node=True  # Mark as output node
    )
```

### Custom Types

Create custom input/output types either via class definition or the `Custom` helper function.

```python theme={null}
from comfy_api.latest import io

# Method 1: Using decorator with class
@io.comfytype(io_type="MY_CUSTOM_TYPE")
class MyCustomType:
    Type = torch.Tensor  # Python type hint

    class Input(io.Input):
        def __init__(self, id: str, **kwargs):
            super().__init__(id, **kwargs)

    class Output(io.Output):
        def __init__(self, **kwargs):
            super().__init__(**kwargs)

# Method 2: Using Custom helper
# The helper can be used directly without saving to a variable first for convenience as well
MyCustomType = io.Custom("MY_CUSTOM_TYPE")
```

### MultiType Inputs

`MultiType` allows an input to accept more than one type. This is useful when a node can operate on different data types through the same input slot.

If the first argument (`id`) is an instance of an `Input` class instead of a string, that input will be used to create a widget with its overridden values. Otherwise, the input is socket-only.

```python theme={null}
# Socket-only multi-type input (no widget)
io.MultiType.Input("input", types=[io.Image, io.Mask])

# Multi-type input with a widget fallback (String widget shown when nothing is connected)
io.MultiType.Input(
    io.String.Input("model_file", default="", multiline=False),
    types=[io.File3DGLB, io.File3DGLTF, io.File3DOBJ],
    tooltip="3D model file or path string",
)
```

### MatchType (Generic Type Matching)

`MatchType` creates type-linked inputs and outputs. When a user connects a specific type to a MatchType input, all other inputs and outputs sharing the same template automatically constrain to that type. This is how nodes like Switch and Create List work with any type.

```python theme={null}
@classmethod
def define_schema(cls):
    # Create a template - all inputs/outputs sharing the same template will match types
    template = io.MatchType.Template("switch")
    return io.Schema(
        node_id="SwitchNode",
        display_name="Switch",
        category="logic",
        inputs=[
            io.Boolean.Input("switch"),
            io.MatchType.Input("on_false", template=template, lazy=True),
            io.MatchType.Input("on_true", template=template, lazy=True),
        ],
        outputs=[
            io.MatchType.Output(template=template, display_name="output"),
        ],
    )
```

You can also restrict which types are allowed:

```python theme={null}
# Only allow Image, Mask, or Latent types
template = io.MatchType.Template("input_type", allowed_types=[io.Image, io.Mask, io.Latent])
```

### Dynamic Inputs

V3 introduces dynamic input types that change the available inputs based on user interaction. There is no V1 equivalent for these features.

#### Autogrow

`Autogrow` creates a variable number of inputs that automatically grow as the user connects more. There are two template types:

**TemplatePrefix** generates inputs with a numbered prefix (e.g. `image0`, `image1`, `image2`...):

```python theme={null}
@classmethod
def define_schema(cls):
    autogrow_template = io.Autogrow.TemplatePrefix(
        input=io.Image.Input("image"),  # template for each input
        prefix="image",                  # prefix for generated input names
        min=2,                           # minimum number of inputs shown
        max=50,                          # maximum number of inputs allowed
    )
    return io.Schema(
        node_id="BatchImagesNode",
        display_name="Batch Images",
        category="image",
        inputs=[io.Autogrow.Input("images", template=autogrow_template)],
        outputs=[io.Image.Output()],
    )

@classmethod
def execute(cls, images: io.Autogrow.Type) -> io.NodeOutput:
    # 'images' is a dict mapping input names to their values
    image_list = list(images.values())
    return io.NodeOutput(batch(image_list))
```

**TemplateNames** generates inputs with specific names:

```python theme={null}
template = io.Autogrow.TemplateNames(
    input=io.Float.Input("float"),
    names=["x", "y", "z"],  # explicit names for each input
    min=1,                    # minimum number of inputs shown
)
```

Autogrow can be combined with MatchType to create lists of type-matched inputs:

```python theme={null}
@classmethod
def define_schema(cls):
    template_matchtype = io.MatchType.Template("type")
    template_autogrow = io.Autogrow.TemplatePrefix(
        input=io.MatchType.Input("input", template=template_matchtype),
        prefix="input",
    )
    return io.Schema(
        node_id="CreateList",
        display_name="Create List",
        category="logic",
        is_input_list=True,
        inputs=[io.Autogrow.Input("inputs", template=template_autogrow)],
        outputs=[
            io.MatchType.Output(
                template=template_matchtype,
                is_output_list=True,
                display_name="list",
            ),
        ],
    )
```

#### DynamicCombo

`DynamicCombo` creates a dropdown that shows/hides different inputs depending on the selected option. This is useful for nodes where different modes require different parameters.

```python theme={null}
@classmethod
def define_schema(cls):
    return io.Schema(
        node_id="ResizeNode",
        display_name="Resize",
        category="transform",
        inputs=[
            io.Image.Input("image"),
            io.DynamicCombo.Input("resize_type", options=[
                io.DynamicCombo.Option("scale by dimensions", [
                    io.Int.Input("width", default=512, min=0, max=8192),
                    io.Int.Input("height", default=512, min=0, max=8192),
                ]),
                io.DynamicCombo.Option("scale by multiplier", [
                    io.Float.Input("multiplier", default=1.0, min=0.01, max=8.0),
                ]),
                io.DynamicCombo.Option("scale to megapixels", [
                    io.Float.Input("megapixels", default=1.0, min=0.01, max=16.0),
                ]),
            ]),
        ],
        outputs=[io.Image.Output()],
    )

@classmethod
def execute(cls, image, resize_type: dict) -> io.NodeOutput:
    # resize_type is a dict containing the selected option key and its inputs
    selected = resize_type["resize_type"]
    if selected == "scale by dimensions":
        width = resize_type["width"]
        height = resize_type["height"]
        # ...
    elif selected == "scale by multiplier":
        multiplier = resize_type["multiplier"]
        # ...
```

DynamicCombo options can also be nested:

```python theme={null}
io.DynamicCombo.Input("combo", options=[
    io.DynamicCombo.Option("option1", [io.String.Input("string")]),
    io.DynamicCombo.Option("option2", [
        io.DynamicCombo.Input("subcombo", options=[
            io.DynamicCombo.Option("sub_opt1", [io.Float.Input("x"), io.Float.Input("y")]),
            io.DynamicCombo.Option("sub_opt2", [io.Mask.Input("mask", optional=True)]),
        ])
    ]),
])
```

### Async Execute

V3 supports async `execute` methods. This is useful for nodes that perform I/O operations, API calls, or other async work. Simply declare `execute` as `async`:

```python theme={null}
@classmethod
async def execute(cls, prompt, **kwargs) -> io.NodeOutput:
    result = await some_async_operation(prompt)
    return io.NodeOutput(result)
```

### ComfyAPI

The `ComfyAPI` class provides access to ComfyUI runtime services like progress reporting and node replacement registration. Import it and create an instance:

```python theme={null}
from comfy_api.latest import ComfyAPI

api = ComfyAPI()
```

#### Progress Reporting

Report execution progress from within a node's `execute` method. The progress bar is displayed in the ComfyUI interface. This replaces the V1 pattern of using `comfy.utils.PROGRESS_BAR_HOOK`.

```python theme={null}
from comfy_api.latest import ComfyAPI

api = ComfyAPI()

@classmethod
async def execute(cls, images, **kwargs) -> io.NodeOutput:
    total = len(images)
    for i, image in enumerate(images):
        process(image)
        await api.execution.set_progress(
            value=i + 1,
            max_value=total,
            preview_image=image,  # optional: show preview during progress
        )
    return io.NodeOutput(result)
```

<Note>
  `set_progress` can accept a PIL Image, an `ImageInput` tensor, or `None` for the `preview_image` parameter. When called from within `execute`, the `node_id` is automatically determined from the executing context.
</Note>

#### Node Replacement

Node replacement allows mapping old/deprecated nodes to new ones, so existing workflows automatically upgrade. Register replacements using the `ComfyAPI` in your extension's `on_load` method.

```python theme={null}
from comfy_api.latest import ComfyAPI, ComfyExtension, io

api = ComfyAPI()

class MyExtension(ComfyExtension):
    async def on_load(self) -> None:
        await api.node_replacement.register(io.NodeReplace(
            new_node_id="MyNewNode",
            old_node_id="MyOldNode",
            old_widget_ids=["param1", "param2"],  # ordered widget IDs for positional mapping
            input_mapping=[
                {"new_id": "image", "old_id": "input_image"},       # rename input
                {"new_id": "method", "set_value": "lanczos"},       # set a fixed value
            ],
            output_mapping=[
                {"new_idx": 0, "old_idx": 0},  # map output by index
            ],
        ))

    async def get_node_list(self) -> list[type[io.ComfyNode]]:
        return [MyNewNode]
```

The `old_widget_ids` parameter is important: workflow JSON stores widget values by position index, not by name. This list maps those positional indexes to input IDs so the replacement system can correctly identify widget values during migration.

For nodes using dynamic inputs (like Autogrow), use dotted paths in the mapping:

```python theme={null}
input_mapping=[
    {"new_id": "images.image0", "old_id": "image1"},
    {"new_id": "images.image1", "old_id": "image2"},
]
```

### Extension Lifecycle

The `ComfyExtension` class supports lifecycle hooks beyond just `get_node_list`:

```python theme={null}
from comfy_api.latest import ComfyExtension, io

class MyExtension(ComfyExtension):
    async def on_load(self) -> None:
        """Called when the extension is loaded.
        Use for one-time initialization: registering node replacements,
        setting up global resources, etc.
        """
        pass

    async def get_node_list(self) -> list[type[io.ComfyNode]]:
        """Return the list of node classes this extension provides."""
        return [MyNode]

async def comfy_entrypoint() -> MyExtension:
    return MyExtension()
```

### NodeOutput

The `NodeOutput` class is the standardized return value from `execute`. It supports several patterns:

```python theme={null}
# Return a single output value
return io.NodeOutput(image)

# Return multiple output values (order matches outputs list in schema)
return io.NodeOutput(width, height, batch_size)

# Return only UI data (no output values)
return io.NodeOutput(ui=ui.PreviewImage(images, cls=cls))

# Return both output values and UI data
return io.NodeOutput(image, ui=ui.PreviewImage(image, cls=cls))

# Return None/empty (for nodes with no outputs)
return io.NodeOutput()
```

## Complete Example

Here is a complete example of a V3 extension file with multiple nodes:

```python theme={null}
from comfy_api.latest import ComfyExtension, io, ui

class InvertImage(io.ComfyNode):
    @classmethod
    def define_schema(cls):
        return io.Schema(
            node_id="MyPack_InvertImage",  # prefixed to avoid clashes
            display_name="Invert Image",
            category="my_pack/image",
            description="Inverts the colors of an image.",
            inputs=[
                io.Image.Input("image"),
            ],
            outputs=[
                io.Image.Output(display_name="inverted"),
            ],
        )

    @classmethod
    def execute(cls, image) -> io.NodeOutput:
        inverted = 1.0 - image
        return io.NodeOutput(inverted, ui=ui.PreviewImage(inverted, cls=cls))


class SaveImage(io.ComfyNode):
    @classmethod
    def define_schema(cls):
        return io.Schema(
            node_id="MyPack_SaveImage",
            display_name="Save Image",
            category="my_pack/image",
            is_output_node=True,
            inputs=[
                io.Image.Input("images"),
                io.String.Input("filename_prefix", default="ComfyUI"),
            ],
            outputs=[],
        )

    @classmethod
    def execute(cls, images, filename_prefix) -> io.NodeOutput:
        return io.NodeOutput(
            ui=ui.ImageSaveHelper.get_save_images_ui(
                images=images,
                filename_prefix=filename_prefix,
                cls=cls,
            )
        )


class MyPackExtension(ComfyExtension):
    async def get_node_list(self) -> list[type[io.ComfyNode]]:
        return [InvertImage, SaveImage]

async def comfy_entrypoint() -> MyPackExtension:
    return MyPackExtension()
```


# Getting Started
Source: https://docs.comfy.org/custom-nodes/walkthrough



This page will take you step-by-step through the process of creating a custom node.

Our example will take a batch of images, and return one of the images. Initially, the node
will return the image which is, on average, the lightest in color; we'll then extend
it to have a range of selection criteria, and then finally add some client side code.

This page assumes very little knowledge of Python or Javascript.

After this walkthrough, dive into the details of [backend code](./backend/server_overview), and
[frontend code](./backend/server_overview).

## Write a basic node

### Prerequisites

* A working ComfyUI [installation](/installation/manual_install). For development, we recommend installing ComfyUI manually.
* A working comfy-cli [installation](/comfy-cli/getting-started).

### Setting up

```bash theme={null}
cd ComfyUI/custom_nodes
comfy node scaffold
```

After answering a few questions, you'll have a new directory set up.

```bash theme={null}
 ~  % comfy node scaffold
You've downloaded .cookiecutters/cookiecutter-comfy-extension before. Is it okay to delete and re-download it? [y/n] (y): y
  [1/9] full_name (): Comfy
  [2/9] email (you@gmail.com): me@comfy.org
  [3/9] github_username (your_github_username): comfy
  [4/9] project_name (My Custom Nodepack): FirstComfyNode
  [5/9] project_slug (firstcomfynode): 
  [6/9] project_short_description (A collection of custom nodes for ComfyUI): 
  [7/9] version (0.0.1): 
  [8/9] Select open_source_license
    1 - GNU General Public License v3
    2 - MIT license
    3 - BSD license
    4 - ISC license
    5 - Apache Software License 2.0
    6 - Not open source
    Choose from [1/2/3/4/5/6] (1): 1
  [9/9] include_web_directory_for_custom_javascript [y/n] (n): y
Initialized empty Git repository in firstcomfynode/.git/
✓ Custom node project created successfully!
```

### Defining the node

Add the following code to the end of `src/nodes.py`:

```Python src/nodes.py theme={null}
class ImageSelector:
    CATEGORY = "example"
    @classmethod    
    def INPUT_TYPES(s):
        return { "required":  { "images": ("IMAGE",), } }
    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "choose_image"
```

<Info>The basic structure of a custom node is described in detail [here](/custom-nodes/backend/server_overview). </Info>

A custom node is defined using a Python class, which must include these four things: `CATEGORY`,
which specifies where in the add new node menu the custom node will be located,
`INPUT_TYPES`, which is a class method defining what inputs the node will take
(see [later](/custom-nodes/backend/server_overview#input-types) for details of the dictionary returned),
`RETURN_TYPES`, which defines what outputs the node will produce, and `FUNCTION`, the name
of the function that will be called when the node is executed.

<Tip>Notice that the data type for input and output is `IMAGE` (singular) even though
we expect to receive a batch of images, and return just one. In Comfy, `IMAGE` means
image batch, and a single image is treated as a batch of size 1.</Tip>

### The main function

The main function, `choose_image`, receives named arguments as defined in `INPUT_TYPES`, and
returns a `tuple` as defined in `RETURN_TYPES`. Since we're dealing with images, which are internally
stored as `torch.Tensor`,

```Python theme={null}
import torch
```

Then add the function to your class. The datatype for image is `torch.Tensor` with shape `[B,H,W,C]`,
where `B` is the batch size and `C` is the number of channels - 3, for RGB. If we iterate over such
a tensor, we will get a series of `B` tensors of shape `[H,W,C]`. The `.flatten()` method turns
this into a one dimensional tensor, of length `H*W*C`, `torch.mean()` takes the mean, and `.item()`
turns a single value tensor into a Python float.

```Python theme={null}
def choose_image(self, images):
    brightness = list(torch.mean(image.flatten()).item() for image in images)
    brightest = brightness.index(max(brightness))
    result = images[brightest].unsqueeze(0)
    return (result,)
```

Notes on those last two lines:

* `images[brightest]` will return a Tensor of shape `[H,W,C]`. `unsqueeze` is used to insert a (length 1) dimension at, in this case, dimension zero, to give
  us `[B,H,W,C]` with `B=1`: a single image.
* in `return (result,)`, the trailing comma is essential to ensure you return a tuple.

### Register the node

To make Comfy recognize the new node, it must be available at the package level. Modify the `NODE_CLASS_MAPPINGS` variable at the end of `src/nodes.py`. You must restart ComfyUI to see any changes.

```Python src/nodes.py theme={null}

NODE_CLASS_MAPPINGS = {
    "Example" : Example,
    "Image Selector" : ImageSelector,
}

# Optionally, you can rename the node in the `NODE_DISPLAY_NAME_MAPPINGS` dictionary.
NODE_DISPLAY_NAME_MAPPINGS = {
    "Example": "Example Node",
    "Image Selector": "Image Selector",
}
```

<Info>For a detailed explanation of how ComfyUI discovers and loads custom nodes, see the [node lifecycle documentation](/custom-nodes/backend/lifecycle).</Info>

## Add some options

That node is maybe a bit boring, so we might add some options; a widget that allows you to
choose the brightest image, or the reddest, bluest, or greenest. Edit your `INPUT_TYPES` to look like:

```Python theme={null}
@classmethod    
def INPUT_TYPES(s):
    return { "required":  { "images": ("IMAGE",), 
                            "mode": (["brightest", "reddest", "greenest", "bluest"],)} }
```

Then update the main function. We'll use a fairly naive definition of 'reddest' as being the average
`R` value of the pixels divided by the average of all three colors. So:

```Python theme={null}
def choose_image(self, images, mode):
    batch_size = images.shape[0]
    brightness = list(torch.mean(image.flatten()).item() for image in images)
    if (mode=="brightest"):
        scores = brightness
    else:
        channel = 0 if mode=="reddest" else (1 if mode=="greenest" else 2)
        absolute = list(torch.mean(image[:,:,channel].flatten()).item() for image in images)
        scores = list( absolute[i]/(brightness[i]+1e-8) for i in range(batch_size) )
    best = scores.index(max(scores))
    result = images[best].unsqueeze(0)
    return (result,)
```

## Tweak the UI

Maybe we'd like a bit of visual feedback, so let's send a little text message to be displayed.

### Send a message from server

This requires two lines to be added to the Python code:

```Python theme={null}
from server import PromptServer
```

and, at the end of the `choose_image` method, add a line to send a message to the front end (`send_sync` takes a message
type, which should be unique, and a dictionary)

```Python theme={null}
PromptServer.instance.send_sync("example.imageselector.textmessage", {"message":f"Picked image {best+1}"})
return (result,)
```

### Write a client extension

To add some Javascript to the client, create a subdirectory, `web/js` in your custom node directory, and modify the end of `__init__.py`
to tell Comfy about it by exporting `WEB_DIRECTORY`:

```Python theme={null}
WEB_DIRECTORY = "./web/js"
__all__ = ['NODE_CLASS_MAPPINGS', 'WEB_DIRECTORY']
```

The client extension is saved as a `.js` file in the `web/js` subdirectory, so create `image_selector/web/js/imageSelector.js` with the
code below. (For more, see [client side coding](./js/javascript_overview)).

```Javascript theme={null}
import { app } from "../../scripts/app.js";
app.registerExtension({
	name: "example.imageselector",
    async setup() {
        function messageHandler(event) { alert(event.detail.message); }
        app.api.addEventListener("example.imageselector.textmessage", messageHandler);
    },
})
```

All we've done is register an extension and add a listener for the message type we are sending in the `setup()` method. This reads the dictionary we sent (which is stored in `event.detail`).

Stop the Comfy server, start it again, reload the webpage, and run your workflow.

### The complete example

The complete example is available [here](https://gist.github.com/robinjhuang/fbf54b7715091c7b478724fc4dffbd03). You can download the example workflow [JSON file](https://github.com/Comfy-Org/docs/blob/main/public/workflow.json) or view it below:

<div>
  <img alt="Image Selector Workflow" />
</div>


# Workflow templates
Source: https://docs.comfy.org/custom-nodes/workflow_templates



If you have example workflow files associated with your custom nodes
then ComfyUI can show these to the user in the template browser (`Workflow`/`Browse Templates` menu).
Workflow templates are a great way to support people getting started with your nodes.

All you have to do as a node developer is to create an `example_workflows` folder and place the `json` files there.
Optionally you can place `jpg` files with the same name to be shown as the template thumbnail.

Under the hood ComfyUI statically serves these files along with an endpoint (`/api/workflow_templates`)
that returns the collection of workflow templates.

<Note>
  The following folder names are also accepted, but we still recommend using `example_workflows`

  * workflow
  * workflows
  * example
  * examples
</Note>

## Example

Under `ComfyUI-MyCustomNodeModule/example_workflows/` directory:

* `My_example_workflow_1.json`
* `My_example_workflow_1.jpg`
* `My_example_workflow_2.json`

In this example ComfyUI's template browser shows a category called `ComfyUI-MyCustomNodeModule` with two items, one of which has a thumbnail.

For a real-world example, see [ComfyUI-Impact-Pack's example\_workflows folder](https://github.com/ltdrdata/ComfyUI-Impact-Pack/tree/Main/example_workflows).


# Getting an API Key
Source: https://docs.comfy.org/development/api-development/getting-an-api-key

Learn how to create and manage your Comfy Platform API Key for accessing Cloud APIs, Partner Nodes, and more.

An API Key is your credential for accessing Comfy Platform services, including:

* [Cloud API](/development/cloud/overview) — call Comfy Cloud endpoints programmatically
* [Partner Node API Integration](/development/comfyui-server/api-key-integration) — use paid Partner Nodes in your local workflows
* [Agent Tools / MCP](/agent-tools) — connect to Comfy through MCP
* [Login to ComfyUI locally](/interface/user#logging-in-with-an-api-key) — authenticate with an API Key instead of email

## Creating an API Key

<Steps>
  <Step title="Visit https://platform.comfy.org/login and Log In">
    Please visit [https://platform.comfy.org/login](https://platform.comfy.org/login) and log in with the corresponding account

    <img alt="Visit Platform Login Page" />
  </Step>

  <Step title="Click `+ New` in API Keys to Create an API Key">
    Click `+ New` in API Keys to create an API Key

    <img alt="Create API Key" />
  </Step>

  <Step title="Enter API Key Name">
    <img alt="Enter API Key Name" />

    1. (Required) Enter the API Key name,
    2. Click `Generate` to create
  </Step>

  <Step title="Save the Obtained API Key">
    <img alt="Obtain API Key" />

    <Warning>
      Since the API Key is only visible upon first creation, please save it immediately after creation. It cannot be viewed later, so please keep it safe.
      Please note that you should not share your API Key with others. Once it leaked, you can delete it and create a new one.
    </Warning>
  </Step>
</Steps>

## Managing your API Keys

You can view and manage all your API Keys on [platform.comfy.org](https://platform.comfy.org) after logging in.

* **View existing keys**: See the name and creation date of each key
* **Delete a key**: If a key is compromised or no longer needed, delete it immediately
* **Create additional keys**: You can have multiple API Keys for different applications

<Warning>
  API Keys are only shown once upon creation. Save it immediately in a secure location. If you lose a key, delete it and create a new one.
</Warning>

## Using your API Key

Once you have an API Key, you can:

1. **Log in to ComfyUI locally** — go to **Settings → User** and select "Comfy API Key" login
2. **Call Partner Node APIs** — include the key in `extra_data.api_key_comfy_org` when sending workflows
3. **Use Cloud API** — include the key in request headers for Cloud API endpoints

For security, never share your API Key or commit it to version control.


# APIs Overview
Source: https://docs.comfy.org/development/api-development/overview

An overview of the different ways to interact with ComfyUI programmatically

ComfyUI offers several API options depending on where you want to run your workflows and how much infrastructure you want to manage. This page helps you choose the right approach.

***

## Which API Should I Use?

|                    | Cloud API                                | ComfyUI Server API                             |
| ------------------ | ---------------------------------------- | ---------------------------------------------- |
| **Where it runs**  | Comfy Cloud (managed GPUs)               | Your own machine                               |
| **GPU management** | Handled for you                          | You manage your own hardware                   |
| **Models**         | Pre-installed and managed by Comfy       | You download and manage locally                |
| **Authentication** | `X-API-Key` header (Comfy Cloud account) | None (local) or API key for Partner Nodes      |
| **Base URL**       | `https://cloud.comfy.org`                | Your server URL (e.g. `http://localhost:8188`) |
| **Protocol**       | REST + WebSocket                         | REST + WebSocket                               |
| **Pricing**        | Subscription-based (Creator/Pro tiers)   | Free (your own compute)                        |
| **Best for**       | Quick integration, no infrastructure     | Full control, custom hardware & models         |

Both APIs use the same workflow format ([API format](/development/api-development/workflow-api-format)), so you can develop and test workflows locally and move them to the cloud without changes.

***

## Getting Started

<CardGroup>
  <Card title="Cloud API" icon="cloud" href="/development/cloud/overview">
    Run workflows on Comfy's managed infrastructure. No GPU setup required.
  </Card>

  <Card title="ComfyUI Server API" icon="server" href="/development/comfyui-server/comms_overview">
    Run ComfyUI as a server on your own machine and call it via API.
  </Card>

  <Card title="Partner Node API Integration" icon="key" href="/development/comfyui-server/api-key-integration">
    Use paid Partner Nodes in headless or API-driven workflows.
  </Card>
</CardGroup>

***

## Prerequisites

Before using any API, you'll need:

* An API key (see [Getting an API Key](/development/api-development/getting-an-api-key))


# Workflow API Format
Source: https://docs.comfy.org/development/api-development/workflow-api-format

Understanding the API format for ComfyUI workflows and how to export them

ComfyUI workflows are JSON objects that describe a graph of nodes. When calling ComfyUI programmatically — whether through the Cloud API or running your own server — the workflow must be submitted in **API format**, a specialized JSON structure that differs from the regular save format used in the browser.

This page explains the differences and how to export your workflows correctly.

***

## Save Format vs API Format

The ComfyUI frontend can save workflows in two formats:

|                          | Save Format                | API Format                     |
| ------------------------ | -------------------------- | ------------------------------ |
| **File menu**            | `File → Save` or `Ctrl+S`  | `File → Export Workflow (API)` |
| **File extension**       | `.json`                    | `.json`                        |
| **Node keys**            | Node titles or labels      | Numeric node IDs               |
| **Widget values**        | Included                   | Included                       |
| **Position/layout data** | Included (x, y, width)     | **Excluded**                   |
| **Colors/groups**        | Included                   | **Excluded**                   |
| **Usage**                | Re-opening in the frontend | API submission                 |
| **Can be loaded in UI**  | Yes                        | Yes, but without layout        |

The key difference: **API format omits UI metadata** (positions, colors, groups, node sizes) that is only needed for visual editing in the frontend. This keeps the JSON smaller and cleaner for programmatic use.

***

## How to Export

Open your workflow in the ComfyUI frontend, then navigate to `File → Export Workflow (API)`:

<Frame>
  <img alt="Saving a workflow in API format" />
</Frame>

This will download a `.json` file containing only the API-relevant data:

```json theme={null}
{
  "3": {
    "inputs": {
      "seed": 156680208700286,
      "steps": 20,
      "cfg": 8,
      "sampler_name": "euler",
      "scheduler": "normal",
      "denoise": 1,
      "model": [
        "4",
        0
      ],
      "positive": [
        "6",
        0
      ],
      "negative": [
        "7",
        0
      ],
      "latent_image": [
        "5",
        0
      ]
    },
    "class_type": "KSampler",
    "_meta": {
      "title": "KSampler"
    }
  },
  "4": {
    "inputs": {
      "ckpt_name": "v1-5-pruned-emaonly-fp16.safetensors"
    },
    "class_type": "CheckpointLoaderSimple",
    "_meta": {
      "title": "Load Checkpoint"
    }
  },
  "5": {
    "inputs": {
      "width": 512,
      "height": 512,
      "batch_size": 1
    },
    "class_type": "EmptyLatentImage",
    "_meta": {
      "title": "Empty Latent Image"
    }
  },
  "6": {
    "inputs": {
      "text": "beautiful scenery nature glass bottle landscape, , purple galaxy bottle,",
      "clip": [
        "4",
        1
      ]
    },
    "class_type": "CLIPTextEncode",
    "_meta": {
      "title": "CLIP Text Encode (Prompt)"
    }
  },
  "7": {
    "inputs": {
      "text": "text, watermark",
      "clip": [
        "4",
        1
      ]
    },
    "class_type": "CLIPTextEncode",
    "_meta": {
      "title": "CLIP Text Encode (Prompt)"
    }
  },
  "8": {
    "inputs": {
      "samples": [
        "3",
        0
      ],
      "vae": [
        "4",
        2
      ]
    },
    "class_type": "VAEDecode",
    "_meta": {
      "title": "VAE Decode"
    }
  },
  "9": {
    "inputs": {
      "filename_prefix": "ComfyUI",
      "images": [
        "8",
        0
      ]
    },
    "class_type": "SaveImage",
    "_meta": {
      "title": "Save Image"
    }
  }
}
```

***

## Converting Between Formats

If you have a save-format workflow and need it in API format, the simplest method is:

1. Open the `.json` file using `File → Load` in the frontend
2. Export it via `File → Export Workflow (API)`

For automated conversion, you can write a script that strips the `x`, `y`, `width` fields from each node and removes the `groups` and `extra` sections from the root JSON.

***

## Related Pages

* [APIs Overview](/development/api-development/overview) — Compare Cloud and Server API options
* [Cloud API Overview](/development/cloud/overview) — Submit API-format workflows to Comfy Cloud
* [API Examples](/development/comfyui-server/api-examples) — See API-format workflows in action
* [Getting an API Key](/development/api-development/getting-an-api-key) — Required for Cloud API and Partner Nodes


# Cloud API Reference
Source: https://docs.comfy.org/development/cloud/api-reference

Complete API reference with code examples for Comfy Cloud

<Warning>
  **Experimental API:** This API is experimental and subject to change. Endpoints, request/response formats, and behavior may be modified without notice. Some endpoints are maintained for compatibility with local ComfyUI but may have different semantics (e.g., ignored fields).
</Warning>

This page provides complete examples for common Comfy Cloud API operations.

<Note>
  **Subscription Required:** Running workflows via the API requires an active Comfy Cloud subscription. See [pricing plans](https://www.comfy.org/cloud/pricing?utm_source=docs\&utm_campaign=cloud-api) for details.
</Note>

## Setup

All examples use these common imports and configuration:

<CodeGroup>
  ```bash curl theme={null}
  export COMFY_CLOUD_API_KEY="your-api-key"
  export BASE_URL="https://cloud.comfy.org"
  ```

  ```typescript TypeScript theme={null}
  import { readFile, writeFile } from "fs/promises";

  const BASE_URL = "https://cloud.comfy.org";
  const API_KEY = process.env.COMFY_CLOUD_API_KEY!;

  function getHeaders(): HeadersInit {
    return {
      "X-API-Key": API_KEY,
      "Content-Type": "application/json",
    };
  }
  ```

  ```python Python theme={null}
  import os
  import requests
  import json
  import time
  import asyncio
  import aiohttp

  BASE_URL = "https://cloud.comfy.org"
  API_KEY = os.environ["COMFY_CLOUD_API_KEY"]

  def get_headers():
      return {
          "X-API-Key": API_KEY,
          "Content-Type": "application/json"
      }
  ```
</CodeGroup>

***

## Object Info

Retrieve available node definitions. This is useful for understanding what nodes are available and their input/output specifications.

<CodeGroup>
  ```bash curl theme={null}
  curl -X GET "$BASE_URL/api/object_info" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY"
  ```

  ```typescript TypeScript theme={null}
  async function getObjectInfo(): Promise<Record<string, any>> {
    const response = await fetch(`${BASE_URL}/api/object_info`, {
      headers: getHeaders(),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return response.json();
  }

  const objectInfo = await getObjectInfo();
  console.log(`Available nodes: ${Object.keys(objectInfo).length}`);

  const ksampler = objectInfo["KSampler"] ?? {};
  console.log(`KSampler inputs: ${Object.keys(ksampler.input?.required ?? {})}`);
  ```

  ```python Python theme={null}
  def get_object_info():
      """Fetch all available node definitions from cloud."""
      response = requests.get(
          f"{BASE_URL}/api/object_info",
          headers=get_headers()
      )
      response.raise_for_status()
      return response.json()

  # Get all nodes
  object_info = get_object_info()
  print(f"Available nodes: {len(object_info)}")

  # Get a specific node's definition
  ksampler = object_info.get("KSampler", {})
  inputs = list(ksampler.get('input', {}).get('required', {}).keys())
  print(f"KSampler inputs: {inputs}")
  ```
</CodeGroup>

***

## Uploading Inputs

Upload images, masks, or other files for use in workflows.

### Direct Upload (Multipart)

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/upload/image" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -F "image=@my_image.png" \
    -F "type=input" \
    -F "overwrite=true"
  ```

  ```typescript TypeScript theme={null}
  async function uploadInput(
    filePath: string,
    inputType: string = "input"
  ): Promise<{ name: string; subfolder: string }> {
    const file = await readFile(filePath);
    const formData = new FormData();
    formData.append("image", new Blob([file]), filePath.split("/").pop());
    formData.append("type", inputType);
    formData.append("overwrite", "true");

    const response = await fetch(`${BASE_URL}/api/upload/image`, {
      method: "POST",
      headers: { "X-API-Key": API_KEY },
      body: formData,
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return response.json();
  }

  const result = await uploadInput("my_image.png");
  console.log(`Uploaded: ${result.name} to ${result.subfolder}`);
  ```

  ```python Python theme={null}
  def upload_input(file_path: str, input_type: str = "input") -> dict:
      """Upload a file directly to cloud.
      
      Args:
          file_path: Path to the file to upload
          input_type: "input" for images, "temp" for temporary files
          
      Returns:
          Upload response with filename and subfolder
      """
      with open(file_path, "rb") as f:
          files = {"image": f}
          data = {"type": input_type, "overwrite": "true"}
          
          response = requests.post(
              f"{BASE_URL}/api/upload/image",
              headers={"X-API-Key": API_KEY},  # No Content-Type for multipart
              files=files,
              data=data
          )
      response.raise_for_status()
      return response.json()

  # Upload an image
  result = upload_input("my_image.png")
  print(f"Uploaded: {result['name']} to {result['subfolder']}")
  ```
</CodeGroup>

### Upload Mask

<Note>
  The `subfolder` parameter is accepted for API compatibility but ignored in cloud storage. All files are stored in a flat, content-addressed namespace.
</Note>

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/upload/mask" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -F "image=@mask.png" \
    -F "type=input" \
    -F "subfolder=clipspace" \
    -F 'original_ref={"filename":"my_image.png","subfolder":"","type":"input"}'
  ```

  ```typescript TypeScript theme={null}
  async function uploadMask(
    filePath: string,
    originalRef: { filename: string; subfolder: string; type: string }
  ): Promise<{ name: string; subfolder: string }> {
    const file = await readFile(filePath);
    const formData = new FormData();
    formData.append("image", new Blob([file]), filePath.split("/").pop());
    formData.append("type", "input");
    formData.append("subfolder", "clipspace");
    formData.append("original_ref", JSON.stringify(originalRef));

    const response = await fetch(`${BASE_URL}/api/upload/mask`, {
      method: "POST",
      headers: { "X-API-Key": API_KEY },
      body: formData,
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return response.json();
  }

  const maskResult = await uploadMask("mask.png", {
    filename: "my_image.png",
    subfolder: "",
    type: "input",
  });
  console.log(`Uploaded mask: ${maskResult.name}`);
  ```

  ```python Python theme={null}
  def upload_mask(file_path: str, original_ref: dict) -> dict:
      """Upload a mask associated with an original image.
      
      Args:
          file_path: Path to the mask file
          original_ref: Reference to the original image {"filename": "...", "subfolder": "...", "type": "..."}
      """
      with open(file_path, "rb") as f:
          files = {"image": f}
          data = {
              "type": "input",
              "subfolder": "clipspace",
              "original_ref": json.dumps(original_ref)
          }
          
          response = requests.post(
              f"{BASE_URL}/api/upload/mask",
              headers={"X-API-Key": API_KEY},
              files=files,
              data=data
          )
      response.raise_for_status()
      return response.json()
  ```
</CodeGroup>

***

## Running Workflows

Submit a workflow for execution.

<Info>
  **Concurrent submissions supported:** Depending on your subscription tier, you can submit multiple workflows without waiting for previous jobs to complete. Jobs run in parallel up to your tier's limit — additional jobs queue automatically. See [Parallel Execution](/development/cloud/overview#parallel-execution-concurrent-jobs) for details and concurrency limits.
</Info>

### Submit Workflow

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/prompt" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{"prompt": '"$(cat workflow_api.json)"'}'
  ```

  ```typescript TypeScript theme={null}
  async function submitWorkflow(workflow: Record<string, any>): Promise<string> {
    const response = await fetch(`${BASE_URL}/api/prompt`, {
      method: "POST",
      headers: getHeaders(),
      body: JSON.stringify({ prompt: workflow }),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    const result = await response.json();

    if (result.error) {
      throw new Error(`Workflow error: ${result.error}`);
    }
    return result.prompt_id;
  }

  const workflow = JSON.parse(await readFile("workflow_api.json", "utf-8"));
  const promptId = await submitWorkflow(workflow);
  console.log(`Submitted job: ${promptId}`);
  ```

  ```python Python theme={null}
  def submit_workflow(workflow: dict) -> str:
      """Submit a workflow and return the prompt_id (job ID).
      
      Args:
          workflow: ComfyUI workflow in API format
          
      Returns:
          prompt_id for tracking the job
      """
      response = requests.post(
          f"{BASE_URL}/api/prompt",
          headers=get_headers(),
          json={"prompt": workflow}
      )
      response.raise_for_status()
      result = response.json()
      
      if "error" in result:
          raise ValueError(f"Workflow error: {result['error']}")
      
      return result["prompt_id"]

  # Load and submit a workflow
  with open("workflow_api.json") as f:
      workflow = json.load(f)

  prompt_id = submit_workflow(workflow)
  print(f"Submitted job: {prompt_id}")
  ```
</CodeGroup>

### Using Partner Nodes

If your workflow contains [Partner Nodes](/tutorials/partner-nodes/overview) (nodes that call external AI services like Flux Pro, Ideogram, etc.), you must include your [Comfy API key](/development/api-development/getting-an-api-key) in the `extra_data` field of the request payload.

<Note>
  The ComfyUI frontend automatically packages your API key into `extra_data` when running workflows in the browser. This section is only relevant when calling the API directly.
</Note>

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/prompt" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "prompt": '"$(cat workflow_api.json)"',
      "extra_data": {
        "api_key_comfy_org": "your-comfy-api-key"
      }
    }'
  ```

  ```typescript TypeScript theme={null}
  async function submitWorkflowWithPartnerNodes(
    workflow: Record<string, any>,
    apiKey: string
  ): Promise<string> {
    const response = await fetch(`${BASE_URL}/api/prompt`, {
      method: "POST",
      headers: getHeaders(),
      body: JSON.stringify({
        prompt: workflow,
        extra_data: {
          api_key_comfy_org: apiKey,
        },
      }),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    const result = await response.json();
    return result.prompt_id;
  }

  // Use when workflow contains Partner Nodes (e.g., Flux Pro, Ideogram, etc.)
  const promptId = await submitWorkflowWithPartnerNodes(workflow, API_KEY);
  ```

  ```python Python theme={null}
  def submit_workflow_with_partner_nodes(workflow: dict, api_key: str) -> str:
      """Submit a workflow that uses Partner Nodes.
      
      Args:
          workflow: ComfyUI workflow in API format
          api_key: Your API key from platform.comfy.org
          
      Returns:
          prompt_id for tracking the job
      """
      response = requests.post(
          f"{BASE_URL}/api/prompt",
          headers=get_headers(),
          json={
              "prompt": workflow,
              "extra_data": {
                  "api_key_comfy_org": api_key
              }
          }
      )
      response.raise_for_status()
      return response.json()["prompt_id"]

  # Use when workflow contains Partner Nodes
  prompt_id = submit_workflow_with_partner_nodes(workflow, API_KEY)
  ```
</CodeGroup>

<Info>
  Generate your API key at [platform.comfy.org](https://platform.comfy.org/login). This is the same key used for Cloud API authentication (`X-API-Key` header). See [Getting an API Key](/development/api-development/getting-an-api-key) for step-by-step instructions.
</Info>

### Modify Workflow Inputs

<CodeGroup>
  ```typescript TypeScript theme={null}
  function setWorkflowInput(
    workflow: Record<string, any>,
    nodeId: string,
    inputName: string,
    value: any
  ): Record<string, any> {
    if (workflow[nodeId]) {
      workflow[nodeId].inputs[inputName] = value;
    }
    return workflow;
  }

  // Example: Set seed and prompt
  let workflow = JSON.parse(await readFile("workflow_api.json", "utf-8"));
  workflow = setWorkflowInput(workflow, "3", "seed", 12345);
  workflow = setWorkflowInput(workflow, "6", "text", "a beautiful landscape");
  ```

  ```python Python theme={null}
  def set_workflow_input(workflow: dict, node_id: str, input_name: str, value) -> dict:
      """Modify a workflow input value.
      
      Args:
          workflow: The workflow dict
          node_id: ID of the node to modify
          input_name: Name of the input field
          value: New value
          
      Returns:
          Modified workflow
      """
      if node_id in workflow:
          workflow[node_id]["inputs"][input_name] = value
      return workflow

  # Example: Set seed and prompt
  workflow = set_workflow_input(workflow, "3", "seed", 12345)
  workflow = set_workflow_input(workflow, "6", "text", "a beautiful landscape")
  ```
</CodeGroup>

***

## Checking Job Status

Poll for job completion.

**Job Status Values:**

The API returns one of the following status values:

| Status        | Description                        |
| ------------- | ---------------------------------- |
| `pending`     | Job is queued and waiting to start |
| `in_progress` | Job is currently executing         |
| `completed`   | Job finished successfully          |
| `failed`      | Job encountered an error           |
| `cancelled`   | Job was cancelled by user          |

<CodeGroup>
  ```bash curl theme={null}
  # Poll for job completion
  curl -X GET "$BASE_URL/api/job/{prompt_id}/status" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY"

  # Response examples:
  # {"status": "pending"}      - Job is queued
  # {"status": "in_progress"}  - Job is currently running
  # {"status": "completed"}    - Job finished successfully
  # {"status": "failed"}       - Job encountered an error
  # {"status": "cancelled"}    - Job was cancelled
  ```

  ```typescript TypeScript theme={null}
  interface JobStatus {
    status: string;
  }

  async function getJobStatus(promptId: string): Promise<JobStatus> {
    const response = await fetch(`${BASE_URL}/api/job/${promptId}/status`, {
      headers: getHeaders(),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return response.json();
  }

  async function pollForCompletion(
    promptId: string,
    timeout: number = 300,
    pollInterval: number = 2000
  ): Promise<void> {
    const startTime = Date.now();

    while (Date.now() - startTime < timeout * 1000) {
      const { status } = await getJobStatus(promptId);

      if (status === "completed") {
        return;
      } else if (["failed", "cancelled"].includes(status)) {
        throw new Error(`Job failed with status: ${status}`);
      }

      await new Promise((resolve) => setTimeout(resolve, pollInterval));
    }

    throw new Error(`Job ${promptId} did not complete within ${timeout}s`);
  }

  await pollForCompletion(promptId);
  console.log("Job completed!");
  ```

  ```python Python theme={null}
  def get_job_status(prompt_id: str) -> str:
      """Get the current status of a job."""
      response = requests.get(
          f"{BASE_URL}/api/job/{prompt_id}/status",
          headers=get_headers()
      )
      response.raise_for_status()
      return response.json()["status"]

  def poll_for_completion(prompt_id: str, timeout: int = 300, poll_interval: float = 2.0) -> None:
      """Poll until job completes or times out."""
      start_time = time.time()

      while time.time() - start_time < timeout:
          status = get_job_status(prompt_id)

          if status == "completed":
              return
          elif status in ("failed", "cancelled"):
              raise RuntimeError(f"Job failed with status: {status}")

          time.sleep(poll_interval)

      raise TimeoutError(f"Job {prompt_id} did not complete within {timeout}s")

  poll_for_completion(prompt_id)
  print("Job completed!")
  ```
</CodeGroup>

***

## WebSocket for Real-Time Progress

Connect to the WebSocket for real-time execution updates.

<Note>
  The `clientId` parameter is currently ignored—all connections for a user receive the same messages. Pass a unique `clientId` for forward compatibility.
</Note>

<CodeGroup>
  ```typescript TypeScript theme={null}
  async function listenForCompletion(
    promptId: string,
    timeout: number = 300000
  ): Promise<Record<string, any>> {
    const wsUrl = `wss://cloud.comfy.org/ws?clientId=${crypto.randomUUID()}&token=${API_KEY}`;
    const outputs: Record<string, any> = {};

    return new Promise((resolve, reject) => {
      const ws = new WebSocket(wsUrl);
      const timer = setTimeout(() => {
        ws.close();
        reject(new Error(`Job did not complete within ${timeout / 1000}s`));
      }, timeout);

      ws.onmessage = (event) => {
        const data = JSON.parse(event.data);
        const msgType = data.type;
        const msgData = data.data ?? {};

        // Filter to our job
        if (msgData.prompt_id !== promptId) return;

        if (msgType === "executing") {
          const node = msgData.node;
          if (node) {
            console.log(`Executing node: ${node}`);
          } else {
            console.log("Execution complete");
          }
        } else if (msgType === "progress") {
          console.log(`Progress: ${msgData.value}/${msgData.max}`);
        } else if (msgType === "executed" && msgData.output) {
          outputs[msgData.node] = msgData.output;
        } else if (msgType === "execution_success") {
          console.log("Job completed successfully!");
          clearTimeout(timer);
          ws.close();
          resolve(outputs);
        } else if (msgType === "execution_error") {
          const errorMsg = msgData.exception_message ?? "Unknown error";
          clearTimeout(timer);
          ws.close();
          reject(new Error(`Execution error: ${errorMsg}`));
        }
      };

      ws.onerror = (err) => {
        clearTimeout(timer);
        reject(err);
      };
    });
  }

  // Wait for completion and collect outputs
  const outputs = await listenForCompletion(promptId);
  ```

  ```python Python theme={null}
  import asyncio
  import aiohttp
  import json
  import uuid

  async def listen_for_completion(prompt_id: str, timeout: float = 300.0) -> dict:
      """Connect to WebSocket and listen for job completion.

      Returns:
          Final outputs from the job
      """
      ws_url = BASE_URL.replace("https://", "wss://")
      client_id = str(uuid.uuid4())
      ws_url = f"{ws_url}/ws?clientId={client_id}&token={API_KEY}"

      outputs = {}

      async with aiohttp.ClientSession() as session:
          async with session.ws_connect(ws_url) as ws:
              async def receive_messages():
                  async for msg in ws:
                      if msg.type == aiohttp.WSMsgType.TEXT:
                          data = json.loads(msg.data)
                          msg_type = data.get("type")
                          msg_data = data.get("data", {})

                          # Filter to our job
                          if msg_data.get("prompt_id") != prompt_id:
                              continue

                          if msg_type == "executing":
                              node = msg_data.get("node")
                              if node:
                                  print(f"Executing node: {node}")

                          elif msg_type == "progress":
                              value = msg_data.get("value", 0)
                              max_val = msg_data.get("max", 100)
                              print(f"Progress: {value}/{max_val}")

                          elif msg_type == "executed":
                              node_id = msg_data.get("node")
                              output = msg_data.get("output", {})
                              if output:
                                  outputs[node_id] = output

                          elif msg_type == "execution_success":
                              print("Job completed successfully!")
                              return outputs

                          elif msg_type == "execution_error":
                              error_msg = msg_data.get("exception_message", "Unknown error")
                              raise RuntimeError(f"Execution error: {error_msg}")

                      elif msg.type == aiohttp.WSMsgType.ERROR:
                          raise RuntimeError(f"WebSocket error: {ws.exception()}")

              try:
                  return await asyncio.wait_for(receive_messages(), timeout=timeout)
              except asyncio.TimeoutError:
                  raise TimeoutError(f"Job did not complete within {timeout}s")

  # Wait for completion and collect outputs
  outputs = await listen_for_completion(prompt_id)
  ```
</CodeGroup>

### WebSocket Message Types

Messages are sent as JSON text frames unless otherwise noted.

| Type                    | Description                                                                              |
| ----------------------- | ---------------------------------------------------------------------------------------- |
| `status`                | Queue status update with `queue_remaining` count                                         |
| `notification`          | User-friendly status message (`value` field contains text like "Executing workflow\...") |
| `execution_start`       | Workflow execution has started                                                           |
| `executing`             | A specific node is now executing (node ID in `node` field)                               |
| `progress`              | Step progress within a node (`value`/`max` for sampling steps)                           |
| `progress_state`        | Extended progress state with node metadata (nested `nodes` object)                       |
| `executed`              | Node completed with outputs (images, video, etc. in `output` field)                      |
| `execution_cached`      | Nodes skipped because outputs are cached (`nodes` array)                                 |
| `execution_success`     | Entire workflow completed successfully                                                   |
| `execution_error`       | Workflow failed (includes `exception_type`, `exception_message`, `traceback`)            |
| `execution_interrupted` | Workflow was cancelled by user                                                           |

#### Binary Messages (Preview Images)

During image generation, ComfyUI sends **binary WebSocket frames** containing preview images. These are raw binary data (not JSON):

| Binary Type                   | Value | Description                                   |
| ----------------------------- | ----- | --------------------------------------------- |
| `PREVIEW_IMAGE`               | `1`   | In-progress preview during diffusion sampling |
| `TEXT`                        | `3`   | Text output from nodes (progress text)        |
| `PREVIEW_IMAGE_WITH_METADATA` | `4`   | Preview image with node context metadata      |

**Binary frame formats** (all integers are big-endian):

<Tabs>
  <Tab title="PREVIEW_IMAGE (1)">
    | Offset | Size     | Field        | Description                 |
    | ------ | -------- | ------------ | --------------------------- |
    | 0      | 4 bytes  | `type`       | `0x00000001`                |
    | 4      | 4 bytes  | `image_type` | Format code (1=JPEG, 2=PNG) |
    | 8      | variable | `image_data` | Raw image bytes             |
  </Tab>

  <Tab title="TEXT (3)">
    | Offset | Size     | Field         | Description                 |
    | ------ | -------- | ------------- | --------------------------- |
    | 0      | 4 bytes  | `type`        | `0x00000003`                |
    | 4      | 4 bytes  | `node_id_len` | Length of node\_id string   |
    | 8      | N bytes  | `node_id`     | UTF-8 encoded node ID       |
    | 8+N    | variable | `text`        | UTF-8 encoded progress text |
  </Tab>

  <Tab title="PREVIEW_WITH_METADATA (4)">
    | Offset | Size     | Field          | Description             |
    | ------ | -------- | -------------- | ----------------------- |
    | 0      | 4 bytes  | `type`         | `0x00000004`            |
    | 4      | 4 bytes  | `metadata_len` | Length of metadata JSON |
    | 8      | N bytes  | `metadata`     | UTF-8 JSON (see below)  |
    | 8+N    | variable | `image_data`   | Raw JPEG/PNG bytes      |

    **Metadata JSON structure:**

    ```json theme={null}
    {
      "node_id": "3",
      "display_node_id": "3",
      "real_node_id": "3",
      "prompt_id": "abc-123",
      "parent_node_id": null
    }
    ```
  </Tab>
</Tabs>

<Note>
  See the [OpenAPI Specification](/development/cloud/openapi) for complete schema definitions of each JSON message type.
</Note>

***

## Downloading Outputs

Retrieve generated files after job completion.

<CodeGroup>
  ```bash curl theme={null}
  # Download a single output file (follow 302 redirect with -L)
  curl -L "$BASE_URL/api/view?filename=output.png&subfolder=&type=output" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -o output.png
  ```

  ```typescript TypeScript theme={null}
  async function downloadOutput(
    filename: string,
    subfolder: string = "",
    outputType: string = "output"
  ): Promise<ArrayBuffer> {
    const params = new URLSearchParams({ filename, subfolder, type: outputType });
    // Get the redirect URL
    const response = await fetch(`${BASE_URL}/api/view?${params}`, {
      headers: { "X-API-Key": API_KEY },
      redirect: "manual",
    });
    if (response.status !== 302) throw new Error(`HTTP ${response.status}`);
    const signedUrl = response.headers.get("location")!;

    // Fetch from signed URL
    const fileResponse = await fetch(signedUrl);
    if (!fileResponse.ok) throw new Error(`HTTP ${fileResponse.status}`);
    return fileResponse.arrayBuffer();
  }

  async function saveOutputs(
    outputs: Record<string, any>,
    outputDir: string = "."
  ): Promise<void> {
    for (const nodeOutputs of Object.values(outputs)) {
      for (const key of ["images", "video", "audio"]) {
        for (const fileInfo of (nodeOutputs as any)[key] ?? []) {
          const data = await downloadOutput(
            fileInfo.filename,
            fileInfo.subfolder ?? "",
            fileInfo.type ?? "output"
          );
          const path = `${outputDir}/${fileInfo.filename}`;
          await writeFile(path, Buffer.from(data));
          console.log(`Saved: ${path}`);
        }
      }
    }
  }

  // Download all outputs
  await saveOutputs(outputs, "./my_outputs");
  ```

  ```python Python theme={null}
  def download_output(filename: str, subfolder: str = "", output_type: str = "output") -> bytes:
      """Download an output file.

      Args:
          filename: Name of the file
          subfolder: Subfolder path (usually empty)
          output_type: "output" for final outputs, "temp" for previews

      Returns:
          File bytes
      """
      params = {
          "filename": filename,
          "subfolder": subfolder,
          "type": output_type
      }

      response = requests.get(
          f"{BASE_URL}/api/view",
          headers=get_headers(),
          params=params
      )
      response.raise_for_status()
      return response.content

  def save_outputs(outputs: dict, output_dir: str = "."):
      """Save all outputs from a job to disk.

      Args:
          outputs: Outputs dict from job (node_id -> output_data)
          output_dir: Directory to save files to
      """
      import os
      os.makedirs(output_dir, exist_ok=True)

      for node_id, node_outputs in outputs.items():
          for key in ("images", "video", "audio"):
              for file_info in node_outputs.get(key, []):
                  filename = file_info["filename"]
                  subfolder = file_info.get("subfolder", "")
                  output_type = file_info.get("type", "output")

                  data = download_output(filename, subfolder, output_type)

                  output_path = os.path.join(output_dir, filename)
                  with open(output_path, "wb") as f:
                      f.write(data)
                  print(f"Saved: {output_path}")

  # Download all outputs
  save_outputs(outputs, "./my_outputs")
  ```
</CodeGroup>

***

## Complete End-to-End Example

Here's a full example that ties everything together:

<CodeGroup>
  ```typescript TypeScript theme={null}
  const BASE_URL = "https://cloud.comfy.org";
  const API_KEY = process.env.COMFY_CLOUD_API_KEY!;

  function getHeaders(): HeadersInit {
    return { "X-API-Key": API_KEY, "Content-Type": "application/json" };
  }

  async function submitWorkflow(workflow: Record<string, any>): Promise<string> {
    const response = await fetch(`${BASE_URL}/api/prompt`, {
      method: "POST",
      headers: getHeaders(),
      body: JSON.stringify({ prompt: workflow }),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return (await response.json()).prompt_id;
  }

  async function waitForCompletion(
    promptId: string,
    timeout: number = 300000
  ): Promise<Record<string, any>> {
    const wsUrl = `wss://cloud.comfy.org/ws?clientId=${crypto.randomUUID()}&token=${API_KEY}`;
    const outputs: Record<string, any> = {};

    return new Promise((resolve, reject) => {
      const ws = new WebSocket(wsUrl);
      const timer = setTimeout(() => {
        ws.close();
        reject(new Error("Job timed out"));
      }, timeout);

      ws.onmessage = (event) => {
        const data = JSON.parse(event.data);
        if (data.data?.prompt_id !== promptId) return;

        const msgType = data.type;
        const msgData = data.data ?? {};

        if (msgType === "progress") {
          console.log(`Progress: ${msgData.value}/${msgData.max}`);
        } else if (msgType === "executed" && msgData.output) {
          outputs[msgData.node] = msgData.output;
        } else if (msgType === "execution_success") {
          clearTimeout(timer);
          ws.close();
          resolve(outputs);
        } else if (msgType === "execution_error") {
          clearTimeout(timer);
          ws.close();
          reject(new Error(msgData.exception_message ?? "Unknown error"));
        }
      };

      ws.onerror = (err) => {
        clearTimeout(timer);
        reject(err);
      };
    });
  }

  async function downloadOutputs(
    outputs: Record<string, any>,
    outputDir: string
  ): Promise<void> {
    for (const nodeOutputs of Object.values(outputs)) {
      for (const key of ["images", "video", "audio"]) {
        for (const fileInfo of (nodeOutputs as any)[key] ?? []) {
          const params = new URLSearchParams({
            filename: fileInfo.filename,
            subfolder: fileInfo.subfolder ?? "",
            type: fileInfo.type ?? "output",
          });
          // Get redirect URL (don't follow to avoid sending auth to storage)
          const response = await fetch(`${BASE_URL}/api/view?${params}`, {
            headers: { "X-API-Key": API_KEY },
            redirect: "manual",
          });
          if (response.status !== 302) throw new Error(`HTTP ${response.status}`);
          const signedUrl = response.headers.get("location")!;
          // Fetch from signed URL without auth headers
          const fileResponse = await fetch(signedUrl);
          if (!fileResponse.ok) throw new Error(`HTTP ${fileResponse.status}`);

          const path = `${outputDir}/${fileInfo.filename}`;
          await writeFile(path, Buffer.from(await fileResponse.arrayBuffer()));
          console.log(`Downloaded: ${path}`);
        }
      }
    }
  }

  async function main() {
    // 1. Load workflow
    const workflow = JSON.parse(await readFile("workflow_api.json", "utf-8"));

    // 2. Modify workflow parameters
    workflow["3"].inputs.seed = 42;
    workflow["6"].inputs.text = "a beautiful sunset over mountains";

    // 3. Submit workflow
    const promptId = await submitWorkflow(workflow);
    console.log(`Job submitted: ${promptId}`);

    // 4. Wait for completion with progress
    const outputs = await waitForCompletion(promptId);
    console.log(`Job completed! Found ${Object.keys(outputs).length} output nodes`);

    // 5. Download outputs
    await downloadOutputs(outputs, "./outputs");
    console.log("Done!");
  }

  main();
  ```

  ```python Python theme={null}
  import os
  import requests
  import json
  import asyncio
  import aiohttp
  import uuid

  BASE_URL = "https://cloud.comfy.org"
  API_KEY = os.environ["COMFY_CLOUD_API_KEY"]

  def get_headers():
      return {"X-API-Key": API_KEY, "Content-Type": "application/json"}

  def upload_image(file_path: str) -> dict:
      """Upload an image and return the reference for use in workflows."""
      with open(file_path, "rb") as f:
          response = requests.post(
              f"{BASE_URL}/api/upload/image",
              headers={"X-API-Key": API_KEY},
              files={"image": f},
              data={"type": "input", "overwrite": "true"}
          )
      response.raise_for_status()
      return response.json()

  def submit_workflow(workflow: dict) -> str:
      """Submit workflow and return prompt_id."""
      response = requests.post(
          f"{BASE_URL}/api/prompt",
          headers=get_headers(),
          json={"prompt": workflow}
      )
      response.raise_for_status()
      return response.json()["prompt_id"]

  async def wait_for_completion(prompt_id: str, timeout: float = 300.0) -> dict:
      """Wait for job completion via WebSocket."""
      ws_url = BASE_URL.replace("https://", "wss://") + f"/ws?clientId={uuid.uuid4()}&token={API_KEY}"
      outputs = {}
      
      async with aiohttp.ClientSession() as session:
          async with session.ws_connect(ws_url) as ws:
              start = asyncio.get_event_loop().time()
              async for msg in ws:
                  if asyncio.get_event_loop().time() - start > timeout:
                      raise TimeoutError("Job timed out")
                  
                  if msg.type != aiohttp.WSMsgType.TEXT:
                      continue
                      
                  data = json.loads(msg.data)
                  if data.get("data", {}).get("prompt_id") != prompt_id:
                      continue
                  
                  msg_type = data.get("type")
                  msg_data = data.get("data", {})
                  
                  if msg_type == "progress":
                      print(f"Progress: {msg_data.get('value')}/{msg_data.get('max')}")
                  elif msg_type == "executed":
                      if output := msg_data.get("output"):
                          outputs[msg_data["node"]] = output
                  elif msg_type == "execution_success":
                      return outputs
                  elif msg_type == "execution_error":
                      raise RuntimeError(msg_data.get("exception_message", "Unknown error"))
      
      return outputs

  def download_outputs(outputs: dict, output_dir: str):
      """Download all output files."""
      os.makedirs(output_dir, exist_ok=True)
      
      for node_outputs in outputs.values():
          for key in ["images", "video", "audio"]:
              for file_info in node_outputs.get(key, []):
                  params = {
                      "filename": file_info["filename"],
                      "subfolder": file_info.get("subfolder", ""),
                      "type": file_info.get("type", "output")
                  }
                  response = requests.get(f"{BASE_URL}/api/view", headers=get_headers(), params=params)
                  response.raise_for_status()
                  
                  path = os.path.join(output_dir, file_info["filename"])
                  with open(path, "wb") as f:
                      f.write(response.content)
                  print(f"Downloaded: {path}")

  async def main():
      # 1. Load workflow
      with open("workflow_api.json") as f:
          workflow = json.load(f)
      
      # 2. Optionally upload input images
      # image_ref = upload_image("input.png")
      # workflow["1"]["inputs"]["image"] = image_ref["name"]
      
      # 3. Modify workflow parameters
      workflow["3"]["inputs"]["seed"] = 42
      workflow["6"]["inputs"]["text"] = "a beautiful sunset over mountains"
      
      # 4. Submit workflow
      prompt_id = submit_workflow(workflow)
      print(f"Job submitted: {prompt_id}")
      
      # 5. Wait for completion with progress
      outputs = await wait_for_completion(prompt_id)
      print(f"Job completed! Found {len(outputs)} output nodes")
      
      # 6. Download outputs
      download_outputs(outputs, "./outputs")
      print("Done!")

  if __name__ == "__main__":
      asyncio.run(main())
  ```
</CodeGroup>

***

## Queue Management

### Get Queue Status

<CodeGroup>
  ```bash curl theme={null}
  curl -X GET "$BASE_URL/api/queue" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY"
  ```

  ```typescript TypeScript theme={null}
  async function getQueue(): Promise<{
    queue_running: any[];
    queue_pending: any[];
  }> {
    const response = await fetch(`${BASE_URL}/api/queue`, {
      headers: getHeaders(),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return response.json();
  }

  const queue = await getQueue();
  console.log(`Running: ${queue.queue_running.length}`);
  console.log(`Pending: ${queue.queue_pending.length}`);
  ```

  ```python Python theme={null}
  def get_queue():
      """Get current queue status."""
      response = requests.get(
          f"{BASE_URL}/api/queue",
          headers=get_headers()
      )
      response.raise_for_status()
      return response.json()

  queue = get_queue()
  print(f"Running: {len(queue.get('queue_running', []))}")
  print(f"Pending: {len(queue.get('queue_pending', []))}")
  ```
</CodeGroup>

### Cancel a Job

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/queue" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{"delete": ["PROMPT_ID_HERE"]}'
  ```

  ```typescript TypeScript theme={null}
  async function cancelJob(promptId: string): Promise<void> {
    const response = await fetch(`${BASE_URL}/api/queue`, {
      method: "POST",
      headers: getHeaders(),
      body: JSON.stringify({ delete: [promptId] }),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
  }
  ```

  ```python Python theme={null}
  def cancel_job(prompt_id: str):
      """Cancel a pending or running job."""
      response = requests.post(
          f"{BASE_URL}/api/queue",
          headers=get_headers(),
          json={"delete": [prompt_id]}
      )
      response.raise_for_status()
      return response.json()
  ```
</CodeGroup>

### Interrupt Current Execution

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "$BASE_URL/api/interrupt" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY"
  ```

  ```typescript TypeScript theme={null}
  async function interrupt(): Promise<void> {
    const response = await fetch(`${BASE_URL}/api/interrupt`, {
      method: "POST",
      headers: getHeaders(),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
  }
  ```

  ```python Python theme={null}
  def interrupt():
      """Interrupt the currently running job."""
      response = requests.post(
          f"{BASE_URL}/api/interrupt",
          headers=get_headers()
      )
      response.raise_for_status()
  ```
</CodeGroup>

***

## Error Handling

### HTTP Errors

REST API endpoints return standard HTTP status codes:

| Status | Description                                    |
| ------ | ---------------------------------------------- |
| `400`  | Invalid request (bad workflow, missing fields) |
| `401`  | Unauthorized (invalid or missing API key)      |
| `402`  | Insufficient credits                           |
| `429`  | Subscription inactive                          |
| `500`  | Internal server error                          |

### Execution Errors

During workflow execution, errors are delivered via the `execution_error` WebSocket message. The `exception_type` field identifies the error category:

| Exception Type              | Description                                        |
| --------------------------- | -------------------------------------------------- |
| `ValidationError`           | Invalid workflow or inputs                         |
| `ModelDownloadError`        | Required model not available or failed to download |
| `ImageDownloadError`        | Failed to download input image from URL            |
| `OOMError`                  | Out of GPU memory                                  |
| `InsufficientFundsError`    | Account balance too low (for Partner Nodes)        |
| `InactiveSubscriptionError` | Subscription not active                            |


# OpenAPI Specification
Source: https://docs.comfy.org/development/cloud/openapi

/openapi-cloud.yaml
Machine-readable OpenAPI specification for Comfy Cloud API

<Warning>
  **Experimental API:** This API is experimental and subject to change. Endpoints, request/response formats, and behavior may be modified without notice.
</Warning>

# Comfy Cloud API Specification

This page provides the complete OpenAPI 3.0 specification for the Comfy Cloud API.

<Note>
  **Subscription Required:** Running workflows via the API requires an active Comfy Cloud subscription. See [pricing plans](https://www.comfy.org/cloud/pricing?utm_source=docs\&utm_campaign=cloud-api) for details.
</Note>

## Interactive API Reference

Explore the full API with interactive documentation:

<Card title="Cloud API Reference" icon="code" href="/api-reference/cloud/overview">
  Browse endpoints, view schemas, and try requests
</Card>

## Using the Specification

The OpenAPI spec can be used to:

* **Generate client libraries** in any language using tools like [OpenAPI Generator](https://openapi-generator.tech/)
* **Import into API tools** like Postman, Insomnia, or Paw
* **Generate documentation** using tools like Redoc or Swagger UI
* **Validate requests** in your application

## Download

You can download the raw OpenAPI specification file:

<Card title="openapi-cloud.yaml" icon="download" href="https://raw.githubusercontent.com/Comfy-Org/docs/main/openapi-cloud.yaml">
  Download the OpenAPI 3.0 specification
</Card>

## Authentication

All API requests require an API key passed in the `X-API-Key` header.

### Getting an API Key

See [Getting an API Key](/development/api-development/getting-an-api-key) for step-by-step instructions with screenshots.

### Using the API Key

```yaml theme={null}
X-API-Key: your-api-key
```

## Base URL

| Environment | URL                       |
| ----------- | ------------------------- |
| Production  | `https://cloud.comfy.org` |

## WebSocket Connection

For real-time updates, connect to the WebSocket endpoint:

```
wss://cloud.comfy.org/ws?clientId={uuid}&token={api_key}
```

See the [API Reference](/development/cloud/api-reference#websocket-for-real-time-progress) for message types and handling.


# Cloud API Overview
Source: https://docs.comfy.org/development/cloud/overview

Programmatic access to Comfy Cloud for running workflows, managing files, and monitoring execution

<Warning>
  **Experimental API:** This API is experimental and subject to change. Endpoints, request/response formats, and behavior may be modified without notice.
</Warning>

# Comfy Cloud API

The Comfy Cloud API provides programmatic access to run workflows on Comfy Cloud infrastructure. The API is compatible with local ComfyUI's API, making it easy to migrate existing integrations.

<Note>
  **Subscription required:** API access is available on the **Standard**, **Creator** and **Pro** tiers. The Free tier does not include API access. See [pricing plans](https://www.comfy.org/cloud/pricing?utm_source=docs\&utm_campaign=cloud-api) for details.
</Note>

## Credits and Usage

API requests draw from the same monthly credit allocation as the Comfy Cloud web UI — there is no separate API credit pool. Each tier's included credits, top-up options, and per-workflow runtime caps apply to API jobs in exactly the same way as UI jobs. See the [pricing page](https://www.comfy.org/cloud/pricing?utm_source=docs\&utm_campaign=cloud-api) for the monthly credit amounts on the Standard, Creator and Pro tiers. If you run out of credits mid-month, top-ups can be purchased from your account dashboard.

## Base URL

```
https://cloud.comfy.org
```

## Authentication

All API requests require an API key passed via the `X-API-Key` header.

### Getting an API Key

See [Getting an API Key](/development/api-development/getting-an-api-key) for instructions on creating and managing your Cloud API key.

### Using the API Key

Pass your API key in the `X-API-Key` header with every request:

<CodeGroup>
  ```bash curl theme={null}
  curl -X GET "https://cloud.comfy.org/api/user" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY"
  ```

  ```typescript TypeScript theme={null}
  const API_KEY = process.env.COMFY_CLOUD_API_KEY!;

  const response = await fetch("https://cloud.comfy.org/api/user", {
    headers: { "X-API-Key": API_KEY },
  });
  const user = await response.json();
  ```

  ```python Python theme={null}
  import os
  import requests

  API_KEY = os.environ["COMFY_CLOUD_API_KEY"]
  headers = {"X-API-Key": API_KEY}

  response = requests.get(
      "https://cloud.comfy.org/api/user",
      headers=headers
  )
  ```
</CodeGroup>

## Core Concepts

### Workflows

ComfyUI workflows are JSON objects describing a graph of nodes. The API accepts workflows in the [API format](/development/api-development/workflow-api-format) (node IDs as keys with class\_type, inputs, etc.) as produced by the ComfyUI frontend's "Export Workflow (API)" option.

### Jobs

When you submit a workflow, a **job** is created. Jobs are executed asynchronously:

1. Submit workflow via `POST /api/prompt`
2. Receive a `prompt_id` (job ID)
3. Monitor progress via WebSocket or poll for status
4. Retrieve outputs when complete

### Parallel Execution (Concurrent Jobs)

API users can submit multiple workflows concurrently without waiting for previous jobs to complete. Simply send multiple `POST /api/prompt` requests — no special headers or parameters are needed. The dispatcher will run them in parallel up to your subscription tier's limit.

| Subscription Tier | Concurrent Jobs |
| ----------------- | --------------- |
| Standard          | 1               |
| Creator           | 3               |
| Pro               | 5               |

Jobs submitted beyond your concurrency limit will queue normally and execute automatically as slots free up.

<Info>
  Parallel execution is currently available via the API only. See [pricing plans](https://www.comfy.org/cloud/pricing?utm_source=docs\&utm_campaign=cloud-api) for subscription details.
</Info>

#### Example: Submitting Multiple Jobs in Parallel

<CodeGroup>
  ```python Python theme={null}
  import os
  import json
  import asyncio
  import aiohttp

  BASE_URL = "https://cloud.comfy.org"
  API_KEY = os.environ["COMFY_CLOUD_API_KEY"]

  async def submit_workflow(session, workflow):
      """Submit a single workflow and return the prompt_id."""
      async with session.post(
          f"{BASE_URL}/api/prompt",
          headers={"X-API-Key": API_KEY, "Content-Type": "application/json"},
          json={"prompt": workflow},
      ) as response:
          result = await response.json()
          return result["prompt_id"]

  async def main():
      with open("workflow_api.json") as f:
          base_workflow = json.load(f)

      # Create variations by changing the seed
      workflows = []
      for seed in [42, 123, 456]:
          workflow = json.loads(json.dumps(base_workflow))
          workflow["3"]["inputs"]["seed"] = seed
          workflows.append(workflow)

      # Submit all workflows concurrently
      async with aiohttp.ClientSession() as session:
          prompt_ids = await asyncio.gather(
              *[submit_workflow(session, wf) for wf in workflows]
          )

      for pid in prompt_ids:
          print(f"Job submitted: {pid}")

      # Poll or use WebSocket to monitor each job...

  asyncio.run(main())
  ```

  ```typescript TypeScript theme={null}
  const BASE_URL = "https://cloud.comfy.org";
  const API_KEY = process.env.COMFY_CLOUD_API_KEY!;

  async function submitWorkflow(
    workflow: Record<string, any>
  ): Promise<string> {
    const response = await fetch(`${BASE_URL}/api/prompt`, {
      method: "POST",
      headers: { "X-API-Key": API_KEY, "Content-Type": "application/json" },
      body: JSON.stringify({ prompt: workflow }),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return (await response.json()).prompt_id;
  }

  async function main() {
    const base = JSON.parse(
      await Deno.readTextFile("workflow_api.json")
    );

    // Create variations by changing the seed
    const seeds = [42, 123, 456];
    const workflows = seeds.map((seed) => {
      const wf = structuredClone(base);
      wf["3"].inputs.seed = seed;
      return wf;
    });

    // Submit all workflows concurrently
    const promptIds = await Promise.all(
      workflows.map((wf) => submitWorkflow(wf))
    );

    for (const pid of promptIds) {
      console.log(`Job submitted: ${pid}`);
    }

    // Poll or use WebSocket to monitor each job...
  }

  main();
  ```
</CodeGroup>

### Outputs

Generated content (images, videos, audio) is stored in cloud storage. Output files can be downloaded via the `/api/view` endpoint, which returns a 302 redirect to a temporary signed URL.

## Quick Start

Here's a complete example showing how to submit a workflow, monitor its progress, and retrieve outputs:

### Step 1: Submit a Workflow

<CodeGroup>
  ```bash curl theme={null}
  curl -X POST "https://cloud.comfy.org/api/prompt" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{"prompt": '"$(cat workflow_api.json)"'}'
  ```

  ```typescript TypeScript theme={null}
  const BASE_URL = "https://cloud.comfy.org";
  const API_KEY = process.env.COMFY_CLOUD_API_KEY!;

  // Load your workflow (exported from ComfyUI in API format)
  const workflow = JSON.parse(await Deno.readTextFile("workflow_api.json"));

  // Submit the workflow
  const response = await fetch(`${BASE_URL}/api/prompt`, {
    method: "POST",
    headers: { "X-API-Key": API_KEY, "Content-Type": "application/json" },
    body: JSON.stringify({ prompt: workflow }),
  });
  const result = await response.json();
  const promptId = result.prompt_id;
  console.log(`Job submitted: ${promptId}`);
  ```

  ```python Python theme={null}
  import os
  import requests
  import json

  BASE_URL = "https://cloud.comfy.org"
  API_KEY = os.environ["COMFY_CLOUD_API_KEY"]

  def get_headers():
      return {"X-API-Key": API_KEY, "Content-Type": "application/json"}

  # Load your workflow (exported from ComfyUI in API format)
  with open("workflow_api.json") as f:
      workflow = json.load(f)

  # Submit the workflow
  response = requests.post(
      f"{BASE_URL}/api/prompt",
      headers=get_headers(),
      json={"prompt": workflow}
  )
  result = response.json()
  prompt_id = result["prompt_id"]
  print(f"Job submitted: {prompt_id}")
  ```
</CodeGroup>

### Step 2: Monitor Job Progress

You can monitor job completion using either polling or WebSocket for real-time updates.

#### Option A: Polling (Simple)

**Job Status Values:**

The API returns one of the following status values:

| Status        | Description                        |
| ------------- | ---------------------------------- |
| `pending`     | Job is queued and waiting to start |
| `in_progress` | Job is currently executing         |
| `completed`   | Job finished successfully          |
| `failed`      | Job encountered an error           |
| `cancelled`   | Job was cancelled by user          |

<CodeGroup>
  ```bash curl theme={null}
  # Poll for job completion
  curl -X GET "$BASE_URL/api/job/{prompt_id}/status" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY"

  # Response examples:
  # {"status": "pending"}      - Job is queued
  # {"status": "in_progress"}  - Job is currently running
  # {"status": "completed"}    - Job finished successfully
  # {"status": "failed"}       - Job encountered an error
  # {"status": "cancelled"}    - Job was cancelled
  ```

  ```typescript TypeScript theme={null}
  interface JobStatus {
    status: string;
  }

  async function getJobStatus(promptId: string): Promise<JobStatus> {
    const response = await fetch(`${BASE_URL}/api/job/${promptId}/status`, {
      headers: getHeaders(),
    });
    if (!response.ok) throw new Error(`HTTP ${response.status}`);
    return response.json();
  }

  async function pollForCompletion(
    promptId: string,
    timeout: number = 300,
    pollInterval: number = 2000
  ): Promise<void> {
    const startTime = Date.now();

    while (Date.now() - startTime < timeout * 1000) {
      const { status } = await getJobStatus(promptId);

      if (status === "completed") {
        return;
      } else if (["failed", "cancelled"].includes(status)) {
        throw new Error(`Job failed with status: ${status}`);
      }

      await new Promise((resolve) => setTimeout(resolve, pollInterval));
    }

    throw new Error(`Job ${promptId} did not complete within ${timeout}s`);
  }

  await pollForCompletion(promptId);
  console.log("Job completed!");
  ```

  ```python Python theme={null}
  def get_job_status(prompt_id: str) -> str:
      """Get the current status of a job."""
      response = requests.get(
          f"{BASE_URL}/api/job/{prompt_id}/status",
          headers=get_headers()
      )
      response.raise_for_status()
      return response.json()["status"]

  def poll_for_completion(prompt_id: str, timeout: int = 300, poll_interval: float = 2.0) -> None:
      """Poll until job completes or times out."""
      start_time = time.time()

      while time.time() - start_time < timeout:
          status = get_job_status(prompt_id)

          if status == "completed":
              return
          elif status in ("failed", "cancelled"):
              raise RuntimeError(f"Job failed with status: {status}")

          time.sleep(poll_interval)

      raise TimeoutError(f"Job {prompt_id} did not complete within {timeout}s")

  poll_for_completion(prompt_id)
  print("Job completed!")
  ```
</CodeGroup>

#### Option B: WebSocket (Real-time Progress)

For real-time progress updates and to collect output metadata:

<CodeGroup>
  ```typescript TypeScript theme={null}
  async function listenForCompletion(
    promptId: string,
    timeout: number = 300000
  ): Promise<Record<string, any>> {
    const wsUrl = `wss://cloud.comfy.org/ws?clientId=${crypto.randomUUID()}&token=${API_KEY}`;
    const outputs: Record<string, any> = {};

    return new Promise((resolve, reject) => {
      const ws = new WebSocket(wsUrl);
      const timer = setTimeout(() => {
        ws.close();
        reject(new Error(`Job did not complete within ${timeout / 1000}s`));
      }, timeout);

      ws.onmessage = (event) => {
        const data = JSON.parse(event.data);
        const msgType = data.type;
        const msgData = data.data ?? {};

        // Filter to our job
        if (msgData.prompt_id !== promptId) return;

        if (msgType === "executing") {
          const node = msgData.node;
          if (node) {
            console.log(`Executing node: ${node}`);
          } else {
            console.log("Execution complete");
          }
        } else if (msgType === "progress") {
          console.log(`Progress: ${msgData.value}/${msgData.max}`);
        } else if (msgType === "executed" && msgData.output) {
          outputs[msgData.node] = msgData.output;
        } else if (msgType === "execution_success") {
          console.log("Job completed successfully!");
          clearTimeout(timer);
          ws.close();
          resolve(outputs);
        } else if (msgType === "execution_error") {
          const errorMsg = msgData.exception_message ?? "Unknown error";
          clearTimeout(timer);
          ws.close();
          reject(new Error(`Execution error: ${errorMsg}`));
        }
      };

      ws.onerror = (err) => {
        clearTimeout(timer);
        reject(err);
      };
    });
  }

  // Wait for completion and collect outputs
  const outputs = await listenForCompletion(promptId);
  ```

  ```python Python theme={null}
  import asyncio
  import aiohttp
  import json
  import uuid

  async def listen_for_completion(prompt_id: str, timeout: float = 300.0) -> dict:
      """Connect to WebSocket and listen for job completion.

      Returns:
          Final outputs from the job
      """
      ws_url = BASE_URL.replace("https://", "wss://")
      client_id = str(uuid.uuid4())
      ws_url = f"{ws_url}/ws?clientId={client_id}&token={API_KEY}"

      outputs = {}

      async with aiohttp.ClientSession() as session:
          async with session.ws_connect(ws_url) as ws:
              async def receive_messages():
                  async for msg in ws:
                      if msg.type == aiohttp.WSMsgType.TEXT:
                          data = json.loads(msg.data)
                          msg_type = data.get("type")
                          msg_data = data.get("data", {})

                          # Filter to our job
                          if msg_data.get("prompt_id") != prompt_id:
                              continue

                          if msg_type == "executing":
                              node = msg_data.get("node")
                              if node:
                                  print(f"Executing node: {node}")

                          elif msg_type == "progress":
                              value = msg_data.get("value", 0)
                              max_val = msg_data.get("max", 100)
                              print(f"Progress: {value}/{max_val}")

                          elif msg_type == "executed":
                              node_id = msg_data.get("node")
                              output = msg_data.get("output", {})
                              if output:
                                  outputs[node_id] = output

                          elif msg_type == "execution_success":
                              print("Job completed successfully!")
                              return outputs

                          elif msg_type == "execution_error":
                              error_msg = msg_data.get("exception_message", "Unknown error")
                              raise RuntimeError(f"Execution error: {error_msg}")

                      elif msg.type == aiohttp.WSMsgType.ERROR:
                          raise RuntimeError(f"WebSocket error: {ws.exception()}")

              try:
                  return await asyncio.wait_for(receive_messages(), timeout=timeout)
              except asyncio.TimeoutError:
                  raise TimeoutError(f"Job did not complete within {timeout}s")

  # Wait for completion and collect outputs
  outputs = await listen_for_completion(prompt_id)
  ```
</CodeGroup>

<Note>
  See [WebSocket Reference](/development/cloud/api-reference#websocket-for-real-time-progress) for detailed message types and handling binary preview images.
</Note>

### Step 3: Download Outputs

Once the job completes, download the generated files. The `outputs` object returned from WebSocket (or available via the history endpoint) contains output data organized by node ID. Each node's output may contain `images`, `video`, or `audio` arrays with file metadata.

**Example outputs structure:**

```json theme={null}
{
  "9": {
    "images": [
      {
        "filename": "ComfyUI_00001_.png",
        "subfolder": "",
        "type": "output"
      }
    ]
  }
}
```

The node ID (`"9"` in this example) corresponds to the SaveImage or other output nodes in your workflow. You can find these IDs by opening your workflow JSON file and looking for nodes with `class_type` like `SaveImage`, `VHS_VideoCombine`, etc.

<CodeGroup>
  ```bash curl theme={null}
  # Download a single output file (follow 302 redirect with -L)
  curl -L "$BASE_URL/api/view?filename=output.png&subfolder=&type=output" \
    -H "X-API-Key: $COMFY_CLOUD_API_KEY" \
    -o output.png
  ```

  ```typescript TypeScript theme={null}
  async function downloadOutput(
    filename: string,
    subfolder: string = "",
    outputType: string = "output"
  ): Promise<ArrayBuffer> {
    const params = new URLSearchParams({ filename, subfolder, type: outputType });
    // Get the redirect URL
    const response = await fetch(`${BASE_URL}/api/view?${params}`, {
      headers: { "X-API-Key": API_KEY },
      redirect: "manual",
    });
    if (response.status !== 302) throw new Error(`HTTP ${response.status}`);
    const signedUrl = response.headers.get("location")!;

    // Fetch from signed URL
    const fileResponse = await fetch(signedUrl);
    if (!fileResponse.ok) throw new Error(`HTTP ${fileResponse.status}`);
    return fileResponse.arrayBuffer();
  }

  async function saveOutputs(
    outputs: Record<string, any>,
    outputDir: string = "."
  ): Promise<void> {
    for (const nodeOutputs of Object.values(outputs)) {
      for (const key of ["images", "video", "audio"]) {
        for (const fileInfo of (nodeOutputs as any)[key] ?? []) {
          const data = await downloadOutput(
            fileInfo.filename,
            fileInfo.subfolder ?? "",
            fileInfo.type ?? "output"
          );
          const path = `${outputDir}/${fileInfo.filename}`;
          await writeFile(path, Buffer.from(data));
          console.log(`Saved: ${path}`);
        }
      }
    }
  }

  // Download all outputs
  await saveOutputs(outputs, "./my_outputs");
  ```

  ```python Python theme={null}
  def download_output(filename: str, subfolder: str = "", output_type: str = "output") -> bytes:
      """Download an output file.

      Args:
          filename: Name of the file
          subfolder: Subfolder path (usually empty)
          output_type: "output" for final outputs, "temp" for previews

      Returns:
          File bytes
      """
      params = {
          "filename": filename,
          "subfolder": subfolder,
          "type": output_type
      }

      response = requests.get(
          f"{BASE_URL}/api/view",
          headers=get_headers(),
          params=params
      )
      response.raise_for_status()
      return response.content

  def save_outputs(outputs: dict, output_dir: str = "."):
      """Save all outputs from a job to disk.

      Args:
          outputs: Outputs dict from job (node_id -> output_data)
          output_dir: Directory to save files to
      """
      import os
      os.makedirs(output_dir, exist_ok=True)

      for node_id, node_outputs in outputs.items():
          for key in ("images", "video", "audio"):
              for file_info in node_outputs.get(key, []):
                  filename = file_info["filename"]
                  subfolder = file_info.get("subfolder", "")
                  output_type = file_info.get("type", "output")

                  data = download_output(filename, subfolder, output_type)

                  output_path = os.path.join(output_dir, filename)
                  with open(output_path, "wb") as f:
                      f.write(data)
                  print(f"Saved: {output_path}")

  # Download all outputs
  save_outputs(outputs, "./my_outputs")
  ```
</CodeGroup>

<Info>
  The `/api/view` endpoint returns a 302 redirect to a temporary signed URL. Your HTTP client must follow redirects to download the file.
</Info>

### Complete Example

Here's a full end-to-end example combining all three steps:

<CodeGroup>
  ```typescript TypeScript theme={null}
  import { readFile, writeFile } from "fs/promises";

  const BASE_URL = "https://cloud.comfy.org";
  const API_KEY = process.env.COMFY_CLOUD_API_KEY!;

  async function main() {
    // 1. Load and modify workflow
    const workflow = JSON.parse(await readFile("workflow_api.json", "utf-8"));
    workflow["3"].inputs.seed = 42;
    workflow["6"].inputs.text = "a beautiful sunset";

    // 2. Submit workflow
    const response = await fetch(`${BASE_URL}/api/prompt`, {
      method: "POST",
      headers: { "X-API-Key": API_KEY, "Content-Type": "application/json" },
      body: JSON.stringify({ prompt: workflow }),
    });
    const { prompt_id } = await response.json();
    console.log(`Job submitted: ${prompt_id}`);

    // 3. Poll for completion
    while (true) {
      const statusRes = await fetch(`${BASE_URL}/api/job/${prompt_id}/status`, {
        headers: { "X-API-Key": API_KEY },
      });
      const { status } = await statusRes.json();

      if (status === "completed") break;
      if (["failed", "cancelled"].includes(status)) {
        throw new Error(`Job ${status}`);
      }
      await new Promise((resolve) => setTimeout(resolve, 2000));
    }

    // 4. Get outputs via job detail endpoint
    const jobRes = await fetch(`${BASE_URL}/api/jobs/${prompt_id}`, {
      headers: { "X-API-Key": API_KEY },
    });
    const job = await jobRes.json();
    const outputs = job.outputs;

    // 5. Download output files
    for (const nodeOutputs of Object.values(outputs)) {
      for (const fileInfo of (nodeOutputs as any).images ?? []) {
        const params = new URLSearchParams({
          filename: fileInfo.filename,
          subfolder: fileInfo.subfolder ?? "",
          type: "output",
        });
        const viewRes = await fetch(`${BASE_URL}/api/view?${params}`, {
          headers: { "X-API-Key": API_KEY },
          redirect: "manual",
        });
        const signedUrl = viewRes.headers.get("location")!;
        const fileRes = await fetch(signedUrl);
        await writeFile(`./${fileInfo.filename}`, Buffer.from(await fileRes.arrayBuffer()));
        console.log(`Downloaded: ${fileInfo.filename}`);
      }
    }
  }

  main();
  ```

  ```python Python theme={null}
  import os
  import requests
  import json
  import time

  BASE_URL = "https://cloud.comfy.org"
  API_KEY = os.environ["COMFY_CLOUD_API_KEY"]

  def main():
      # 1. Load and modify workflow
      with open("workflow_api.json") as f:
          workflow = json.load(f)

      workflow["3"]["inputs"]["seed"] = 42
      workflow["6"]["inputs"]["text"] = "a beautiful sunset"

      # 2. Submit workflow
      response = requests.post(
          f"{BASE_URL}/api/prompt",
          headers={"X-API-Key": API_KEY, "Content-Type": "application/json"},
          json={"prompt": workflow}
      )
      prompt_id = response.json()["prompt_id"]
      print(f"Job submitted: {prompt_id}")

      # 3. Poll for completion
      while True:
          status_res = requests.get(
              f"{BASE_URL}/api/job/{prompt_id}/status",
              headers={"X-API-Key": API_KEY}
          )
          status = status_res.json()["status"]

          if status == "completed":
              break
          if status in ("failed", "cancelled"):
              raise RuntimeError(f"Job {status}")
          time.sleep(2)

      # 4. Get outputs via job detail endpoint
      job_res = requests.get(
          f"{BASE_URL}/api/jobs/{prompt_id}",
          headers={"X-API-Key": API_KEY}
      )
      job = job_res.json()
      outputs = job["outputs"]

      # 5. Download output files
      for node_outputs in outputs.values():
          for file_info in node_outputs.get("images", []):
              params = {
                  "filename": file_info["filename"],
                  "subfolder": file_info.get("subfolder", ""),
                  "type": "output"
              }
              view_res = requests.get(
                  f"{BASE_URL}/api/view",
                  headers={"X-API-Key": API_KEY},
                  params=params
              )
              with open(file_info["filename"], "wb") as f:
                  f.write(view_res.content)
              print(f"Downloaded: {file_info['filename']}")

  if __name__ == "__main__":
      main()
  ```
</CodeGroup>

## Available Endpoints

| Category                                                                       | Description                            |
| ------------------------------------------------------------------------------ | -------------------------------------- |
| [Workflows](/development/cloud/api-reference#running-workflows)                | Submit workflows, check status         |
| [Jobs](/development/cloud/api-reference#checking-job-status)                   | Monitor job status and queue           |
| [Inputs](/development/cloud/api-reference#uploading-inputs)                    | Upload images, masks, and other inputs |
| [Outputs](/development/cloud/api-reference#downloading-outputs)                | Download generated content             |
| [WebSocket](/development/cloud/api-reference#websocket-for-real-time-progress) | Real-time progress updates             |
| [Object Info](/development/cloud/api-reference#object-info)                    | Available nodes and their definitions  |

## Next Steps

The quick start above covers the basics of submitting workflows and retrieving results. For more advanced use cases, refer to the [Cloud API Reference](/development/cloud/api-reference):

* **[Uploading Input Files](/development/cloud/api-reference#uploading-inputs)** - Upload images, masks, or other user-provided content for workflows that require external inputs
* **[Modifying Workflow Inputs](/development/cloud/api-reference#modify-workflow-inputs)** - Dynamically change workflow parameters like prompts, seeds, or node settings before submission
* **[Using Partner Nodes](/development/cloud/api-reference#using-partner-nodes)** - Call external AI services (Flux Pro, Ideogram, etc.) that require additional API key configuration
* **[Queue Management](/development/cloud/api-reference#queue-management)** - Monitor queue status, cancel jobs, or interrupt running executions
* **[Error Handling](/development/cloud/api-reference#error-handling)** - Handle HTTP errors, execution failures, and understand exception types

Additional resources:

* [OpenAPI Specification](/development/cloud/openapi) - Machine-readable API spec for code generation


# API Examples
Source: https://docs.comfy.org/development/comfyui-server/api-examples

Three common patterns for calling the ComfyUI Server API

This page demonstrates three ways to interact with the ComfyUI Server API, from a simple HTTP submission to a full WebSocket integration with real-time image output.

All examples use the [default SD1.5 workflow](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples) for illustration. Before using the API, you need to export your workflow in [API format](/development/api-development/workflow-api-format).

<Note>
  These examples use Python with the standard library and the `websocket-client` package (`pip install websocket-client`). The underlying API protocol is the same regardless of language — see the [Cloud API Reference](/development/cloud/api-reference) for TypeScript and curl equivalents.
</Note>

***

## Method 1: Submit and Forget (HTTP only)

Source: [`basic_api_example.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples/basic_api_example.py)

The simplest approach: submit a workflow and don't wait for results. Useful for fire-and-forget jobs where you check outputs later.

```python theme={null}
"""basic_api_example.py — Submit a workflow via HTTP only."""

import json
from urllib import request

SERVER_ADDRESS = "127.0.0.1:8188"


def queue_prompt(prompt):
    p = {"prompt": prompt}
    data = json.dumps(p).encode("utf-8")
    req = request.Request(
        f"http://{SERVER_ADDRESS}/prompt", data=data
    )
    request.urlopen(req)


if __name__ == "__main__":
    # Load a workflow exported in API format
    prompt_text = """{
        "3": {
            "class_type": "KSampler",
            "inputs": {
                "cfg": 8, "denoise": 1,
                "latent_image": ["5", 0],
                "model": ["4", 0],
                "negative": ["7", 0],
                "positive": ["6", 0],
                "sampler_name": "euler",
                "scheduler": "normal",
                "seed": 8566257, "steps": 20
            }
        },
        "4": {
            "class_type": "CheckpointLoaderSimple",
            "inputs": {"ckpt_name": "v1-5-pruned-emaonly.safetensors"}
        },
        "5": {
            "class_type": "EmptyLatentImage",
            "inputs": {"batch_size": 1, "height": 512, "width": 512}
        },
        "6": {
            "class_type": "CLIPTextEncode",
            "inputs": {"clip": ["4", 1], "text": "masterpiece best quality man"}
        },
        "7": {
            "class_type": "CLIPTextEncode",
            "inputs": {"clip": ["4", 1], "text": "bad hands"}
        },
        "8": {
            "class_type": "VAEDecode",
            "inputs": {"samples": ["3", 0], "vae": ["4", 2]}
        },
        "9": {
            "class_type": "SaveImage",
            "inputs": {"filename_prefix": "ComfyUI", "images": ["8", 0]}
        }
    }"""

    prompt = json.loads(prompt_text)
    # Modify inputs before submitting
    prompt["3"]["inputs"]["seed"] = 5
    prompt["6"]["inputs"]["text"] = "masterpiece best quality man"

    queue_prompt(prompt)
    print("Prompt submitted successfully.")
```

<Info>
  This method uses the `SaveImage` node, which saves images to disk on the server. To retrieve them, you'd need to follow up with a call to `GET /view?filename=...`.
</Info>

***

## Method 2: WebSocket + History (Monitor Completion)

Source: [`websockets_api_example.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples/websockets_api_example.py)

Use WebSocket to wait for execution to finish, then retrieve outputs via the `/history` endpoint. This is the recommended pattern for most use cases.

```python theme={null}
"""websockets_api_example.py — Monitor execution via WebSocket, download via /history."""

import websocket  # pip install websocket-client
import uuid
import json
import urllib.request
import urllib.parse

SERVER_ADDRESS = "127.0.0.1:8188"
client_id = str(uuid.uuid4())


def queue_prompt(prompt, prompt_id):
    p = {"prompt": prompt, "client_id": client_id, "prompt_id": prompt_id}
    data = json.dumps(p).encode("utf-8")
    req = urllib.request.Request(
        f"http://{SERVER_ADDRESS}/prompt", data=data
    )
    urllib.request.urlopen(req)


def get_image(filename, subfolder, folder_type):
    params = urllib.parse.urlencode({
        "filename": filename,
        "subfolder": subfolder,
        "type": folder_type,
    })
    with urllib.request.urlopen(
        f"http://{SERVER_ADDRESS}/view?{params}"
    ) as response:
        return response.read()


def get_history(prompt_id):
    with urllib.request.urlopen(
        f"http://{SERVER_ADDRESS}/history/{prompt_id}"
    ) as response:
        return json.loads(response.read())


def get_images(ws, prompt):
    prompt_id = str(uuid.uuid4())
    queue_prompt(prompt, prompt_id)

    while True:
        out = ws.recv()
        if isinstance(out, str):
            message = json.loads(out)
            if message["type"] == "executing":
                data = message["data"]
                if data["node"] is None and data["prompt_id"] == prompt_id:
                    break  # Execution done
        # Binary frames are preview images — skip them here
        continue

    history = get_history(prompt_id)[prompt_id]
    output_images = {}
    for node_id in history["outputs"]:
        node_output = history["outputs"][node_id]
        images_output = []
        if "images" in node_output:
            for image in node_output["images"]:
                image_data = get_image(
                    image["filename"], image["subfolder"], image["type"]
                )
                images_output.append(image_data)
        output_images[node_id] = images_output
    return output_images


if __name__ == "__main__":
    prompt_text = """{
        "3": { ... }, "4": { ... }, "5": { ... },
        "6": { ... }, "7": { ... }, "8": { ... },
        "9": { "class_type": "SaveImage", "inputs": { ... } }
    }"""
    prompt = json.loads(prompt_text)
    prompt["3"]["inputs"]["seed"] = 5
    prompt["6"]["inputs"]["text"] = "masterpiece best quality man"

    ws = websocket.WebSocket()
    ws.connect(f"ws://{SERVER_ADDRESS}/ws?clientId={client_id}")
    images = get_images(ws, prompt)
    ws.close()

    print(f"Got {len(images)} output node(s) with images.")

    # Display the images (requires Pillow):
    # for node_id in images:
    #     for image_data in images[node_id]:
    #         from PIL import Image
    #         import io
    #         img = Image.open(io.BytesIO(image_data))
    #         img.show()
```

<Tip>
  The WebSocket binary frames contain in-progress preview images during generation. You can decode them for live previews (see the [Server Messages](/development/comfyui-server/comms_messages) page for the binary format).
</Tip>

***

## Method 3: WebSocket with SaveImageWebsocket (Real-time Images)

Source: [`websockets_api_example_ws_images.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples/websockets_api_example_ws_images.py)

For scenarios where you don't want images saved to disk, use the `SaveImageWebsocket` node. Images are delivered directly via WebSocket binary frames.

```python theme={null}
"""websockets_api_example_ws_images.py — Receive images directly via WebSocket."""

import websocket  # pip install websocket-client
import uuid
import json
import urllib.request
import urllib.parse

SERVER_ADDRESS = "127.0.0.1:8188"
client_id = str(uuid.uuid4())


def queue_prompt(prompt):
    p = {"prompt": prompt, "client_id": client_id}
    data = json.dumps(p).encode("utf-8")
    req = urllib.request.Request(
        f"http://{SERVER_ADDRESS}/prompt", data=data
    )
    return json.loads(urllib.request.urlopen(req).read())


def get_images(ws, prompt):
    prompt_id = queue_prompt(prompt)["prompt_id"]
    output_images = {}
    current_node = ""

    while True:
        out = ws.recv()
        if isinstance(out, str):
            message = json.loads(out)
            if message["type"] == "executing":
                data = message["data"]
                if data["prompt_id"] == prompt_id:
                    if data["node"] is None:
                        break  # Execution done
                    current_node = data["node"]
        else:
            # Binary frame — image data from SaveImageWebsocket
            if current_node == "save_image_websocket_node":
                images_output = output_images.get(current_node, [])
                # The first 8 bytes are type/meta, rest is image data
                images_output.append(out[8:])
                output_images[current_node] = images_output

    return output_images


if __name__ == "__main__":
    prompt_text = """{
        "3": { "class_type": "KSampler", "inputs": { ... } },
        ...
        "save_image_websocket_node": {
            "class_type": "SaveImageWebsocket",
            "inputs": {"images": ["8", 0]}
        }
    }"""
    prompt = json.loads(prompt_text)
    prompt["3"]["inputs"]["seed"] = 5

    ws = websocket.WebSocket()
    ws.connect(f"ws://{SERVER_ADDRESS}/ws?clientId={client_id}")
    images = get_images(ws, prompt)
    ws.close()

    print(f"Received {len(images)} image(s) via WebSocket.")

    # Display (requires Pillow):
    # for image_data in images.get("save_image_websocket_node", []):
    #     from PIL import Image
    #     import io
    #     img = Image.open(io.BytesIO(image_data))
    #     img.show()
```

<Info>
  The workflow must use a node with `class_type: "SaveImageWebsocket"` (a built-in node) instead of the regular `SaveImage` node.
</Info>

***

## Which Method Should I Use?

<CardGroup>
  <Card title="Method 1: HTTP Only" icon="paper-plane">
    **Fire and forget.** Use when you don't need immediate output, or when retrieving results later is acceptable.
  </Card>

  <Card title="Method 2: WebSocket + History" icon="chart-line" href="#method-2-websocket--history-monitor-completion">
    **Recommended.** Wait for completion, then download outputs. Best balance of simplicity and reliability.
  </Card>

  <Card title="Method 3: SaveImageWebsocket" icon="images" href="#method-3-websocket-with-saveimagewebsocket-real-time-images">
    **Real-time images.** Best for interactive apps where you want images delivered without disk writes.
  </Card>
</CardGroup>

For the full API reference (endpoints, payload formats, error handling), see the [Server Routes](/development/comfyui-server/comms_routes) and [Server Messages](/development/comfyui-server/comms_messages) pages.


# ComfyUI Account API Key Integration
Source: https://docs.comfy.org/development/comfyui-server/api-key-integration

This article explains how to use ComfyUI Account API Key to call paid Partner Nodes in headless mode

Starting from [PR #8041](https://github.com/Comfy-Org/ComfyUI/pull/8041), ComfyUI supports directly using built-in paid Partner Nodes through your ComfyUI Account API Key, without requiring a specific frontend interface (you can even run without a frontend).

This means you can create workflows that combine:

* local OS models
* tools from the custom node community
* popular paid models

Then run everything together by simply sending the prompt to the Comfy webserver API, letting it handle all the orchestration.

This is helpful for users who want to use Comfy as a backend service, via the command line, with their own frontend, etc.

## Prerequisites

Using your ComfyUI Account API Key to call paid Partner Nodes requires:

* A [ComfyUI Account API Key](/development/api-development/getting-an-api-key)
* Sufficient account credits

<Note>
  **Important:** This page describes the **ComfyUI Account API Key** used for accessing paid Partner Nodes in workflows. If you're looking to publish custom nodes to the registry instead, see [Publishing Nodes](/registry/publishing).
</Note>

To use your ComfyUI Account API Key to call paid Partner Nodes, you need to first register an account on [ComfyUI Platform](https://platform.comfy.org/login) and [create an API key](/development/api-development/getting-an-api-key)

You need to ensure your ComfyUI account has sufficient credits to test the corresponding features.

<Card title="Credits" icon="link" href="/interface/credits">
  Please refer to the Credits section to learn how to purchase credits for your account
</Card>

## Python Example

Here is an example of how to send a workflow containing Partner Nodes to the ComfyUI API using Python code:

```python theme={null}
"""Using Partner Nodes when running ComfyUI headless or with alternative frontend

You can execute a ComfyUI workflow that contains Partner Nodes by including an API key in the prompt.
The API key should be added to the `extra_data` field of the payload.
Below we show an example of how to do this.

See more:

- Partner Nodes overview: https://docs.comfy.org/tutorials/partner-nodes/overview
- To generate an API key, login here: https://platform.comfy.org/login
"""

import json
from urllib import request

SERVER_URL = "http://127.0.0.1:8188"

# We have a prompt/job (workflow in "API format") that contains Partner Nodes.
workflow_with_api_nodes = """{
  "11": {
    "inputs": {
      "prompt": "A dreamy, surreal half-body portrait of a young woman meditating. She has a short, straight bob haircut dyed in pastel pink, with soft bangs covering her forehead. Her eyes are gently closed, and her hands are raised in a calm, open-palmed meditative pose, fingers slightly curved, as if levitating or in deep concentration. She wears a colorful dress made of patchwork-like pastel tiles, featuring clouds, stars, and rainbows. Around her float translucent, iridescent soap bubbles reflecting the rainbow hues. The background is a fantastical sky filled with cotton-candy clouds and vivid rainbow waves, giving the entire scene a magical, dreamlike atmosphere. Emphasis on youthful serenity, whimsical ambiance, and vibrant soft lighting.",
      "prompt_upsampling": false,
      "seed": 589991183902375,
      "aspect_ratio": "1:1",
      "raw": false,
      "image_prompt_strength": 0.4000000000000001,
      "image_prompt": [
        "14",
        0
      ]
    },
    "class_type": "FluxProUltraImageNode",
    "_meta": {
      "title": "Flux 1.1 [pro] Ultra Image"
    }
  },
  "12": {
    "inputs": {
      "filename_prefix": "ComfyUI",
      "images": [
        "11",
        0
      ]
    },
    "class_type": "SaveImage",
    "_meta": {
      "title": "Save Image"
    }
  },
  "14": {
    "inputs": {
      "image": "example.png"
    },
    "class_type": "LoadImage",
    "_meta": {
      "title": "Load Image"
    }
  }
}"""


prompt = json.loads(workflow_with_api_nodes)
payload = {
    "prompt": prompt,
    # Add the `api_key_comfy_org` to the payload.
    # You can first get the key from the associated user if handling multiple clients.
    "extra_data": {
        "api_key_comfy_org": "comfyui-87d01e28d*******************************************************"  # replace with actual key
    },
}
data = json.dumps(payload).encode("utf-8")
req = request.Request(f"{SERVER_URL}/prompt", data=data)
request.urlopen(req)

```

## Related Documentation

* [Partner Nodes overview](https://docs.comfy.org/tutorials/partner-nodes/overview)
* [Account management](https://docs.comfy.org/interface/user)
* [Credits](https://docs.comfy.org/interface/credits)


# Messages
Source: https://docs.comfy.org/development/comfyui-server/comms_messages



## Messages

During execution (or when the state of the queue changes), the `PromptExecutor` sends messages back to the client
through the `send_sync` method of `PromptServer`.

These messages are received by a socket event listener defined in `api.js` (at time of writing around line 90, or search for `this.socket.addEventListener`),
which creates a `CustomEvent` object for any known message type, and dispatches it to any registered listeners.

An extension can register to receive events (normally done in the `setup()` function) following the standard Javascript idiom:

```Javascript theme={null}
api.addEventListener(message_type, messageHandler);
```

If the `message_type` is not one of the built in ones, it will be added to the list of known message types automatically. The message `messageHandler`
will be called with a `CustomEvent` object, which extends the event raised by the socket to add a `.detail` property, which is a dictionary of
the data sent by the server. So usage is generally along the lines of:

```Javascript theme={null}
function messageHandler(event) {
    if (event.detail.node == aNodeIdThatIsInteresting) {
        // do something with event.detail.other_things
    }
}
```

### Built in message types

During execution (or when the state of the queue changes), the `PromptExecutor` sends the following messages back to the client
through the `send_sync` method of `PromptServer`. An extension can register as a listener for any of these.

| event                   | when                                                                       | data                                                                                                    |
| ----------------------- | -------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------- |
| `execution_start`       | When a prompt is about to run                                              | `prompt_id`                                                                                             |
| `execution_error`       | When an error occurs during execution                                      | `prompt_id`, plus additional information                                                                |
| `execution_interrupted` | When execution is stopped by a node raising `InterruptProcessingException` | `prompt_id`, `node_id`, `node_type` and `executed` (a list of executed nodes)                           |
| `execution_cached`      | At the start of execution                                                  | `prompt_id`, `nodes` (a list of nodes which are being skipped because their cached outputs can be used) |
| `execution_success`     | When all nodes from the prompt have been successfully executed             | `prompt_id`, `timestamp`                                                                                |
| `executing`             | When a new node is about to be executed                                    | `node` (node id or `None` to indicate completion), `prompt_id`                                          |
| `executed`              | When a node returns a ui element                                           | `node` (node id), `prompt_id`, `output`                                                                 |
| `progress`              | During execution of a node that implements the required hook               | `node` (node id), `prompt_id`, `value`, `max`                                                           |
| `status`                | When the state of the queue changes                                        | `exec_info`, a dictionary holding `queue_remaining`, the number of entries in the queue                 |

### Using executed

Despite the name, an `executed` message is not sent whenever a node completes execution (unlike `executing`), but only when the node
returns a ui update.

To do this, the main function needs to return a dictionary instead of a tuple:

```python theme={null}
# at the end of my main method
        return { "ui":a_new_dictionary, "result": the_tuple_of_output_values }
```

`a_new_dictionary` will then be sent as the value of `output` in an `executed` message.
The `result` key can be omitted if the node has no outputs (see, for instance, the code for `SaveImage` in `nodes.py`)

### Custom message types

As indicated above, on the client side, a custom message type can be added simply by registering as a listener for a unique message type name.

```Javascript theme={null}
api.addEventListener("my.custom.message", messageHandler);
```

On the server, the code is equally simple:

```Python theme={null}
from server import PromptServer
# then, in your main execution function (normally)
        PromptServer.instance.send_sync("my.custom.message", a_dictionary)
```

#### Getting node\_id

Most of the built-in messages include the current node id in the value of `node`. It's likely that you will want to do the same.

The node\_id is available on the server side through a hidden input, which is obtained with the `hidden` key in the `INPUT_TYPES` dictionary:

```Python theme={null}
    @classmethod    
    def INPUT_TYPES(s):
        return {"required" : { }, # whatever your required inputs are 
                "hidden": { "node_id": "UNIQUE_ID" } } # Add the hidden key

    def my_main_function(self, required_inputs, node_id):
        # do some things
        PromptServer.instance.send_sync("my.custom.message", {"node": node_id, "other_things": etc})
```


# Server Overview
Source: https://docs.comfy.org/development/comfyui-server/comms_overview

Run ComfyUI as a server and interact with it programmatically via REST and WebSocket APIs

ComfyUI runs as an HTTP server on your machine by default. You can call it programmatically to submit workflows, upload files, download outputs, and monitor progress — all without opening the browser.

## Starting the Server

When you launch ComfyUI, it automatically starts an HTTP server at `http://127.0.0.1:8188`.

To run ComfyUI as a headless server (no browser):

<CodeGroup>
  ```bash theme={null}
  # Run without opening the browser
  python main.py --headless
  ```

  ```bash theme={null}
  # Specify a custom port
  python main.py --port 8288
  ```

  ```bash theme={null}
  # Listen on all network interfaces (for remote access)
  python main.py --listen 0.0.0.0
  ```
</CodeGroup>

<Tip>
  For a full list of startup flags, run `python main.py --help` or see the [install guide](/installation/manual_install#basic-usage).
</Tip>

## Key Pages in This Section

<CardGroup>
  <Card title="API Routes" icon="route" href="/development/comfyui-server/comms_routes">
    Available HTTP endpoints for submitting workflows, uploading files, and querying status.
  </Card>

  <Card title="API Examples" icon="code" href="/development/comfyui-server/api-examples">
    Code examples for calling the API: HTTP-only, WebSocket + History, and SaveImageWebsocket.
  </Card>

  <Card title="Server Messages" icon="comments" href="/development/comfyui-server/comms_messages">
    WebSocket message types the server sends to the client during execution.
  </Card>

  <Card title="Execution Model Inversion" icon="code-branch" href="/development/comfyui-server/execution_model_inversion_guide">
    Advanced: invert execution for custom control flows.
  </Card>
</CardGroup>

## Using Partner Nodes

If your workflow contains paid Partner Nodes, you can include your API key in the payload. See the [Partner Node API Integration](/development/comfyui-server/api-key-integration) guide for details.

***

## How the Server Works

The Comfy server runs on top of the [aiohttp framework](https://docs.aiohttp.org/), which in turn uses [asyncio](https://pypi.org/project/asyncio/).

Messages from the server to the client are sent by socket messages through the `send_sync` method of the server, which is an instance of `PromptServer` (defined in `server.py`). They are processed by a socket event listener registered in `api.js`. See [messages](/development/comfyui-server/comms_messages).

Messages from the client to the server are sent by the `api.fetchApi()` method defined in `api.js`, and are handled by HTTP routes defined by the server. See [routes](/development/comfyui-server/comms_routes).

<Tip>
  The client submits the whole workflow (widget values and all) when you queue a request.
  The server does not receive any changes you make after you send a request to the queue.
  If you want to modify server behavior during execution, you'll need routes.
</Tip>


# Routes
Source: https://docs.comfy.org/development/comfyui-server/comms_routes



## Routes

The server defines a series of `get` and `post` methods
which can be found by searching for `@routes` in `server.py`. When you submit a workflow
in the web client, it is posted to `/prompt` which validates the prompt and adds it to an execution queue,
returning either a `prompt_id` and `number` (the position in the queue), or `error` and `node_errors` if validation fails.
The prompt queue is defined in `execution.py`, which also defines the `PromptExecutor` class.

### Built in routes

`server.py` defines the following routes:

#### Core API Routes

| path                           | get/post/ws | purpose                                                                   |
| ------------------------------ | ----------- | ------------------------------------------------------------------------- |
| `/`                            | get         | load the comfy webpage                                                    |
| `/ws`                          | websocket   | WebSocket endpoint for real-time communication with the server            |
| `/embeddings`                  | get         | retrieve a list of the names of embeddings available                      |
| `/extensions`                  | get         | retrieve a list of the extensions registering a `WEB_DIRECTORY`           |
| `/features`                    | get         | retrieve server features and capabilities                                 |
| `/models`                      | get         | retrieve a list of available model types                                  |
| `/models/{folder}`             | get         | retrieve models in a specific folder                                      |
| `/workflow_templates`          | get         | retrieve a map of custom node modules and associated template workflows   |
| `/upload/image`                | post        | upload an image                                                           |
| `/upload/mask`                 | post        | upload a mask                                                             |
| `/view`                        | get         | view an image. Lots of options, see `@routes.get("/view")` in `server.py` |
| `/view_metadata`/              | get         | retrieve metadata for a model                                             |
| `/system_stats`                | get         | retrieve information about the system (python version, devices, vram etc) |
| `/prompt`                      | get         | retrieve current queue status and execution information                   |
| `/prompt`                      | post        | submit a prompt to the queue                                              |
| `/object_info`                 | get         | retrieve details of all node types                                        |
| `/object_info/{node_class}`    | get         | retrieve details of one node type                                         |
| `/history`                     | get         | retrieve the queue history                                                |
| `/history/{prompt_id}`         | get         | retrieve the queue history for a specific prompt                          |
| `/history`                     | post        | clear history or delete history item                                      |
| `/queue`                       | get         | retrieve the current state of the execution queue                         |
| `/queue`                       | post        | manage queue operations (clear pending/running)                           |
| `/interrupt`                   | post        | stop the current workflow execution                                       |
| `/free`                        | post        | free memory by unloading specified models                                 |
| `/userdata`                    | get         | list user data files in a specified directory                             |
| `/v2/userdata`                 | get         | enhanced version that lists files and directories in structured format    |
| `/userdata/{file}`             | get         | retrieve a specific user data file                                        |
| `/userdata/{file}`             | post        | upload or update a user data file                                         |
| `/userdata/{file}`             | delete      | delete a specific user data file                                          |
| `/userdata/{file}/move/{dest}` | post        | move or rename a user data file                                           |
| `/users`                       | get         | get user information                                                      |
| `/users`                       | post        | create a new user (multi-user mode only)                                  |

### WebSocket Communication

The `/ws` endpoint provides real-time bidirectional communication between the client and server. This is used for:

* Receiving execution progress updates
* Getting node execution status in real-time
* Receiving error messages and debugging information
* Live updates when queue status changes

The WebSocket connection sends JSON messages with different types such as:

* `status` - Overall system status updates
* `execution_start` - When a prompt execution begins
* `execution_cached` - When cached results are used
* `executing` - Updates during node execution
* `progress` - Progress updates for long-running operations
* `executed` - When a node completes execution

### Custom routes

If you want to send a message from the client to the server during execution, you will need to add a custom route to the server.
For anything complicated, you will need to dive into the [aiohttp framework docs](https://docs.aiohttp.org/), but most cases can
be handled as follows:

```Python theme={null}
from server import PromptServer
from aiohttp import web
routes = PromptServer.instance.routes
@routes.post('/my_new_path')
async def my_function(request):
    the_data = await request.post()
    # the_data now holds a dictionary of the values sent
    MyClass.handle_my_message(the_data)
    return web.json_response({})
```

<Tip>Unless you know what you are doing, don't try to define `my_function` within a class.
The `@routes.post` decorator does a lot of work! Instead, define the function as above
and then call a classmethod.</Tip>

<Tip>You can also define a `@routes.get` if you aren't changing anything.</Tip>

The client can use this new route by sending a `FormData` object with code something like this,
which would result in `the_data`, in the above code, containing `message` and `node_id` keys:

```Javascript theme={null}
import { api } from "../../scripts/api.js";
function send_message(node_id, message) {
    const body = new FormData();
    body.append('message',message);
    body.append('node_id', node_id);
    api.fetchApi("/my_new_path", { method: "POST", body, });
}
```


# Execution Model Inversion Guide
Source: https://docs.comfy.org/development/comfyui-server/execution_model_inversion_guide



[PR #2666](https://github.com/Comfy-Org/ComfyUI/pull/2666) inverts the execution model from a back-to-front recursive model to a front-to-back topological sort. While most custom nodes should continue to "just work", this page is intended to serve as a guide for custom node creators to the things that *could* break.

## Breaking Changes

### Monkey Patching

Any code that monkey patched the execution model is likely to stop working. Note that the performance of execution with this PR exceeds that with the most popular monkey patches, so many of them will be unnecessary.

### Optional Input Validation

Prior to this PR, only nodes that were connected to outputs exclusively through a string of `"required"` inputs were actually validated. If you had custom nodes that were only ever connected to `"optional"` inputs, you previously wouldn't have been seeing that they failed validation.

<Tip>If your nodes' outputs could already be connected to `"required"` inputs, it is unlikely that anything in this section applies to you. It will primarily apply to custom node authors who use custom types and exclusively use `"optional"` inputs.</Tip>

Here are some of the things that could cause you to fail validation along with recommended solutions:

* Use of reserved [Additional Parameters](/custom-nodes/backend/datatypes#additional-parameters) like `min` and `max` on types that aren't comparable (e.g. dictionaries) in order to configure custom widgets.
  * Change the additional parameters used to non-reserved keys like `uiMin` and `uiMax`. *(Recommended Solution)*
    ```python theme={null}
    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "my_size": ("VEC2", {"uiMin": 0.0, "uiMax": 1.0}),
            }
        }
    ```

  * Define a custom [VALIDATE\_INPUTS](/custom-nodes/backend/server_overview#validate-inputs) function with this input so validation of it is skipped. *(Quick Solution)*
    ```python theme={null}
    @classmethod
    def VALIDATE_INPUTS(cls, my_size):
        return True
    ```

* Use of composite types (e.g. `CUSTOM_A,CUSTOM_B`)
  * (When used as output) Define and use a wrapper like `MakeSmartType` [seen here in the PR's unit tests](https://github.com/Comfy-Org/ComfyUI/pull/2666/files#diff-714643f1fdb6f8798c45f77ab10d212ca7f41dd71bbe55069f1f9f146a8f0cb9R2)
    ```python theme={null}
    class MyCustomNode:

        @classmethod
        def INPUT_TYPES(cls):
            return {
                "required": {
                    "input": (MakeSmartType("FOO,BAR"), {}),
                }
            }

        RETURN_TYPES = (MakeSmartType("FOO,BAR"),)

        # ...
    ```
  * (When used as input) Define a custom[VALIDATE\_INPUTS](/custom-nodes/backend/server_overview#validate-inputs) function that takes a `input_types` argument so type validation is skipped.
    ```python theme={null}
    @classmethod
    def VALIDATE_INPUTS(cls, input_types):
        return True
    ```
  * (Supports both, convenient) Define and use the `@VariantSupport` decorator [seen here in the PR's unit tests](https://github.com/Comfy-Org/ComfyUI/pull/2666/files#diff-714643f1fdb6f8798c45f77ab10d212ca7f41dd71bbe55069f1f9f146a8f0cb9R15)
    ```python theme={null}
    @VariantSupport
    class MyCustomNode:

        @classmethod
        def INPUT_TYPES(cls):
            return {
                "required": {
                    "input": ("FOO,BAR", {}),
                }
            }
        
        RETURN_TYPES = (MakeSmartType("FOO,BAR"),)

        # ...
    ```

* The use of lists (e.g. `[1, 2, 3]`) as constants in the graph definition (e.g. to represent a const `VEC3` input). This would have required a front-end extension before. Previously, lists of size exactly `2` would have failed anyway -- they would have been treated as broken links.
  * Wrap the lists in a dictionary like `{ "value": [1, 2, 3] }`

### Execution Order

Execution order has always changed depending on which nodes happen to have which IDs, but it may now change depending on which values are cached as well. In general, the execution order should be considered non-deterministic and subject to change (beyond what is enforced by the graph's structure).

Don't rely on the execution order.

*HIC SUNT DRACONES*

## New Functionality

### Validation Changes

A number of features were added to the `VALIDATE_INPUTS` function in order to lessen the impact of the [Optional Input Validation](#optional-input-validation) mentioned above.

* Default validation will now be skipped for inputs which are received by the `VALIDATE_INPUTS` function.
* The `VALIDATE_INPUTS` function can now take `**kwargs` which causes all inputs to be treated as validated by the node creator.
* The `VALIDATE_INPUTS` function can take an input named `input_types`. This input will be a dict mapping each input (connected via a link) to the type of the connected output. When this argument exists, type validation for the node's inputs is skipped.

You can read more at [VALIDATE\_INPUTS](/custom-nodes/backend/server_overview#validate-inputs).

### Lazy Evaluation

Inputs can be evaluated lazily (i.e. you can wait to see if they are needed before evaluating the attached node and all its ancestors). See [Lazy Evaluation](/custom-nodes/backend/lazy_evaluation) for more information.

### Node Expansion

At runtime, nodes can expand into a subgraph of nodes. This is what allows loops to be implemented (via tail-recursion). See [Node Expansion](/custom-nodes/backend/expansion) for more information.


# Overview
Source: https://docs.comfy.org/development/overview

Using ComfyUI as a Developer

ComfyUI is a modular GenAI inference engine that can be run as a server, accessed via API, extended with custom nodes, and managed from the command line. Choose your path below.

## Deploy ComfyUI as a Server

Run ComfyUI in your own environment and expose it as an API endpoint. Learn about the WebSocket message protocol, available routes, and execution modes.

<Card title="ComfyUI Server API" icon="server" href="/development/comfyui-server/comms_overview">
  Run ComfyUI as a server on your own machine. Start, configure, and call it via REST and WebSocket APIs.
</Card>

See also: [API Examples](/development/comfyui-server/api-examples) · [Partner Node API Integration](/development/comfyui-server/api-key-integration)

## Cloud API

Run workflows programmatically on Comfy Cloud without managing your own hardware. Use the REST API, browse the OpenAPI spec, and integrate Partner Nodes via API Key.

<Card title="Cloud API Overview" icon="cloud" href="/development/cloud/overview">
  Learn how to authenticate, submit jobs, check status, and download results from Comfy Cloud.
</Card>

See also: [API Reference](/development/cloud/api-reference) · [OpenAPI Specification](/development/cloud/openapi) · [Getting an API Key](/development/api-development/getting-an-api-key) · [APIs Overview](/development/api-development/overview)

## Agent Tools / MCP

Connect AI agents to ComfyUI via the Model Context Protocol (MCP). Use the hosted Cloud MCP or run the Partner MCP server locally for generation across 30+ providers.

<Card title="MCP Overview" icon="robot" href="/agent-tools">
  Compare Cloud MCP and Partner MCP, and find the right setup for your AI agent integration.
</Card>

See also: [Comfy Cloud MCP](/agent-tools/cloud) · [Comfy Partner MCP](/agent-tools/partner-mcp)

## Comfy CLI

Manage your ComfyUI installation, custom nodes, and workflows from the command line. Install, update, configure, and automate with ease.

<Card title="CLI Getting Started" icon="terminal" href="/comfy-cli/getting-started">
  Learn how to install, update, and manage ComfyUI from the terminal.
</Card>

See also: [CLI Reference](/comfy-cli/reference) · [Troubleshooting](/comfy-cli/troubleshooting)

## Develop Custom Nodes

Custom nodes let you extend ComfyUI with your own Python backends, JavaScript UI widgets, and integrations. This is one of the most powerful ways to contribute to the ecosystem.

<CardGroup>
  <Card title="Getting Started" icon="compass" href="/custom-nodes/overview">
    New to custom nodes? Learn the anatomy of a node, how to publish it, and best practices.

    <br />

    <br />

    Key pages: <a href="/custom-nodes/walkthrough">Walkthrough</a> · <a href="/custom-nodes/v3_migration">v3 Migration Guide</a>
  </Card>

  <Card title="Backend (Python)" icon="python" href="/custom-nodes/backend/server_overview">
    Build the server-side of your custom node. Covers data types, image & mask handling, lazy evaluation, tensors, and more.

    <br />

    <br />

    Key pages: <a href="/custom-nodes/backend/datatypes">Data Types</a> · <a href="/custom-nodes/backend/images_and_masks">Images & Masks</a> · <a href="/custom-nodes/backend/lazy_evaluation">Lazy Evaluation</a> · <a href="/custom-nodes/backend/expansion">Node Expansion</a>
  </Card>

  <Card title="Frontend (JavaScript)" icon="js" href="/custom-nodes/js/javascript_overview">
    Add custom UI widgets, sidebar tabs, keybindings, and dialogs to your nodes. Full control over the ComfyUI frontend.

    <br />

    <br />

    Key pages: <a href="/custom-nodes/js/javascript_hooks">Hooks</a> · <a href="/custom-nodes/js/javascript_sidebar_tabs">Sidebar Tabs</a> · <a href="/custom-nodes/js/javascript_commands_keybindings">Commands & Keybindings</a> · <a href="/custom-nodes/js/javascript_examples">Examples</a>
  </Card>
</CardGroup>

See also: <a href="/custom-nodes/i18n">Internationalization (i18n)</a>

## Registry

Publish and manage your custom nodes through the Comfy Registry. The Registry provides versioning, security scanning, and discovery for the community.

<Card title="Publishing Overview" icon="puzzle-piece" href="/registry/overview">
  Register as a publisher, publish your first node, claim existing ones, and set up CI/CD for automated releases.
</Card>

See also: [Publishing Tutorial](/registry/publishing) · [Standards](/registry/standards) · [CI/CD](/registry/cicd) · [Specifications](/registry/specifications)


# API Overview
Source: https://docs.comfy.org/registry/api-reference/overview



## Overview

The Custom Node Registry follows this structure:

```mermaid theme={null}
erDiagram
    PUBLISHER {
        string id PK
    }

    USER {
        string id PK
        string name
        string publisher_id FK
    }

    CUSTOM_NODE {
        string id PK
        string name
        string publisher_id FK
    }

    NODE_VERSION {
        string id PK
        string version
        string node_id FK
    }

    PUBLISHER ||--o{ USER: "has many"
    PUBLISHER ||--o{ CUSTOM_NODE: "has many"
    CUSTOM_NODE ||--o{ NODE_VERSION: "has many"
```

## Commonly Used APIs

* **List All Nodes** [API](/registry/api-reference/nodes/retrieves-a-list-of-nodes)
* **Install a Node** [API](/registry/api-reference/nodes/returns-a-node-version-to-be-installed)


# Custom Node CI/CD
Source: https://docs.comfy.org/registry/cicd



## Introduction

When making changes to custom nodes, it's not uncommon to break things in Comfy or other custom nodes. It is often unrealistic to test on every operating system and different configurations of Pytorch.

### Run Comfy Workflows using Github Actions

[Comfy-Action](https://github.com/Comfy-Org/comfy-action) allows you to run a Comfy workflow\.json file on Github Actions. It supports downloading models, custom nodes, and runs on Linux/Mac/Windows.

### Results

Output files are uploaded to the [CI/CD Dashboard](https://ci.comfy.org/) and can be viewed as a last step before committing new changes or publishing new versions of the custom node.

<img alt="ComfyCI" />


# Claim My Node
Source: https://docs.comfy.org/registry/claim-my-node



## Overview

The **Claim My Node** feature allows developers to claim ownership of custom nodes in the ComfyUI Registry. This system ensures that only the rightful authors can manage and update their published nodes, providing security and accountability within the community.

## What are Unclaimed Nodes?

As we migrate from ComfyUI Manager to the Comfy Registry with new standards, many custom nodes that were previously listed in the ComfyUI Manager legacy system now appear as "unclaimed" in the registry. These are nodes that:

* Were originally published in the ComfyUI Manager legacy system
* Have been migrated to the Comfy Registry to meet the latest standards
* Are waiting for their original authors to claim ownership

We provide an easy way for developers to claim these migrated nodes, ensuring a smooth transition from the legacy system to the new registry standard while maintaining proper ownership and control.

## Getting Started

To claim your nodes:

1. **Navigate to Your Unclaimed Node Page**: Visit your unclaimed node page, Click "Claim my node!" button.

2. **Create a Publisher (if you don't have one yet)**:
   * If you haven't created a publisher yet, you'll be prompted to create one. A publisher is required to claim nodes and manage them effectively.

3. **Select a Publisher**: Choose the publisher under which you want to claim the node. this step will redirect you to the claim page.

<img alt="Choose a Publisher - Light Mode" />

<img alt="Choose a Publisher - Dark Mode" />

To claim the node under the chosen publisher, follow these steps:

1. **Review Node Information:**
   * Check the node details, including the name, repository link, and publisher status as shown on the screen.

<img alt="Claim Node Process Stage 1 - Light Mode" />

<img alt="Claim Node Process Stage 1 - Dark Mode" />

2. **GitHub Authentication:**
   * Click the "Continue with GitHub" button to start the authentication process. Ensure you're logged in to the correct GitHub account with admin rights to the repository.

3. **Verify Admin Access:**
   * Once logged in, the system will verify if you have admin privileges for the specified GitHub repository. This step is crucial to ensure you have the necessary permissions.

4. **Claim the Node:**
   * If the verification is successful, Click "Claim" to claim the node. The publisher status will change, indicating ownership.

5. **Complete!:**
   * After successfully claiming the node, you can continue on [publishing](./publishing) and managing your node as the rightful owner.

## Frequently Asked Questions

<AccordionGroup>
  <Accordion title="Who can claim nodes?">
    Any GitHub user can submit a claim request, but claims are verified against the original node repository and author information.
  </Accordion>

  <Accordion title="How long does the claim process take?">
    Claims are automatically approved once GitHub admin permissions to the repository are verified. This happens instantly upon submitting your claim.
  </Accordion>

  <Accordion title="What happens after my claim is approved?">
    Once approved, you'll have full control over your node's management, including publish versions, updates meta, deprecation, and policy settings.
  </Accordion>

  <Accordion title="Can I claim nodes I didn't create?">
    No, claims are automatically validated against GitHub repository admin permissions. Only users with admin access to the original repository can successfully claim nodes.
  </Accordion>

  <Accordion title="What if my claim is denied?">
    Claims are automatically processed based on GitHub admin permissions. If you don't have admin access to the repository, the claim will be automatically denied. Contact the repository owner to request admin access if you believe you should have ownership rights.
  </Accordion>
</AccordionGroup>


# Overview
Source: https://docs.comfy.org/registry/overview



## Introduction

The Registry is a public collection of custom nodes that powers [ComfyUI-Manager](https://github.com/Comfy-Org/ComfyUI-Manager). Developers can publish, version, deprecate, and track metrics related to their custom nodes. ComfyUI users can discover, install, and rate custom nodes from the registry through ComfyUI-Manager.

## Why use the Registry?

The Comfy Registry helps the community by standardizing the development of custom nodes:

<Icon icon="timeline" />  **Node Versioning:** Developers frequently publish new versions of their custom nodes which often break workflows that rely on them. With registry nodes being [semantically versioned](https://semver.org/), users can now choose to safely upgrade, deprecate, or lock their node versions in place, knowing in advance how their actions will impact their workflows. The workflow JSON will store the version of the node used, so you can always reliably reproduce your workflows.

<Icon icon="shield" />  **Node Security:** The registry will serve as a backend for the [ComfyUI-manager](https://github.com/Comfy-Org/ComfyUI-Manager). All nodes will be scanned for malicious behaviour such as custom pip wheels, arbitrary system calls, etc. Nodes that pass these checks will have a verification flag (<Icon icon="check" />) beside their name on the UI-manager. For a list of security standards, see the [standards](/registry/standards).

<Icon icon="magnifying-glass" />  **Search:** Search across all nodes on the Registry to find existing nodes for your workflow\.x

## Publishing Nodes

Get started publishing your first node by following the [tutorial](/registry/publishing).

## Frequently Asked Questions

<AccordionGroup>
  <Accordion title="Do registry nodes have unique identifiers?">
    Yes, a custom node on the Registry has a globally unique name and this allows Comfy Workflow JSON files to uniquely identify any custom node without collisions.
  </Accordion>

  <Accordion title="Are there any restrictions on what I can publish?">
    Check the [standards](/registry/standards) for more information.
  </Accordion>

  <Accordion title="How do you ensure node stability?">
    Once a custom node version is published, it cannot be changed. This ensures that users can rely on the stability of the custom node over time.
  </Accordion>

  <Accordion title="How are nodes versioned?">
    Custom nodes are versioned using [semantic versioning](https://semver.org/). This allows users to understand the impact of upgrading to a new version.
  </Accordion>

  <Accordion title="How do I deprecate a node version?">
    You can deprecate a version in the Comfy Registry website by clicking **More Actions > Deprecate**. Users who installed this version will be shown the deprecation message and be encouraged to upgrade to a newer version.

    Deprecating versions is useful when an issue is discovered after publishing.
  </Accordion>
</AccordionGroup>


# Publishing Nodes
Source: https://docs.comfy.org/registry/publishing



## Set up a Registry Account

Follow the steps below to set up a registry account and publish your first node.

### Watch a Tutorial

<iframe title="YouTube video player" />

### Create a Publisher

A publisher is an identity that can publish custom nodes to the registry. Every custom node needs to include a publisher identifier in the pyproject.toml [file]().

Go to [Comfy Registry](https://registry.comfy.org), and create a publisher account. Your publisher id is globally unique, and cannot be changed later because it is used in the URL of your custom node.

Your publisher id is found after the `@` symbol on your profile page.

<img alt="Hero Dark" />

### Create a Registry Publishing API Key

<Note>
  **Important:** This API key is specifically for **publishing custom nodes to the Registry and ComfyUI-Manager**. If you're looking to use paid Partner Nodes in your workflows instead, see [Partner Nodes Overview](/tutorials/partner-nodes/overview).
</Note>

Go [here](https://registry.comfy.org/nodes) and click on the publisher you want to create an API key for. This key will be used to publish custom nodes to the Registry (which powers ComfyUI-Manager) via the CLI or GitHub Actions.

<img alt="Create key for Specific Publisher" />

Name the API key and save it somewhere safe. If you lose it, you'll have to create a new key.

<img alt="Create API Key" />

### Add Metadata

<Tip>Have you installed the comfy-cli? [Do that first](/comfy-cli/getting-started).</Tip>

```bash theme={null}
comfy node init
```

This command will generate the following metadata:

```toml theme={null}
# pyproject.toml
[project]
name = "" # Unique identifier for your node. Immutable after creation.
description = ""
version = "1.0.0" # Custom Node version. Must be semantically versioned.
license = { file = "LICENSE.txt" }
dependencies  = [] # Filled in from requirements.txt

[project.urls]
Repository = "https://github.com/..."

[tool.comfy]
PublisherId = "" # TODO (fill in Publisher ID from Comfy Registry Website).
DisplayName = "" # Display name for the Custom Node. Can be changed later.
Icon = "https://example.com/icon.png" # SVG, PNG, JPG or GIF (MAX. 800x400px)
```

Add this file to your repository. Check the [specifications](/registry/specifications) for more information on the pyproject.toml file.

### Exclude Files with `.comfyignore`

By default `comfy node publish` packages every file tracked by `git`. To keep development-only files (tests, design assets, large samples) out of the published archive, add a `.comfyignore` file to your repository root. The syntax matches [`.gitignore`](https://git-scm.com/docs/gitignore):

```gitignore theme={null}
# Development-only assets
docs/
tests/
*.psd
.vscode/
```

<Note>
  * `.comfyignore` layers on top of `.gitignore` — files not tracked by git are already excluded. Use `.comfyignore` to drop files you *keep* in git but don't want in the registry archive.
  * Directories listed in [`[tool.comfy].includes`](/registry/specifications) are force-included even if they match a `.comfyignore` pattern (useful when a built `dist/` folder is git-ignored but must ship).
  * Commit `.comfyignore` to your repo so local runs and CI produce the same archive.
</Note>

## Publish to the Registry

### Option 1: Comfy CLI

Run the command below to manually publish your node to the registry.

```bash theme={null}
comfy node publish
```

You'll be prompted for the API key.

```bash theme={null}
API Key for publisher '<publisher id>': ****************************************************

...Version 1.0.0 Published. 
See it here: https://registry.comfy.org/publisherId/your-node
```

<Warning>
  Keep in mind that the API key is hidden by default.
</Warning>

<Warning>
  When copy-pasting, your API key might have an additional \x16 at the back when using CTRL+V (for Windows), eg: \*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\*\x16.

  It is recommended to copy-paste your API key via right-clicking instead.
</Warning>

### Option 2: Github Actions

Automatically publish your node through github actions.

<Steps>
  <Step title="Set up a Github Secret">
    Go to Settings -> Secrets and Variables -> Actions -> Under Secrets Tab and Repository secrets -> New Repository Secret.

    Create a secret called `REGISTRY_ACCESS_TOKEN` and store your API key as the value.
  </Step>

  <Step title="Create a Github Action">
    Copy the code below and paste it here `/.github/workflows/publish_action.yml`

    ```bash theme={null}
    name: Publish to Comfy registry
    on:
      workflow_dispatch:
      push:
        branches:
          - main
        paths:
          - "pyproject.toml"

    jobs:
      publish-node:
        name: Publish Custom Node to registry
        runs-on: ubuntu-latest
        steps:
          - name: Check out code
            uses: actions/checkout@v4
          - name: Publish Custom Node
            uses: Comfy-Org/publish-node-action@main
            with:
              personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }} ## Add your own personal access token to your Github Repository secrets and reference it here.
    ```

    <Warning>If your working branch is named something besides `main`, such as `master`, add the name under the branches section.</Warning>
  </Step>

  <Step title="Test the Github Action">
    Push an update to your `pyproject.toml`'s version number. You should see your updated node on the registry.

    <Tip>The github action will automatically run every time you push an update to your `pyproject.toml` file</Tip>
  </Step>
</Steps>


# pyproject.toml
Source: https://docs.comfy.org/registry/specifications



# Specifications

The `pyproject.toml` file contains two main sections for ComfyUI custom nodes: `[project]` and `[tool.comfy]`. Below are the specifications for each section.

## \[project] Section

### name (required)

The node id uniquely identifies the custom node and will be used in URLs from the registry. Users can install the node by referencing this name:

```bash theme={null}
comfy node install <node-id>
```

**Requirements:**

* Must be less than 100 characters
* Can only contain alphanumeric characters, hyphens, underscores, and periods
* Cannot have consecutive special characters
* Cannot start with a number or special character
* Case-insensitive comparison

**Best Practices:**

* Use a short, descriptive name
* Don't include "ComfyUI" in the name
* Make it memorable and easy to type

**Examples:**

```toml theme={null}
name = "image-processor"      # ✅ Good: Simple and clear
name = "super-resolution"     # ✅ Good: Describes functionality
name = "ComfyUI-enhancer"    # ❌ Bad: Includes ComfyUI
name = "123-tool"            # ❌ Bad: Starts with number
```

See the official [python documentation](https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#name) for more details.

### version (required)

Uses [semantic versioning](https://semver.org/) with a three-digit version number X.Y.Z:

* X (**MAJOR**): Breaking changes
* Y (**MINOR**): New features (backwards compatible)
* Z (**PATCH**): Bug fixes

**Examples:**

```toml theme={null}
version = "1.0.0"    # Initial release
version = "1.1.0"    # Added new features
version = "1.1.1"    # Bug fix
version = "2.0.0"    # Breaking changes
```

### license (optional)

Specifies the license for your custom node. Can be specified in two ways:

1. **File Reference:**

```toml theme={null}
license = { file = "LICENSE" }     # ✅ Points to LICENSE file
license = { file = "LICENSE.txt" } # ✅ Points to LICENSE.txt
license = "LICENSE"                # ❌ Incorrect format
```

2. **License Name:**

```toml theme={null}
license = { text = "MIT License" }  # ✅ Correct format
license = { text = "Apache-2.0" }   # ✅ Correct format
license = "MIT LICENSE"             # ❌ Incorrect format
```

Common licenses: [MIT](https://opensource.org/license/mit), [GPL](https://www.gnu.org/licenses/gpl-3.0.en.html), [Apache](https://www.apache.org/licenses/LICENSE-2.0)

### description (recommended)

A brief description of what your custom node does.

```toml theme={null}
description = "A super resolution node for enhancing image quality"
```

### repository (required)

Links to related resources:

```toml theme={null}
[project.urls]
Repository = "https://github.com/username/repository"
```

### urls (recommended)

Links to related resources:

```toml theme={null}
[project.urls]
Documentation = "https://github.com/username/repository/wiki"
"Bug Tracker" = "https://github.com/username/repository/issues"
```

### requires-python (recommended)

Specifies the Python versions that your node supports:

```toml theme={null}
requires-python = ">=3.8"        # Python 3.8 or higher
requires-python = ">=3.8,<3.11"  # Python 3.8 up to (but not including) 3.11
```

### Frontend Version Compatibility (optional)

If your node has specific requirements for which ComfyUI frontend versions it supports, you can specify this using the `comfyui-frontend-package` dependency. This package is published on [PyPI](https://pypi.org/project/comfyui-frontend-package/).

For example, use this field when:

* Your custom node uses frontend APIs that were introduced in a specific version
* You've identified incompatibilities between your node and certain frontend versions
* Your node requires specific UI features only available in newer frontend versions

```toml theme={null}
[project]
dependencies = [
    "comfyui-frontend-package>=1.20.0"       # Requires frontend 1.20.0 or newer
    "comfyui-frontend-package<=1.21.6"       # Restricts to frontend versions up to 1.21.6
    "comfyui-frontend-package>=1.19,<1.22"   # Works with frontend 1.19 to 1.21.x
    "comfyui-frontend-package~=1.20.0"       # Compatible with 1.20.x but not 1.21.0
    "comfyui-frontend-package!=1.21.3"       # Works with any version except 1.21.3
]
```

### classifiers (recommended)

Use classifiers to specify operating system compatibility and GPU accelerators. This information is used to help users find the right node for their system.

```toml theme={null}
[project]
classifiers = [
    # For OS-independent nodes (works on all operating systems)
    "Operating System :: OS Independent",

    # OR for OS-specific nodes, specify the supported systems:
    "Operating System :: Microsoft :: Windows",  # Windows specific
    "Operating System :: POSIX :: Linux",  # Linux specific
    "Operating System :: MacOS",  # macOS specific
    
    # GPU Accelerator support
    "Environment :: GPU :: NVIDIA CUDA",    # NVIDIA CUDA support
    "Environment :: GPU :: AMD ROCm",       # AMD ROCm support
    "Environment :: GPU :: Intel Arc",      # Intel Arc support
    "Environment :: NPU :: Huawei Ascend",  # Huawei Ascend support
    "Environment :: GPU :: Apple Metal",    # Apple Metal support
]
```

## \[tool.comfy] Section

### PublisherId (required)

Your unique publisher identifier, typically matching your GitHub username.

**Examples:**

```toml theme={null}
PublisherId = "john-doe"        # ✅ Matches GitHub username
PublisherId = "image-wizard"    # ✅ Unique identifier
```

### DisplayName (optional)

A user-friendly name for your custom node.

```toml theme={null}
DisplayName = "Super Resolution Node"
```

### Icon (optional)

URL to your custom node's icon that will be displayed on the ComfyUI Registry and ComfyUI-Manager.

**Requirements:**

* File types: SVG, PNG, JPG, or GIF
* Maximum resolution: 400px × 400px
* Aspect ratio should be square

```toml theme={null}
Icon = "https://raw.githubusercontent.com/username/repo/main/icon.png"
```

### Banner (optional)

URL to a larger banner image that will be displayed on the ComfyUI Registry and ComfyUI-Manager.

**Requirements:**

* File types: SVG, PNG, JPG, or GIF
* Aspect ratio: 21:9

```toml theme={null}
Banner = "https://raw.githubusercontent.com/username/repo/main/banner.png"
```

### requires-comfyui (optional)

Specifies which version of ComfyUI your node is compatible with. This helps users ensure they have the correct version of ComfyUI installed.

**Supported operators:** `<`, `>`, `<=`, `>=`, `~=`, `<>`, `!=` and ranges

```toml theme={null}
requires-comfyui = ">=1.0.0"        # ComfyUI 1.0.0 or higher
requires-comfyui = ">=1.0.0,<2.0.0"  # ComfyUI 1.0.0 up to (but not including) 2.0.0
requires-comfyui = "~=1.0.0"         # Compatible release: version 1.0.0 or newer, but not version 2.0.0
requires-comfyui = "!=1.2.3"         # Any version except 1.2.3
requires-comfyui = ">0.1.3,<1.0.0"   # Greater than 0.1.3 and less than 1.0.0
```

### includes (optional)

Specifies whether to force include certain specific folders. For some situations, such as custom nodes in frontend projects, the final packaged output folder might be included in .gitignore. In such cases, we need to force include it for registry use.

```toml theme={null}
includes = ['dist']
```

<Tip>To exclude files from the published archive (the inverse of `includes`), see [`.comfyignore`](/registry/publishing#exclude-files-with-comfyignore) on the publishing page.</Tip>

## Complete Example

```toml theme={null}
[project]
name = "super-resolution-node"
version = "1.0.0"
description = "Enhance image quality using advanced super resolution techniques"
license = { file = "LICENSE" }
requires-python = ">=3.8"
dependencies = [
    "comfyui-frontend-package<=1.21.6"  # Frontend version compatibility
]
classifiers = [
    "Operating System :: OS Independent"  # Works on all operating systems
]
dynamic = ["dependencies"]

[tool.setuptools.dynamic]
dependencies = {file = ["requirements.txt"]}

[project.urls]
Repository = "https://github.com/username/super-resolution-node"
Documentation = "https://github.com/username/super-resolution-node/wiki"
"Bug Tracker" = "https://github.com/username/super-resolution-node/issues"

[tool.comfy]
PublisherId = "image-wizard"
DisplayName = "Super Resolution Node"
Icon = "https://raw.githubusercontent.com/username/super-resolution-node/main/icon.png"
Banner = "https://raw.githubusercontent.com/username/super-resolution-node/main/banner.png"
requires-comfyui = ">=1.0.0"  # ComfyUI version compatibility
```


# Standards
Source: https://docs.comfy.org/registry/standards

Security and other standards for publishing to the Registry

## Base Standards

### 1. Community Value

Custom nodes must provide valuable functionality to the ComfyUI community

Avoid:

* Excessive self-promotion
* Impersonation or misleading behavior
* Malicious behavior
* Self-promotion is permitted only within your designated settings menu section
* Top and side menus should contain only useful functionality

### 2. Node Compatibility

Do not interfere with other custom nodes' operations (installation, updates, removal)

* For dependencies on other custom nodes:
  * Display clear warnings when dependent functionality is used
  * Provide example workflows demonstrating required nodes

### 3. Legal Compliance

Must comply with all applicable laws and regulations

### 5. Quality Requirements

Nodes must be fully functional, well documented, and actively maintained.

### 6. Fork Guidelines

Forked nodes must:

* Have clearly distinct names from original
* Provide significant differences in functionality or code

Below are standards that must be met to publish custom nodes to the registry.

## Security Standards

Custom nodes should be secure. We will start working with custom nodes that violate these standards to be rewritten. If there is some major functionality that should be exposed by core, please request it in the [rfcs repo](https://github.com/comfy-org/rfcs).

### eval/exec Calls

#### Policy

The use of `eval` and `exec` functions is prohibited in custom nodes due to security concerns.

#### Reasoning

These functions can enable arbitrary code execution, creating potential Remote Code Execution (RCE) vulnerabilities when processing user inputs. Workflows containing nodes that pass user inputs into `eval` or `exec` could be exploited for various cyberattacks, including:

* Keylogging
* Ransomware
* Other malicious code execution

### subprocess for pip install

#### Policy

Runtime package installation through subprocess calls is not permitted.

#### Reasoning

* First item
  ComfyUI manager will ship with ComfyUI and lets the user install dependencies
* Centralized dependency management improves security and user experience
* Helps prevent potential supply chain attacks
* Eliminates need for multiple ComfyUI reloads

### Code Obfuscation

#### Policy

Code obfuscation is prohibited in custom nodes.

#### Reasoning

Obfuscated code:

* Impossible to review and likely to be malicious


# Node Definition JSON
Source: https://docs.comfy.org/specs/nodedef_json

JSON schema for a ComfyUI Node.

The node definition JSON is defined using [JSON Schema](https://json-schema.org/). Changes to this schema will be discussed in the [rfcs repo](https://github.com/comfy-org/rfcs).

## v2.0 (Latest)

```json Node Definition v2.0 theme={null}
{
  "$ref": "#/definitions/ComfyNodeDefV2",
  "definitions": {
    "ComfyNodeDefV2": {
      "type": "object",
      "properties": {
        "inputs": {
          "type": "object",
          "additionalProperties": {
            "anyOf": [
              {
                "type": "object",
                "properties": {
                  "default": {
                    "anyOf": [
                      {
                        "type": "number"
                      },
                      {
                        "type": "array",
                        "items": {
                          "type": "number"
                        }
                      }
                    ]
                  },
                  "defaultInput": {
                    "type": "boolean"
                  },
                  "forceInput": {
                    "type": "boolean"
                  },
                  "tooltip": {
                    "type": "string"
                  },
                  "hidden": {
                    "type": "boolean"
                  },
                  "advanced": {
                    "type": "boolean"
                  },
                  "rawLink": {
                    "type": "boolean"
                  },
                  "lazy": {
                    "type": "boolean"
                  },
                  "min": {
                    "type": "number"
                  },
                  "max": {
                    "type": "number"
                  },
                  "step": {
                    "type": "number"
                  },
                  "display": {
                    "type": "string",
                    "enum": [
                      "slider",
                      "number",
                      "knob"
                    ]
                  },
                  "control_after_generate": {
                    "type": "boolean"
                  },
                  "type": {
                    "type": "string",
                    "const": "INT"
                  },
                  "name": {
                    "type": "string"
                  },
                  "isOptional": {
                    "type": "boolean"
                  }
                },
                "required": [
                  "type",
                  "name"
                ],
                "additionalProperties": true
              },
              {
                "type": "object",
                "properties": {
                  "default": {
                    "anyOf": [
                      {
                        "type": "number"
                      },
                      {
                        "type": "array",
                        "items": {
                          "type": "number"
                        }
                      }
                    ]
                  },
                  "defaultInput": {
                    "type": "boolean"
                  },
                  "forceInput": {
                    "type": "boolean"
                  },
                  "tooltip": {
                    "type": "string"
                  },
                  "hidden": {
                    "type": "boolean"
                  },
                  "advanced": {
                    "type": "boolean"
                  },
                  "rawLink": {
                    "type": "boolean"
                  },
                  "lazy": {
                    "type": "boolean"
                  },
                  "min": {
                    "type": "number"
                  },
                  "max": {
                    "type": "number"
                  },
                  "step": {
                    "type": "number"
                  },
                  "display": {
                    "type": "string",
                    "enum": [
                      "slider",
                      "number",
                      "knob"
                    ]
                  },
                  "round": {
                    "anyOf": [
                      {
                        "type": "number"
                      },
                      {
                        "type": "boolean",
                        "const": false
                      }
                    ]
                  },
                  "type": {
                    "type": "string",
                    "const": "FLOAT"
                  },
                  "name": {
                    "type": "string"
                  },
                  "isOptional": {
                    "type": "boolean"
                  }
                },
                "required": [
                  "type",
                  "name"
                ],
                "additionalProperties": true
              },
              {
                "type": "object",
                "properties": {
                  "default": {
                    "type": "boolean"
                  },
                  "defaultInput": {
                    "type": "boolean"
                  },
                  "forceInput": {
                    "type": "boolean"
                  },
                  "tooltip": {
                    "type": "string"
                  },
                  "hidden": {
                    "type": "boolean"
                  },
                  "advanced": {
                    "type": "boolean"
                  },
                  "rawLink": {
                    "type": "boolean"
                  },
                  "lazy": {
                    "type": "boolean"
                  },
                  "label_on": {
                    "type": "string"
                  },
                  "label_off": {
                    "type": "string"
                  },
                  "type": {
                    "type": "string",
                    "const": "BOOLEAN"
                  },
                  "name": {
                    "type": "string"
                  },
                  "isOptional": {
                    "type": "boolean"
                  }
                },
                "required": [
                  "type",
                  "name"
                ],
                "additionalProperties": true
              },
              {
                "type": "object",
                "properties": {
                  "default": {
                    "type": "string"
                  },
                  "defaultInput": {
                    "type": "boolean"
                  },
                  "forceInput": {
                    "type": "boolean"
                  },
                  "tooltip": {
                    "type": "string"
                  },
                  "hidden": {
                    "type": "boolean"
                  },
                  "advanced": {
                    "type": "boolean"
                  },
                  "rawLink": {
                    "type": "boolean"
                  },
                  "lazy": {
                    "type": "boolean"
                  },
                  "multiline": {
                    "type": "boolean"
                  },
                  "dynamicPrompts": {
                    "type": "boolean"
                  },
                  "defaultVal": {
                    "type": "string"
                  },
                  "placeholder": {
                    "type": "string"
                  },
                  "type": {
                    "type": "string",
                    "const": "STRING"
                  },
                  "name": {
                    "type": "string"
                  },
                  "isOptional": {
                    "type": "boolean"
                  }
                },
                "required": [
                  "type",
                  "name"
                ],
                "additionalProperties": true
              },
              {
                "type": "object",
                "properties": {
                  "default": {},
                  "defaultInput": {
                    "type": "boolean"
                  },
                  "forceInput": {
                    "type": "boolean"
                  },
                  "tooltip": {
                    "type": "string"
                  },
                  "hidden": {
                    "type": "boolean"
                  },
                  "advanced": {
                    "type": "boolean"
                  },
                  "rawLink": {
                    "type": "boolean"
                  },
                  "lazy": {
                    "type": "boolean"
                  },
                  "control_after_generate": {
                    "type": "boolean"
                  },
                  "image_upload": {
                    "type": "boolean"
                  },
                  "image_folder": {
                    "type": "string",
                    "enum": [
                      "input",
                      "output",
                      "temp"
                    ]
                  },
                  "allow_batch": {
                    "type": "boolean"
                  },
                  "video_upload": {
                    "type": "boolean"
                  },
                  "remote": {
                    "type": "object",
                    "properties": {
                      "route": {
                        "anyOf": [
                          {
                            "type": "string",
                            "format": "uri"
                          },
                          {
                            "type": "string",
                            "pattern": "^\\/"
                          }
                        ]
                      },
                      "refresh": {
                        "anyOf": [
                          {
                            "type": "number",
                            "minimum": -9007199254740991,
                            "maximum": 9007199254740991
                          },
                          {
                            "type": "number",
                            "maximum": 9007199254740991,
                            "minimum": -9007199254740991
                          }
                        ]
                      },
                      "response_key": {
                        "type": "string"
                      },
                      "query_params": {
                        "type": "object",
                        "additionalProperties": {
                          "type": "string"
                        }
                      },
                      "refresh_button": {
                        "type": "boolean"
                      },
                      "control_after_refresh": {
                        "type": "string",
                        "enum": [
                          "first",
                          "last"
                        ]
                      },
                      "timeout": {
                        "type": "number",
                        "minimum": 0
                      },
                      "max_retries": {
                        "type": "number",
                        "minimum": 0
                      }
                    },
                    "required": [
                      "route"
                    ],
                    "additionalProperties": false
                  },
                  "options": {
                    "type": "array",
                    "items": {
                      "type": [
                        "string",
                        "number"
                      ]
                    }
                  },
                  "type": {
                    "type": "string",
                    "const": "COMBO"
                  },
                  "name": {
                    "type": "string"
                  },
                  "isOptional": {
                    "type": "boolean"
                  }
                },
                "required": [
                  "type",
                  "name"
                ],
                "additionalProperties": true
              },
              {
                "type": "object",
                "properties": {
                  "default": {},
                  "defaultInput": {
                    "type": "boolean"
                  },
                  "forceInput": {
                    "type": "boolean"
                  },
                  "tooltip": {
                    "type": "string"
                  },
                  "hidden": {
                    "type": "boolean"
                  },
                  "advanced": {
                    "type": "boolean"
                  },
                  "rawLink": {
                    "type": "boolean"
                  },
                  "lazy": {
                    "type": "boolean"
                  },
                  "type": {
                    "type": "string"
                  },
                  "name": {
                    "type": "string"
                  },
                  "isOptional": {
                    "type": "boolean"
                  }
                },
                "required": [
                  "type",
                  "name"
                ],
                "additionalProperties": true
              }
            ]
          }
        },
        "outputs": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "index": {
                "type": "number"
              },
              "name": {
                "type": "string"
              },
              "type": {
                "type": "string"
              },
              "is_list": {
                "type": "boolean"
              },
              "options": {
                "type": "array"
              },
              "tooltip": {
                "type": "string"
              }
            },
            "required": [
              "index",
              "name",
              "type",
              "is_list"
            ],
            "additionalProperties": false
          }
        },
        "hidden": {
          "type": "object",
          "additionalProperties": {}
        },
        "name": {
          "type": "string"
        },
        "display_name": {
          "type": "string"
        },
        "description": {
          "type": "string"
        },
        "category": {
          "type": "string"
        },
        "output_node": {
          "type": "boolean"
        },
        "python_module": {
          "type": "string"
        },
        "deprecated": {
          "type": "boolean"
        },
        "experimental": {
          "type": "boolean"
        }
      },
      "required": [
        "inputs",
        "outputs",
        "name",
        "display_name",
        "description",
        "category",
        "output_node",
        "python_module"
      ],
      "additionalProperties": false
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}
```


# Node Definition JSON 1.0
Source: https://docs.comfy.org/specs/nodedef_json_1_0

JSON schema for a ComfyUI Node.

## v1.0

```json Node Definition v1.0 theme={null}
{
  "$ref": "#/definitions/ComfyNodeDefV1",
  "definitions": {
    "ComfyNodeDefV1": {
      "type": "object",
      "properties": {
        "input": {
          "type": "object",
          "properties": {
            "required": {
              "type": "object",
              "additionalProperties": {
                "anyOf": [
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string",
                        "const": "INT"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {
                                "anyOf": [
                                  {
                                    "type": "number"
                                  },
                                  {
                                    "type": "array",
                                    "items": {
                                      "type": "number"
                                    }
                                  }
                                ]
                              },
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "min": {
                                "type": "number"
                              },
                              "max": {
                                "type": "number"
                              },
                              "step": {
                                "type": "number"
                              },
                              "display": {
                                "type": "string",
                                "enum": [
                                  "slider",
                                  "number",
                                  "knob"
                                ]
                              },
                              "control_after_generate": {
                                "type": "boolean"
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string",
                        "const": "FLOAT"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {
                                "anyOf": [
                                  {
                                    "type": "number"
                                  },
                                  {
                                    "type": "array",
                                    "items": {
                                      "type": "number"
                                    }
                                  }
                                ]
                              },
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "min": {
                                "type": "number"
                              },
                              "max": {
                                "type": "number"
                              },
                              "step": {
                                "type": "number"
                              },
                              "display": {
                                "type": "string",
                                "enum": [
                                  "slider",
                                  "number",
                                  "knob"
                                ]
                              },
                              "round": {
                                "anyOf": [
                                  {
                                    "type": "number"
                                  },
                                  {
                                    "type": "boolean",
                                    "const": false
                                  }
                                ]
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string",
                        "const": "BOOLEAN"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {
                                "type": "boolean"
                              },
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "label_on": {
                                "type": "string"
                              },
                              "label_off": {
                                "type": "string"
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string",
                        "const": "STRING"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {
                                "type": "string"
                              },
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "multiline": {
                                "type": "boolean"
                              },
                              "dynamicPrompts": {
                                "type": "boolean"
                              },
                              "defaultVal": {
                                "type": "string"
                              },
                              "placeholder": {
                                "type": "string"
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "array",
                        "items": {
                          "type": [
                            "string",
                            "number"
                          ]
                        }
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {},
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "control_after_generate": {
                                "type": "boolean"
                              },
                              "image_upload": {
                                "type": "boolean"
                              },
                              "image_folder": {
                                "type": "string",
                                "enum": [
                                  "input",
                                  "output",
                                  "temp"
                                ]
                              },
                              "allow_batch": {
                                "type": "boolean"
                              },
                              "video_upload": {
                                "type": "boolean"
                              },
                              "remote": {
                                "type": "object",
                                "properties": {
                                  "route": {
                                    "anyOf": [
                                      {
                                        "type": "string",
                                        "format": "uri"
                                      },
                                      {
                                        "type": "string",
                                        "pattern": "^\\/"
                                      }
                                    ]
                                  },
                                  "refresh": {
                                    "anyOf": [
                                      {
                                        "type": "number",
                                        "minimum": -9007199254740991,
                                        "maximum": 9007199254740991
                                      },
                                      {
                                        "type": "number",
                                        "maximum": 9007199254740991,
                                        "minimum": -9007199254740991
                                      }
                                    ]
                                  },
                                  "response_key": {
                                    "type": "string"
                                  },
                                  "query_params": {
                                    "type": "object",
                                    "additionalProperties": {
                                      "type": "string"
                                    }
                                  },
                                  "refresh_button": {
                                    "type": "boolean"
                                  },
                                  "control_after_refresh": {
                                    "type": "string",
                                    "enum": [
                                      "first",
                                      "last"
                                    ]
                                  },
                                  "timeout": {
                                    "type": "number",
                                    "minimum": 0
                                  },
                                  "max_retries": {
                                    "type": "number",
                                    "minimum": 0
                                  }
                                },
                                "required": [
                                  "route"
                                ],
                                "additionalProperties": false
                              },
                              "options": {
                                "type": "array",
                                "items": {
                                  "type": [
                                    "string",
                                    "number"
                                  ]
                                }
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string",
                        "const": "COMBO"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {},
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "control_after_generate": {
                                "type": "boolean"
                              },
                              "image_upload": {
                                "type": "boolean"
                              },
                              "image_folder": {
                                "type": "string",
                                "enum": [
                                  "input",
                                  "output",
                                  "temp"
                                ]
                              },
                              "allow_batch": {
                                "type": "boolean"
                              },
                              "video_upload": {
                                "type": "boolean"
                              },
                              "remote": {
                                "type": "object",
                                "properties": {
                                  "route": {
                                    "anyOf": [
                                      {
                                        "type": "string",
                                        "format": "uri"
                                      },
                                      {
                                        "type": "string",
                                        "pattern": "^\\/"
                                      }
                                    ]
                                  },
                                  "refresh": {
                                    "anyOf": [
                                      {
                                        "type": "number",
                                        "minimum": -9007199254740991,
                                        "maximum": 9007199254740991
                                      },
                                      {
                                        "type": "number",
                                        "maximum": 9007199254740991,
                                        "minimum": -9007199254740991
                                      }
                                    ]
                                  },
                                  "response_key": {
                                    "type": "string"
                                  },
                                  "query_params": {
                                    "type": "object",
                                    "additionalProperties": {
                                      "type": "string"
                                    }
                                  },
                                  "refresh_button": {
                                    "type": "boolean"
                                  },
                                  "control_after_refresh": {
                                    "type": "string",
                                    "enum": [
                                      "first",
                                      "last"
                                    ]
                                  },
                                  "timeout": {
                                    "type": "number",
                                    "minimum": 0
                                  },
                                  "max_retries": {
                                    "type": "number",
                                    "minimum": 0
                                  }
                                },
                                "required": [
                                  "route"
                                ],
                                "additionalProperties": false
                              },
                              "options": {
                                "type": "array",
                                "items": {
                                  "type": [
                                    "string",
                                    "number"
                                  ]
                                }
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {},
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  }
                ]
              }
            },
            "optional": {
              "type": "object",
              "additionalProperties": {
                "anyOf": [
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string",
                        "const": "INT"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {
                                "anyOf": [
                                  {
                                    "type": "number"
                                  },
                                  {
                                    "type": "array",
                                    "items": {
                                      "type": "number"
                                    }
                                  }
                                ]
                              },
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "min": {
                                "type": "number"
                              },
                              "max": {
                                "type": "number"
                              },
                              "step": {
                                "type": "number"
                              },
                              "display": {
                                "type": "string",
                                "enum": [
                                  "slider",
                                  "number",
                                  "knob"
                                ]
                              },
                              "control_after_generate": {
                                "type": "boolean"
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string",
                        "const": "FLOAT"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {
                                "anyOf": [
                                  {
                                    "type": "number"
                                  },
                                  {
                                    "type": "array",
                                    "items": {
                                      "type": "number"
                                    }
                                  }
                                ]
                              },
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "min": {
                                "type": "number"
                              },
                              "max": {
                                "type": "number"
                              },
                              "step": {
                                "type": "number"
                              },
                              "display": {
                                "type": "string",
                                "enum": [
                                  "slider",
                                  "number",
                                  "knob"
                                ]
                              },
                              "round": {
                                "anyOf": [
                                  {
                                    "type": "number"
                                  },
                                  {
                                    "type": "boolean",
                                    "const": false
                                  }
                                ]
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string",
                        "const": "BOOLEAN"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {
                                "type": "boolean"
                              },
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "label_on": {
                                "type": "string"
                              },
                              "label_off": {
                                "type": "string"
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string",
                        "const": "STRING"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {
                                "type": "string"
                              },
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "multiline": {
                                "type": "boolean"
                              },
                              "dynamicPrompts": {
                                "type": "boolean"
                              },
                              "defaultVal": {
                                "type": "string"
                              },
                              "placeholder": {
                                "type": "string"
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "array",
                        "items": {
                          "type": [
                            "string",
                            "number"
                          ]
                        }
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {},
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "control_after_generate": {
                                "type": "boolean"
                              },
                              "image_upload": {
                                "type": "boolean"
                              },
                              "image_folder": {
                                "type": "string",
                                "enum": [
                                  "input",
                                  "output",
                                  "temp"
                                ]
                              },
                              "allow_batch": {
                                "type": "boolean"
                              },
                              "video_upload": {
                                "type": "boolean"
                              },
                              "remote": {
                                "type": "object",
                                "properties": {
                                  "route": {
                                    "anyOf": [
                                      {
                                        "type": "string",
                                        "format": "uri"
                                      },
                                      {
                                        "type": "string",
                                        "pattern": "^\\/"
                                      }
                                    ]
                                  },
                                  "refresh": {
                                    "anyOf": [
                                      {
                                        "type": "number",
                                        "minimum": -9007199254740991,
                                        "maximum": 9007199254740991
                                      },
                                      {
                                        "type": "number",
                                        "maximum": 9007199254740991,
                                        "minimum": -9007199254740991
                                      }
                                    ]
                                  },
                                  "response_key": {
                                    "type": "string"
                                  },
                                  "query_params": {
                                    "type": "object",
                                    "additionalProperties": {
                                      "type": "string"
                                    }
                                  },
                                  "refresh_button": {
                                    "type": "boolean"
                                  },
                                  "control_after_refresh": {
                                    "type": "string",
                                    "enum": [
                                      "first",
                                      "last"
                                    ]
                                  },
                                  "timeout": {
                                    "type": "number",
                                    "minimum": 0
                                  },
                                  "max_retries": {
                                    "type": "number",
                                    "minimum": 0
                                  }
                                },
                                "required": [
                                  "route"
                                ],
                                "additionalProperties": false
                              },
                              "options": {
                                "type": "array",
                                "items": {
                                  "type": [
                                    "string",
                                    "number"
                                  ]
                                }
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string",
                        "const": "COMBO"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {},
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              },
                              "control_after_generate": {
                                "type": "boolean"
                              },
                              "image_upload": {
                                "type": "boolean"
                              },
                              "image_folder": {
                                "type": "string",
                                "enum": [
                                  "input",
                                  "output",
                                  "temp"
                                ]
                              },
                              "allow_batch": {
                                "type": "boolean"
                              },
                              "video_upload": {
                                "type": "boolean"
                              },
                              "remote": {
                                "type": "object",
                                "properties": {
                                  "route": {
                                    "anyOf": [
                                      {
                                        "type": "string",
                                        "format": "uri"
                                      },
                                      {
                                        "type": "string",
                                        "pattern": "^\\/"
                                      }
                                    ]
                                  },
                                  "refresh": {
                                    "anyOf": [
                                      {
                                        "type": "number",
                                        "minimum": -9007199254740991,
                                        "maximum": 9007199254740991
                                      },
                                      {
                                        "type": "number",
                                        "maximum": 9007199254740991,
                                        "minimum": -9007199254740991
                                      }
                                    ]
                                  },
                                  "response_key": {
                                    "type": "string"
                                  },
                                  "query_params": {
                                    "type": "object",
                                    "additionalProperties": {
                                      "type": "string"
                                    }
                                  },
                                  "refresh_button": {
                                    "type": "boolean"
                                  },
                                  "control_after_refresh": {
                                    "type": "string",
                                    "enum": [
                                      "first",
                                      "last"
                                    ]
                                  },
                                  "timeout": {
                                    "type": "number",
                                    "minimum": 0
                                  },
                                  "max_retries": {
                                    "type": "number",
                                    "minimum": 0
                                  }
                                },
                                "required": [
                                  "route"
                                ],
                                "additionalProperties": false
                              },
                              "options": {
                                "type": "array",
                                "items": {
                                  "type": [
                                    "string",
                                    "number"
                                  ]
                                }
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "string"
                      },
                      {
                        "anyOf": [
                          {
                            "not": {}
                          },
                          {
                            "type": "object",
                            "properties": {
                              "default": {},
                              "defaultInput": {
                                "type": "boolean"
                              },
                              "forceInput": {
                                "type": "boolean"
                              },
                              "tooltip": {
                                "type": "string"
                              },
                              "hidden": {
                                "type": "boolean"
                              },
                              "advanced": {
                                "type": "boolean"
                              },
                              "rawLink": {
                                "type": "boolean"
                              },
                              "lazy": {
                                "type": "boolean"
                              }
                            },
                            "additionalProperties": true
                          }
                        ]
                      }
                    ]
                  }
                ]
              }
            },
            "hidden": {
              "type": "object",
              "additionalProperties": {}
            }
          },
          "additionalProperties": false
        },
        "output": {
          "type": "array",
          "items": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "array",
                "items": {
                  "type": [
                    "string",
                    "number"
                  ]
                }
              }
            ]
          }
        },
        "output_is_list": {
          "type": "array",
          "items": {
            "type": "boolean"
          }
        },
        "output_name": {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "output_tooltips": {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "name": {
          "type": "string"
        },
        "display_name": {
          "type": "string"
        },
        "description": {
          "type": "string"
        },
        "category": {
          "type": "string"
        },
        "output_node": {
          "type": "boolean"
        },
        "python_module": {
          "type": "string"
        },
        "deprecated": {
          "type": "boolean"
        },
        "experimental": {
          "type": "boolean"
        }
      },
      "required": [
        "name",
        "display_name",
        "description",
        "category",
        "output_node",
        "python_module"
      ],
      "additionalProperties": false
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}
```


# Workflow JSON
Source: https://docs.comfy.org/specs/workflow_json

JSON schema for a ComfyUI workflow.

The workflow JSON is defined using [JSON Schema](https://json-schema.org/). Changes to this schema will be discussed in the [rfcs repo](https://github.com/comfy-org/rfcs).

## Version 1.0 (Latest)

```json ComfyUI Workflow v1.0 theme={null}
{
  "$ref": "#/definitions/ComfyWorkflow1_0",
  "definitions": {
    "ComfyWorkflow1_0": {
      "type": "object",
      "properties": {
        "version": {
          "type": "number",
          "const": 1
        },
        "config": {
          "anyOf": [
            {
              "anyOf": [
                {
                  "not": {}
                },
                {
                  "type": "object",
                  "properties": {
                    "links_ontop": {
                      "type": "boolean"
                    },
                    "align_to_grid": {
                      "type": "boolean"
                    }
                  },
                  "additionalProperties": true
                }
              ]
            },
            {
              "type": "null"
            }
          ]
        },
        "state": {
          "type": "object",
          "properties": {
            "lastGroupid": {
              "type": "number"
            },
            "lastNodeId": {
              "type": "number"
            },
            "lastLinkId": {
              "type": "number"
            },
            "lastRerouteId": {
              "type": "number"
            }
          },
          "additionalProperties": true
        },
        "groups": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "title": {
                "type": "string"
              },
              "bounding": {
                "type": "array",
                "minItems": 4,
                "maxItems": 4,
                "items": [
                  {
                    "type": "number"
                  },
                  {
                    "type": "number"
                  },
                  {
                    "type": "number"
                  },
                  {
                    "type": "number"
                  }
                ]
              },
              "color": {
                "type": "string"
              },
              "font_size": {
                "type": "number"
              },
              "locked": {
                "type": "boolean"
              }
            },
            "required": [
              "title",
              "bounding"
            ],
            "additionalProperties": true
          }
        },
        "nodes": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "id": {
                "anyOf": [
                  {
                    "type": "integer"
                  },
                  {
                    "type": "string"
                  }
                ]
              },
              "type": {
                "type": "string"
              },
              "pos": {
                "anyOf": [
                  {
                    "type": "object",
                    "properties": {
                      "0": {
                        "type": "number"
                      },
                      "1": {
                        "type": "number"
                      }
                    },
                    "required": [
                      "0",
                      "1"
                    ],
                    "additionalProperties": true
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "number"
                      },
                      {
                        "type": "number"
                      }
                    ]
                  }
                ]
              },
              "size": {
                "anyOf": [
                  {
                    "type": "object",
                    "properties": {
                      "0": {
                        "type": "number"
                      },
                      "1": {
                        "type": "number"
                      }
                    },
                    "required": [
                      "0",
                      "1"
                    ],
                    "additionalProperties": true
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "number"
                      },
                      {
                        "type": "number"
                      }
                    ]
                  }
                ]
              },
              "flags": {
                "type": "object",
                "properties": {
                  "collapsed": {
                    "type": "boolean"
                  },
                  "pinned": {
                    "type": "boolean"
                  },
                  "allow_interaction": {
                    "type": "boolean"
                  },
                  "horizontal": {
                    "type": "boolean"
                  },
                  "skip_repeated_outputs": {
                    "type": "boolean"
                  }
                },
                "additionalProperties": true
              },
              "order": {
                "type": "number"
              },
              "mode": {
                "type": "number"
              },
              "inputs": {
                "type": "array",
                "items": {
                  "type": "object",
                  "properties": {
                    "name": {
                      "type": "string"
                    },
                    "type": {
                      "anyOf": [
                        {
                          "type": "string"
                        },
                        {
                          "type": "array",
                          "items": {
                            "type": "string"
                          }
                        },
                        {
                          "type": "number"
                        }
                      ]
                    },
                    "link": {
                      "type": [
                        "number",
                        "null"
                      ]
                    },
                    "slot_index": {
                      "anyOf": [
                        {
                          "type": "integer"
                        },
                        {
                          "type": "string"
                        }
                      ]
                    }
                  },
                  "required": [
                    "name",
                    "type"
                  ],
                  "additionalProperties": true
                }
              },
              "outputs": {
                "type": "array",
                "items": {
                  "type": "object",
                  "properties": {
                    "name": {
                      "type": "string"
                    },
                    "type": {
                      "anyOf": [
                        {
                          "type": "string"
                        },
                        {
                          "type": "array",
                          "items": {
                            "type": "string"
                          }
                        },
                        {
                          "type": "number"
                        }
                      ]
                    },
                    "links": {
                      "anyOf": [
                        {
                          "type": "array",
                          "items": {
                            "type": "number"
                          }
                        },
                        {
                          "type": "null"
                        }
                      ]
                    },
                    "slot_index": {
                      "anyOf": [
                        {
                          "type": "integer"
                        },
                        {
                          "type": "string"
                        }
                      ]
                    }
                  },
                  "required": [
                    "name",
                    "type"
                  ],
                  "additionalProperties": true
                }
              },
              "properties": {
                "type": "object",
                "properties": {
                  "Node name for S&R": {
                    "type": "string"
                  }
                },
                "additionalProperties": true
              },
              "widgets_values": {
                "anyOf": [
                  {
                    "type": "array"
                  },
                  {
                    "type": "object",
                    "additionalProperties": {}
                  }
                ]
              },
              "color": {
                "type": "string"
              },
              "bgcolor": {
                "type": "string"
              }
            },
            "required": [
              "id",
              "type",
              "pos",
              "size",
              "flags",
              "order",
              "mode",
              "properties"
            ],
            "additionalProperties": true
          }
        },
        "links": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "id": {
                "type": "number"
              },
              "origin_id": {
                "anyOf": [
                  {
                    "type": "integer"
                  },
                  {
                    "type": "string"
                  }
                ]
              },
              "origin_slot": {
                "anyOf": [
                  {
                    "type": "integer"
                  },
                  {
                    "type": "string"
                  }
                ]
              },
              "target_id": {
                "anyOf": [
                  {
                    "type": "integer"
                  },
                  {
                    "type": "string"
                  }
                ]
              },
              "target_slot": {
                "anyOf": [
                  {
                    "type": "integer"
                  },
                  {
                    "type": "string"
                  }
                ]
              },
              "type": {
                "anyOf": [
                  {
                    "type": "string"
                  },
                  {
                    "type": "array",
                    "items": {
                      "type": "string"
                    }
                  },
                  {
                    "type": "number"
                  }
                ]
              },
              "parentId": {
                "type": "number"
              }
            },
            "required": [
              "id",
              "origin_id",
              "origin_slot",
              "target_id",
              "target_slot",
              "type"
            ],
            "additionalProperties": true
          }
        },
        "reroutes": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "id": {
                "type": "number"
              },
              "parentId": {
                "type": "number"
              },
              "pos": {
                "anyOf": [
                  {
                    "type": "object",
                    "properties": {
                      "0": {
                        "type": "number"
                      },
                      "1": {
                        "type": "number"
                      }
                    },
                    "required": [
                      "0",
                      "1"
                    ],
                    "additionalProperties": true
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "number"
                      },
                      {
                        "type": "number"
                      }
                    ]
                  }
                ]
              },
              "linkIds": {
                "anyOf": [
                  {
                    "type": "array",
                    "items": {
                      "type": "number"
                    }
                  },
                  {
                    "type": "null"
                  }
                ]
              }
            },
            "required": [
              "id",
              "pos"
            ],
            "additionalProperties": true
          }
        },
        "extra": {
          "anyOf": [
            {
              "anyOf": [
                {
                  "not": {}
                },
                {
                  "type": "object",
                  "properties": {
                    "ds": {
                      "type": "object",
                      "properties": {
                        "scale": {
                          "type": "number"
                        },
                        "offset": {
                          "anyOf": [
                            {
                              "type": "object",
                              "properties": {
                                "0": {
                                  "type": "number"
                                },
                                "1": {
                                  "type": "number"
                                }
                              },
                              "required": [
                                "0",
                                "1"
                              ],
                              "additionalProperties": true
                            },
                            {
                              "type": "array",
                              "minItems": 2,
                              "maxItems": 2,
                              "items": [
                                {
                                  "type": "number"
                                },
                                {
                                  "type": "number"
                                }
                              ]
                            }
                          ]
                        }
                      },
                      "required": [
                        "scale",
                        "offset"
                      ],
                      "additionalProperties": true
                    },
                    "info": {
                      "type": "object",
                      "properties": {
                        "name": {
                          "type": "string"
                        },
                        "author": {
                          "type": "string"
                        },
                        "description": {
                          "type": "string"
                        },
                        "version": {
                          "type": "string"
                        },
                        "created": {
                          "type": "string"
                        },
                        "modified": {
                          "type": "string"
                        },
                        "software": {
                          "type": "string"
                        }
                      },
                      "required": [
                        "name",
                        "author",
                        "description",
                        "version",
                        "created",
                        "modified",
                        "software"
                      ],
                      "additionalProperties": true
                    },
                    "linkExtensions": {
                      "type": "array",
                      "items": {
                        "type": "object",
                        "properties": {
                          "id": {
                            "type": "number"
                          },
                          "parentId": {
                            "type": "number"
                          }
                        },
                        "required": [
                          "id",
                          "parentId"
                        ],
                        "additionalProperties": true
                      }
                    },
                    "reroutes": {
                      "type": "array",
                      "items": {
                        "type": "object",
                        "properties": {
                          "id": {
                            "type": "number"
                          },
                          "parentId": {
                            "type": "number"
                          },
                          "pos": {
                            "anyOf": [
                              {
                                "type": "object",
                                "properties": {
                                  "0": {
                                    "type": "number"
                                  },
                                  "1": {
                                    "type": "number"
                                  }
                                },
                                "required": [
                                  "0",
                                  "1"
                                ],
                                "additionalProperties": true
                              },
                              {
                                "type": "array",
                                "minItems": 2,
                                "maxItems": 2,
                                "items": [
                                  {
                                    "type": "number"
                                  },
                                  {
                                    "type": "number"
                                  }
                                ]
                              }
                            ]
                          },
                          "linkIds": {
                            "anyOf": [
                              {
                                "type": "array",
                                "items": {
                                  "type": "number"
                                }
                              },
                              {
                                "type": "null"
                              }
                            ]
                          }
                        },
                        "required": [
                          "id",
                          "pos"
                        ],
                        "additionalProperties": true
                      }
                    }
                  },
                  "additionalProperties": true
                }
              ]
            },
            {
              "type": "null"
            }
          ]
        },
        "models": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "name": {
                "type": "string"
              },
              "url": {
                "type": "string",
                "format": "uri"
              },
              "hash": {
                "type": "string"
              },
              "hash_type": {
                "type": "string"
              },
              "directory": {
                "type": "string"
              }
            },
            "required": [
              "name",
              "url",
              "directory"
            ],
            "additionalProperties": false
          }
        }
      },
      "required": [
        "version",
        "state",
        "nodes"
      ],
      "additionalProperties": true
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}
```

## Older versions

* [0.4](./workflow_json_0.4)


# Workflow JSON 0.4
Source: https://docs.comfy.org/specs/workflow_json_0.4

JSON schema for a ComfyUI workflow.

## v0.4

```json theme={null}
{
  "$ref": "#/definitions/ComfyWorkflow0_4",
  "definitions": {
    "ComfyWorkflow0_4": {
      "type": "object",
      "properties": {
        "last_node_id": {
          "anyOf": [
            {
              "type": "integer"
            },
            {
              "type": "string"
            }
          ]
        },
        "last_link_id": {
          "type": "number"
        },
        "nodes": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "id": {
                "anyOf": [
                  {
                    "type": "integer"
                  },
                  {
                    "type": "string"
                  }
                ]
              },
              "type": {
                "type": "string"
              },
              "pos": {
                "anyOf": [
                  {
                    "type": "object",
                    "properties": {
                      "0": {
                        "type": "number"
                      },
                      "1": {
                        "type": "number"
                      }
                    },
                    "required": [
                      "0",
                      "1"
                    ],
                    "additionalProperties": true
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "number"
                      },
                      {
                        "type": "number"
                      }
                    ]
                  }
                ]
              },
              "size": {
                "anyOf": [
                  {
                    "type": "object",
                    "properties": {
                      "0": {
                        "type": "number"
                      },
                      "1": {
                        "type": "number"
                      }
                    },
                    "required": [
                      "0",
                      "1"
                    ],
                    "additionalProperties": true
                  },
                  {
                    "type": "array",
                    "minItems": 2,
                    "maxItems": 2,
                    "items": [
                      {
                        "type": "number"
                      },
                      {
                        "type": "number"
                      }
                    ]
                  }
                ]
              },
              "flags": {
                "type": "object",
                "properties": {
                  "collapsed": {
                    "type": "boolean"
                  },
                  "pinned": {
                    "type": "boolean"
                  },
                  "allow_interaction": {
                    "type": "boolean"
                  },
                  "horizontal": {
                    "type": "boolean"
                  },
                  "skip_repeated_outputs": {
                    "type": "boolean"
                  }
                },
                "additionalProperties": true
              },
              "order": {
                "type": "number"
              },
              "mode": {
                "type": "number"
              },
              "inputs": {
                "type": "array",
                "items": {
                  "type": "object",
                  "properties": {
                    "name": {
                      "type": "string"
                    },
                    "type": {
                      "anyOf": [
                        {
                          "type": "string"
                        },
                        {
                          "type": "array",
                          "items": {
                            "type": "string"
                          }
                        },
                        {
                          "type": "number"
                        }
                      ]
                    },
                    "link": {
                      "type": [
                        "number",
                        "null"
                      ]
                    },
                    "slot_index": {
                      "anyOf": [
                        {
                          "type": "integer"
                        },
                        {
                          "type": "string"
                        }
                      ]
                    }
                  },
                  "required": [
                    "name",
                    "type"
                  ],
                  "additionalProperties": true
                }
              },
              "outputs": {
                "type": "array",
                "items": {
                  "type": "object",
                  "properties": {
                    "name": {
                      "type": "string"
                    },
                    "type": {
                      "anyOf": [
                        {
                          "type": "string"
                        },
                        {
                          "type": "array",
                          "items": {
                            "type": "string"
                          }
                        },
                        {
                          "type": "number"
                        }
                      ]
                    },
                    "links": {
                      "anyOf": [
                        {
                          "type": "array",
                          "items": {
                            "type": "number"
                          }
                        },
                        {
                          "type": "null"
                        }
                      ]
                    },
                    "slot_index": {
                      "anyOf": [
                        {
                          "type": "integer"
                        },
                        {
                          "type": "string"
                        }
                      ]
                    }
                  },
                  "required": [
                    "name",
                    "type"
                  ],
                  "additionalProperties": true
                }
              },
              "properties": {
                "type": "object",
                "properties": {
                  "Node name for S&R": {
                    "type": "string"
                  }
                },
                "additionalProperties": true
              },
              "widgets_values": {
                "anyOf": [
                  {
                    "type": "array"
                  },
                  {
                    "type": "object",
                    "additionalProperties": {}
                  }
                ]
              },
              "color": {
                "type": "string"
              },
              "bgcolor": {
                "type": "string"
              }
            },
            "required": [
              "id",
              "type",
              "pos",
              "size",
              "flags",
              "order",
              "mode",
              "properties"
            ],
            "additionalProperties": true
          }
        },
        "links": {
          "type": "array",
          "items": {
            "type": "array",
            "minItems": 6,
            "maxItems": 6,
            "items": [
              {
                "type": "number"
              },
              {
                "anyOf": [
                  {
                    "type": "integer"
                  },
                  {
                    "type": "string"
                  }
                ]
              },
              {
                "anyOf": [
                  {
                    "type": "integer"
                  },
                  {
                    "type": "string"
                  }
                ]
              },
              {
                "anyOf": [
                  {
                    "type": "integer"
                  },
                  {
                    "type": "string"
                  }
                ]
              },
              {
                "anyOf": [
                  {
                    "type": "integer"
                  },
                  {
                    "type": "string"
                  }
                ]
              },
              {
                "anyOf": [
                  {
                    "type": "string"
                  },
                  {
                    "type": "array",
                    "items": {
                      "type": "string"
                    }
                  },
                  {
                    "type": "number"
                  }
                ]
              }
            ]
          }
        },
        "groups": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "title": {
                "type": "string"
              },
              "bounding": {
                "type": "array",
                "minItems": 4,
                "maxItems": 4,
                "items": [
                  {
                    "type": "number"
                  },
                  {
                    "type": "number"
                  },
                  {
                    "type": "number"
                  },
                  {
                    "type": "number"
                  }
                ]
              },
              "color": {
                "type": "string"
              },
              "font_size": {
                "type": "number"
              },
              "locked": {
                "type": "boolean"
              }
            },
            "required": [
              "title",
              "bounding"
            ],
            "additionalProperties": true
          }
        },
        "config": {
          "anyOf": [
            {
              "anyOf": [
                {
                  "not": {}
                },
                {
                  "type": "object",
                  "properties": {
                    "links_ontop": {
                      "type": "boolean"
                    },
                    "align_to_grid": {
                      "type": "boolean"
                    }
                  },
                  "additionalProperties": true
                }
              ]
            },
            {
              "type": "null"
            }
          ]
        },
        "extra": {
          "anyOf": [
            {
              "anyOf": [
                {
                  "not": {}
                },
                {
                  "type": "object",
                  "properties": {
                    "ds": {
                      "type": "object",
                      "properties": {
                        "scale": {
                          "type": "number"
                        },
                        "offset": {
                          "anyOf": [
                            {
                              "type": "object",
                              "properties": {
                                "0": {
                                  "type": "number"
                                },
                                "1": {
                                  "type": "number"
                                }
                              },
                              "required": [
                                "0",
                                "1"
                              ],
                              "additionalProperties": true
                            },
                            {
                              "type": "array",
                              "minItems": 2,
                              "maxItems": 2,
                              "items": [
                                {
                                  "type": "number"
                                },
                                {
                                  "type": "number"
                                }
                              ]
                            }
                          ]
                        }
                      },
                      "required": [
                        "scale",
                        "offset"
                      ],
                      "additionalProperties": true
                    },
                    "info": {
                      "type": "object",
                      "properties": {
                        "name": {
                          "type": "string"
                        },
                        "author": {
                          "type": "string"
                        },
                        "description": {
                          "type": "string"
                        },
                        "version": {
                          "type": "string"
                        },
                        "created": {
                          "type": "string"
                        },
                        "modified": {
                          "type": "string"
                        },
                        "software": {
                          "type": "string"
                        }
                      },
                      "required": [
                        "name",
                        "author",
                        "description",
                        "version",
                        "created",
                        "modified",
                        "software"
                      ],
                      "additionalProperties": true
                    },
                    "linkExtensions": {
                      "type": "array",
                      "items": {
                        "type": "object",
                        "properties": {
                          "id": {
                            "type": "number"
                          },
                          "parentId": {
                            "type": "number"
                          }
                        },
                        "required": [
                          "id",
                          "parentId"
                        ],
                        "additionalProperties": true
                      }
                    },
                    "reroutes": {
                      "type": "array",
                      "items": {
                        "type": "object",
                        "properties": {
                          "id": {
                            "type": "number"
                          },
                          "parentId": {
                            "type": "number"
                          },
                          "pos": {
                            "anyOf": [
                              {
                                "type": "object",
                                "properties": {
                                  "0": {
                                    "type": "number"
                                  },
                                  "1": {
                                    "type": "number"
                                  }
                                },
                                "required": [
                                  "0",
                                  "1"
                                ],
                                "additionalProperties": true
                              },
                              {
                                "type": "array",
                                "minItems": 2,
                                "maxItems": 2,
                                "items": [
                                  {
                                    "type": "number"
                                  },
                                  {
                                    "type": "number"
                                  }
                                ]
                              }
                            ]
                          },
                          "linkIds": {
                            "anyOf": [
                              {
                                "type": "array",
                                "items": {
                                  "type": "number"
                                }
                              },
                              {
                                "type": "null"
                              }
                            ]
                          }
                        },
                        "required": [
                          "id",
                          "pos"
                        ],
                        "additionalProperties": true
                      }
                    }
                  },
                  "additionalProperties": true
                }
              ]
            },
            {
              "type": "null"
            }
          ]
        },
        "version": {
          "type": "number"
        },
        "models": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "name": {
                "type": "string"
              },
              "url": {
                "type": "string",
                "format": "uri"
              },
              "hash": {
                "type": "string"
              },
              "hash_type": {
                "type": "string"
              },
              "directory": {
                "type": "string"
              }
            },
            "required": [
              "name",
              "url",
              "directory"
            ],
            "additionalProperties": false
          }
        }
      },
      "required": [
        "last_node_id",
        "last_link_id",
        "nodes",
        "links",
        "version"
      ],
      "additionalProperties": true
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}
```


# Contact support
Source: https://docs.comfy.org/support/contact-support

Get help and report issues for ComfyUI

Get help with ComfyUI through our support channels and report issues in the appropriate repository.

## Support channels

<CardGroup>
  <Card title="Support" icon="life-ring" href="https://support.comfy.org/">
    Get help from our support team
  </Card>
</CardGroup>

## Report issues

Report bugs and issues in the corresponding GitHub repository:

<CardGroup>
  <Card title="UI Issues" icon="browser" href="https://github.com/Comfy-Org/ComfyUI_frontend/issues">
    Report UI-related issues in ComfyUI\_frontend
  </Card>

  <Card title="Core Issues" icon="code" href="https://github.com/Comfy-Org/ComfyUI/issues">
    Report core functionality issues
  </Card>

  <Card title="Desktop Issues" icon="desktop" href="https://github.com/Comfy-Org/desktop/issues">
    Report issues with the desktop version
  </Card>
</CardGroup>


# Data Retention
Source: https://docs.comfy.org/support/data-retention

How Comfy retains and manages customer data

This page describes how Comfy retains customer data. For the full legal terms governing your use of Comfy, see our [Terms of Service](https://www.comfy.org/terms-of-service?utm_source=docs) and [Privacy Policy](https://www.comfy.org/privacy-policy?utm_source=docs).

## Retention periods

| Data type             | Description                                                            | Retention                                                                      |
| --------------------- | ---------------------------------------------------------------------- | ------------------------------------------------------------------------------ |
| Account data          | Email, profile, and organization details                               | Lifetime of account                                                            |
| Customer content      | Prompts, workflows, outputs, and other content you create or upload    | Retained for as long as necessary to operate, analyze, and improve the service |
| Analytics data        | Aggregated and pseudonymized metrics on platform usage and performance | Retained for as long as necessary to operate, analyze, and improve the service |
| Behavioral event data | In-product actions such as clicks, sessions, and feature interactions  | Retained for as long as necessary to operate, analyze, and improve the service |
| Product usage data    | Workflow runs, asset metadata, and operational telemetry               | Retained for as long as necessary to operate, analyze, and improve the service |

## Requesting deletion

<Note>
  To request deletion of your account or associated data, contact [support@comfy.org](mailto:support@comfy.org). Certain records may be retained where necessary to comply with legal, security, audit, or fraud prevention obligations.
</Note>


# Accepted payment methods
Source: https://docs.comfy.org/support/payment/accepted-payment-methods

Learn about the payment methods accepted by Comfy Organization Inc

Comfy Organization Inc uses Stripe as our payment processor, which means you can only use payment methods that Stripe accepts. Generally, you can pay with major credit and debit cards like Visa, Mastercard, and American Express, as well as some digital wallets such as Google Pay and Link in some regions. The options you see during checkout are the ones available to you.

## Credit and debit cards

We accept the following major credit and debit cards:

* Visa
* Mastercard
* American Express

## Digital wallets

You can also pay using digital wallet services:

* Google Pay
* Link

## Alternative payment methods

We also support the following payment methods, but only in USD:

* Alipay
* WeChat Pay

<Note>
  WeChat Pay and Alipay are only available in specific regions. Check the `Business locations` section in the Stripe documentation to verify availability in your country:

  * [Stripe WeChat Pay documentation](https://docs.stripe.com/payments/wechat-pay#get-started)
  * [Stripe Alipay documentation](https://docs.stripe.com/payments/alipay)
</Note>

<img alt="Checkout screen showing USD selected and Alipay/WeChat Pay options available" />

*Select **USD** as your payment currency (1) to unlock the Alipay and WeChat Pay options (2) during checkout.*

<Note>
  Alipay and WeChat Pay are not yet supported for Comfy Cloud Subscription.
</Note>

To enable these options, choose **USD** in the Stripe billing portal currency selector. Once USD is selected, Alipay and WeChat Pay appear in the payment method list.

<img alt="Stripe payment form showing USD currency selection and Alipay/WeChat options" />

## Requirements

To successfully process your payment:

* Your card must have sufficient funds or available credit
* Your billing address must match the address on file with your card issuer
* International cards are accepted, but may be subject to currency conversion fees from your bank

## Security

Stripe is a PCI Service Provider Level 1, the most stringent level of certification available in the payments industry. All payment information is processed securely using industry-standard encryption. Comfy Organization Inc does not store your complete card details on our servers.

## Payment processing

Payments are processed immediately upon subscription or renewal. You will receive a confirmation email once your payment has been successfully processed.

If you experience any issues with payment processing, please contact our [support team](https://support.comfy.org/) for assistance.


# Editing your payment information
Source: https://docs.comfy.org/support/payment/editing-payment-information

Learn how to update your payment method and billing details

You can update your payment information at any time through your account settings.

## How to edit payment information

1. Log in to your ComfyUI account and open the profile menu
2. Click **User Settings**
3. Select the **Credits** tab in the settings panel
4. Choose **Invoice History** to open the Stripe billing portal in a new tab
5. Click **Update information** and edit your billing or payment details
6. Save your changes in the Stripe portal

### Visual walkthrough

<img alt="Profile menu highlighting the User Settings option" />

*Open the profile menu and choose **User Settings** to manage billing.*

<img alt="Credits tab in settings with Invoice History button highlighted" />

*Go to the **Credits** tab and select **Invoice History**.*

<img alt="Stripe billing information form ready for updates" />

*Review the billing information fields in the Stripe portal.*

<img alt="Stripe portal with Update information button emphasized" />

*Click **Update information** to edit payment details and save your changes.*

## What you can update

You can modify the following payment details:

* Credit or debit card number
* Card expiration date
* CVV/security code
* Billing address
* Payment method type (switch between card and digital wallet)

## When changes take effect

* Changes to your payment method take effect immediately
* Your next billing cycle will use the updated payment information
* Updates to billing details (name, address, tax ID) only apply to future invoices; existing invoices cannot be modified
* Active subscriptions will not be interrupted when you update payment details

## Important notes

* You must have an active payment method on file to maintain your subscription
* If you remove a payment method, you must add a new one before the next billing date
* Keep a copy of past invoices before making changes if you need them for record keeping
* Updating your payment information does not change your billing date or subscription plan

## Troubleshooting

If you encounter issues updating your payment information:

* Verify that all information is entered correctly
* Ensure your card has not expired
* Check that your billing address matches your card issuer's records
* Try using a different browser or clearing your cache
* Contact our [support team](https://support.comfy.org/) if problems persist


# Invoice information
Source: https://docs.comfy.org/support/payment/invoice-information

Learn how your invoice information is managed

Your invoice is based on the information you provide to Stripe during checkout. The details you enter will appear on all your invoices.

<Card title="Update your payment information" icon="credit-card" href="/support/payment/editing-payment-information">
  Learn how to update your billing details and payment information
</Card>

## Important notes

* Changes to your payment information only apply to **future invoices**
* Unfortunately, we cannot change invoices that have already been issued
* Ensure that the payment details you enter at checkout are the ones you want to see on your invoice


# Payment currency
Source: https://docs.comfy.org/support/payment/payment-currency

Information about supported currencies and currency conversion

Comfy Organization Inc processes payments in multiple currencies to serve our global user base.

## Primary currency

All subscription prices are listed in **US Dollars (USD)** by default.

## Payment method availability

### Alipay and WeChat Pay

* **Alipay** is now supported for both local API credits and Comfy Cloud subscriptions
* **WeChat Pay** is currently only available for local API credits

## Currency selection

Your payment currency is typically determined by:

* Your account location
* Your billing address
* Your payment method's default currency

## Currency conversion

### Automatic conversion

If your card's currency differs from the billing currency:

* Your bank or card issuer will automatically convert the amount
* Conversion rates are set by your financial institution
* Additional currency conversion fees may apply

### Conversion fees

* Currency conversion fees are charged by your bank, not by Comfy Organization Inc
* These fees typically range from 1-3% of the transaction amount
* Check with your bank for specific conversion fee rates

## Viewing charges in your currency

To see the approximate charge in your local currency:

1. Check your bank or card statement
2. Use your bank's currency converter
3. Note that exchange rates fluctuate daily

## Changing your billing currency

To change your billing currency:

1. Contact our [support team](https://support.comfy.org/)
2. Provide your preferred currency
3. Note that currency changes may affect your subscription price due to exchange rates

## Price variations by region

Subscription prices may vary slightly by region due to:

* Local tax requirements
* Currency exchange rates
* Regional pricing adjustments

## Tax and VAT

Depending on your location, additional charges may apply:

* Sales tax (US customers)
* VAT (European customers)
* GST (Australian, Canadian, and other applicable regions)

These taxes are calculated based on your billing address and added to your total.


# Viewing your payment history
Source: https://docs.comfy.org/support/payment/payment-history

Access and review your past payments and invoices

You can view your complete payment history and download invoices through your account dashboard.

## Accessing payment history

1. Log in to your ComfyUI account and open the profile menu
2. Click **User Settings**
3. Select the **Credits** tab in the settings panel
4. Click **Invoice History** to open the Stripe billing portal and view your payment history

### Visual walkthrough

<img alt="Profile menu highlighting the User Settings option" />

*Open the profile menu and choose **User Settings** to manage billing.*

<img alt="Credits tab in settings with Invoice History button highlighted" />

*Go to the **Credits** tab and select **Invoice History**.*

<img alt="Stripe billing portal showing invoice history table" />

*Review your invoice list in the Stripe billing portal.*

## Downloading invoices

In the Stripe portal, open any entry in the invoice history list to view its details and download the PDF copy.

<img alt="Invoice history details with download option highlighted" />

Make sure your billing details are correct before new invoices are generated. Update them from [Editing your payment information](/support/payment/editing-payment-information).


# Unsuccessful payments
Source: https://docs.comfy.org/support/payment/unsuccessful-payments

Understand why payments fail and how to resolve payment issues

If your payment fails, your subscription may be interrupted. This guide helps you understand and resolve payment issues.

## Common reasons for payment failure

### Insufficient funds

* Your card does not have enough available balance or credit
* **Solution**: Add funds to your account or use a different payment method

### Expired card

* Your credit or debit card has passed its expiration date
* **Solution**: Update your payment information with a valid card

### Incorrect information

* Card number, CVV, or billing address is entered incorrectly
* **Solution**: Verify and correct your payment details

### Card declined by issuer

* Your bank or card issuer has declined the transaction
* **Solution**: Contact your bank to authorize the payment

### International restrictions

* Your card does not support international transactions
* **Solution**: Enable international payments or use a different card

### Security holds

* Your bank has flagged the transaction as suspicious
* **Solution**: Contact your bank to verify and approve the charge

## What happens when payment fails

## Resolving payment issues

### Update your payment method

1. Log in to your account
2. Go to **Account Settings** > **Billing & Payment**
3. Update your payment information
4. Click **Retry Payment** if available

### Contact your bank

* Verify that your card is active and has sufficient funds
* Ensure international transactions are enabled
* Confirm that the charge from Comfy Organization Inc is authorized

### Try a different payment method

If your current payment method continues to fail, consider using:

* A different credit or debit card
* A digital wallet (Apple Pay, Google Pay, PayPal)
* An alternative payment method

## Preventing future payment failures

* Keep your payment information up to date
* Ensure your card has sufficient funds before billing dates
* Update your card details before expiration
* Whitelist charges from Comfy Organization Inc with your bank
* Enable email notifications for billing reminders

## Grace period and account suspension

* You typically have 7-14 days to resolve payment issues
* During this period, you may have limited access to services
* If payment is not resolved, your subscription will be cancelled
* You can reactivate your subscription at any time by updating payment information

## Need assistance?

If you continue to experience payment issues after trying these solutions, please contact our [support team](https://support.comfy.org/) with:

* Your account email
* The error message you received
* The payment method you're attempting to use
* Any relevant transaction IDs

We're here to help resolve your payment issues quickly.


# Canceling your Comfy Cloud subscription
Source: https://docs.comfy.org/support/subscription/canceling

Learn how to cancel your Comfy Cloud subscription

## How to cancel

To cancel your Comfy Cloud subscription:

1. Visit and log in to [cloud.comfy.org](https://cloud.comfy.org/?utm_source=docs)
2. Navigate to the settings menu
3. Go to **Plan & Credits**
4. Click **Manage subscription**

<img alt="Subscription settings menu" />

5. Click `Cancel subscription` button in Stripe to cancel your subscription

<img alt="Stripe billing portal" />

## Important notes

* All Comfy Cloud subscription plans automatically renew unless you set your plan to cancel
* Your subscription will remain active until the end of your current billing period
* You can resubscribe at any time by visiting [cloud.comfy.org](https://cloud.comfy.org/?utm_source=docs)


# Changing your subscription plan
Source: https://docs.comfy.org/support/subscription/changing-plan

Learn how to change your Comfy Cloud subscription plan

## How to change your subscription plan

You can upgrade or downgrade your Comfy Cloud subscription plan at any time. Follow these steps to change your plan:

### Step 1: Open the settings panel

Click the **Plan & Credits** menu to open the settings panel.

<img alt="Plan & Credits menu" />

### Step 2: Access subscription management

In the **Plan & Credits** panel, click the **Manage subscription** button to open the subscription settings.

<img alt="Manage subscription button" />

### Step 3: Select a new plan

Select any plan you want, then click the **Change** button.

<img alt="Select subscription plan" />

### Step 4: Open the billing portal

After opening the Comfy billing portal, click the **Update subscription** button.

<img alt="Comfy billing portal" />

### Step 5: Confirm your new plan

Select the plan you want, then click **Continue** to confirm your selection.

<img alt="Confirm subscription change" />

## Billing for plan changes

### Upgrading to a higher-priced plan

If your current subscription plan price is lower than the target plan, you will need to pay the price difference. You will receive an equivalent credit amount corresponding to the price difference.

### Downgrading to a lower-priced plan

If your current subscription plan price is higher than the target plan, your subscription will switch to the new plan after the current billing cycle ends. The new subscription will be based on the new pricing plan.


# Managing your Comfy Cloud subscription
Source: https://docs.comfy.org/support/subscription/managing

Learn how to manage your Comfy Cloud subscription

## Accessing subscription management

To manage your Comfy Cloud subscription:

1. Visit and log in to [cloud.comfy.org](https://cloud.comfy.org/?utm_source=docs)
2. Navigate to the settings menu
3. Go to **Plan & Credits**

<img alt="Subscription settings menu" />

4. Click **Manage subscription**

This will take you to Stripe, where you can manage your subscription details.


# Subscribing to Comfy Cloud
Source: https://docs.comfy.org/support/subscription/subscribing

Learn how to subscribe to Comfy Cloud

## How to subscribe

You can browse and use Comfy Cloud normally without a subscription, but you need to subscribe to run workflows.

To subscribe to Comfy Cloud:

1. Visit [cloud.comfy.org](https://cloud.comfy.org/?utm_source=docs) and log in to your account.
2. Click the **Subscribe** button.

<img alt="Subscribe button location" />

3. Select your desired subscription plan.

For detailed information about Comfy Cloud subscription plans and pricing, visit [comfy.org/cloud/pricing](https://www.comfy.org/cloud/pricing).

Comfy Cloud subscriptions are managed through Stripe, our payment processor.

## Applying a promotion code

If you have a promotion code, you can apply it during checkout to receive a discount on your subscription:

### Step 1: Activate the promotion code field

During checkout, click the **Add promotion code** button to reveal the input field.

<img alt="Click Add promotion code button" />

### Step 2: Enter and apply your code

Type your promotion code into the field and click **Apply**.

<img alt="Enter promotion code and click Apply" />

### Step 3: Verify the discount

If the code is valid, you'll see the updated price reflecting your discount.

<img alt="Discount applied successfully" />

Complete the payment process to activate your subscription with the applied discount.

<Note>
  Promotion codes may have specific terms and conditions, such as expiration dates or usage limits. Make sure to review the details of your promotion code before applying it.
</Note>

## Subscription renewal

Your subscription renews automatically on the same day and time each month as when you first subscribed.

All Comfy Cloud subscription plans automatically renew unless you set your plan to cancel.


# How to Troubleshoot and Solve ComfyUI Issues
Source: https://docs.comfy.org/troubleshooting/custom-node-issues

Troubleshoot and fix problems caused by custom nodes and extensions

Here is the overall approach for troubleshooting custom node issues:

```mermaid theme={null}
flowchart TD
   A[Issue Encountered] --> B{Does the issue disappear after <a href="#how-to-disable-all-custom-nodes%3F">disabling all custom nodes</a>?}
   B -- Yes --> C[Issue caused by custom nodes]
   B -- No --> D[Issue not caused by custom nodes, refer to other troubleshooting docs]
   C --> E{<a href="#1-troubleshooting-the-custom-nodes’-frontend-extensions">Check frontend extensions first</a>?}
   E -- Yes --> F[<a href="#1-troubleshooting-the-custom-nodes’-frontend-extensions">Troubleshoot in ComfyUI frontend</a><br/><li>Only need reload the frontend</li>]
   E -- No --> G[<a href="#2-general-custom-node-troubleshooting">Use general binary search method</a><li>Need to restart ComfyUI multiple times</li>]
   F --> H[Use binary search to locate problematic node]
   G --> H
   H --> I[<a href="#how-to-fix-the-issue">Fix, replace, report or remove problematic node</a>]
   I --> J[Issue solved]
```

## How to disable all custom nodes?

<Tabs>
  <Tab title="Desktop Users">
    Start ComfyUI Desktop with custom nodes disabled from the settings menu

    <img alt="Settings menu - Disable custom nodes" />

    or run the server manually:

    ```bash theme={null}
    cd path/to/your/comfyui
    python main.py --disable-all-custom-nodes
    ```
  </Tab>

  <Tab title="Manual Install">
    ```bash theme={null}
    cd ComfyUI
    python main.py --disable-all-custom-nodes
    ```
  </Tab>

  <Tab title="Portable">
    <Tabs>
      <Tab title="Modify `.bat` file">
        Open the folder where the portable version is located, and find the `run_nvidia_gpu.bat` or `run_cpu.bat` file

        <img alt="Modify .bat file" />

        1. Copy `run_nvidia_gpu.bat` or `run_cpu.bat` file and rename it to `run_nvidia_gpu_disable_custom_nodes.bat`
        2. Open the copied file with Notepad
        3. Add the `--disable-all-custom-nodes` parameter to the file, or copy the parameters below into a `.txt` file and rename the file to `run_nvidia_gpu_disable_custom_nodes.bat`

        ```bash theme={null}
        .\python_embeded\python.exe -s ComfyUI\main.py --disable-all-custom-nodes  --windows-standalone-build
        pause
        ```

        4. Save the file and close it
        5. Double-click the file to run it. If everything is normal, you should see ComfyUI start and custom nodes disabled
      </Tab>

      <Tab title="Through Command Line">
        <img alt="ComfyUI troubleshooting" />

        1. Enter the folder where the portable version is located
        2. Open the terminal by right-clicking the menu → Open terminal
           <img alt="ComfyUI troubleshooting" />
        3. Ensure that the folder name is the current directory of the portable version
        4. Enter the following command to start ComfyUI through the portable python and disable custom nodes

        ```
        .\python_embeded\python.exe -s ComfyUI\main.py --disable-all-custom-nodes
        ```
      </Tab>
    </Tabs>
  </Tab>
</Tabs>

**Results:**

* ✅ **Issue disappears**: A custom node is causing the problem → Continue to Step 2
* ❌ **Issue persists**: Not a custom node issue → [Report the issue](#reporting-issues)

## What is Binary Search?

In this document, we will introduce the binary search approach for troubleshooting custom node issues, which involves checking half of the custom nodes at a time until we locate the problematic node.

Please refer to the flowchart below for the specific approach - enable half of the currently disabled nodes each time and check if the issue appears, until we identify which custom node is causing the issue

```mermaid theme={null}
flowchart TD
   A[Start] --> B{Split all custom nodes in half}
   B --> C[Enable first half of custom nodes]
   C --> D[Restart ComfyUI and test]
   D --> E{Does the issue appear?}
   E --> |Yes| F[Issue is in enabled custom nodes]
   E --> |No| G[Issue is in disabled custom nodes]
   F --> H{Enabled custom nodes > 1?}
   G --> I{Disabled custom nodes > 1?}
   H --> |Yes| J[Continue binary search on enabled nodes]
   I --> |Yes| K[Continue binary search on disabled nodes]
   H --> |No| L[Found problematic custom node]
   I --> |No| L
   J --> B
   K --> B
   L --> M[End]
```

## Two Troubleshooting Methods

In this document, we categorize custom nodes into two types for troubleshooting:

<img alt="Custom node types" />

* A: Custom nodes with frontend extensions
* B: Regular custom nodes

Let's first understand the potential issues and causes for different types of custom nodes:

<Tabs>
  <Tab title="Custom Nodes with Frontend Extensions">
    For custom nodes, we can prioritize troubleshooting those with frontend extensions, as they cause the most issues. Their main conflicts arise from incompatibilities with ComfyUI frontend version updates.

    Common issues include:

    * Workflows not executing
    * Some nodes can't show preview images(such as save image node)
    * Misaligned UI elements
    * Unable to access ComfyUI frontend
    * Completely broken UI or blank screen
    * Unable to communicate normally with ComfyUI backend
    * Node connections not working properly
    * And more

    Common causes for these issues:

    * Frontend modifications during updates that custom nodes haven't adapted to yet
    * Users updating ComfyUI without synchronously upgrading custom nodes, even though authors have released compatible versions
    * Authors stopping maintenance, leading to incompatibility between custom node extensions and the ComfyUI frontend
  </Tab>

  <Tab title="Regular Custom Nodes">
    If the problem isn't caused by custom nodes' frontend extensions, issues often relate to dependencies. Common problems include:

    * "Failed to import" errors in console/logs
    * Missing nodes still showing as missing after installation and restart
    * ComfyUI crashes or fails to start
    * And more

    Common causes for these errors:

    * Custom nodes requiring additional wheels like ComfyUI-Nunchaku
    * Custom nodes using strict dependency versions (e.g., `torch==2.4.1`) while other plugins use different versions (e.g., `torch>=2.4.2`), causing conflicts after installation
    * Network issues preventing successful dependency installation

    When problems involve Python environment interdependencies and versions, troubleshooting becomes more complex and requires knowledge of Python environment management, including how to install and uninstall dependencies
  </Tab>
</Tabs>

## Using Binary Search for Troubleshooting

Among these two different types of custom node issues, conflicts between custom node frontend extensions and ComfyUI are more common. We'll prioritize troubleshooting these nodes first. Here's the overall troubleshooting approach:

### 1. Troubleshooting the Custom Nodes' Frontend Extensions

<Steps>
  <Step title="Disable All Third-Party Frontend Extensions">
    <img alt="Disable all plugin frontend extensions" />

    After starting ComfyUI, find the `Extensions` menu in settings and follow the steps shown in the image to disable all third-party extensions

    <Tip>
      If you can't enter ComfyUI frontend, just skip the frontend extensions troubleshooting section and continue to [General Custom Node Troubleshooting Approach](#2-general-custom-node-troubleshooting-approach)
    </Tip>
  </Step>

  <Step title="Restart ComfyUI">
    After disabling frontend extensions for the first time, it's recommended to restart ComfyUI to ensure all frontend extensions are properly disabled

    * If the problem disappears, then it was caused by custom node frontend extensions, and we can proceed with binary search troubleshooting
    * If the problem persists, then it's not caused by frontend extensions - please refer to the other troubleshooting approaches in this document
  </Step>

  <Step title="Use Binary Search to Locate Problem Nodes">
    Use the method mentioned at the beginning of this document to troubleshoot, enabling half of the custom nodes at a time until you find the problematic node

    <img alt="Enable frontend extensions" />

    Refer to the image to enable half of the frontend extensions. Note that if extension names are similar, they likely come from the same custom node's frontend extensions
  </Step>

  <Step title="Follow-up Actions">
    If you find the problematic custom node, please refer to the problem fixing section of this document to resolve the custom node issues
  </Step>
</Steps>

Using this method, you don't need to restart ComfyUI multiple times - just reload ComfyUI after enabling/disabling custom node frontend extensions. Plus, your troubleshooting scope is limited to nodes with frontend extensions, which greatly narrows down the search range.

### 2. General Custom Node Troubleshooting

<Steps>
  <Step title="Use Binary Search to Locate Custom Nodes">
    For the binary search localization method, in addition to manual search, we also have automated binary search using comfy-cli, as detailed below:

    <Tabs>
      <Tab title="Using Comfy CLI (Recommended)">
        Using Comfy CLI requires some command line experience. If you're not comfortable with it, use manual binary search instead.

        If you have [Comfy CLI](/comfy-cli/getting-started) installed, you can use the automated bisect tool to find the problematic node:

        ```bash theme={null}
        # Start a bisect session
        comfy-cli node bisect start

        # Follow the prompts:
        # - Test ComfyUI with the current set of enabled nodes
        # - Mark as 'good' if the issue is gone: comfy-cli node bisect good
        # - Mark as 'bad' if the issue persists: comfy-cli node bisect bad
        # - Repeat until the problematic node is identified

        # Reset when done
        comfy-cli node bisect reset
        ```

        The bisect tool will automatically enable/disable nodes and guide you through the process.
      </Tab>

      <Tab title="Manual Binary Search">
        <Warning>
          Before starting, please **create a backup** of your custom\_nodes folder in case something goes wrong.
        </Warning>

        If you prefer to do the process manually or don't have Comfy CLI installed, follow the steps below:

        <Steps>
          <Step title="Create Temporary Folders">
            Before starting, enter the `<YOUR_COMFYUI_FOLDER>\ComfyUI\` folder

            <Tabs>
              <Tab title="Windows">
                * **Backup all custom nodes**: Copy and rename `custom_nodes` to `custom_nodes_backup`
                * **Create a temporary folder**: Create a folder named `custom_nodes_temp`

                Or use the following command line to backup:

                ```bash theme={null}
                # Create backup and temporary folder
                mkdir "%USERPROFILE%\custom_nodes_backup"
                mkdir "%USERPROFILE%\custom_nodes_temp"

                # Backup all content
                xcopy "custom_nodes\*" "%USERPROFILE%\custom_nodes_backup\" /E /H /Y
                ```
              </Tab>

              <Tab title="macOS/Linux">
                Manually backup custom\_nodes folder
                Or use the following command line to backup:

                ```bash theme={null}
                # Create backup and temporary folder
                mkdir ~/custom_nodes_backup
                mkdir ~/custom_nodes_temp

                # Backup all content
                cp -r custom_nodes/* ~/custom_nodes_backup/
                ```
              </Tab>

              <Tab title="Cloud/Colab">
                ```bash theme={null}
                # Create backup and temporary folder
                mkdir /content/custom_nodes_backup
                mkdir /content/custom_nodes_temp

                # Backup all content
                cp -r /content/ComfyUI/custom_nodes/* /content/custom_nodes_backup/
                ```
              </Tab>
            </Tabs>
          </Step>

          <Step title="List all custom nodes">
            <Tabs>
              <Tab title="Windows">
                Since Windows has a visual interface, you can skip this step unless you're only using the command line

                ```bash theme={null}
                dir custom_nodes
                ```
              </Tab>

              <Tab title="macOS/Linux">
                ```bash theme={null}
                ls custom_nodes/
                ```
              </Tab>

              <Tab title="Cloud/Colab">
                ```bash theme={null}
                ls /content/ComfyUI/custom_nodes/
                ```
              </Tab>
            </Tabs>
          </Step>

          <Step title="Split nodes in half">
            Let's assume that you have 8 custom nodes. Move the first half to temporary storage:

            <Tabs>
              <Tab title="Windows">
                ```bash theme={null}
                # Move first half (nodes 1-4) to temp
                move "custom_nodes\node1" "%USERPROFILE%\custom_nodes_temp\"
                move "custom_nodes\node2" "%USERPROFILE%\custom_nodes_temp\"
                move "custom_nodes\node3" "%USERPROFILE%\custom_nodes_temp\"
                move "custom_nodes\node4" "%USERPROFILE%\custom_nodes_temp\"
                ```
              </Tab>

              <Tab title="macOS/Linux">
                ```bash theme={null}
                # Move first half (nodes 1-4) to temp
                mv custom_nodes/node1 ~/custom_nodes_temp/
                mv custom_nodes/node2 ~/custom_nodes_temp/
                mv custom_nodes/node3 ~/custom_nodes_temp/
                mv custom_nodes/node4 ~/custom_nodes_temp/
                ```
              </Tab>

              <Tab title="Cloud/Colab">
                ```bash theme={null}
                # Move first half (nodes 1-4) to temp
                mv /content/ComfyUI/custom_nodes/node1 /content/custom_nodes_temp/
                mv /content/ComfyUI/custom_nodes/node2 /content/custom_nodes_temp/
                mv /content/ComfyUI/custom_nodes/node3 /content/custom_nodes_temp/
                mv /content/ComfyUI/custom_nodes/node4 /content/custom_nodes_temp/
                ```
              </Tab>
            </Tabs>
          </Step>

          <Step title="Test ComfyUI">
            Start ComfyUI normally

            ```bash theme={null}
            python main.py
            ```
          </Step>

          <Step title="Interpret results">
            * **Issue persists**: Problem is in the remaining nodes (5-8)
            * **Issue disappears**: Problem was in the moved nodes (1-4)
          </Step>

          <Step title="Narrow it down">
            * If issue persists: Move half of remaining nodes (e.g., nodes 7-8) to temp
            * If issue gone: Move half of temp nodes (e.g., nodes 3-4) back to custom\_nodes
          </Step>

          <Step title="Repeat until you find the single problematic node">
            * Repeat until you find the single problematic node
          </Step>
        </Steps>
      </Tab>
    </Tabs>
  </Step>
</Steps>

## How to Fix the Issue

Once you've identified the problematic custom node:

### Option 1: Update the Node

1. Check if there's an update available in ComfyUI Manager
2. Update the node and test again

### Option 2: Replace the Node

1. Look for alternative custom nodes with similar functionality
2. Check the [ComfyUI Registry](https://registry.comfy.org) for alternatives

### Option 3: Report the Issue

Contact the custom node developer:

1. Find the node's GitHub repository
2. Create an issue with:
   * Your ComfyUI version
   * Error messages/logs
   * Steps to reproduce
   * Your operating system

### Option 4: Remove or Disable the Node

If no fix is available and you don't need the functionality:

1. Remove the problematic node from `custom_nodes/` or disable it in the ComfyUI Manager interface
2. Restart ComfyUI

## Reporting Issues

If the issue isn't caused by custom nodes, refer to the general [troubleshooting overview](/troubleshooting/overview) for other common problems.

### For Custom Node-Specific Issues

Contact the custom node developer:

* Find the node's GitHub repository
* Create an issue with your ComfyUI version, error messages, reproduction steps, and OS
* Check the node's documentation and Issues page for known issues

### For ComfyUI Core Issues

* **GitHub**: [ComfyUI Issues](https://github.com/Comfy-Org/ComfyUI/issues)
* **Forum**: [Official ComfyUI Forum](https://forum.comfy.org/)

### For Desktop App Issues

* **GitHub**: [ComfyUI Desktop Issues](https://github.com/Comfy-Org/desktop/issues)

### For Frontend Issues

* **GitHub**: [ComfyUI Frontend Issues](https://github.com/Comfy-Org/ComfyUI_frontend/issues)

<Note>
  For general installation, model, or performance issues, see our [troubleshooting overview](/troubleshooting/overview) and [model issues](/troubleshooting/model-issues) pages.
</Note>


# How to Troubleshoot and Solve ComfyUI Model Issues
Source: https://docs.comfy.org/troubleshooting/model-issues

Troubleshooting model-related problems including architecture mismatches, missing models, and loading errors

## Model Architecture Mismatch

**Symptoms:** Tensor dimension errors during generation, especially during VAE decode stage

**Common error messages:**

* `Given groups=1, weight of size [64, 4, 3, 3], expected input[1, 16, 128, 128] to have 4 channels, but got 16 channels instead`
* `Given groups=1, weight of size [4, 4, 1, 1], expected input[1, 16, 144, 112] to have 4 channels, but got 16 channels instead`
* `Given groups=1, weight of size [320, 4, 3, 3], expected input[2, 16, 192, 128] to have 4 channels, but got 16 channels instead`
* `The size of tensor a (49) must match the size of tensor b (16) at non-singleton dimension 1`
* `Tensors must have same number of dimensions: got 2 and 3`
* `mat1 and mat2 shapes cannot be multiplied (154x2048 and 768x320)`

**Root cause:** Using models from different architecture families together

### Solutions

1. **Verify model family compatibility:**
   * **Flux models** use 16-channel latent space with dual text encoder conditioning (CLIP-L + T5-XXL)
   * **SD1.5 models** use 4-channel latent space with single CLIP ViT-L/14 text encoder
   * **SDXL models** use 4-channel latent space with dual text encoders (CLIP ViT-L/14 + OpenCLIP ViT-bigG/14)
   * **SD3 models** use 16-channel latent space with triple text encoder conditioning (CLIP-L + OpenCLIP bigG + T5-XXL)
   * **ControlNet models** must match the architecture of the base checkpoint (SD1.5 ControlNets only work with SD1.5 checkpoints, SDXL ControlNets only work with SDXL checkpoints, etc.)

2. **Common mismatch scenarios and fixes:**

   **Flux + wrong VAE:**

   ```
   Problem: Using taesd or sdxl_vae.safetensors with Flux checkpoint
   Fix: Use ae.safetensors (Flux VAE) from Hugging Face Flux releases
   ```

   **Flux + incorrect CLIP configuration:**

   ```
   Problem: Using t5xxl_fp8_e4m3fn.safetensors in both CLIP slots of DualClipLoader
   Fix: Use t5xxl_fp8_e4m3fn.safetensors in one slot and clip_l.safetensors in the other
   ```

   **ControlNet architecture mismatch:**

   ```
   Problem: SD1.5 ControlNet with SDXL checkpoint (or vice versa)
   Error: "mat1 and mat2 shapes cannot be multiplied (154x2048 and 768x320)"
   Fix: Use ControlNet models designed for your checkpoint architecture
        - SD1.5 checkpoints require SD1.5 ControlNets
        - SDXL checkpoints require SDXL ControlNets
   ```

3. **Quick diagnostics:**
   ```bash theme={null}
   # Check if error occurs at VAE decode stage
   # Look for "expected input[X, Y, Z] to have N channels, but got M channels"
   # Y value indicates channel count: 4 = SD models, 16 = Flux models
   ```

4. **Prevention strategies:**
   * Keep all workflow models within the same architecture family
   * Download complete model packages from same source/release (often all in a Hugging Face repo)
   * When trying new models, start with the template workflows or official ComfyUI workflow examples before customizing

## Missing Models Error

**Example error message:**

```
Prompt execution failed
Prompt outputs failed validation:
CheckpointLoaderSimple:
- Value not in list: ckpt_name: 'model-name.safetensors' not in []
```

### Solutions

1. **Download required models:**
   * Use ComfyUI Manager to auto-download models
   * Verify models are in correct subfolders

2. **Check model paths:**
   * **Checkpoints**: `models/checkpoints/`
   * **VAE**: `models/vae/`
   * **LoRA**: `models/loras/`
   * **ControlNet**: `models/controlnet/`
   * **Embeddings**: `models/embeddings/`

3. **Share models between UIs or use custom paths:**
   * See [ComfyUI Model Sharing and Custom Model Directory Configuration](/installation/comfyui_portable_windows#2-comfyui-model-sharing-and-custom-model-directory-configuration) for detailed instructions
   * Edit `extra_model_paths.yaml` file to add custom model directories

### Model Search Path Configuration

If you have models in custom locations, see the detailed guide for [ComfyUI Model Sharing and Custom Model Directory Configuration](/installation/comfyui_portable_windows#2-comfyui-model-sharing-and-custom-model-directory-configuration) to configure ComfyUI to find them.

## Model Loading Errors

**Error message:** "Error while deserializing header"

### Solutions

1. **Re-download the model** - File may be corrupted during download
2. **Check available disk space** - Ensure enough space for model loading (models can be 2-15GB+)
3. **Check file permissions** - Ensure ComfyUI can read the model files
4. **Test with different model** - Verify if issue is model-specific or system-wide

## Model Performance Issues

### Slow Model Loading

**Symptoms:** Long delays when switching models or starting generation

**Solutions:**

1. **Use faster storage:**
   * Move models to SSD if using HDD
   * Use NVMe SSD for best performance

2. **Adjust caching settings:**
   ```bash theme={null}
   python main.py --cache-classic       # Use the old style (aggressive) caching. 
   python main.py --cache-lru 10         # Increase size of LRU cache
   ```

### Memory Issues with Large Models

**"RuntimeError: CUDA out of memory":**

```bash theme={null}
# Progressive memory reduction
python main.py --lowvram          # First try
python main.py --novram           # If lowvram insufficient  
python main.py --cpu              # Last resort
```

**Model-specific memory optimization:**

```bash theme={null}
# Force lower precision
python main.py --force-fp16

# Reduce attention memory usage
python main.py --use-pytorch-cross-attention
```

<Note>
  For additional model configuration and setup information, see the [Models documentation](/development/core-concepts/models).
</Note>


# How to Troubleshoot and Solve ComfyUI Issues
Source: https://docs.comfy.org/troubleshooting/overview

Common ComfyUI issues, solutions, and how to report bugs effectively

<Tip>
  We receive a lot of feedback issues, and we find that most of the issues submitted are related to custom nodes. So please ensure that you have read the [custom node troubleshooting guide](/troubleshooting/custom-node-issues) before submitting an error report to ensure that the issue is not caused by ComfyUI core issues.
</Tip>

<Card title="Custom Node Troubleshooting Guide" icon="puzzle-piece" href="/troubleshooting/custom-node-issues">
  Check how to troubleshoot issues caused by custom nodes.
</Card>

## Common Issues & Quick Fixes

Before diving into detailed troubleshooting, try these common solutions:

### ComfyUI Won't Start

**Symptoms:** Application crashes on startup, black screen, or fails to load

**Quick fixes:**

1. **Check system requirements** - Ensure your system meets the [minimum requirements](/installation/system_requirements)
2. **Update GPU drivers** - Download latest drivers from NVIDIA/AMD/Intel

### Generation Fails or Produces Errors

**Symptoms:** "Prompt execution failed" dialog with "Show report" button, workflow stops executing

**Quick fixes:**

1. **Click "Show report"** - Read the detailed error message to identify the specific issue
2. **Check if it's a custom node issue** - [Follow our custom node troubleshooting guide](/troubleshooting/custom-node-issues)
3. **Verify model files** - See [Models documentation](/development/core-concepts/models) for model setup
4. **Check VRAM usage** - Close other applications using GPU memory

### Slow Performance

**Symptoms:** Very slow generation times, system freezing, out of memory errors

**Quick fixes:**

1. **Lower resolution/batch size** - Reduce image size or number of images
2. **Use memory optimization flags** - See performance optimization section below
3. **Close unnecessary applications** - Free up RAM and VRAM
4. **Check CPU/GPU usage** - Use Task Manager to identify bottlenecks

**Performance Optimization Commands:**

For low VRAM systems:

```bash theme={null}
# Low VRAM mode (uses cpu for text encoder)
python main.py --lowvram

# CPU mode (very slow but works with any hardware, only use as absolute last resort)
python main.py --cpu
```

For better performance:

```bash theme={null}
# Disable previews (saves VRAM and processing)
python main.py --preview-method none

# Use optimized attention mechanisms
python main.py --use-pytorch-cross-attention
python main.py --use-flash-attention

# Async weight offloading
python main.py --async-offload
```

For memory management:

```bash theme={null}
# Reserve specific VRAM amount for OS (in GB)
python main.py --reserve-vram 2

# Disable smart memory management
python main.py --disable-smart-memory

# Use different caching strategies
python main.py --cache-none      # Less RAM usage, but slower
python main.py --cache-lru 10    # Cache 10 results, faster
python main.py --cache-classic   # Use the old style (aggressive) caching. 
```

## Installation-Specific Issues

### Desktop App Issues

For comprehensive desktop installation troubleshooting, see the [Desktop Installation Guide](/installation/desktop/windows).

<Tabs>
  <Tab title="Windows">
    * **Unsupported device**: ComfyUI Desktop Windows only supports NVIDIA GPUs with CUDA. Use [ComfyUI Portable](/installation/comfyui_portable_windows) or [manual installation](/installation/manual_install) for other GPUs
    * **Installation fails**: Run installer as administrator, ensure at least 15GB disk space
    * **Maintenance page**: Check [mirror settings](/installation/desktop/windows#mirror-settings) if downloads fail
    * **Missing models**: Models are not copied during migration, only linked. Verify model paths
  </Tab>

  <Tab title="macOS">
    * **"App is damaged"**: Allow app in Security & Privacy settings
    * **Performance issues**: Grant Full Disk Access in Privacy settings
    * **Crashes**: Check Console app for crash reports
  </Tab>

  <Tab title="Linux">
    * **Missing libraries**: Install dependencies with package manager
    * **LD\_LIBRARY\_PATH errors**: PyTorch library path issues (see below)
  </Tab>
</Tabs>

### Manual Installation Issues

<Note>
  The documentation may be slightly out of date. If an issue occurs, please manually verify whether a newer stable version of pytorch or any of the listed libraries exists. Refer to resources like the [pytorch installation matrix](https://pytorch.org/get-started/locally/) or the [ROCm website](https://rocm.docs.amd.com/projects/install-on-linux/en/develop/install/3rd-party/pytorch-install.html#using-a-wheels-package).
</Note>

**Python version conflicts:**

```bash theme={null}
# Check Python version (3.9+ required, 3.12 recommended)
python --version

# Use virtual environment (recommended)
python -m venv comfyui_env
source comfyui_env/bin/activate  # Linux/Mac
comfyui_env\Scripts\activate     # Windows
```

**Package installation failures:**

```bash theme={null}
# Update pip first
python -m pip install --upgrade pip

# Install dependencies
pip install -r requirements.txt

# For NVIDIA GPUs (CUDA 13.0)
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu130

# For AMD GPUs (Linux only - ROCm 7.2)
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.2
```

### Linux-Specific Issues

**LD\_LIBRARY\_PATH errors:**

Common symptoms:

* "libcuda.so.1: cannot open shared object file"
* "libnccl.so: cannot open shared object file"
* "ImportError: libnvinfer.so.X: cannot open shared object file"

**Solutions:**

1. **Modern PyTorch installations (most common):**

```bash theme={null}
# For virtual environments with NVIDIA packages
export LD_LIBRARY_PATH=$VIRTUAL_ENV/lib/python3.12/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH

# For conda environments
export LD_LIBRARY_PATH=$CONDA_PREFIX/lib/python3.12/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH

# Or find your Python site-packages automatically
PYTHON_PATH=$(python -c "import site; print(site.getsitepackages()[0])")
export LD_LIBRARY_PATH=$PYTHON_PATH/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH

# You may also need other NVIDIA libraries
export LD_LIBRARY_PATH=$PYTHON_PATH/nvidia/cuda_runtime/lib:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=$PYTHON_PATH/nvidia/cublas/lib:$LD_LIBRARY_PATH
```

2. **Find what libraries you have:**

```bash theme={null}
# Check installed NVIDIA packages
python -c "import site; import os; nvidia_path=os.path.join(site.getsitepackages()[0], 'nvidia'); print('NVIDIA libs:', [d for d in os.listdir(nvidia_path) if os.path.isdir(os.path.join(nvidia_path, d))] if os.path.exists(nvidia_path) else 'Not found')"

# Find missing libraries that PyTorch needs
python -c "import torch; print(torch.__file__)"
ldd $(python -c "import torch; print(torch.__file__.replace('__init__.py', 'lib/libtorch_cuda.so'))")
```

3. **Set permanently for your environment:**

```bash theme={null}
# For virtual environments, add to activation script
echo 'export LD_LIBRARY_PATH=$VIRTUAL_ENV/lib/python*/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH' >> $VIRTUAL_ENV/bin/activate

# For conda environments
conda env config vars set LD_LIBRARY_PATH=$CONDA_PREFIX/lib/python*/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH

# For global bashrc (adjust Python version as needed)
echo 'export LD_LIBRARY_PATH=$(python -c "import site; print(site.getsitepackages()[0])")/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH' >> ~/.bashrc
```

4. **Alternative: Use ldconfig:**

```bash theme={null}
# Check current library cache
ldconfig -p | grep cuda
ldconfig -p | grep nccl

# If missing, add library paths (requires root)
sudo echo "/usr/local/cuda/lib64" > /etc/ld.so.conf.d/cuda.conf
sudo ldconfig
```

5. **Debug library loading:**

```bash theme={null}
# Verbose library loading to see what's missing
LD_DEBUG=libs python main.py 2>&1 | grep "looking for"

# Check PyTorch CUDA availability
python -c "import torch; print('CUDA available:', torch.cuda.is_available()); print('CUDA version:', torch.version.cuda)"
```

## Model-Related Issues

For comprehensive model troubleshooting including architecture mismatches, missing models, and loading errors, see the dedicated [Model Issues](/troubleshooting/model-issues) page.

## Network & API Issues

### Partner Nodes Not Working

**Symptoms:** API calls fail, timeout errors, quota exceeded

**Solutions:**

1. **Check API key validity** - Verify keys in [user settings](/interface/user)
2. **Check account credits** - Ensure sufficient [API credits](/interface/credits)
3. **Verify internet connection** - Test with other online services
4. **Check service status** - Provider may be experiencing downtime

### Connection Issues

**Symptoms:** "Failed to connect to server", timeout errors

**Solutions:**

1. **Check firewall settings** - Allow ComfyUI through firewall
2. **Try different port** - Default is 8188, try 8189 or 8190
3. **Disable VPN temporarily** - VPN may be blocking connections
4. **Check proxy settings** - Disable proxy if not required

### Frontend Issues

**"Frontend or Templates Package Not Updated":**

```bash theme={null}
# After updating ComfyUI via Git, update frontend dependencies
pip install -r requirements.txt
```

**"Can't Find Custom Node":**

* Disable node validation in ComfyUI settings

**"Error Toast About Workflow Failing Validation":**

* Disable workflow validation in settings temporarily
* Report the issue to the ComfyUI team

**Login Issues When Not on Localhost:**

* Normal login only works when accessing from localhost
* For LAN/remote access: Generate API key at [platform.comfy.org/login](https://platform.comfy.org/login)
* Use API key in login dialog or with `--api-key` command line argument

## Hardware-Specific Issues

### NVIDIA GPU Issues

**"Torch not compiled with CUDA enabled" error:**

```bash theme={null}
# First uninstall torch
pip uninstall torch

# Install stable PyTorch with CUDA 13.0
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu130

# For nightly builds (might have performance improvements)
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu132

# Verify CUDA support
python -c "import torch; print(torch.cuda.is_available())"
```

**GPU not detected:**

```bash theme={null}
# Check if GPU is visible
nvidia-smi

# Check driver version and CUDA compatibility
nvidia-smi --query-gpu=driver_version --format=csv
```

### AMD GPU Issues

**ROCm support (Linux only):**

```bash theme={null}
# Install stable ROCm PyTorch (7.2 at the time of writing)
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.2

# For nightly builds (ROCm 7.2 at the time of writing, which might have performance improvements)
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.2
```

**Unsupported AMD GPUs:**

```bash theme={null}
# For RDNA2 or older (6700, 6600)
HSA_OVERRIDE_GFX_VERSION=10.3.0 python main.py

# For RDNA3 cards (7600)
HSA_OVERRIDE_GFX_VERSION=11.0.0 python main.py
```

**Performance optimization:**

```bash theme={null}
# Enable experimental memory efficient attention (no longer necessary with PyTorch 2.4)
TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL=1 python main.py --use-pytorch-cross-attention

# Enable tunable operations (slow first run, but faster subsequent runs)
PYTORCH_TUNABLEOP_ENABLED=1 python main.py
```

### Apple Silicon (M1/M2/M3) Issues

**MPS backend setup:**

```bash theme={null}
# Install PyTorch nightly for Apple Silicon
# Follow Apple's guide: https://developer.apple.com/metal/pytorch/

# Check MPS availability
python -c "import torch; print(torch.backends.mps.is_available())"

# Launch ComfyUI
python main.py
```

**If MPS causes issues:**

```bash theme={null}
# Force CPU mode
python main.py --cpu

# With memory optimization
python main.py --force-fp16 --cpu
```

### Intel GPU Issues

**Option 1: Native PyTorch XPU support (Windows/Linux):**

```bash theme={null}
# Install PyTorch nightly with XPU support
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/xpu

# Launch ComfyUI
python main.py
```

**Option 2: Intel Extension for PyTorch (IPEX):**

```bash theme={null}
# For Intel Arc A-Series Graphics
conda install libuv
pip install torch==2.3.1.post0+cxx11.abi torchvision==0.18.1.post0+cxx11.abi torchaudio==2.3.1.post0+cxx11.abi intel-extension-for-pytorch==2.3.110.post0+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
```

## Getting Help & Reporting Bugs

### Before Reporting a Bug

1. **Check if it's a known issue:**
   * Search [GitHub Issues](https://github.com/Comfy-Org/ComfyUI/issues)
   * Check [ComfyUI Forum](https://forum.comfy.org/)
   * Review [Discord discussions](https://discord.com/invite/comfyorg)

2. **Try basic troubleshooting:**
   * Test with [default workflow](/get_started/first_generation)
   * Disable all custom nodes (see [custom node troubleshooting](/troubleshooting/custom-node-issues))
   * Check console/terminal for error messages
   * If using comfy-cli, try updating: `comfy node update all`

### How to Report Bugs Effectively

#### For ComfyUI Core Issues

**Where to report:** [GitHub Issues](https://github.com/Comfy-Org/ComfyUI/issues)

#### For Desktop App Issues

**Where to report:** [Desktop GitHub Issues](https://github.com/Comfy-Org/desktop/issues)

#### For Frontend Issues

**Where to report:** [Frontend GitHub Issues](https://github.com/Comfy-Org/ComfyUI_frontend/issues)

#### For Custom Node Issues

**Where to report:** Contact the specific custom node developer

### Required Information

When reporting any issue, include:

<Steps>
  <Step title="System Information">
    <Tabs>
      <Tab title="From ComfyUI Interface">
        **System Information (can be found in the About page in settings):**

        * Operating System (Windows 11, macOS 14.1, Ubuntu 22.04, etc.)
        * ComfyUI version (check About page in settings)
        * Python version: `python --version`
        * PyTorch version: `python -c "import torch; print(torch.__version__)"`
        * GPU model and driver version
        * Installation method (Desktop, Portable, Manual, comfy-cli)

          <img alt="About page in settings" />
      </Tab>

      <Tab title="From Command Line">
        <Tabs>
          <Tab title="Windows">
            ```bash theme={null}
            # System info
            systeminfo | findstr /C:"OS Name" /C:"OS Version"

            # GPU info
            wmic path win32_VideoController get name

            # Python & PyTorch info
            python --version
            python -c "import torch; print(f'PyTorch: {torch.__version__}')"
            python -c "import torch; print(f'CUDA Available: {torch.cuda.is_available()}')"
            ```
          </Tab>

          <Tab title="macOS/Linux">
            ```bash theme={null}
            # System info
            uname -a

            # GPU info (Linux)
            lspci | grep VGA

            # Python & PyTorch info
            python --version
            python -c "import torch; print(f'PyTorch: {torch.__version__}')"
            python -c "import torch; print(f'CUDA Available: {torch.cuda.is_available()}')"
            ```
          </Tab>
        </Tabs>
      </Tab>
    </Tabs>
  </Step>

  <Step title="Desktop App issues">
    **For Desktop App issues, also include:**

    * Log files from: `C:\Users\<username>\AppData\Roaming\ComfyUI\logs` (Windows)
    * Config files from: `C:\Users\<username>\AppData\Roaming\ComfyUI` (Windows)
  </Step>

  <Step title="Problem Details">
    **Problem Details:**

    * Clear description of the issue
    * Steps to reproduce the problem
    * Expected vs actual behavior
    * Screenshots or videos if applicable

    **Error Messages:**

    * Full error text from console/terminal
    * Browser console errors (F12 → Console tab)
    * Any crash logs or error dialogs
  </Step>

  <Step title="Additional Context">
    **Additional Context:**

    * List of installed custom nodes
    * Workflow file (.json) that reproduces the issue
    * Recent changes (new installations, updates, etc.)
  </Step>
</Steps>

## Community Resources

* **Official Forum:** [forum.comfy.org](https://forum.comfy.org/)
* **Discord:** [ComfyUI Discord Server](https://discord.com/invite/comfyorg)
* **Reddit:** [r/comfyui](https://reddit.com/r/comfyui)
* **YouTube:** [ComfyUI Tutorials](https://www.youtube.com/@comfyorg)


# Get proxyvidutasks creations
Source: https://docs.comfy.org/api-reference/api-nodes/get-proxyvidutasks-creations

https://api.comfy.org/openapi get /proxy/vidu/tasks/{id}/creations



# Post proxyviduextend
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyviduextend

https://api.comfy.org/openapi post /proxy/vidu/extend



# Post proxyviduimg2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyviduimg2video

https://api.comfy.org/openapi post /proxy/vidu/img2video



# Post proxyvidumultiframe
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidumultiframe

https://api.comfy.org/openapi post /proxy/vidu/multiframe



# Post proxyvidureference2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidureference2video

https://api.comfy.org/openapi post /proxy/vidu/reference2video



# Post proxyvidustart end2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidustart-end2video

https://api.comfy.org/openapi post /proxy/vidu/start-end2video



# Post proxyvidutext2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidutext2video

https://api.comfy.org/openapi post /proxy/vidu/text2video



# Add tags to asset
Source: https://docs.comfy.org/api-reference/cloud/asset/add-tags-to-asset

/openapi-cloud.yaml post /api/assets/{id}/tags
Adds one or more tags to an existing asset



# Check if asset exists by hash
Source: https://docs.comfy.org/api-reference/cloud/asset/check-if-asset-exists-by-hash

/openapi-cloud.yaml head /api/assets/hash/{hash}
Checks if content with the given hash exists in cloud storage.
Returns 200 if the content exists, 404 if it doesn't.
Useful for checking availability before using `/api/assets/from-hash`.




# Create asset reference from existing hash
Source: https://docs.comfy.org/api-reference/cloud/asset/create-asset-reference-from-existing-hash

/openapi-cloud.yaml post /api/assets/from-hash
Creates a new asset reference using an existing hash from cloud storage.
This avoids re-uploading file content when the underlying data already exists,
which is useful for large files or when referencing well-known assets.
The user provides their own metadata and tags for the new reference.




# Delete asset
Source: https://docs.comfy.org/api-reference/cloud/asset/delete-asset

/openapi-cloud.yaml delete /api/assets/{id}
Deletes an asset and its content from storage.
Both the database record and storage content are deleted.




# Get asset details
Source: https://docs.comfy.org/api-reference/cloud/asset/get-asset-details

/openapi-cloud.yaml get /api/assets/{id}
Retrieves detailed information about a specific asset



# Get asset metadata from remote URL
Source: https://docs.comfy.org/api-reference/cloud/asset/get-asset-metadata-from-remote-url

/openapi-cloud.yaml get /api/assets/remote-metadata
Retrieves metadata for an asset from a remote download URL without downloading the entire file.
Supports various sources including CivitAI and other model repositories.
Uses HEAD requests or API calls to fetch metadata efficiently.
This endpoint is for previewing metadata before downloading, not for getting metadata of existing assets.




# Get tag histogram for filtered assets
Source: https://docs.comfy.org/api-reference/cloud/asset/get-tag-histogram-for-filtered-assets

/openapi-cloud.yaml get /api/assets/tags/refine
Returns a histogram of tags appearing on assets matching the given filters.
Useful for refining asset searches by showing available tags and their counts.
Only returns tags with non-zero counts (tags that exist on matching assets).




# Initiate background download for large files
Source: https://docs.comfy.org/api-reference/cloud/asset/initiate-background-download-for-large-files

/openapi-cloud.yaml post /api/assets/download
Initiates a background download job for large files from Huggingface or Civitai.

If the file already exists in storage, the asset record is created immediately and returned (200 OK).
If the file doesn't exist, a background task is created and the task ID is returned (202 Accepted).
The frontend can track progress using GET /api/tasks/{task_id}.




# List all tags
Source: https://docs.comfy.org/api-reference/cloud/asset/list-all-tags

/openapi-cloud.yaml get /api/tags
Retrieves a list of all tags used across assets.
Includes usage counts and filtering options.




# List user assets
Source: https://docs.comfy.org/api-reference/cloud/asset/list-user-assets

/openapi-cloud.yaml get /api/assets
Retrieves a paginated list of assets belonging to the authenticated user.
Supports filtering by tags, name, metadata, and sorting options.




# Remove tags from asset
Source: https://docs.comfy.org/api-reference/cloud/asset/remove-tags-from-asset

/openapi-cloud.yaml delete /api/assets/{id}/tags
Removes one or more tags from an existing asset



# Update asset metadata
Source: https://docs.comfy.org/api-reference/cloud/asset/update-asset-metadata

/openapi-cloud.yaml put /api/assets/{id}
Updates an asset's metadata. At least one field must be provided.
Only name, tags, and user_metadata can be updated.




# Upload a new asset
Source: https://docs.comfy.org/api-reference/cloud/asset/upload-a-new-asset

/openapi-cloud.yaml post /api/assets
Uploads a new asset to the system with associated metadata.
Supports two upload methods:
1. Direct file upload (multipart/form-data)
2. URL-based upload (application/json with source: "url")

If an asset with the same hash already exists, returns the existing asset.




# Get related mask layer files
Source: https://docs.comfy.org/api-reference/cloud/file/get-related-mask-layer-files

/openapi-cloud.yaml get /api/files/mask-layers
Given a mask file (any of the 4 layers), returns all related mask layer files.
This is used by the mask editor to load the paint, mask, and painted layers
when reopening a previously edited mask.




# Upload a mask image
Source: https://docs.comfy.org/api-reference/cloud/file/upload-a-mask-image

/openapi-cloud.yaml post /api/upload/mask
Upload a mask image to be applied to an existing image.

Image limits apply to both the uploaded mask and the referenced
original image:
  - Maximum file size: 50 MB
  - Maximum width/height per edge: 16384 px
  - Maximum total pixel count: 64 megapixels (67108864 pixels)

Uploads that exceed any of these limits are rejected with HTTP 400.




# Upload an image file
Source: https://docs.comfy.org/api-reference/cloud/file/upload-an-image-file

/openapi-cloud.yaml post /api/upload/image
Upload an image file to cloud storage.

Image limits:
  - Maximum file size: 50 MB
  - Maximum width/height per edge: 16384 px
  - Maximum total pixel count: 64 megapixels (67108864 pixels)

Uploads that exceed any of these limits are rejected with HTTP 400.




# View a file
Source: https://docs.comfy.org/api-reference/cloud/file/view-a-file

/openapi-cloud.yaml get /api/view
Retrieve and view a file from the ComfyUI file system.
This endpoint is typically used to view generated images or other output files.




# Get execution history (v2)
Source: https://docs.comfy.org/api-reference/cloud/job/get-execution-history-v2

/openapi-cloud.yaml get /api/history_v2
**Deprecated.** Use [`/api/jobs`](#tag/job/GET/api/jobs) instead. This endpoint is maintained for ComfyUI compatibility but will be removed in a future release; no removal date set.

Retrieve execution history for the authenticated user with pagination support.
Returns a lightweight history format with filtered prompt data (workflow removed from extra_pnginfo).




# Get full job details
Source: https://docs.comfy.org/api-reference/cloud/job/get-full-job-details

/openapi-cloud.yaml get /api/jobs/{job_id}
Retrieve complete details for a specific job including workflow and outputs.
Used for detail views, workflow re-execution, and debugging.




# Get history for specific prompt
Source: https://docs.comfy.org/api-reference/cloud/job/get-history-for-specific-prompt

/openapi-cloud.yaml get /api/history_v2/{prompt_id}
**Deprecated.** Use [`/api/jobs/{job_id}`](#tag/job/GET/api/jobs/{job_id}) instead — the `prompt_id` returned by `/api/prompt` is the same value as `job_id`. This endpoint is maintained for ComfyUI compatibility but will be removed in a future release; no removal date set.

Retrieve detailed execution history for a specific prompt ID.
Returns full history data including complete prompt information.




# Get job status
Source: https://docs.comfy.org/api-reference/cloud/job/get-job-status

/openapi-cloud.yaml get /api/job/{job_id}/status
Returns the current status of a specific job by ID



# Get queue information
Source: https://docs.comfy.org/api-reference/cloud/job/get-queue-information

/openapi-cloud.yaml get /api/queue
Returns information about running and pending items in the queue



# Interrupt currently running jobs
Source: https://docs.comfy.org/api-reference/cloud/job/interrupt-currently-running-jobs

/openapi-cloud.yaml post /api/interrupt
Cancel all currently RUNNING jobs for the authenticated user.
This will interrupt any job that is currently in 'in_progress' status.
Note: This endpoint only affects running jobs. To cancel pending jobs, use /api/queue.




# List jobs with pagination and filtering
Source: https://docs.comfy.org/api-reference/cloud/job/list-jobs-with-pagination-and-filtering

/openapi-cloud.yaml get /api/jobs
Retrieve a paginated list of jobs for the authenticated user.
Returns lightweight job data optimized for list views.
Workflow and full outputs are excluded to reduce payload size.




# Manage execution history
Source: https://docs.comfy.org/api-reference/cloud/job/manage-execution-history

/openapi-cloud.yaml post /api/history
Clear all history for the authenticated user or delete specific job IDs.
Supports clearing all history or deleting specific job IDs.




# Manage queue operations
Source: https://docs.comfy.org/api-reference/cloud/job/manage-queue-operations

/openapi-cloud.yaml post /api/queue
Cancel specific PENDING jobs by ID or clear all pending jobs in the queue.
Note: This endpoint only affects pending jobs. To cancel running jobs, use /api/interrupt.




# Get available model folders
Source: https://docs.comfy.org/api-reference/cloud/model/get-available-model-folders

/openapi-cloud.yaml get /api/experiment/models
Returns a list of model folders available in the system.
This is an experimental endpoint that replaces the legacy /models endpoint.




# Get model preview image
Source: https://docs.comfy.org/api-reference/cloud/model/get-model-preview-image

/openapi-cloud.yaml get /api/experiment/models/preview/{folder}/{path_index}/{filename}
Returns a preview image for the specified model.
The image is returned in WebP format for optimal performance.




# Get models in a specific folder
Source: https://docs.comfy.org/api-reference/cloud/model/get-models-in-a-specific-folder

/openapi-cloud.yaml get /api/experiment/models/{folder}
Returns a list of models available in the specified folder.
This is an experimental endpoint that provides enhanced model information.




# Get all node information
Source: https://docs.comfy.org/api-reference/cloud/node/get-all-node-information

/openapi-cloud.yaml get /api/object_info
Returns information about all available nodes



# Get server feature flags
Source: https://docs.comfy.org/api-reference/cloud/node/get-server-feature-flags

/openapi-cloud.yaml get /api/features
Returns the server's feature capabilities



# Get system statistics
Source: https://docs.comfy.org/api-reference/cloud/system/get-system-statistics

/openapi-cloud.yaml get /api/system_stats
Returns system statistics including ComfyUI version, device info, and system resources



# Delete a user data file
Source: https://docs.comfy.org/api-reference/cloud/user/delete-a-user-data-file

/openapi-cloud.yaml delete /api/userdata/{file}
Delete a user data file from the database. The file parameter should be
the relative path within the user's data directory.




# Get current user information
Source: https://docs.comfy.org/api-reference/cloud/user/get-current-user-information

/openapi-cloud.yaml get /api/user
Returns information about the currently authenticated user



# Get user data file
Source: https://docs.comfy.org/api-reference/cloud/user/get-user-data-file

/openapi-cloud.yaml get /api/userdata/{file}
Returns the requested user data file if it exists.



# List user data files
Source: https://docs.comfy.org/api-reference/cloud/user/list-user-data-files

/openapi-cloud.yaml get /api/userdata
Returns a list of user data files in the specified directory, optionally recursively and with full metadata.



# Upload or update a user data file
Source: https://docs.comfy.org/api-reference/cloud/user/upload-or-update-a-user-data-file

/openapi-cloud.yaml post /api/userdata/{file}
Upload a file to a user's data directory. Optional query parameters allow
control over overwrite behavior and response detail.




# Get a specific subgraph blueprint
Source: https://docs.comfy.org/api-reference/cloud/workflow/get-a-specific-subgraph-blueprint

/openapi-cloud.yaml get /api/global_subgraphs/{id}
Returns the full data for a specific subgraph blueprint by ID



# Get available subgraph blueprints
Source: https://docs.comfy.org/api-reference/cloud/workflow/get-available-subgraph-blueprints

/openapi-cloud.yaml get /api/global_subgraphs
Returns a list of globally available subgraph blueprints.
These are pre-built workflow components that can be used as nodes.
The data field contains a promise that resolves to the full subgraph JSON.




# Get available workflow templates
Source: https://docs.comfy.org/api-reference/cloud/workflow/get-available-workflow-templates

/openapi-cloud.yaml get /api/workflow_templates
Returns available workflow templates



# Get information about current prompt execution
Source: https://docs.comfy.org/api-reference/cloud/workflow/get-information-about-current-prompt-execution

/openapi-cloud.yaml get /api/prompt
Returns information about the current prompt in the execution queue



# Submit a workflow for execution
Source: https://docs.comfy.org/api-reference/cloud/workflow/submit-a-workflow-for-execution

/openapi-cloud.yaml post /api/prompt
Submit a workflow to be executed by the backend.
The workflow is a JSON object describing the nodes and their connections.




# Get the status of one skin enhancer task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-one-skin-enhancer-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/skin-enhancer/{task_id}
Get the status of a skin enhancer task (works for both Creative and Faithful modes)



# Get the status of the Precision V2 upscaling task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-precision-v2-upscaling-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-upscaler-precision-v2/{task_id}
Returns the current status and output URL of a specific precision upscaler V2 task.



# Get the status of the relight task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-relight-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-relight/{task_id}
Get the status of the relight task



# Get the status of the style transfer task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-style-transfer-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-style-transfer/{task_id}
Get the status of the style transfer task



# Get the status of the upscaling task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-upscaling-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-upscaler/{task_id}
Get the status of the upscaling task



# Relight an image
Source: https://docs.comfy.org/api-reference/freepik/relight-an-image

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-relight
Relight an image using AI. This endpoint accepts a variety of parameters to customize the generated images.




# Skin enhancer using AI (Creative)
Source: https://docs.comfy.org/api-reference/freepik/skin-enhancer-using-ai-creative

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/skin-enhancer/creative
Enhance skin in images using AI with the Creative mode. This mode provides more artistic and stylized enhancements.



# Skin enhancer using AI (Faithful)
Source: https://docs.comfy.org/api-reference/freepik/skin-enhancer-using-ai-faithful

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/skin-enhancer/faithful
Enhance skin in images using AI with the Faithful mode. This mode preserves the original appearance while improving skin quality.



# Skin enhancer using AI (Flexible)
Source: https://docs.comfy.org/api-reference/freepik/skin-enhancer-using-ai-flexible

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/skin-enhancer/flexible
Enhance skin in images using AI with the Flexible mode. This mode allows you to choose the optimization target for the enhancement.



# Style transfer an image
Source: https://docs.comfy.org/api-reference/freepik/style-transfer-an-image

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-style-transfer
Style transfer an image using AI.



# Upscale an image with Magnific
Source: https://docs.comfy.org/api-reference/freepik/upscale-an-image-with-magnific

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-upscaler
This asynchronous endpoint enables image upscaling using advanced AI algorithms.
Upon submission, it returns a unique task_id which can be used to track the progress.
For real-time production use, include the optional webhook_url parameter to receive
an automated notification once the task has been completed.




# Upscale an image with Precision V2
Source: https://docs.comfy.org/api-reference/freepik/upscale-an-image-with-precision-v2

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-upscaler-precision-v2
Upscales an image while adding new visual elements or details (V2).
This endpoint may modify the original image content based on the prompt and inferred context.
Upon submission, it returns a unique task_id which can be used to track the progress.




# Add review to a specific version of a node
Source: https://docs.comfy.org/api-reference/registry/add-review-to-a-specific-version-of-a-node

https://api.comfy.org/openapi post /nodes/{nodeId}/reviews



# Claim nodeId into publisherId for the authenticated publisher
Source: https://docs.comfy.org/api-reference/registry/claim-nodeid-into-publisherid-for-the-authenticated-publisher

https://api.comfy.org/openapi post /publishers/{publisherId}/nodes/{nodeId}/claim-my-node
This endpoint allows a publisher to claim an unclaimed node that they own the repo, which is identified by the nodeId. The unclaimed node's repository must be owned by the authenticated user.




# Create a new custom node
Source: https://docs.comfy.org/api-reference/registry/create-a-new-custom-node

https://api.comfy.org/openapi post /publishers/{publisherId}/nodes



# Create a new personal access token
Source: https://docs.comfy.org/api-reference/registry/create-a-new-personal-access-token

https://api.comfy.org/openapi post /publishers/{publisherId}/tokens



# Create a new publisher
Source: https://docs.comfy.org/api-reference/registry/create-a-new-publisher

https://api.comfy.org/openapi post /publishers



# create comfy-nodes for certain node
Source: https://docs.comfy.org/api-reference/registry/create-comfy-nodes-for-certain-node

https://api.comfy.org/openapi post /nodes/{nodeId}/versions/{version}/comfy-nodes



# Create Node Translations
Source: https://docs.comfy.org/api-reference/registry/create-node-translations

https://api.comfy.org/openapi post /nodes/{nodeId}/translations



# Delete a publisher
Source: https://docs.comfy.org/api-reference/registry/delete-a-publisher

https://api.comfy.org/openapi delete /publishers/{publisherId}



# Delete a specific node
Source: https://docs.comfy.org/api-reference/registry/delete-a-specific-node

https://api.comfy.org/openapi delete /publishers/{publisherId}/nodes/{nodeId}



# Delete a specific personal access token
Source: https://docs.comfy.org/api-reference/registry/delete-a-specific-personal-access-token

https://api.comfy.org/openapi delete /publishers/{publisherId}/tokens/{tokenId}



# Get information about the calling user.
Source: https://docs.comfy.org/api-reference/registry/get-information-about-the-calling-user

https://api.comfy.org/openapi get /users



# get specify comfy-node based on its id
Source: https://docs.comfy.org/api-reference/registry/get-specify-comfy-node-based-on-its-id

https://api.comfy.org/openapi get /nodes/{nodeId}/versions/{version}/comfy-nodes/{comfyNodeName}



# List all node versions given some filters.
Source: https://docs.comfy.org/api-reference/registry/list-all-node-versions-given-some-filters

https://api.comfy.org/openapi get /versions



# List all versions of a node
Source: https://docs.comfy.org/api-reference/registry/list-all-versions-of-a-node

https://api.comfy.org/openapi get /nodes/{nodeId}/versions



# list comfy-nodes for node version
Source: https://docs.comfy.org/api-reference/registry/list-comfy-nodes-for-node-version

https://api.comfy.org/openapi get /nodes/{nodeId}/versions/{version}/comfy-nodes



# Publish a new version of a node
Source: https://docs.comfy.org/api-reference/registry/publish-a-new-version-of-a-node

https://api.comfy.org/openapi post /publishers/{publisherId}/nodes/{nodeId}/versions



# Retrieve a publisher by ID
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-publisher-by-id

https://api.comfy.org/openapi get /publishers/{publisherId}



# Retrieve a specific version of a node
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-specific-version-of-a-node

https://api.comfy.org/openapi get /nodes/{nodeId}/versions/{versionId}



# Retrieve all nodes
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-nodes

https://api.comfy.org/openapi get /publishers/{publisherId}/nodes



# Retrieve all nodes
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-nodes-1

https://api.comfy.org/openapi get /publishers/{publisherId}/nodes/v2



# Retrieve all publishers
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-publishers

https://api.comfy.org/openapi get /publishers



# Retrieve all publishers for a given user
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-publishers-for-a-given-user

https://api.comfy.org/openapi get /users/publishers/



# Retrieve permissions the user has for a given publisher
Source: https://docs.comfy.org/api-reference/registry/retrieve-permissions-the-user-has-for-a-given-publisher

https://api.comfy.org/openapi get /publishers/{publisherId}/nodes/{nodeId}/permissions



# Retrieve permissions the user has for a given publisher
Source: https://docs.comfy.org/api-reference/registry/retrieve-permissions-the-user-has-for-a-given-publisher-1

https://api.comfy.org/openapi get /publishers/{publisherId}/permissions



# Unpublish (delete) a specific version of a node
Source: https://docs.comfy.org/api-reference/registry/unpublish-delete-a-specific-version-of-a-node

https://api.comfy.org/openapi delete /publishers/{publisherId}/nodes/{nodeId}/versions/{versionId}



# Update a publisher
Source: https://docs.comfy.org/api-reference/registry/update-a-publisher

https://api.comfy.org/openapi put /publishers/{publisherId}



# Update a specific comfy-node
Source: https://docs.comfy.org/api-reference/registry/update-a-specific-comfy-node

https://api.comfy.org/openapi put /nodes/{nodeId}/versions/{version}/comfy-nodes/{comfyNodeName}



# Update a specific node
Source: https://docs.comfy.org/api-reference/registry/update-a-specific-node

https://api.comfy.org/openapi put /publishers/{publisherId}/nodes/{nodeId}



# Update changelog and deprecation status of a node version
Source: https://docs.comfy.org/api-reference/registry/update-changelog-and-deprecation-status-of-a-node-version

https://api.comfy.org/openapi put /publishers/{publisherId}/nodes/{nodeId}/versions/{versionId}
Update only the changelog and deprecated status of a specific version of a node.



# Validate if a publisher username is available
Source: https://docs.comfy.org/api-reference/registry/validate-if-a-publisher-username-is-available

https://api.comfy.org/openapi get /publishers/validate
Checks if the publisher username is already taken.



# Get release notes
Source: https://docs.comfy.org/api-reference/releases/get-release-notes

https://api.comfy.org/openapi get /releases
Fetch release notes from Strapi with caching



# Generate music from text prompt
Source: https://docs.comfy.org/api-reference/sonilo/generate-music-from-text-prompt

https://api.comfy.org/openapi post /proxy/sonilo/t2m/generate
Generate music from a text prompt using Sonilo text-to-music AI.
Requires a prompt describing the desired music. Duration is optional and will be inferred if not provided.
Returns a streaming NDJSON response with duration, titles, audio chunks, and completion events.




# Generate music from video
Source: https://docs.comfy.org/api-reference/sonilo/generate-music-from-video

https://api.comfy.org/openapi post /proxy/sonilo/v2m/generate
Generate music from a video using Sonilo video-to-music AI.
Accepts either a video file upload or a video URL, with an optional prompt.
Returns a streaming NDJSON response with duration, titles, audio chunks, and completion events.
Max video duration: 6 minutes. Max upload size: 1024MB.




# ComfyUI Hunyuan3D-2 Examples
Source: https://docs.comfy.org/tutorials/3d/hunyuan3D-2

This guide will demonstrate how to use Hunyuan3D-2 in ComfyUI to generate 3D assets.

# Hunyuan3D 2.0 Introduction

![Hunyuan 3D 2](https://raw.githubusercontent.com/Tencent/Hunyuan3D-2/main/assets/images/e2e-1.gif)
![Hunyuan 3D 2](https://raw.githubusercontent.com/Tencent/Hunyuan3D-2/main/assets/images/e2e-2.gif)
[Hunyuan3D 2.0](https://github.com/Tencent/Hunyuan3D-2) is an open-source 3D asset generation model released by Tencent, capable of generating high-fidelity 3D models with high-resolution texture maps through text or images.

Hunyuan3D 2.0 adopts a two-stage generation approach, first generating a geometry model without textures, then synthesizing high-resolution texture maps. This effectively separates the complexity of shape and texture generation. Below are the two core components of Hunyuan3D 2.0:

1. **Geometry Generation Model (Hunyuan3D-DiT)**: Based on a flow diffusion Transformer architecture, it generates untextured geometric models that precisely match input conditions.
2. **Texture Generation Model (Hunyuan3D-Paint)**: Combines geometric conditions and multi-view diffusion techniques to add high-resolution textures to models, supporting PBR materials.

**Key Advantages**

* **High-Precision Generation**: Sharp geometric structures, rich texture colors, support for PBR material generation, achieving near-realistic lighting effects.
* **Diverse Usage Methods**: Provides code calls, Blender plugins, Gradio applications, and online experience through the official website, suitable for different user needs.
* **Lightweight and Compatibility**: The Hunyuan3D-2mini model requires only 5GB VRAM, the standard version needs 6GB VRAM for shape generation, and the complete process (shape + texture) requires only 12GB VRAM.

Recently (March 18, 2025), Hunyuan3D 2.0 also introduced a multi-view shape generation model (Hunyuan3D-2mv), which supports generating more detailed geometric structures from inputs at different angles.

This example includes three workflows:

* Using Hunyuan3D-2mv with multiple view inputs to generate 3D models
* Using Hunyuan3D-2mv-turbo with multiple view inputs to generate 3D models
* Using Hunyuan3D-2 with a single view input to generate 3D models

<Tip>
  ComfyUI now natively supports Hunyuan3D-2mv, but does not yet support texture and material generation. Please make sure you have updated to the latest version of [ComfyUI](https://github.com/Comfy-Org/ComfyUI) before starting.

  The workflow example PNG images in this tutorial contain workflow JSON in their metadata:

  * You can drag them directly into ComfyUI
  * Or use the menu `Workflows` -> `Open (ctrl+o)`

  This will load the corresponding workflow and prompt you to download the required models. The generated `.glb` format models will be output to the `ComfyUI/output/mesh` folder.
</Tip>

## ComfyUI Hunyuan3D-2mv Workflow Example

In the Hunyuan3D-2mv workflow, we'll use multi-view images to generate a 3D model. Note that multiple view images are not mandatory in this workflow - you can use only the `front` view image to generate a 3D model.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<a href="https://cloud.comfy.org/?template=3d_hunyuan3d_multiview_to_model&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 1. Workflow

Please download the images below and drag  into ComfyUI to load the workflow.
![Hunyuan3D-2mv workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/hunyuan-3d-multiview-elf.webp)

Download the images below we will use them as input images.

![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/front.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/left.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/back.png)

<Tip>
  In this example, the input images have already been preprocessed to remove excess background. In actual use, you can use custom nodes like [ComfyUI\_essentials](https://github.com/cubiq/ComfyUI_essentials) to automatically remove excess background.
</Tip>

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-mv: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2mv/resolve/main/hunyuan3d-dit-v2-mv/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2-mv.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2-mv.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2mv" />

1. Ensure that the Image Only Checkpoint Loader(img2vid model) has loaded our downloaded and renamed `hunyuan3d-dit-v2-mv.safetensors` model
2. Load the corresponding view images in each of the `Load Image` nodes
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

If you need to add more views, make sure to load other view images in the `Hunyuan3Dv2ConditioningMultiView` node, and ensure that you load the corresponding view images in the `Load Image` nodes.

## Hunyuan3D-2mv-turbo Workflow

In the Hunyuan3D-2mv-turbo workflow, we'll use the Hunyuan3D-2mv-turbo model to generate 3D models. This model is a step distillation version of Hunyuan3D-2mv, allowing for faster 3D model generation. In this version of the workflow, we set `cfg` to 1.0 and add a `flux guidance` node to control the `distilled cfg` generation.

<a href="https://cloud.comfy.org/?template=3d_hunyuan3d_multiview_to_model_turbo&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 1. Workflow

Please download the images below and drag into ComfyUI to load the workflow.

![Hunyuan3D-2mv-turbo workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/hunyuan-3d-turbo.webp)

Download the images below we will use them as input images.

![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/front.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/right.png)

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-mv-turbo: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2mv/resolve/main/hunyuan3d-dit-v2-mv-turbo/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2-mv-turbo.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2-mv-turbo.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2mv_turbo" />

1. Ensure that the `Image Only Checkpoint Loader(img2vid model)` node has loaded our renamed `hunyuan3d-dit-v2-mv-turbo.safetensors` model
2. Load the corresponding view images in each of the `Load Image` nodes
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Hunyuan3D-2 Single View Workflow

In the Hunyuan3D-2 workflow, we'll use the Hunyuan3D-2 model to generate 3D models. This model is not a multi-view model. In this workflow, we use the `Hunyuan3Dv2Conditioning` node instead of the `Hunyuan3Dv2ConditioningMultiView` node.

<a href="https://cloud.comfy.org/?template=3d_hunyuan3d_image_to_model&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 1. Workflow

Please download the image below and drag it into ComfyUI to load the workflow.

![Hunyuan3D-2 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d-non-multiview-train.webp)

Download the image below we will use it as input image.
![ComfyUI Hunyuan 3D 2 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan_3d_v2_non_multiview_train.png)

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-0: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2/resolve/main/hunyuan3d-dit-v2-0/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2" />

1. Ensure that the `Image Only Checkpoint Loader(img2vid model)` node has loaded our renamed `hunyuan3d-dit-v2.safetensors` model
2. Load the image in the `Load Image` node
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Community Resources

Below are ComfyUI community resources related to Hunyuan3D-2

* [ComfyUI-Hunyuan3DWrapper](https://github.com/kijai/ComfyUI-Hunyuan3DWrapper)
* [Kijai/Hunyuan3D-2\_safetensors](https://huggingface.co/Kijai/Hunyuan3D-2_safetensors/tree/main)
* [ComfyUI-3D-Pack](https://github.com/MrForExample/ComfyUI-3D-Pack)

## Hunyuan3D 2.0 Open-Source Model Series

Currently, Hunyuan3D 2.0 has open-sourced multiple models covering the complete 3D generation process. You can visit [Hunyuan3D-2](https://github.com/Tencent/Hunyuan3D-2) for more information.

**Hunyuan3D-2mini Series**

| Model                 | Description               | Date       | Parameters | Huggingface                                                                             |
| --------------------- | ------------------------- | ---------- | ---------- | --------------------------------------------------------------------------------------- |
| Hunyuan3D-DiT-v2-mini | Mini Image to Shape Model | 2025-03-18 | 0.6B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mini/tree/main/hunyuan3d-dit-v2-mini) |

**Hunyuan3D-2mv Series**

| Model                    | Description                                                                                                 | Date       | Parameters | Huggingface                                                                              |
| ------------------------ | ----------------------------------------------------------------------------------------------------------- | ---------- | ---------- | ---------------------------------------------------------------------------------------- |
| Hunyuan3D-DiT-v2-mv-Fast | Guidance Distillation Version, can halve DIT inference time                                                 | 2025-03-18 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mv/tree/main/hunyuan3d-dit-v2-mv-fast) |
| Hunyuan3D-DiT-v2-mv      | Multi-view Image to Shape Model, suitable for 3D creation requiring multiple angles to understand the scene | 2025-03-18 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mv/tree/main/hunyuan3d-dit-v2-mv)      |

**Hunyuan3D-2 Series**

| Model                   | Description                 | Date       | Parameters | Huggingface                                                                           |
| ----------------------- | --------------------------- | ---------- | ---------- | ------------------------------------------------------------------------------------- |
| Hunyuan3D-DiT-v2-0-Fast | Guidance Distillation Model | 2025-02-03 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-dit-v2-0-fast) |
| Hunyuan3D-DiT-v2-0      | Image to Shape Model        | 2025-01-21 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-dit-v2-0)      |
| Hunyuan3D-Paint-v2-0    | Texture Generation Model    | 2025-01-21 | 1.3B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-paint-v2-0)    |
| Hunyuan3D-Delight-v2-0  | Image Delight Model         | 2025-01-21 | 1.3B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-delight-v2-0)  |


# Generate a short-lived JWT admin token
Source: https://docs.comfy.org/api-reference/admin/generate-a-short-lived-jwt-admin-token

https://api.comfy.org/openapi post /admin/generate-token
Generates a short-lived JWT admin token for browser-based admin operations.
The user must already be authenticated with Firebase and have admin privileges.
The generated token expires after 1 hour.




# Add review to a specific version of a node
Source: https://docs.comfy.org/api-reference/registry/add-review-to-a-specific-version-of-a-node

https://api.comfy.org/openapi post /nodes/{nodeId}/reviews



# create comfy-nodes for certain node
Source: https://docs.comfy.org/api-reference/registry/create-comfy-nodes-for-certain-node

https://api.comfy.org/openapi post /nodes/{nodeId}/versions/{version}/comfy-nodes



# Create Node Translations
Source: https://docs.comfy.org/api-reference/registry/create-node-translations

https://api.comfy.org/openapi post /nodes/{nodeId}/translations



# Get server feature flags
Source: https://docs.comfy.org/api-reference/registry/get-server-feature-flags

https://api.comfy.org/openapi get /features
Returns the server's feature capabilities



# get specify comfy-node based on its id
Source: https://docs.comfy.org/api-reference/registry/get-specify-comfy-node-based-on-its-id

https://api.comfy.org/openapi get /nodes/{nodeId}/versions/{version}/comfy-nodes/{comfyNodeName}



# list all comfy-nodes
Source: https://docs.comfy.org/api-reference/registry/list-all-comfy-nodes

https://api.comfy.org/openapi get /comfy-nodes



# List all versions of a node
Source: https://docs.comfy.org/api-reference/registry/list-all-versions-of-a-node

https://api.comfy.org/openapi get /nodes/{nodeId}/versions



# list comfy-nodes for node version
Source: https://docs.comfy.org/api-reference/registry/list-comfy-nodes-for-node-version

https://api.comfy.org/openapi get /nodes/{nodeId}/versions/{version}/comfy-nodes



# Retrieve a node by ComfyUI node name
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-node-by-comfyui-node-name

https://api.comfy.org/openapi get /comfy-nodes/{comfyNodeName}/node
Returns the node that contains a ComfyUI node with the specified name



# Retrieve a specific node by ID
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-specific-node-by-id

https://api.comfy.org/openapi get /nodes/{nodeId}
Returns the details of a specific node.



# Retrieve a specific version of a node
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-specific-version-of-a-node

https://api.comfy.org/openapi get /nodes/{nodeId}/versions/{versionId}



# Retrieve multiple node versions in a single request
Source: https://docs.comfy.org/api-reference/registry/retrieve-multiple-node-versions-in-a-single-request

https://api.comfy.org/openapi post /bulk/nodes/versions



# Retrieves a list of nodes
Source: https://docs.comfy.org/api-reference/registry/retrieves-a-list-of-nodes

https://api.comfy.org/openapi get /nodes
Returns a paginated list of nodes across all publishers.



# Retrieves a list of nodes
Source: https://docs.comfy.org/api-reference/registry/retrieves-a-list-of-nodes-1

https://api.comfy.org/openapi get /nodes/search
Returns a paginated list of nodes across all publishers.



# Returns a node version to be installed.
Source: https://docs.comfy.org/api-reference/registry/returns-a-node-version-to-be-installed

https://api.comfy.org/openapi get /nodes/{nodeId}/install
Retrieves the node data for installation, either the latest or a specific version.



# Get proxyvidutasks creations
Source: https://docs.comfy.org/api-reference/api-nodes/get-proxyvidutasks-creations

https://api.comfy.org/openapi get /proxy/vidu/tasks/{id}/creations



# Post proxyviduextend
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyviduextend

https://api.comfy.org/openapi post /proxy/vidu/extend



# Post proxyviduimg2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyviduimg2video

https://api.comfy.org/openapi post /proxy/vidu/img2video



# Post proxyvidumultiframe
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidumultiframe

https://api.comfy.org/openapi post /proxy/vidu/multiframe



# Post proxyvidureference2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidureference2video

https://api.comfy.org/openapi post /proxy/vidu/reference2video



# Post proxyvidustart end2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidustart-end2video

https://api.comfy.org/openapi post /proxy/vidu/start-end2video



# Post proxyvidutext2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidutext2video

https://api.comfy.org/openapi post /proxy/vidu/text2video



# Get the status of one skin enhancer task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-one-skin-enhancer-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/skin-enhancer/{task_id}
Get the status of a skin enhancer task (works for both Creative and Faithful modes)



# Get the status of the Precision V2 upscaling task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-precision-v2-upscaling-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-upscaler-precision-v2/{task_id}
Returns the current status and output URL of a specific precision upscaler V2 task.



# Get the status of the relight task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-relight-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-relight/{task_id}
Get the status of the relight task



# Get the status of the style transfer task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-style-transfer-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-style-transfer/{task_id}
Get the status of the style transfer task



# Get the status of the upscaling task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-upscaling-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-upscaler/{task_id}
Get the status of the upscaling task



# Relight an image
Source: https://docs.comfy.org/api-reference/freepik/relight-an-image

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-relight
Relight an image using AI. This endpoint accepts a variety of parameters to customize the generated images.




# Skin enhancer using AI (Creative)
Source: https://docs.comfy.org/api-reference/freepik/skin-enhancer-using-ai-creative

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/skin-enhancer/creative
Enhance skin in images using AI with the Creative mode. This mode provides more artistic and stylized enhancements.



# Skin enhancer using AI (Faithful)
Source: https://docs.comfy.org/api-reference/freepik/skin-enhancer-using-ai-faithful

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/skin-enhancer/faithful
Enhance skin in images using AI with the Faithful mode. This mode preserves the original appearance while improving skin quality.



# Skin enhancer using AI (Flexible)
Source: https://docs.comfy.org/api-reference/freepik/skin-enhancer-using-ai-flexible

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/skin-enhancer/flexible
Enhance skin in images using AI with the Flexible mode. This mode allows you to choose the optimization target for the enhancement.



# Style transfer an image
Source: https://docs.comfy.org/api-reference/freepik/style-transfer-an-image

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-style-transfer
Style transfer an image using AI.



# Upscale an image with Magnific
Source: https://docs.comfy.org/api-reference/freepik/upscale-an-image-with-magnific

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-upscaler
This asynchronous endpoint enables image upscaling using advanced AI algorithms.
Upon submission, it returns a unique task_id which can be used to track the progress.
For real-time production use, include the optional webhook_url parameter to receive
an automated notification once the task has been completed.




# Upscale an image with Precision V2
Source: https://docs.comfy.org/api-reference/freepik/upscale-an-image-with-precision-v2

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-upscaler-precision-v2
Upscales an image while adding new visual elements or details (V2).
This endpoint may modify the original image content based on the prompt and inferred context.
Upon submission, it returns a unique task_id which can be used to track the progress.




# Claim nodeId into publisherId for the authenticated publisher
Source: https://docs.comfy.org/api-reference/registry/claim-nodeid-into-publisherid-for-the-authenticated-publisher

https://api.comfy.org/openapi post /publishers/{publisherId}/nodes/{nodeId}/claim-my-node
This endpoint allows a publisher to claim an unclaimed node that they own the repo, which is identified by the nodeId. The unclaimed node's repository must be owned by the authenticated user.




# Create a new custom node
Source: https://docs.comfy.org/api-reference/registry/create-a-new-custom-node

https://api.comfy.org/openapi post /publishers/{publisherId}/nodes



# Create a new personal access token
Source: https://docs.comfy.org/api-reference/registry/create-a-new-personal-access-token

https://api.comfy.org/openapi post /publishers/{publisherId}/tokens



# Create a new publisher
Source: https://docs.comfy.org/api-reference/registry/create-a-new-publisher

https://api.comfy.org/openapi post /publishers



# Delete a publisher
Source: https://docs.comfy.org/api-reference/registry/delete-a-publisher

https://api.comfy.org/openapi delete /publishers/{publisherId}



# Delete a specific node
Source: https://docs.comfy.org/api-reference/registry/delete-a-specific-node

https://api.comfy.org/openapi delete /publishers/{publisherId}/nodes/{nodeId}



# Delete a specific personal access token
Source: https://docs.comfy.org/api-reference/registry/delete-a-specific-personal-access-token

https://api.comfy.org/openapi delete /publishers/{publisherId}/tokens/{tokenId}



# Get information about the calling user.
Source: https://docs.comfy.org/api-reference/registry/get-information-about-the-calling-user

https://api.comfy.org/openapi get /users



# List all node versions given some filters.
Source: https://docs.comfy.org/api-reference/registry/list-all-node-versions-given-some-filters

https://api.comfy.org/openapi get /versions



# Publish a new version of a node
Source: https://docs.comfy.org/api-reference/registry/publish-a-new-version-of-a-node

https://api.comfy.org/openapi post /publishers/{publisherId}/nodes/{nodeId}/versions



# Retrieve a publisher by ID
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-publisher-by-id

https://api.comfy.org/openapi get /publishers/{publisherId}



# Retrieve all nodes
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-nodes

https://api.comfy.org/openapi get /publishers/{publisherId}/nodes



# Retrieve all nodes
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-nodes-1

https://api.comfy.org/openapi get /publishers/{publisherId}/nodes/v2



# Retrieve all publishers
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-publishers

https://api.comfy.org/openapi get /publishers



# Retrieve all publishers for a given user
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-publishers-for-a-given-user

https://api.comfy.org/openapi get /users/publishers/



# Retrieve permissions the user has for a given publisher
Source: https://docs.comfy.org/api-reference/registry/retrieve-permissions-the-user-has-for-a-given-publisher

https://api.comfy.org/openapi get /publishers/{publisherId}/nodes/{nodeId}/permissions



# Retrieve permissions the user has for a given publisher
Source: https://docs.comfy.org/api-reference/registry/retrieve-permissions-the-user-has-for-a-given-publisher-1

https://api.comfy.org/openapi get /publishers/{publisherId}/permissions



# Unpublish (delete) a specific version of a node
Source: https://docs.comfy.org/api-reference/registry/unpublish-delete-a-specific-version-of-a-node

https://api.comfy.org/openapi delete /publishers/{publisherId}/nodes/{nodeId}/versions/{versionId}



# Update a publisher
Source: https://docs.comfy.org/api-reference/registry/update-a-publisher

https://api.comfy.org/openapi put /publishers/{publisherId}



# Update a specific comfy-node
Source: https://docs.comfy.org/api-reference/registry/update-a-specific-comfy-node

https://api.comfy.org/openapi put /nodes/{nodeId}/versions/{version}/comfy-nodes/{comfyNodeName}



# Update a specific node
Source: https://docs.comfy.org/api-reference/registry/update-a-specific-node

https://api.comfy.org/openapi put /publishers/{publisherId}/nodes/{nodeId}



# Update changelog and deprecation status of a node version
Source: https://docs.comfy.org/api-reference/registry/update-changelog-and-deprecation-status-of-a-node-version

https://api.comfy.org/openapi put /publishers/{publisherId}/nodes/{nodeId}/versions/{versionId}
Update only the changelog and deprecated status of a specific version of a node.



# Validate if a publisher username is available
Source: https://docs.comfy.org/api-reference/registry/validate-if-a-publisher-username-is-available

https://api.comfy.org/openapi get /publishers/validate
Checks if the publisher username is already taken.



# Get release notes
Source: https://docs.comfy.org/api-reference/releases/get-release-notes

https://api.comfy.org/openapi get /releases
Fetch release notes from Strapi with caching



# Generate music from text prompt
Source: https://docs.comfy.org/api-reference/sonilo/generate-music-from-text-prompt

https://api.comfy.org/openapi post /proxy/sonilo/t2m/generate
Generate music from a text prompt using Sonilo text-to-music AI.
Requires a prompt describing the desired music. Duration is optional and will be inferred if not provided.
Returns a streaming NDJSON response with duration, titles, audio chunks, and completion events.




# Generate music from video
Source: https://docs.comfy.org/api-reference/sonilo/generate-music-from-video

https://api.comfy.org/openapi post /proxy/sonilo/v2m/generate
Generate music from a video using Sonilo video-to-music AI.
Accepts either a video file upload or a video URL, with an optional prompt.
Returns a streaming NDJSON response with duration, titles, audio chunks, and completion events.
Max video duration: 6 minutes. Max upload size: 1024MB.




# ComfyUI Hunyuan3D-2 Examples
Source: https://docs.comfy.org/tutorials/3d/hunyuan3D-2

This guide will demonstrate how to use Hunyuan3D-2 in ComfyUI to generate 3D assets.

# Hunyuan3D 2.0 Introduction

![Hunyuan 3D 2](https://raw.githubusercontent.com/Tencent/Hunyuan3D-2/main/assets/images/e2e-1.gif)
![Hunyuan 3D 2](https://raw.githubusercontent.com/Tencent/Hunyuan3D-2/main/assets/images/e2e-2.gif)
[Hunyuan3D 2.0](https://github.com/Tencent/Hunyuan3D-2) is an open-source 3D asset generation model released by Tencent, capable of generating high-fidelity 3D models with high-resolution texture maps through text or images.

Hunyuan3D 2.0 adopts a two-stage generation approach, first generating a geometry model without textures, then synthesizing high-resolution texture maps. This effectively separates the complexity of shape and texture generation. Below are the two core components of Hunyuan3D 2.0:

1. **Geometry Generation Model (Hunyuan3D-DiT)**: Based on a flow diffusion Transformer architecture, it generates untextured geometric models that precisely match input conditions.
2. **Texture Generation Model (Hunyuan3D-Paint)**: Combines geometric conditions and multi-view diffusion techniques to add high-resolution textures to models, supporting PBR materials.

**Key Advantages**

* **High-Precision Generation**: Sharp geometric structures, rich texture colors, support for PBR material generation, achieving near-realistic lighting effects.
* **Diverse Usage Methods**: Provides code calls, Blender plugins, Gradio applications, and online experience through the official website, suitable for different user needs.
* **Lightweight and Compatibility**: The Hunyuan3D-2mini model requires only 5GB VRAM, the standard version needs 6GB VRAM for shape generation, and the complete process (shape + texture) requires only 12GB VRAM.

Recently (March 18, 2025), Hunyuan3D 2.0 also introduced a multi-view shape generation model (Hunyuan3D-2mv), which supports generating more detailed geometric structures from inputs at different angles.

This example includes three workflows:

* Using Hunyuan3D-2mv with multiple view inputs to generate 3D models
* Using Hunyuan3D-2mv-turbo with multiple view inputs to generate 3D models
* Using Hunyuan3D-2 with a single view input to generate 3D models

<Tip>
  ComfyUI now natively supports Hunyuan3D-2mv, but does not yet support texture and material generation. Please make sure you have updated to the latest version of [ComfyUI](https://github.com/Comfy-Org/ComfyUI) before starting.

  The workflow example PNG images in this tutorial contain workflow JSON in their metadata:

  * You can drag them directly into ComfyUI
  * Or use the menu `Workflows` -> `Open (ctrl+o)`

  This will load the corresponding workflow and prompt you to download the required models. The generated `.glb` format models will be output to the `ComfyUI/output/mesh` folder.
</Tip>

## ComfyUI Hunyuan3D-2mv Workflow Example

In the Hunyuan3D-2mv workflow, we'll use multi-view images to generate a 3D model. Note that multiple view images are not mandatory in this workflow - you can use only the `front` view image to generate a 3D model.

<Tip>
  <Tabs>
    <Tab title="Portable or self deployed users">
      Make sure your ComfyUI is updated.

      * [Download ComfyUI](https://www.comfy.org/download)
      * [Update Guide](/installation/update_comfyui)

      Workflows in this guide can be found in the [Workflow Templates](/interface/features/template).
      If you can't find them in the template, your ComfyUI may be outdated. (Desktop version's update will delay sometime)

      If nodes are missing when loading a workflow, possible reasons:

      1. You are not using the latest ComfyUI version (Nightly version)
      2. Some nodes failed to import at startup
    </Tab>

    <Tab title="Desktop or Cloud users">
      * The Desktop is base on ComfyUI stable release, it will auto-update when there is a new Desktop stable release available.
      * [Cloud](https://cloud.comfy.org) will update after ComfyUI stable release.

      So, if you find any core node missing in this document, it might be because the new core nodes have not yet been released in the latest stable version. Please wait for the next stable release.
    </Tab>
  </Tabs>
</Tip>

<a href="https://cloud.comfy.org/?template=3d_hunyuan3d_multiview_to_model&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 1. Workflow

Please download the images below and drag  into ComfyUI to load the workflow.
![Hunyuan3D-2mv workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/hunyuan-3d-multiview-elf.webp)

Download the images below we will use them as input images.

![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/front.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/left.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_elf/back.png)

<Tip>
  In this example, the input images have already been preprocessed to remove excess background. In actual use, you can use custom nodes like [ComfyUI\_essentials](https://github.com/cubiq/ComfyUI_essentials) to automatically remove excess background.
</Tip>

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-mv: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2mv/resolve/main/hunyuan3d-dit-v2-mv/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2-mv.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2-mv.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2mv" />

1. Ensure that the Image Only Checkpoint Loader(img2vid model) has loaded our downloaded and renamed `hunyuan3d-dit-v2-mv.safetensors` model
2. Load the corresponding view images in each of the `Load Image` nodes
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

If you need to add more views, make sure to load other view images in the `Hunyuan3Dv2ConditioningMultiView` node, and ensure that you load the corresponding view images in the `Load Image` nodes.

## Hunyuan3D-2mv-turbo Workflow

In the Hunyuan3D-2mv-turbo workflow, we'll use the Hunyuan3D-2mv-turbo model to generate 3D models. This model is a step distillation version of Hunyuan3D-2mv, allowing for faster 3D model generation. In this version of the workflow, we set `cfg` to 1.0 and add a `flux guidance` node to control the `distilled cfg` generation.

<a href="https://cloud.comfy.org/?template=3d_hunyuan3d_multiview_to_model_turbo&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 1. Workflow

Please download the images below and drag into ComfyUI to load the workflow.

![Hunyuan3D-2mv-turbo workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/hunyuan-3d-turbo.webp)

Download the images below we will use them as input images.

![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/front.png)
![input image](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d_2mv_turbo/right.png)

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-mv-turbo: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2mv/resolve/main/hunyuan3d-dit-v2-mv-turbo/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2-mv-turbo.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2-mv-turbo.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2mv_turbo" />

1. Ensure that the `Image Only Checkpoint Loader(img2vid model)` node has loaded our renamed `hunyuan3d-dit-v2-mv-turbo.safetensors` model
2. Load the corresponding view images in each of the `Load Image` nodes
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Hunyuan3D-2 Single View Workflow

In the Hunyuan3D-2 workflow, we'll use the Hunyuan3D-2 model to generate 3D models. This model is not a multi-view model. In this workflow, we use the `Hunyuan3Dv2Conditioning` node instead of the `Hunyuan3Dv2ConditioningMultiView` node.

<a href="https://cloud.comfy.org/?template=3d_hunyuan3d_image_to_model&utm_source=docs">
  <p>Run on Comfy Cloud</p>
</a>

### 1. Workflow

Please download the image below and drag it into ComfyUI to load the workflow.

![Hunyuan3D-2 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan3d-non-multiview-train.webp)

Download the image below we will use it as input image.
![ComfyUI Hunyuan 3D 2 workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/3d/hunyuan3d-2/hunyuan_3d_v2_non_multiview_train.png)

### 2. Manual Model Installation

Download the model below and save it to the corresponding ComfyUI folder

* hunyuan3d-dit-v2-0: [model.fp16.safetensors](https://huggingface.co/tencent/Hunyuan3D-2/resolve/main/hunyuan3d-dit-v2-0/model.fp16.safetensors?download=true) - after downloading, you can rename it to `hunyuan3d-dit-v2.safetensors`

```
ComfyUI/
├── models/
│   ├── checkpoints/
│   │   └── hunyuan3d-dit-v2.safetensors  // renamed file
```

### 3. Steps to Run the Workflow

<img alt="ComfyUI hunyuan3d_2" />

1. Ensure that the `Image Only Checkpoint Loader(img2vid model)` node has loaded our renamed `hunyuan3d-dit-v2.safetensors` model
2. Load the image in the `Load Image` node
3. Click the `Queue` button, or use the shortcut `Ctrl(cmd) + Enter` to run the workflow

## Community Resources

Below are ComfyUI community resources related to Hunyuan3D-2

* [ComfyUI-Hunyuan3DWrapper](https://github.com/kijai/ComfyUI-Hunyuan3DWrapper)
* [Kijai/Hunyuan3D-2\_safetensors](https://huggingface.co/Kijai/Hunyuan3D-2_safetensors/tree/main)
* [ComfyUI-3D-Pack](https://github.com/MrForExample/ComfyUI-3D-Pack)

## Hunyuan3D 2.0 Open-Source Model Series

Currently, Hunyuan3D 2.0 has open-sourced multiple models covering the complete 3D generation process. You can visit [Hunyuan3D-2](https://github.com/Tencent/Hunyuan3D-2) for more information.

**Hunyuan3D-2mini Series**

| Model                 | Description               | Date       | Parameters | Huggingface                                                                             |
| --------------------- | ------------------------- | ---------- | ---------- | --------------------------------------------------------------------------------------- |
| Hunyuan3D-DiT-v2-mini | Mini Image to Shape Model | 2025-03-18 | 0.6B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mini/tree/main/hunyuan3d-dit-v2-mini) |

**Hunyuan3D-2mv Series**

| Model                    | Description                                                                                                 | Date       | Parameters | Huggingface                                                                              |
| ------------------------ | ----------------------------------------------------------------------------------------------------------- | ---------- | ---------- | ---------------------------------------------------------------------------------------- |
| Hunyuan3D-DiT-v2-mv-Fast | Guidance Distillation Version, can halve DIT inference time                                                 | 2025-03-18 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mv/tree/main/hunyuan3d-dit-v2-mv-fast) |
| Hunyuan3D-DiT-v2-mv      | Multi-view Image to Shape Model, suitable for 3D creation requiring multiple angles to understand the scene | 2025-03-18 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2mv/tree/main/hunyuan3d-dit-v2-mv)      |

**Hunyuan3D-2 Series**

| Model                   | Description                 | Date       | Parameters | Huggingface                                                                           |
| ----------------------- | --------------------------- | ---------- | ---------- | ------------------------------------------------------------------------------------- |
| Hunyuan3D-DiT-v2-0-Fast | Guidance Distillation Model | 2025-02-03 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-dit-v2-0-fast) |
| Hunyuan3D-DiT-v2-0      | Image to Shape Model        | 2025-01-21 | 1.1B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-dit-v2-0)      |
| Hunyuan3D-Paint-v2-0    | Texture Generation Model    | 2025-01-21 | 1.3B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-paint-v2-0)    |
| Hunyuan3D-Delight-v2-0  | Image Delight Model         | 2025-01-21 | 1.3B       | [Visit](https://huggingface.co/tencent/Hunyuan3D-2/tree/main/hunyuan3d-delight-v2-0)  |


# Generate a short-lived JWT admin token
Source: https://docs.comfy.org/api-reference/admin/generate-a-short-lived-jwt-admin-token

https://api.comfy.org/openapi post /admin/generate-token
Generates a short-lived JWT admin token for browser-based admin operations.
The user must already be authenticated with Firebase and have admin privileges.
The generated token expires after 1 hour.




# Add review to a specific version of a node
Source: https://docs.comfy.org/api-reference/registry/add-review-to-a-specific-version-of-a-node

https://api.comfy.org/openapi post /nodes/{nodeId}/reviews



# Create a new publisher
Source: https://docs.comfy.org/api-reference/registry/create-a-new-publisher

https://api.comfy.org/openapi post /publishers



# create comfy-nodes for certain node
Source: https://docs.comfy.org/api-reference/registry/create-comfy-nodes-for-certain-node

https://api.comfy.org/openapi post /nodes/{nodeId}/versions/{version}/comfy-nodes



# Create Node Translations
Source: https://docs.comfy.org/api-reference/registry/create-node-translations

https://api.comfy.org/openapi post /nodes/{nodeId}/translations



# Delete a publisher
Source: https://docs.comfy.org/api-reference/registry/delete-a-publisher

https://api.comfy.org/openapi delete /publishers/{publisherId}



# Get server feature flags
Source: https://docs.comfy.org/api-reference/registry/get-server-feature-flags

https://api.comfy.org/openapi get /features
Returns the server's feature capabilities



# get specify comfy-node based on its id
Source: https://docs.comfy.org/api-reference/registry/get-specify-comfy-node-based-on-its-id

https://api.comfy.org/openapi get /nodes/{nodeId}/versions/{version}/comfy-nodes/{comfyNodeName}



# list all comfy-nodes
Source: https://docs.comfy.org/api-reference/registry/list-all-comfy-nodes

https://api.comfy.org/openapi get /comfy-nodes



# List all versions of a node
Source: https://docs.comfy.org/api-reference/registry/list-all-versions-of-a-node

https://api.comfy.org/openapi get /nodes/{nodeId}/versions



# list comfy-nodes for node version
Source: https://docs.comfy.org/api-reference/registry/list-comfy-nodes-for-node-version

https://api.comfy.org/openapi get /nodes/{nodeId}/versions/{version}/comfy-nodes



# Retrieve a node by ComfyUI node name
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-node-by-comfyui-node-name

https://api.comfy.org/openapi get /comfy-nodes/{comfyNodeName}/node
Returns the node that contains a ComfyUI node with the specified name



# Retrieve a publisher by ID
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-publisher-by-id

https://api.comfy.org/openapi get /publishers/{publisherId}



# Retrieve a specific node by ID
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-specific-node-by-id

https://api.comfy.org/openapi get /nodes/{nodeId}
Returns the details of a specific node.



# Retrieve a specific version of a node
Source: https://docs.comfy.org/api-reference/registry/retrieve-a-specific-version-of-a-node

https://api.comfy.org/openapi get /nodes/{nodeId}/versions/{versionId}



# Retrieve all publishers
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-publishers

https://api.comfy.org/openapi get /publishers



# Retrieve multiple node versions in a single request
Source: https://docs.comfy.org/api-reference/registry/retrieve-multiple-node-versions-in-a-single-request

https://api.comfy.org/openapi post /bulk/nodes/versions



# Retrieves a list of nodes
Source: https://docs.comfy.org/api-reference/registry/retrieves-a-list-of-nodes

https://api.comfy.org/openapi get /nodes
Returns a paginated list of nodes across all publishers.



# Retrieves a list of nodes
Source: https://docs.comfy.org/api-reference/registry/retrieves-a-list-of-nodes-1

https://api.comfy.org/openapi get /nodes/search
Returns a paginated list of nodes across all publishers.



# Returns a node version to be installed.
Source: https://docs.comfy.org/api-reference/registry/returns-a-node-version-to-be-installed

https://api.comfy.org/openapi get /nodes/{nodeId}/install
Retrieves the node data for installation, either the latest or a specific version.



# Update a publisher
Source: https://docs.comfy.org/api-reference/registry/update-a-publisher

https://api.comfy.org/openapi put /publishers/{publisherId}



# Update a specific comfy-node
Source: https://docs.comfy.org/api-reference/registry/update-a-specific-comfy-node

https://api.comfy.org/openapi put /nodes/{nodeId}/versions/{version}/comfy-nodes/{comfyNodeName}



# Validate if a publisher username is available
Source: https://docs.comfy.org/api-reference/registry/validate-if-a-publisher-username-is-available

https://api.comfy.org/openapi get /publishers/validate
Checks if the publisher username is already taken.



# Get proxyvidutasks creations
Source: https://docs.comfy.org/api-reference/api-nodes/get-proxyvidutasks-creations

https://api.comfy.org/openapi get /proxy/vidu/tasks/{id}/creations



# Post proxyviduextend
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyviduextend

https://api.comfy.org/openapi post /proxy/vidu/extend



# Post proxyviduimg2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyviduimg2video

https://api.comfy.org/openapi post /proxy/vidu/img2video



# Post proxyvidumultiframe
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidumultiframe

https://api.comfy.org/openapi post /proxy/vidu/multiframe



# Post proxyvidureference2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidureference2video

https://api.comfy.org/openapi post /proxy/vidu/reference2video



# Post proxyvidustart end2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidustart-end2video

https://api.comfy.org/openapi post /proxy/vidu/start-end2video



# Post proxyvidutext2video
Source: https://docs.comfy.org/api-reference/api-nodes/post-proxyvidutext2video

https://api.comfy.org/openapi post /proxy/vidu/text2video



# Get the status of one skin enhancer task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-one-skin-enhancer-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/skin-enhancer/{task_id}
Get the status of a skin enhancer task (works for both Creative and Faithful modes)



# Get the status of the Precision V2 upscaling task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-precision-v2-upscaling-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-upscaler-precision-v2/{task_id}
Returns the current status and output URL of a specific precision upscaler V2 task.



# Get the status of the relight task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-relight-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-relight/{task_id}
Get the status of the relight task



# Get the status of the style transfer task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-style-transfer-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-style-transfer/{task_id}
Get the status of the style transfer task



# Get the status of the upscaling task
Source: https://docs.comfy.org/api-reference/freepik/get-the-status-of-the-upscaling-task

https://api.comfy.org/openapi get /proxy/freepik/v1/ai/image-upscaler/{task_id}
Get the status of the upscaling task



# Relight an image
Source: https://docs.comfy.org/api-reference/freepik/relight-an-image

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-relight
Relight an image using AI. This endpoint accepts a variety of parameters to customize the generated images.




# Skin enhancer using AI (Creative)
Source: https://docs.comfy.org/api-reference/freepik/skin-enhancer-using-ai-creative

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/skin-enhancer/creative
Enhance skin in images using AI with the Creative mode. This mode provides more artistic and stylized enhancements.



# Skin enhancer using AI (Faithful)
Source: https://docs.comfy.org/api-reference/freepik/skin-enhancer-using-ai-faithful

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/skin-enhancer/faithful
Enhance skin in images using AI with the Faithful mode. This mode preserves the original appearance while improving skin quality.



# Skin enhancer using AI (Flexible)
Source: https://docs.comfy.org/api-reference/freepik/skin-enhancer-using-ai-flexible

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/skin-enhancer/flexible
Enhance skin in images using AI with the Flexible mode. This mode allows you to choose the optimization target for the enhancement.



# Style transfer an image
Source: https://docs.comfy.org/api-reference/freepik/style-transfer-an-image

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-style-transfer
Style transfer an image using AI.



# Upscale an image with Magnific
Source: https://docs.comfy.org/api-reference/freepik/upscale-an-image-with-magnific

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-upscaler
This asynchronous endpoint enables image upscaling using advanced AI algorithms.
Upon submission, it returns a unique task_id which can be used to track the progress.
For real-time production use, include the optional webhook_url parameter to receive
an automated notification once the task has been completed.




# Upscale an image with Precision V2
Source: https://docs.comfy.org/api-reference/freepik/upscale-an-image-with-precision-v2

https://api.comfy.org/openapi post /proxy/freepik/v1/ai/image-upscaler-precision-v2
Upscales an image while adding new visual elements or details (V2).
This endpoint may modify the original image content based on the prompt and inferred context.
Upon submission, it returns a unique task_id which can be used to track the progress.




# Claim nodeId into publisherId for the authenticated publisher
Source: https://docs.comfy.org/api-reference/registry/claim-nodeid-into-publisherid-for-the-authenticated-publisher

https://api.comfy.org/openapi post /publishers/{publisherId}/nodes/{nodeId}/claim-my-node
This endpoint allows a publisher to claim an unclaimed node that they own the repo, which is identified by the nodeId. The unclaimed node's repository must be owned by the authenticated user.




# Create a new custom node
Source: https://docs.comfy.org/api-reference/registry/create-a-new-custom-node

https://api.comfy.org/openapi post /publishers/{publisherId}/nodes



# Create a new personal access token
Source: https://docs.comfy.org/api-reference/registry/create-a-new-personal-access-token

https://api.comfy.org/openapi post /publishers/{publisherId}/tokens



# Delete a specific node
Source: https://docs.comfy.org/api-reference/registry/delete-a-specific-node

https://api.comfy.org/openapi delete /publishers/{publisherId}/nodes/{nodeId}



# Delete a specific personal access token
Source: https://docs.comfy.org/api-reference/registry/delete-a-specific-personal-access-token

https://api.comfy.org/openapi delete /publishers/{publisherId}/tokens/{tokenId}



# Get information about the calling user.
Source: https://docs.comfy.org/api-reference/registry/get-information-about-the-calling-user

https://api.comfy.org/openapi get /users



# List all node versions given some filters.
Source: https://docs.comfy.org/api-reference/registry/list-all-node-versions-given-some-filters

https://api.comfy.org/openapi get /versions



# Publish a new version of a node
Source: https://docs.comfy.org/api-reference/registry/publish-a-new-version-of-a-node

https://api.comfy.org/openapi post /publishers/{publisherId}/nodes/{nodeId}/versions



# Retrieve all nodes
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-nodes

https://api.comfy.org/openapi get /publishers/{publisherId}/nodes



# Retrieve all nodes
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-nodes-1

https://api.comfy.org/openapi get /publishers/{publisherId}/nodes/v2



# Retrieve all publishers for a given user
Source: https://docs.comfy.org/api-reference/registry/retrieve-all-publishers-for-a-given-user

https://api.comfy.org/openapi get /users/publishers/



# Retrieve permissions the user has for a given publisher
Source: https://docs.comfy.org/api-reference/registry/retrieve-permissions-the-user-has-for-a-given-publisher

https://api.comfy.org/openapi get /publishers/{publisherId}/nodes/{nodeId}/permissions



# Retrieve permissions the user has for a given publisher
Source: https://docs.comfy.org/api-reference/registry/retrieve-permissions-the-user-has-for-a-given-publisher-1

https://api.comfy.org/openapi get /publishers/{publisherId}/permissions



# Unpublish (delete) a specific version of a node
Source: https://docs.comfy.org/api-reference/registry/unpublish-delete-a-specific-version-of-a-node

https://api.comfy.org/openapi delete /publishers/{publisherId}/nodes/{nodeId}/versions/{versionId}



# Update a specific node
Source: https://docs.comfy.org/api-reference/registry/update-a-specific-node

https://api.comfy.org/openapi put /publishers/{publisherId}/nodes/{nodeId}



# Update changelog and deprecation status of a node version
Source: https://docs.comfy.org/api-reference/registry/update-changelog-and-deprecation-status-of-a-node-version

https://api.comfy.org/openapi put /publishers/{publisherId}/nodes/{nodeId}/versions/{versionId}
Update only the changelog and deprecated status of a specific version of a node.



# Get release notes
Source: https://docs.comfy.org/api-reference/releases/get-release-notes

https://api.comfy.org/openapi get /releases
Fetch release notes from Strapi with caching



# Generate music from text prompt
Source: https://docs.comfy.org/api-reference/sonilo/generate-music-from-text-prompt

https://api.comfy.org/openapi post /proxy/sonilo/t2m/generate
Generate music from a text prompt using Sonilo text-to-music AI.
Requires a prompt describing the desired music. Duration is optional and will be inferred if not provided.
Returns a streaming NDJSON response with duration, titles, audio chunks, and completion events.




# Generate music from video
Source: https://docs.comfy.org/api-reference/sonilo/generate-music-from-video

https://api.comfy.org/openapi post /proxy/sonilo/v2m/generate
Generate music from a video using Sonilo video-to-music AI.
Accepts either a video file upload or a video URL, with an optional prompt.
Returns a streaming NDJSON response with duration, titles, audio chunks, and completion events.
Max video duration: 6 minutes. Max upload size: 1024MB.