> ## Documentation Index
> Fetch the complete documentation index at: https://docs.comfy.org/llms.txt
> Use this file to discover all available pages before exploring further.

# TextEncodeMageFlowEdit - ComfyUI Built-in Node Documentation

> Complete documentation for the TextEncodeMageFlowEdit node in ComfyUI. Learn its inputs, outputs, parameters and usage.

## Overview

This node encodes an edit instruction (prompt) along with one or more reference images for the Mage-Flow-Edit model. It resizes all reference images to the target output resolution, encodes them into latent space if a VAE is provided, and attaches the reference latents to the conditioning output. A blank latent tensor with the correct dimensions for sampling is also generated, ensuring the size always matches the output width and height.

## Inputs

| Parameter         | Description                                                                                                                               | Data Type        | Required | Range                                                    |
| ----------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | ---------------- | -------- | -------------------------------------------------------- |
| `clip`            | The CLIP model used to tokenize and encode the text prompts.                                                                              | CLIP             | Yes      |                                                          |
| `prompt`          | The editing instruction (positive prompt) to apply.                                                                                       | STRING           | Yes      | multiline, dynamic prompts enabled                       |
| `negative_prompt` | The negative prompt to steer away from. Default: empty string (uses a space internally when blank).                                       | STRING           | No       | multiline, dynamic prompts enabled                       |
| `vae`             | VAE model to encode reference images into latent space. If not provided, no reference latents are added to the conditioning.              | VAE              | No       |                                                          |
| `images`          | One or more reference images to edit. All images are resized to the output resolution before encoding.                                    | IMAGE (autogrow) | No       | Up to 16 images (named `image_1`…`image_16`), at least 0 |
| `width`           | Output width in pixels. If set to 0, the width of the first reference image is used. Always rounded down to a multiple of 16. Default: 0. | INT              | Yes      | 0 to 8192 (step 16)                                      |
| `height`          | Output height in pixels. Same fallback behavior as width. Default: 0.                                                                     | INT              | Yes      | 0 to 8192 (step 16)                                      |
| `batch_size`      | Number of latent samples to generate. Default: 1.                                                                                         | INT              | Yes      | 1 to 4096                                                |

**Notes on parameter dependencies:**

* If `width` and/or `height` are 0 and no reference images are provided, they fall back to 1024 each.
* The `vae` parameter is optional; reference latents are only generated and attached to conditioning when a VAE is connected.
* The `negative_prompt` field is optional – if left empty, a single space is used internally as the negative text.

## Outputs

| Output Name | Description                                                                                                             | Data Type    |
| ----------- | ----------------------------------------------------------------------------------------------------------------------- | ------------ |
| `positive`  | Conditioning output containing the positive prompt tokens, plus (if a VAE was provided) the encoded reference latents.  | CONDITIONING |
| `negative`  | Conditioning output containing the negative prompt tokens, plus the same reference latents (if VAE provided).           | CONDITIONING |
| `latent`    | A blank latent tensor with shape `[batch_size, 128, height÷16, width÷16]` for use as the initial noise during sampling. | LATENT       |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/TextEncodeMageFlowEdit/en.md)

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