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

ParameterTypeDefaultDescription
promptstring""Text prompt describing the video content to generate
modelselect-Video generation model to use
aspect_ratioselect”ratio_16_9”Video aspect ratio
resolutionselect”res_540p”Video resolution
durationselect-Video length options
loopbooleanFalseWhether to loop the video
seedinteger0Seed value for node rerun, results are nondeterministic

When using Ray 1.6 model, duration and resolution parameters will not take effect.

Optional Parameters

ParameterTypeDescription
luma_conceptsLUMA_CONCEPTSCamera concepts to control motion via Luma Concepts node

Output

OutputTypeDescription
VIDEOvideoGenerated video

Usage Example

Luma Text to Video Workflow Example

Luma Text to Video Workflow Example

Source Code

[Node source code (Updated on 2025-05-03)]


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)),)