Luma Text to Video 节点允许你使用Luma AI的创新视频生成技术，通过文本描述创建高质量、流畅的视频内容。

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节点功能

此节点连接到Luma AI的文本到视频API，让用户能够通过详细的文本提示词生成动态视频内容。

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参数说明

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基本参数

参数类型默认值说明
prompt字符串""描述要生成视频内容的文本提示词
model选择项-使用的视频生成模型
aspect_ratio选择项”ratio_16_9”视频宽高比
resolution选择项”res_540p”视频分辨率
duration选择项-视频时长选项
loop布尔值False是否循环播放视频
seed整数0随机种子，用于决定节点是否需要重新运行；实际结果与种子无关

当使用 Ray 1.6 模型时，duration 和 resolution 参数将不会生效。

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可选参数

参数类型说明
luma_conceptsLUMA_CONCEPTS可选的摄像机概念，通过Luma Concepts节点控制摄像机运动

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输出

输出类型说明
VIDEO视频生成的视频结果

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使用示例

Luma Text to Video 工作流示例

Luma Text to Video 工作流示例

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源码参考

[节点源码 (更新于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)),)