MiniMax Text to Video 节点通过连接 MiniMax 的API，允许用户利用文本提示词生成高质量、流畅的视频内容。该节点支持不同的视频生成模型，可以创建各种风格和类型的短视频片段。

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参数说明

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必需参数

参数类型默认值说明
prompt_text字符串""用于指导视频生成的文本提示词
model选择项”T2V-01”使用的视频生成模型，可选值包括”T2V-01”和”T2V-01-Director”
seed整数0生成的随机种子，影响初始噪声创建，默认值为0

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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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源码参考

[节点源码 (更新于2025-05-03)]

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),)