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https://git.datalinker.icu/comfyanonymous/ComfyUI
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feat(api-nodes): add LTXV API nodes (#10496)
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191
comfy_api_nodes/nodes_ltxv.py
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191
comfy_api_nodes/nodes_ltxv.py
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from io import BytesIO
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from typing import Optional
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import torch
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from pydantic import BaseModel, Field
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from typing_extensions import override
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from comfy_api.input_impl import VideoFromFile
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from comfy_api.latest import IO, ComfyExtension
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from comfy_api_nodes.util import (
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ApiEndpoint,
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get_number_of_images,
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sync_op_raw,
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upload_images_to_comfyapi,
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validate_string,
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)
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MODELS_MAP = {
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"LTX-2 (Pro)": "ltx-2-pro",
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"LTX-2 (Fast)": "ltx-2-fast",
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}
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class ExecuteTaskRequest(BaseModel):
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prompt: str = Field(...)
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model: str = Field(...)
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duration: int = Field(...)
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resolution: str = Field(...)
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fps: Optional[int] = Field(25)
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generate_audio: Optional[bool] = Field(True)
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image_uri: Optional[str] = Field(None)
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class TextToVideoNode(IO.ComfyNode):
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@classmethod
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def define_schema(cls):
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return IO.Schema(
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node_id="LtxvApiTextToVideo",
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display_name="LTXV Text To Video",
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category="api node/video/LTXV",
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description="Professional-quality videos with customizable duration and resolution.",
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inputs=[
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IO.Combo.Input("model", options=list(MODELS_MAP.keys())),
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IO.String.Input(
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"prompt",
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multiline=True,
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default="",
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),
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IO.Combo.Input("duration", options=[6, 8, 10], default=8),
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IO.Combo.Input(
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"resolution",
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options=[
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"1920x1080",
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"2560x1440",
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"3840x2160",
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],
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),
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IO.Combo.Input("fps", options=[25, 50], default=25),
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IO.Boolean.Input(
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"generate_audio",
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default=False,
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optional=True,
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tooltip="When true, the generated video will include AI-generated audio matching the scene.",
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),
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],
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outputs=[
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IO.Video.Output(),
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],
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hidden=[
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IO.Hidden.auth_token_comfy_org,
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IO.Hidden.api_key_comfy_org,
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IO.Hidden.unique_id,
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],
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is_api_node=True,
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)
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@classmethod
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async def execute(
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cls,
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model: str,
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prompt: str,
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duration: int,
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resolution: str,
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fps: int = 25,
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generate_audio: bool = False,
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) -> IO.NodeOutput:
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validate_string(prompt, min_length=1, max_length=10000)
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response = await sync_op_raw(
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cls,
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ApiEndpoint("/proxy/ltx/v1/text-to-video", "POST"),
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data=ExecuteTaskRequest(
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prompt=prompt,
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model=MODELS_MAP[model],
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duration=duration,
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resolution=resolution,
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fps=fps,
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generate_audio=generate_audio,
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),
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as_binary=True,
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max_retries=1,
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)
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return IO.NodeOutput(VideoFromFile(BytesIO(response)))
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class ImageToVideoNode(IO.ComfyNode):
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@classmethod
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def define_schema(cls):
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return IO.Schema(
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node_id="LtxvApiImageToVideo",
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display_name="LTXV Image To Video",
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category="api node/video/LTXV",
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description="Professional-quality videos with customizable duration and resolution based on start image.",
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inputs=[
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IO.Image.Input("image", tooltip="First frame to be used for the video."),
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IO.Combo.Input("model", options=list(MODELS_MAP.keys())),
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IO.String.Input(
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"prompt",
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multiline=True,
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default="",
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),
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IO.Combo.Input("duration", options=[6, 8, 10], default=8),
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IO.Combo.Input(
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"resolution",
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options=[
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"1920x1080",
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"2560x1440",
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"3840x2160",
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],
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),
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IO.Combo.Input("fps", options=[25, 50], default=25),
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IO.Boolean.Input(
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"generate_audio",
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default=False,
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optional=True,
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tooltip="When true, the generated video will include AI-generated audio matching the scene.",
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),
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],
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outputs=[
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IO.Video.Output(),
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],
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hidden=[
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IO.Hidden.auth_token_comfy_org,
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IO.Hidden.api_key_comfy_org,
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IO.Hidden.unique_id,
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],
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is_api_node=True,
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)
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@classmethod
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async def execute(
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cls,
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image: torch.Tensor,
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model: str,
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prompt: str,
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duration: int,
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resolution: str,
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fps: int = 25,
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generate_audio: bool = False,
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) -> IO.NodeOutput:
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validate_string(prompt, min_length=1, max_length=10000)
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if get_number_of_images(image) != 1:
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raise ValueError("Currently only one input image is supported.")
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response = await sync_op_raw(
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cls,
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ApiEndpoint("/proxy/ltx/v1/image-to-video", "POST"),
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data=ExecuteTaskRequest(
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image_uri=(await upload_images_to_comfyapi(cls, image, max_images=1, mime_type="image/png"))[0],
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prompt=prompt,
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model=MODELS_MAP[model],
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duration=duration,
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resolution=resolution,
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fps=fps,
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generate_audio=generate_audio,
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),
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as_binary=True,
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max_retries=1,
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)
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return IO.NodeOutput(VideoFromFile(BytesIO(response)))
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class LtxvApiExtension(ComfyExtension):
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@override
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async def get_node_list(self) -> list[type[IO.ComfyNode]]:
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return [
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TextToVideoNode,
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ImageToVideoNode,
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]
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async def comfy_entrypoint() -> LtxvApiExtension:
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return LtxvApiExtension()
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