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