[Partner Nodes] feat(LTX): add new nodes for model version 2.5 (#15501)
* [Partner Nodes] feat(LTX): add new nodes for model version 2.5 Signed-off-by: Alexander Piskun <bigcat88@icloud.com>
This commit is contained in:
Alexander Piskun
GitHub
parent
57ce8e1a27
commit
ce4fc13094
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@ -6,8 +6,12 @@ from typing_extensions import override
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from comfy_api.latest import IO, ComfyExtension, Input, InputImpl
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from comfy_api_nodes.util import (
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ApiEndpoint,
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download_url_to_video_output,
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get_number_of_images,
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poll_op,
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sync_op,
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sync_op_raw,
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upload_audio_to_comfyapi,
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upload_images_to_comfyapi,
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validate_string,
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)
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@ -17,6 +21,11 @@ MODELS_MAP = {
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"LTX-2 (Fast)": "ltx-2-fast",
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}
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V25_MODELS_MAP = {
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"LTX-2.5 (Fast)": "ltx-2-5-fast",
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"LTX-2.5 (Pro)": "ltx-2-5-pro",
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}
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class ExecuteTaskRequest(BaseModel):
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prompt: str = Field(...)
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@ -26,6 +35,48 @@ class ExecuteTaskRequest(BaseModel):
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fps: int | None = Field(25)
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generate_audio: bool | None = Field(True)
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image_uri: str | None = Field(None)
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last_frame_uri: str | None = Field(None)
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class AudioToVideoRequest(BaseModel):
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prompt: str = Field(...)
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model: str = Field(...)
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resolution: str = Field(...)
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audio_uri: str = Field(...)
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image_uri: str | None = Field(None)
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class Ltx25SubmitResponse(BaseModel):
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id: str = Field(...)
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class Ltx25JobResult(BaseModel):
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video_url: str | None = Field(None)
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class Ltx25JobStatusResponse(BaseModel):
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id: str = Field(...)
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status: str = Field(...)
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result: Ltx25JobResult | None = Field(None)
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async def _v25_submit_and_poll(cls: type[IO.ComfyNode], route: str, data: BaseModel) -> IO.NodeOutput:
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submit = await sync_op(
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cls,
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ApiEndpoint(f"/proxy/ltx/v2/{route}", "POST"),
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response_model=Ltx25SubmitResponse,
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data=data,
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max_retries=1,
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)
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job = await poll_op(
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cls,
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ApiEndpoint(f"/proxy/ltx/v2/{route}/{submit.id}"),
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response_model=Ltx25JobStatusResponse,
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status_extractor=lambda r: r.status,
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)
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if not job.result or not job.result.video_url:
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raise RuntimeError(f"LTX job {job.id} completed without a video URL.")
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return IO.NodeOutput(await download_url_to_video_output(job.result.video_url, cls=cls))
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PRICE_BADGE = IO.PriceBadge(
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@ -43,6 +94,128 @@ PRICE_BADGE = IO.PriceBadge(
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""",
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)
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V25_PRICE_BADGE = IO.PriceBadge(
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depends_on=IO.PriceBadgeDepends(widgets=["model", "model.duration", "model.resolution"]),
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expr="""
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(
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$prices := {
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"ltx-2.5 (fast)": {
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"1280x720":0.1287,"720x1280":0.1287,
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"1920x1080":0.1859,"1080x1920":0.1859,
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"2560x1440":0.2717,"1440x2560":0.2717,
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"3840x2160":0.429,"2160x3840":0.429
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},
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"ltx-2.5 (pro)": {
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"1280x720":0.1716,"720x1280":0.1716,
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"1920x1080":0.2431,"1080x1920":0.2431
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}
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};
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$model := $lookup(widgets, "model");
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$table := $type($model) = "string" ? $lookup($prices, $model) : undefined;
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$res := $lookup(widgets, "model.resolution");
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$pps := $type($table) = "object" and $type($res) = "string" ? $lookup($table, $res) : undefined;
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$durRaw := $lookup(widgets, "model.duration");
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$dur := $type($durRaw) in ["string", "number"] ? $number($durRaw) : undefined;
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$type($pps) = "number" and $type($dur) = "number"
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? {"type":"usd","usd": $pps * $dur}
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: undefined
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)
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""",
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)
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V25_A2V_PRICE_BADGE = IO.PriceBadge(
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depends_on=IO.PriceBadgeDepends(widgets=["model"]),
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expr="""
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(
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$rates := {"ltx-2.5 (fast)":0.1859, "ltx-2.5 (pro)":0.2431};
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$model := $lookup(widgets, "model");
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$rate := $type($model) = "string" ? $lookup($rates, $model) : undefined;
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$type($rate) = "number"
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? {"type":"usd","usd": $rate, "format":{"suffix":"/second"}}
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: undefined
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)
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""",
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)
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def _v25_generation_inputs(
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durations: list[str], resolutions: list[str], fps_options: list[str], tooltip: str | None
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) -> list:
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return [
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IO.Combo.Input(
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"duration",
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options=durations,
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default="8",
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tooltip=tooltip,
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),
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IO.Combo.Input(
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"resolution",
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options=resolutions,
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default="1920x1080",
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),
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IO.Combo.Input("fps", options=fps_options, default="25"),
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IO.Boolean.Input(
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"generate_audio",
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default=True,
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tooltip="When true, the generated video will include AI-generated audio matching the scene.",
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advanced=True,
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),
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]
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def _v25_model_combo() -> IO.DynamicCombo.Input:
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return IO.DynamicCombo.Input(
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"model",
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options=[
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IO.DynamicCombo.Option(
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"LTX-2.5 (Fast)",
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_v25_generation_inputs(
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["2", "3", "4", "5", "6", "8", "10", "12", "14", "16", "18", "20"],
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[
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"1280x720",
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"720x1280",
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"1920x1080",
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"1080x1920",
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"2560x1440",
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"1440x2560",
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"3840x2160",
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"2160x3840",
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],
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["24", "25", "48", "50"],
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"Video duration in seconds. Durations over 10s require a 720p/1080p resolution and 24/25 FPS.",
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),
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),
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IO.DynamicCombo.Option(
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"LTX-2.5 (Pro)",
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_v25_generation_inputs(
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["2", "3", "4", "5", "6", "8", "10"],
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["1280x720", "720x1280", "1920x1080", "1080x1920"],
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["24", "25", "50"],
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"Video duration in seconds.",
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),
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),
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],
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)
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def _v25_seed_input() -> IO.Int.Input:
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return IO.Int.Input(
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"seed",
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default=42,
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min=0,
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max=0xFFFFFFFF,
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control_after_generate=True,
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tooltip="Seed to determine if node should re-run; "
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"actual results are nondeterministic regardless of seed.",
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)
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def _v25_validate_settings(model: dict) -> None:
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if int(model["duration"]) > 10 and (
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int(model["fps"]) > 25 or model["resolution"] in ("2560x1440", "1440x2560", "3840x2160", "2160x3840")
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):
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raise ValueError("Durations over 10s require a 720p or 1080p resolution and 24/25 FPS.")
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class TextToVideoNode(IO.ComfyNode):
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@classmethod
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@ -86,6 +259,7 @@ class TextToVideoNode(IO.ComfyNode):
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IO.Hidden.unique_id,
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],
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is_api_node=True,
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is_deprecated=True,
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price_badge=PRICE_BADGE,
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)
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@ -164,6 +338,7 @@ class ImageToVideoNode(IO.ComfyNode):
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IO.Hidden.unique_id,
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],
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is_api_node=True,
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is_deprecated=True,
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price_badge=PRICE_BADGE,
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)
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@ -203,12 +378,217 @@ class ImageToVideoNode(IO.ComfyNode):
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return IO.NodeOutput(InputImpl.VideoFromFile(BytesIO(response)))
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class Ltx25TextToVideoNode(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="LtxApi25TextToVideo",
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display_name="LTX 2.5 Text To Video",
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category="partner/video/LTXV",
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description="Professional-quality videos with customizable duration and resolution.",
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inputs=[
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_v25_model_combo(),
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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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_v25_seed_input(),
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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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price_badge=V25_PRICE_BADGE,
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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: dict,
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prompt: str,
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seed: int = 42,
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) -> IO.NodeOutput:
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validate_string(prompt, min_length=1, max_length=10000)
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_v25_validate_settings(model)
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return await _v25_submit_and_poll(
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cls,
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"text-to-video",
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ExecuteTaskRequest(
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prompt=prompt,
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model=V25_MODELS_MAP[model["model"]],
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duration=int(model["duration"]),
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resolution=model["resolution"],
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fps=int(model["fps"]),
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generate_audio=model["generate_audio"],
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),
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)
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class Ltx25ImageToVideoNode(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="LtxApi25ImageToVideo",
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display_name="LTX 2.5 Image To Video",
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category="partner/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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_v25_model_combo(),
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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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_v25_seed_input(),
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IO.Image.Input(
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"last_frame",
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optional=True,
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tooltip="Last frame to be used for the video.",
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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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price_badge=V25_PRICE_BADGE,
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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: Input.Image,
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model: dict,
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prompt: str,
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seed: int = 42,
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last_frame: Input.Image | None = None,
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) -> IO.NodeOutput:
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validate_string(prompt, min_length=1, max_length=10000)
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_v25_validate_settings(model)
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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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last_frame_uri = None
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if last_frame is not None:
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if get_number_of_images(last_frame) != 1:
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raise ValueError("Currently only one last frame image is supported.")
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last_frame_uri = (await upload_images_to_comfyapi(cls, last_frame, max_images=1, mime_type="image/png"))[0]
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return await _v25_submit_and_poll(
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cls,
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"image-to-video",
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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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last_frame_uri=last_frame_uri,
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prompt=prompt,
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model=V25_MODELS_MAP[model["model"]],
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duration=int(model["duration"]),
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resolution=model["resolution"],
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fps=int(model["fps"]),
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generate_audio=model["generate_audio"],
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),
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)
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class Ltx25AudioToVideoNode(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="LtxApi25AudioToVideo",
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display_name="LTX 2.5 Audio To Video",
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category="partner/video/LTXV",
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description="Generate a video driven by an audio track, with an optional first frame image.",
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inputs=[
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IO.Audio.Input(
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"audio",
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tooltip="Audio track driving the video. Its length (2-20 seconds) sets the video duration.",
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),
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IO.DynamicCombo.Input(
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"model",
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options=[
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IO.DynamicCombo.Option(
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"LTX-2.5 (Fast)",
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[IO.Combo.Input("resolution", options=["1920x1080", "1080x1920"])],
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),
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IO.DynamicCombo.Option(
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"LTX-2.5 (Pro)",
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[IO.Combo.Input("resolution", options=["1920x1080", "1080x1920"])],
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),
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],
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),
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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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_v25_seed_input(),
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IO.Image.Input(
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"image",
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optional=True,
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tooltip="Optional first frame to be used for the video.",
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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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price_badge=V25_A2V_PRICE_BADGE,
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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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audio: Input.Audio,
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model: dict,
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prompt: str,
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seed: int = 42,
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image: Input.Image | None = None,
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) -> IO.NodeOutput:
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validate_string(prompt, min_length=1, max_length=10000)
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audio_duration = audio["waveform"].shape[-1] / audio["sample_rate"]
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if not 2 <= audio_duration <= 20:
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raise ValueError(f"Audio duration must be between 2 and 20 seconds, got {audio_duration:.1f}s.")
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image_uri = None
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if image is not None:
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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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image_uri = (await upload_images_to_comfyapi(cls, image, max_images=1, mime_type="image/png"))[0]
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return await _v25_submit_and_poll(
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cls,
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"audio-to-video",
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AudioToVideoRequest(
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prompt=prompt,
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model=V25_MODELS_MAP[model["model"]],
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resolution=model["resolution"],
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audio_uri=await upload_audio_to_comfyapi(cls, audio),
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image_uri=image_uri,
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),
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)
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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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Ltx25TextToVideoNode,
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Ltx25ImageToVideoNode,
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Ltx25AudioToVideoNode,
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]
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