mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2026-03-28 20:43:32 +08:00
729 lines
26 KiB
Python
729 lines
26 KiB
Python
import torch
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from typing_extensions import override
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from comfy_api.latest import IO, ComfyExtension, Input
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from comfy_api_nodes.apis.grok import (
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ImageEditRequest,
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ImageGenerationRequest,
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ImageGenerationResponse,
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InputUrlObject,
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VideoEditRequest,
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VideoExtensionRequest,
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VideoGenerationRequest,
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VideoGenerationResponse,
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VideoStatusResponse,
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)
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from comfy_api_nodes.util import (
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ApiEndpoint,
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download_url_to_image_tensor,
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download_url_to_video_output,
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get_fs_object_size,
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get_number_of_images,
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poll_op,
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sync_op,
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tensor_to_base64_string,
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upload_images_to_comfyapi,
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upload_video_to_comfyapi,
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validate_string,
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validate_video_duration,
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)
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def _extract_grok_price(response) -> float | None:
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if response.usage and response.usage.cost_in_usd_ticks is not None:
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return response.usage.cost_in_usd_ticks / 10_000_000_000
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return None
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def _extract_grok_video_price(response) -> float | None:
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price = _extract_grok_price(response)
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if price is not None:
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return price * 1.43
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return None
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class GrokImageNode(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="GrokImageNode",
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display_name="Grok Image",
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category="api node/image/Grok",
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description="Generate images using Grok based on a text prompt",
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inputs=[
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IO.Combo.Input(
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"model",
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options=["grok-imagine-image-pro", "grok-imagine-image", "grok-imagine-image-beta"],
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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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tooltip="The text prompt used to generate the image",
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),
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IO.Combo.Input(
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"aspect_ratio",
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options=[
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"1:1",
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"2:3",
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"3:2",
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"3:4",
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"4:3",
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"9:16",
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"16:9",
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"9:19.5",
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"19.5:9",
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"9:20",
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"20:9",
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"1:2",
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"2:1",
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],
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),
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IO.Int.Input(
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"number_of_images",
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default=1,
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min=1,
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max=10,
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step=1,
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tooltip="Number of images to generate",
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display_mode=IO.NumberDisplay.number,
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),
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IO.Int.Input(
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"seed",
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default=0,
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min=0,
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max=2147483647,
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step=1,
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display_mode=IO.NumberDisplay.number,
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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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IO.Combo.Input("resolution", options=["1K", "2K"], optional=True),
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],
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outputs=[
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IO.Image.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=IO.PriceBadge(
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depends_on=IO.PriceBadgeDepends(widgets=["model", "number_of_images"]),
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expr="""
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(
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$rate := $contains(widgets.model, "pro") ? 0.07 : 0.02;
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{"type":"usd","usd": $rate * widgets.number_of_images}
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)
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""",
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),
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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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aspect_ratio: str,
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number_of_images: int,
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seed: int,
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resolution: str = "1K",
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) -> IO.NodeOutput:
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validate_string(prompt, strip_whitespace=True, min_length=1)
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response = await sync_op(
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cls,
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ApiEndpoint(path="/proxy/xai/v1/images/generations", method="POST"),
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data=ImageGenerationRequest(
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model=model,
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prompt=prompt,
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aspect_ratio=aspect_ratio,
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n=number_of_images,
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seed=seed,
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resolution=resolution.lower(),
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),
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response_model=ImageGenerationResponse,
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price_extractor=_extract_grok_price,
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)
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if len(response.data) == 1:
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return IO.NodeOutput(await download_url_to_image_tensor(response.data[0].url))
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return IO.NodeOutput(
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torch.cat(
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[await download_url_to_image_tensor(i) for i in [str(d.url) for d in response.data if d.url]],
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)
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)
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class GrokImageEditNode(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="GrokImageEditNode",
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display_name="Grok Image Edit",
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category="api node/image/Grok",
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description="Modify an existing image based on a text prompt",
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inputs=[
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IO.Combo.Input(
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"model",
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options=["grok-imagine-image-pro", "grok-imagine-image", "grok-imagine-image-beta"],
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),
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IO.Image.Input("image", display_name="images"),
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IO.String.Input(
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"prompt",
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multiline=True,
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tooltip="The text prompt used to generate the image",
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),
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IO.Combo.Input("resolution", options=["1K", "2K"]),
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IO.Int.Input(
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"number_of_images",
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default=1,
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min=1,
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max=10,
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step=1,
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tooltip="Number of edited images to generate",
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display_mode=IO.NumberDisplay.number,
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),
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IO.Int.Input(
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"seed",
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default=0,
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min=0,
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max=2147483647,
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step=1,
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display_mode=IO.NumberDisplay.number,
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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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IO.Combo.Input(
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"aspect_ratio",
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options=[
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"auto",
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"1:1",
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"2:3",
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"3:2",
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"3:4",
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"4:3",
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"9:16",
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"16:9",
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"9:19.5",
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"19.5:9",
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"9:20",
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"20:9",
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"1:2",
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"2:1",
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],
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optional=True,
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tooltip="Only allowed when multiple images are connected to the image input.",
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),
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],
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outputs=[
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IO.Image.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=IO.PriceBadge(
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depends_on=IO.PriceBadgeDepends(widgets=["model", "number_of_images"]),
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expr="""
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(
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$rate := $contains(widgets.model, "pro") ? 0.07 : 0.02;
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{"type":"usd","usd": 0.002 + $rate * widgets.number_of_images}
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)
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""",
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),
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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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image: Input.Image,
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prompt: str,
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resolution: str,
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number_of_images: int,
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seed: int,
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aspect_ratio: str = "auto",
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) -> IO.NodeOutput:
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validate_string(prompt, strip_whitespace=True, min_length=1)
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if model == "grok-imagine-image-pro":
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if get_number_of_images(image) > 1:
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raise ValueError("The pro model supports only 1 input image.")
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elif get_number_of_images(image) > 3:
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raise ValueError("A maximum of 3 input images is supported.")
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if aspect_ratio != "auto" and get_number_of_images(image) == 1:
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raise ValueError(
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"Custom aspect ratio is only allowed when multiple images are connected to the image input."
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)
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response = await sync_op(
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cls,
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ApiEndpoint(path="/proxy/xai/v1/images/edits", method="POST"),
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data=ImageEditRequest(
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model=model,
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images=[InputUrlObject(url=f"data:image/png;base64,{tensor_to_base64_string(i)}") for i in image],
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prompt=prompt,
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resolution=resolution.lower(),
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n=number_of_images,
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seed=seed,
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aspect_ratio=None if aspect_ratio == "auto" else aspect_ratio,
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),
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response_model=ImageGenerationResponse,
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price_extractor=_extract_grok_price,
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)
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if len(response.data) == 1:
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return IO.NodeOutput(await download_url_to_image_tensor(response.data[0].url))
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return IO.NodeOutput(
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torch.cat(
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[await download_url_to_image_tensor(i) for i in [str(d.url) for d in response.data if d.url]],
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)
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)
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class GrokVideoNode(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="GrokVideoNode",
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display_name="Grok Video",
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category="api node/video/Grok",
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description="Generate video from a prompt or an image",
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inputs=[
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IO.Combo.Input("model", options=["grok-imagine-video", "grok-imagine-video-beta"]),
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IO.String.Input(
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"prompt",
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multiline=True,
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tooltip="Text description of the desired video.",
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),
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IO.Combo.Input(
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"resolution",
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options=["480p", "720p"],
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tooltip="The resolution of the output video.",
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),
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IO.Combo.Input(
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"aspect_ratio",
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options=["auto", "16:9", "4:3", "3:2", "1:1", "2:3", "3:4", "9:16"],
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tooltip="The aspect ratio of the output video.",
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),
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IO.Int.Input(
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"duration",
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default=6,
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min=1,
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max=15,
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step=1,
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tooltip="The duration of the output video in seconds.",
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display_mode=IO.NumberDisplay.slider,
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),
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IO.Int.Input(
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"seed",
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default=0,
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min=0,
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max=2147483647,
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step=1,
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display_mode=IO.NumberDisplay.number,
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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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IO.Image.Input("image", optional=True),
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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=IO.PriceBadge(
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depends_on=IO.PriceBadgeDepends(widgets=["duration", "resolution"], inputs=["image"]),
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expr="""
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(
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$rate := widgets.resolution = "720p" ? 0.07 : 0.05;
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$base := $rate * widgets.duration;
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{"type":"usd","usd": inputs.image.connected ? $base + 0.002 : $base}
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)
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""",
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),
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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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resolution: str,
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aspect_ratio: str,
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duration: int,
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seed: int,
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image: Input.Image | None = None,
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) -> IO.NodeOutput:
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if model == "grok-imagine-video-beta":
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model = "grok-imagine-video"
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image_url = 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("Only one input image is supported.")
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image_url = InputUrlObject(url=f"data:image/png;base64,{tensor_to_base64_string(image)}")
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validate_string(prompt, strip_whitespace=True, min_length=1)
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initial_response = await sync_op(
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cls,
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ApiEndpoint(path="/proxy/xai/v1/videos/generations", method="POST"),
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data=VideoGenerationRequest(
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model=model,
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image=image_url,
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prompt=prompt,
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resolution=resolution,
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duration=duration,
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aspect_ratio=None if aspect_ratio == "auto" else aspect_ratio,
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seed=seed,
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),
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response_model=VideoGenerationResponse,
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)
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response = await poll_op(
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cls,
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ApiEndpoint(path=f"/proxy/xai/v1/videos/{initial_response.request_id}"),
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status_extractor=lambda r: r.status if r.status is not None else "complete",
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response_model=VideoStatusResponse,
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price_extractor=_extract_grok_price,
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)
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return IO.NodeOutput(await download_url_to_video_output(response.video.url))
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class GrokVideoEditNode(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="GrokVideoEditNode",
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display_name="Grok Video Edit",
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category="api node/video/Grok",
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description="Edit an existing video based on a text prompt.",
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inputs=[
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IO.Combo.Input("model", options=["grok-imagine-video", "grok-imagine-video-beta"]),
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IO.String.Input(
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"prompt",
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multiline=True,
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tooltip="Text description of the desired video.",
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),
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IO.Video.Input("video", tooltip="Maximum supported duration is 8.7 seconds and 50MB file size."),
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IO.Int.Input(
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"seed",
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default=0,
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min=0,
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max=2147483647,
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step=1,
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display_mode=IO.NumberDisplay.number,
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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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],
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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=IO.PriceBadge(
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expr="""{"type":"usd","usd": 0.06, "format": {"suffix": "/sec", "approximate": true}}""",
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),
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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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video: Input.Video,
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seed: int,
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) -> IO.NodeOutput:
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validate_string(prompt, strip_whitespace=True, min_length=1)
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validate_video_duration(video, min_duration=1, max_duration=8.7)
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video_stream = video.get_stream_source()
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video_size = get_fs_object_size(video_stream)
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if video_size > 50 * 1024 * 1024:
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raise ValueError(f"Video size ({video_size / 1024 / 1024:.1f}MB) exceeds 50MB limit.")
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initial_response = await sync_op(
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cls,
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ApiEndpoint(path="/proxy/xai/v1/videos/edits", method="POST"),
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data=VideoEditRequest(
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model=model,
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video=InputUrlObject(url=await upload_video_to_comfyapi(cls, video)),
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prompt=prompt,
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seed=seed,
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),
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response_model=VideoGenerationResponse,
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)
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response = await poll_op(
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cls,
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ApiEndpoint(path=f"/proxy/xai/v1/videos/{initial_response.request_id}"),
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status_extractor=lambda r: r.status if r.status is not None else "complete",
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response_model=VideoStatusResponse,
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price_extractor=_extract_grok_price,
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)
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return IO.NodeOutput(await download_url_to_video_output(response.video.url))
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|
|
|
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class GrokVideoReferenceNode(IO.ComfyNode):
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|
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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="GrokVideoReferenceNode",
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display_name="Grok Reference-to-Video",
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category="api node/video/Grok",
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description="Generate video guided by reference images as style and content references.",
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inputs=[
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IO.String.Input(
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"prompt",
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multiline=True,
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tooltip="Text description of the desired video.",
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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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"grok-imagine-video",
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[
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IO.Autogrow.Input(
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"reference_images",
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template=IO.Autogrow.TemplatePrefix(
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IO.Image.Input("image"),
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prefix="reference_",
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min=1,
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max=7,
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),
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tooltip="Up to 7 reference images to guide the video generation.",
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),
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IO.Combo.Input(
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"resolution",
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options=["480p", "720p"],
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tooltip="The resolution of the output video.",
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),
|
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IO.Combo.Input(
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"aspect_ratio",
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options=["16:9", "4:3", "3:2", "1:1", "2:3", "3:4", "9:16"],
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tooltip="The aspect ratio of the output video.",
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),
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IO.Int.Input(
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"duration",
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default=6,
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min=2,
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max=10,
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step=1,
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tooltip="The duration of the output video in seconds.",
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display_mode=IO.NumberDisplay.slider,
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),
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],
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),
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],
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tooltip="The model to use for video generation.",
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),
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IO.Int.Input(
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"seed",
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default=0,
|
|
min=0,
|
|
max=2147483647,
|
|
step=1,
|
|
display_mode=IO.NumberDisplay.number,
|
|
control_after_generate=True,
|
|
tooltip="Seed to determine if node should re-run; "
|
|
"actual results are nondeterministic regardless of seed.",
|
|
),
|
|
],
|
|
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,
|
|
price_badge=IO.PriceBadge(
|
|
depends_on=IO.PriceBadgeDepends(
|
|
widgets=["model.duration", "model.resolution"],
|
|
input_groups=["model.reference_images"],
|
|
),
|
|
expr="""
|
|
(
|
|
$res := $lookup(widgets, "model.resolution");
|
|
$dur := $lookup(widgets, "model.duration");
|
|
$refs := inputGroups["model.reference_images"];
|
|
$rate := $res = "720p" ? 0.07 : 0.05;
|
|
$price := ($rate * $dur + 0.002 * $refs) * 1.43;
|
|
{"type":"usd","usd": $price}
|
|
)
|
|
""",
|
|
),
|
|
)
|
|
|
|
@classmethod
|
|
async def execute(
|
|
cls,
|
|
prompt: str,
|
|
model: dict,
|
|
seed: int,
|
|
) -> IO.NodeOutput:
|
|
validate_string(prompt, strip_whitespace=True, min_length=1)
|
|
ref_image_urls = await upload_images_to_comfyapi(
|
|
cls,
|
|
list(model["reference_images"].values()),
|
|
mime_type="image/png",
|
|
wait_label="Uploading base images",
|
|
max_images=7,
|
|
)
|
|
initial_response = await sync_op(
|
|
cls,
|
|
ApiEndpoint(path="/proxy/xai/v1/videos/generations", method="POST"),
|
|
data=VideoGenerationRequest(
|
|
model=model["model"],
|
|
reference_images=[InputUrlObject(url=i) for i in ref_image_urls],
|
|
prompt=prompt,
|
|
resolution=model["resolution"],
|
|
duration=model["duration"],
|
|
aspect_ratio=model["aspect_ratio"],
|
|
seed=seed,
|
|
),
|
|
response_model=VideoGenerationResponse,
|
|
)
|
|
response = await poll_op(
|
|
cls,
|
|
ApiEndpoint(path=f"/proxy/xai/v1/videos/{initial_response.request_id}"),
|
|
status_extractor=lambda r: r.status if r.status is not None else "complete",
|
|
response_model=VideoStatusResponse,
|
|
price_extractor=_extract_grok_video_price,
|
|
)
|
|
return IO.NodeOutput(await download_url_to_video_output(response.video.url))
|
|
|
|
|
|
class GrokVideoExtendNode(IO.ComfyNode):
|
|
|
|
@classmethod
|
|
def define_schema(cls):
|
|
return IO.Schema(
|
|
node_id="GrokVideoExtendNode",
|
|
display_name="Grok Video Extend",
|
|
category="api node/video/Grok",
|
|
description="Extend an existing video with a seamless continuation based on a text prompt.",
|
|
inputs=[
|
|
IO.String.Input(
|
|
"prompt",
|
|
multiline=True,
|
|
tooltip="Text description of what should happen next in the video.",
|
|
),
|
|
IO.Video.Input("video", tooltip="Source video to extend. MP4 format, 2-15 seconds."),
|
|
IO.DynamicCombo.Input(
|
|
"model",
|
|
options=[
|
|
IO.DynamicCombo.Option(
|
|
"grok-imagine-video",
|
|
[
|
|
IO.Int.Input(
|
|
"duration",
|
|
default=8,
|
|
min=2,
|
|
max=10,
|
|
step=1,
|
|
tooltip="Length of the extension in seconds.",
|
|
display_mode=IO.NumberDisplay.slider,
|
|
),
|
|
],
|
|
),
|
|
],
|
|
tooltip="The model to use for video extension.",
|
|
),
|
|
IO.Int.Input(
|
|
"seed",
|
|
default=0,
|
|
min=0,
|
|
max=2147483647,
|
|
step=1,
|
|
display_mode=IO.NumberDisplay.number,
|
|
control_after_generate=True,
|
|
tooltip="Seed to determine if node should re-run; "
|
|
"actual results are nondeterministic regardless of seed.",
|
|
),
|
|
],
|
|
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,
|
|
price_badge=IO.PriceBadge(
|
|
depends_on=IO.PriceBadgeDepends(widgets=["model.duration"]),
|
|
expr="""
|
|
(
|
|
$dur := $lookup(widgets, "model.duration");
|
|
{
|
|
"type": "range_usd",
|
|
"min_usd": (0.02 + 0.05 * $dur) * 1.43,
|
|
"max_usd": (0.15 + 0.05 * $dur) * 1.43
|
|
}
|
|
)
|
|
""",
|
|
),
|
|
)
|
|
|
|
@classmethod
|
|
async def execute(
|
|
cls,
|
|
prompt: str,
|
|
video: Input.Video,
|
|
model: dict,
|
|
seed: int,
|
|
) -> IO.NodeOutput:
|
|
validate_string(prompt, strip_whitespace=True, min_length=1)
|
|
validate_video_duration(video, min_duration=2, max_duration=15)
|
|
video_size = get_fs_object_size(video.get_stream_source())
|
|
if video_size > 50 * 1024 * 1024:
|
|
raise ValueError(f"Video size ({video_size / 1024 / 1024:.1f}MB) exceeds 50MB limit.")
|
|
initial_response = await sync_op(
|
|
cls,
|
|
ApiEndpoint(path="/proxy/xai/v1/videos/extensions", method="POST"),
|
|
data=VideoExtensionRequest(
|
|
prompt=prompt,
|
|
video=InputUrlObject(url=await upload_video_to_comfyapi(cls, video)),
|
|
duration=model["duration"],
|
|
),
|
|
response_model=VideoGenerationResponse,
|
|
)
|
|
response = await poll_op(
|
|
cls,
|
|
ApiEndpoint(path=f"/proxy/xai/v1/videos/{initial_response.request_id}"),
|
|
status_extractor=lambda r: r.status if r.status is not None else "complete",
|
|
response_model=VideoStatusResponse,
|
|
price_extractor=_extract_grok_video_price,
|
|
)
|
|
return IO.NodeOutput(await download_url_to_video_output(response.video.url))
|
|
|
|
|
|
class GrokExtension(ComfyExtension):
|
|
@override
|
|
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
|
|
return [
|
|
GrokImageNode,
|
|
GrokImageEditNode,
|
|
GrokVideoNode,
|
|
GrokVideoReferenceNode,
|
|
GrokVideoEditNode,
|
|
GrokVideoExtendNode,
|
|
]
|
|
|
|
|
|
async def comfy_entrypoint() -> GrokExtension:
|
|
return GrokExtension()
|