mirror of
https://github.com/comfyanonymous/ComfyUI.git
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1611 lines
60 KiB
Python
1611 lines
60 KiB
Python
import logging
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import math
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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.bytedance import (
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RECOMMENDED_PRESETS,
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RECOMMENDED_PRESETS_SEEDREAM_4,
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SEEDANCE2_PRICE_PER_1K_TOKENS,
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SEEDANCE2_REF_VIDEO_PIXEL_LIMITS,
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VIDEO_TASKS_EXECUTION_TIME,
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Image2VideoTaskCreationRequest,
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ImageTaskCreationResponse,
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Seedance2TaskCreationRequest,
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Seedream4Options,
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Seedream4TaskCreationRequest,
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TaskAudioContent,
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TaskAudioContentUrl,
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TaskCreationResponse,
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TaskImageContent,
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TaskImageContentUrl,
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TaskStatusResponse,
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TaskTextContent,
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TaskVideoContent,
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TaskVideoContentUrl,
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Text2ImageTaskCreationRequest,
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Text2VideoTaskCreationRequest,
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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_number_of_images,
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image_tensor_pair_to_batch,
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poll_op,
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sync_op,
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upload_audio_to_comfyapi,
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upload_image_to_comfyapi,
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upload_images_to_comfyapi,
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upload_video_to_comfyapi,
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validate_image_aspect_ratio,
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validate_image_dimensions,
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validate_string,
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)
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BYTEPLUS_IMAGE_ENDPOINT = "/proxy/byteplus/api/v3/images/generations"
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SEEDREAM_MODELS = {
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"seedream 5.0 lite": "seedream-5-0-260128",
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"seedream-4-5-251128": "seedream-4-5-251128",
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"seedream-4-0-250828": "seedream-4-0-250828",
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}
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# Long-running tasks endpoints(e.g., video)
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BYTEPLUS_TASK_ENDPOINT = "/proxy/byteplus/api/v3/contents/generations/tasks"
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BYTEPLUS_TASK_STATUS_ENDPOINT = "/proxy/byteplus/api/v3/contents/generations/tasks" # + /{task_id}
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BYTEPLUS_SEEDANCE2_TASK_STATUS_ENDPOINT = "/proxy/byteplus-seedance2/api/v3/contents/generations/tasks" # + /{task_id}
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SEEDANCE_MODELS = {
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"Seedance 2.0": "dreamina-seedance-2-0-260128",
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"Seedance 2.0 Fast": "dreamina-seedance-2-0-fast-260128",
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}
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DEPRECATED_MODELS = {"seedance-1-0-lite-t2v-250428", "seedance-1-0-lite-i2v-250428"}
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logger = logging.getLogger(__name__)
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def _validate_ref_video_pixels(video: Input.Video, model_id: str, index: int) -> None:
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"""Validate reference video pixel count against Seedance 2.0 model limits."""
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limits = SEEDANCE2_REF_VIDEO_PIXEL_LIMITS.get(model_id)
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if not limits:
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return
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try:
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w, h = video.get_dimensions()
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except Exception:
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return
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pixels = w * h
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min_px = limits.get("min")
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max_px = limits.get("max")
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if min_px and pixels < min_px:
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raise ValueError(
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f"Reference video {index} is too small: {w}x{h} = {pixels:,}px. " f"Minimum is {min_px:,}px for this model."
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)
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if max_px and pixels > max_px:
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raise ValueError(
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f"Reference video {index} is too large: {w}x{h} = {pixels:,}px. "
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f"Maximum is {max_px:,}px for this model. Try downscaling the video."
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)
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def _seedance2_price_extractor(model_id: str, has_video_input: bool):
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"""Returns a price_extractor closure for Seedance 2.0 poll_op."""
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rate = SEEDANCE2_PRICE_PER_1K_TOKENS.get((model_id, has_video_input))
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if rate is None:
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return None
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def extractor(response: TaskStatusResponse) -> float | None:
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if response.usage is None:
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return None
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return response.usage.total_tokens * 1.43 * rate / 1_000.0
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return extractor
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def get_image_url_from_response(response: ImageTaskCreationResponse) -> str:
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if response.error:
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error_msg = f"ByteDance request failed. Code: {response.error['code']}, message: {response.error['message']}"
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logging.info(error_msg)
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raise RuntimeError(error_msg)
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logging.info("ByteDance task succeeded, image URL: %s", response.data[0]["url"])
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return response.data[0]["url"]
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class ByteDanceImageNode(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="ByteDanceImageNode",
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display_name="ByteDance Image",
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category="api node/image/ByteDance",
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description="Generate images using ByteDance models via api based on prompt",
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inputs=[
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IO.Combo.Input("model", options=["seedream-3-0-t2i-250415"]),
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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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"size_preset",
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options=[label for label, _, _ in RECOMMENDED_PRESETS],
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tooltip="Pick a recommended size. Select Custom to use the width and height below",
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),
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IO.Int.Input(
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"width",
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default=1024,
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min=512,
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max=2048,
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step=64,
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tooltip="Custom width for image. Value is working only if `size_preset` is set to `Custom`",
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),
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IO.Int.Input(
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"height",
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default=1024,
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min=512,
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max=2048,
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step=64,
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tooltip="Custom height for image. Value is working only if `size_preset` is set to `Custom`",
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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 use for generation",
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optional=True,
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),
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IO.Float.Input(
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"guidance_scale",
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default=2.5,
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min=1.0,
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max=10.0,
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step=0.01,
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display_mode=IO.NumberDisplay.number,
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tooltip="Higher value makes the image follow the prompt more closely",
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optional=True,
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),
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IO.Boolean.Input(
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"watermark",
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default=False,
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tooltip='Whether to add an "AI generated" watermark to the image',
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optional=True,
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advanced=True,
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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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expr="""{"type":"usd","usd":0.03}""",
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),
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is_deprecated=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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size_preset: str,
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width: int,
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height: int,
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seed: int,
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guidance_scale: float,
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watermark: bool,
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) -> IO.NodeOutput:
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validate_string(prompt, strip_whitespace=True, min_length=1)
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w = h = None
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for label, tw, th in RECOMMENDED_PRESETS:
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if label == size_preset:
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w, h = tw, th
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break
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if w is None or h is None:
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w, h = width, height
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if not (512 <= w <= 2048) or not (512 <= h <= 2048):
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raise ValueError(
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f"Custom size out of range: {w}x{h}. " "Both width and height must be between 512 and 2048 pixels."
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)
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payload = Text2ImageTaskCreationRequest(
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model=model,
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prompt=prompt,
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size=f"{w}x{h}",
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seed=seed,
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guidance_scale=guidance_scale,
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watermark=watermark,
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)
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response = await sync_op(
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cls,
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ApiEndpoint(path=BYTEPLUS_IMAGE_ENDPOINT, method="POST"),
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data=payload,
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response_model=ImageTaskCreationResponse,
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)
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return IO.NodeOutput(await download_url_to_image_tensor(get_image_url_from_response(response)))
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class ByteDanceSeedreamNode(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="ByteDanceSeedreamNode",
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display_name="ByteDance Seedream 4.5 & 5.0",
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category="api node/image/ByteDance",
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description="Unified text-to-image generation and precise single-sentence editing at up to 4K resolution.",
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inputs=[
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IO.Combo.Input(
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"model",
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options=list(SEEDREAM_MODELS.keys()),
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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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tooltip="Text prompt for creating or editing an image.",
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),
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IO.Image.Input(
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"image",
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tooltip="Input image(s) for image-to-image generation. "
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"Reference image(s) for single or multi-reference generation.",
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optional=True,
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),
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IO.Combo.Input(
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"size_preset",
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options=[label for label, _, _ in RECOMMENDED_PRESETS_SEEDREAM_4],
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tooltip="Pick a recommended size. Select Custom to use the width and height below.",
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),
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IO.Int.Input(
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"width",
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default=2048,
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min=1024,
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max=6240,
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step=2,
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tooltip="Custom width for image. Value is working only if `size_preset` is set to `Custom`",
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optional=True,
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),
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IO.Int.Input(
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"height",
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default=2048,
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min=1024,
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max=4992,
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step=2,
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tooltip="Custom height for image. Value is working only if `size_preset` is set to `Custom`",
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optional=True,
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),
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IO.Combo.Input(
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"sequential_image_generation",
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options=["disabled", "auto"],
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tooltip="Group image generation mode. "
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"'disabled' generates a single image. "
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"'auto' lets the model decide whether to generate multiple related images "
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"(e.g., story scenes, character variations).",
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optional=True,
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),
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IO.Int.Input(
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"max_images",
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default=1,
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min=1,
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max=15,
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step=1,
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display_mode=IO.NumberDisplay.number,
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tooltip="Maximum number of images to generate when sequential_image_generation='auto'. "
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"Total images (input + generated) cannot exceed 15.",
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optional=True,
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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 use for generation.",
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optional=True,
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),
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IO.Boolean.Input(
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"watermark",
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default=False,
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tooltip='Whether to add an "AI generated" watermark to the image.',
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optional=True,
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advanced=True,
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),
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IO.Boolean.Input(
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"fail_on_partial",
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default=True,
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tooltip="If enabled, abort execution if any requested images are missing or return an error.",
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optional=True,
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advanced=True,
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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"]),
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expr="""
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(
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$price := $contains(widgets.model, "5.0 lite") ? 0.035 :
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$contains(widgets.model, "4-5") ? 0.04 : 0.03;
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{
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"type":"usd",
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"usd": $price,
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"format": { "suffix":" x images/Run", "approximate": true }
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}
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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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image: Input.Image | None = None,
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size_preset: str = RECOMMENDED_PRESETS_SEEDREAM_4[0][0],
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width: int = 2048,
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height: int = 2048,
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sequential_image_generation: str = "disabled",
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max_images: int = 1,
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seed: int = 0,
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watermark: bool = False,
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fail_on_partial: bool = True,
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) -> IO.NodeOutput:
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model = SEEDREAM_MODELS[model]
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validate_string(prompt, strip_whitespace=True, min_length=1)
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w = h = None
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for label, tw, th in RECOMMENDED_PRESETS_SEEDREAM_4:
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if label == size_preset:
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w, h = tw, th
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break
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if w is None or h is None:
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w, h = width, height
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out_num_pixels = w * h
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mp_provided = out_num_pixels / 1_000_000.0
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if ("seedream-4-5" in model or "seedream-5-0" in model) and out_num_pixels < 3686400:
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raise ValueError(
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f"Minimum image resolution for the selected model is 3.68MP, " f"but {mp_provided:.2f}MP provided."
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)
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if "seedream-4-0" in model and out_num_pixels < 921600:
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raise ValueError(
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f"Minimum image resolution that the selected model can generate is 0.92MP, "
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f"but {mp_provided:.2f}MP provided."
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)
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max_pixels = 10_404_496 if "seedream-5-0" in model else 16_777_216
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if out_num_pixels > max_pixels:
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raise ValueError(
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f"Maximum image resolution for the selected model is {max_pixels / 1_000_000:.2f}MP, "
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f"but {mp_provided:.2f}MP provided."
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)
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n_input_images = get_number_of_images(image) if image is not None else 0
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max_num_of_images = 14 if model == "seedream-5-0-260128" else 10
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if n_input_images > max_num_of_images:
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raise ValueError(
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f"Maximum of {max_num_of_images} reference images are supported, but {n_input_images} received."
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)
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if sequential_image_generation == "auto" and n_input_images + max_images > 15:
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raise ValueError(
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"The maximum number of generated images plus the number of reference images cannot exceed 15."
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)
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reference_images_urls = []
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if n_input_images:
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for i in image:
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validate_image_aspect_ratio(i, (1, 3), (3, 1))
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reference_images_urls = await upload_images_to_comfyapi(
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cls,
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image,
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max_images=n_input_images,
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mime_type="image/png",
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)
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response = await sync_op(
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cls,
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ApiEndpoint(path=BYTEPLUS_IMAGE_ENDPOINT, method="POST"),
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response_model=ImageTaskCreationResponse,
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data=Seedream4TaskCreationRequest(
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model=model,
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prompt=prompt,
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image=reference_images_urls,
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size=f"{w}x{h}",
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seed=seed,
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sequential_image_generation=sequential_image_generation,
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sequential_image_generation_options=Seedream4Options(max_images=max_images),
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watermark=watermark,
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output_format="png" if model == "seedream-5-0-260128" else None,
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),
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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(get_image_url_from_response(response)))
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urls = [str(d["url"]) for d in response.data if isinstance(d, dict) and "url" in d]
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if fail_on_partial and len(urls) < len(response.data):
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raise RuntimeError(f"Only {len(urls)} of {len(response.data)} images were generated before error.")
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return IO.NodeOutput(torch.cat([await download_url_to_image_tensor(i) for i in urls]))
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|
|
|
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class ByteDanceTextToVideoNode(IO.ComfyNode):
|
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|
|
@classmethod
|
|
def define_schema(cls):
|
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return IO.Schema(
|
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node_id="ByteDanceTextToVideoNode",
|
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display_name="ByteDance Text to Video",
|
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category="api node/video/ByteDance",
|
|
description="Generate video using ByteDance models via api based on prompt",
|
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inputs=[
|
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IO.Combo.Input(
|
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"model",
|
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options=[
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"seedance-1-5-pro-251215",
|
|
"seedance-1-0-pro-250528",
|
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"seedance-1-0-lite-t2v-250428",
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"seedance-1-0-pro-fast-251015",
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],
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default="seedance-1-0-pro-fast-251015",
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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 video.",
|
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),
|
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IO.Combo.Input(
|
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"resolution",
|
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options=["480p", "720p", "1080p"],
|
|
tooltip="The resolution of the output video.",
|
|
),
|
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IO.Combo.Input(
|
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"aspect_ratio",
|
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options=["16:9", "4:3", "1:1", "3:4", "9:16", "21:9"],
|
|
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=5,
|
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min=3,
|
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max=12,
|
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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 use for generation.",
|
|
optional=True,
|
|
),
|
|
IO.Boolean.Input(
|
|
"camera_fixed",
|
|
default=False,
|
|
tooltip="Specifies whether to fix the camera. The platform appends an instruction "
|
|
"to fix the camera to your prompt, but does not guarantee the actual effect.",
|
|
optional=True,
|
|
advanced=True,
|
|
),
|
|
IO.Boolean.Input(
|
|
"watermark",
|
|
default=False,
|
|
tooltip='Whether to add an "AI generated" watermark to the video.',
|
|
optional=True,
|
|
advanced=True,
|
|
),
|
|
IO.Boolean.Input(
|
|
"generate_audio",
|
|
default=False,
|
|
tooltip="This parameter is ignored for any model except seedance-1-5-pro.",
|
|
optional=True,
|
|
advanced=True,
|
|
),
|
|
],
|
|
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=PRICE_BADGE_VIDEO,
|
|
)
|
|
|
|
@classmethod
|
|
async def execute(
|
|
cls,
|
|
model: str,
|
|
prompt: str,
|
|
resolution: str,
|
|
aspect_ratio: str,
|
|
duration: int,
|
|
seed: int,
|
|
camera_fixed: bool,
|
|
watermark: bool,
|
|
generate_audio: bool = False,
|
|
) -> IO.NodeOutput:
|
|
if model == "seedance-1-5-pro-251215" and duration < 4:
|
|
raise ValueError("Minimum supported duration for Seedance 1.5 Pro is 4 seconds.")
|
|
validate_string(prompt, strip_whitespace=True, min_length=1)
|
|
raise_if_text_params(prompt, ["resolution", "ratio", "duration", "seed", "camerafixed", "watermark"])
|
|
|
|
prompt = (
|
|
f"{prompt} "
|
|
f"--resolution {resolution} "
|
|
f"--ratio {aspect_ratio} "
|
|
f"--duration {duration} "
|
|
f"--seed {seed} "
|
|
f"--camerafixed {str(camera_fixed).lower()} "
|
|
f"--watermark {str(watermark).lower()}"
|
|
)
|
|
return await process_video_task(
|
|
cls,
|
|
payload=Text2VideoTaskCreationRequest(
|
|
model=model,
|
|
content=[TaskTextContent(text=prompt)],
|
|
generate_audio=generate_audio if model == "seedance-1-5-pro-251215" else None,
|
|
),
|
|
estimated_duration=max(1, math.ceil(VIDEO_TASKS_EXECUTION_TIME[model][resolution] * (duration / 10.0))),
|
|
)
|
|
|
|
|
|
class ByteDanceImageToVideoNode(IO.ComfyNode):
|
|
|
|
@classmethod
|
|
def define_schema(cls):
|
|
return IO.Schema(
|
|
node_id="ByteDanceImageToVideoNode",
|
|
display_name="ByteDance Image to Video",
|
|
category="api node/video/ByteDance",
|
|
description="Generate video using ByteDance models via api based on image and prompt",
|
|
inputs=[
|
|
IO.Combo.Input(
|
|
"model",
|
|
options=[
|
|
"seedance-1-5-pro-251215",
|
|
"seedance-1-0-pro-250528",
|
|
"seedance-1-0-lite-i2v-250428",
|
|
"seedance-1-0-pro-fast-251015",
|
|
],
|
|
default="seedance-1-0-pro-fast-251015",
|
|
),
|
|
IO.String.Input(
|
|
"prompt",
|
|
multiline=True,
|
|
tooltip="The text prompt used to generate the video.",
|
|
),
|
|
IO.Image.Input(
|
|
"image",
|
|
tooltip="First frame to be used for the video.",
|
|
),
|
|
IO.Combo.Input(
|
|
"resolution",
|
|
options=["480p", "720p", "1080p"],
|
|
tooltip="The resolution of the output video.",
|
|
),
|
|
IO.Combo.Input(
|
|
"aspect_ratio",
|
|
options=["adaptive", "16:9", "4:3", "1:1", "3:4", "9:16", "21:9"],
|
|
tooltip="The aspect ratio of the output video.",
|
|
),
|
|
IO.Int.Input(
|
|
"duration",
|
|
default=5,
|
|
min=3,
|
|
max=12,
|
|
step=1,
|
|
tooltip="The duration of the output video in seconds.",
|
|
display_mode=IO.NumberDisplay.slider,
|
|
),
|
|
IO.Int.Input(
|
|
"seed",
|
|
default=0,
|
|
min=0,
|
|
max=2147483647,
|
|
step=1,
|
|
display_mode=IO.NumberDisplay.number,
|
|
control_after_generate=True,
|
|
tooltip="Seed to use for generation.",
|
|
optional=True,
|
|
),
|
|
IO.Boolean.Input(
|
|
"camera_fixed",
|
|
default=False,
|
|
tooltip="Specifies whether to fix the camera. The platform appends an instruction "
|
|
"to fix the camera to your prompt, but does not guarantee the actual effect.",
|
|
optional=True,
|
|
advanced=True,
|
|
),
|
|
IO.Boolean.Input(
|
|
"watermark",
|
|
default=False,
|
|
tooltip='Whether to add an "AI generated" watermark to the video.',
|
|
optional=True,
|
|
advanced=True,
|
|
),
|
|
IO.Boolean.Input(
|
|
"generate_audio",
|
|
default=False,
|
|
tooltip="This parameter is ignored for any model except seedance-1-5-pro.",
|
|
optional=True,
|
|
advanced=True,
|
|
),
|
|
],
|
|
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=PRICE_BADGE_VIDEO,
|
|
)
|
|
|
|
@classmethod
|
|
async def execute(
|
|
cls,
|
|
model: str,
|
|
prompt: str,
|
|
image: Input.Image,
|
|
resolution: str,
|
|
aspect_ratio: str,
|
|
duration: int,
|
|
seed: int,
|
|
camera_fixed: bool,
|
|
watermark: bool,
|
|
generate_audio: bool = False,
|
|
) -> IO.NodeOutput:
|
|
if model == "seedance-1-5-pro-251215" and duration < 4:
|
|
raise ValueError("Minimum supported duration for Seedance 1.5 Pro is 4 seconds.")
|
|
validate_string(prompt, strip_whitespace=True, min_length=1)
|
|
raise_if_text_params(prompt, ["resolution", "ratio", "duration", "seed", "camerafixed", "watermark"])
|
|
validate_image_dimensions(image, min_width=300, min_height=300, max_width=6000, max_height=6000)
|
|
validate_image_aspect_ratio(image, (2, 5), (5, 2), strict=False) # 0.4 to 2.5
|
|
|
|
image_url = (await upload_images_to_comfyapi(cls, image, max_images=1))[0]
|
|
prompt = (
|
|
f"{prompt} "
|
|
f"--resolution {resolution} "
|
|
f"--ratio {aspect_ratio} "
|
|
f"--duration {duration} "
|
|
f"--seed {seed} "
|
|
f"--camerafixed {str(camera_fixed).lower()} "
|
|
f"--watermark {str(watermark).lower()}"
|
|
)
|
|
|
|
return await process_video_task(
|
|
cls,
|
|
payload=Image2VideoTaskCreationRequest(
|
|
model=model,
|
|
content=[TaskTextContent(text=prompt), TaskImageContent(image_url=TaskImageContentUrl(url=image_url))],
|
|
generate_audio=generate_audio if model == "seedance-1-5-pro-251215" else None,
|
|
),
|
|
estimated_duration=max(1, math.ceil(VIDEO_TASKS_EXECUTION_TIME[model][resolution] * (duration / 10.0))),
|
|
)
|
|
|
|
|
|
class ByteDanceFirstLastFrameNode(IO.ComfyNode):
|
|
|
|
@classmethod
|
|
def define_schema(cls):
|
|
return IO.Schema(
|
|
node_id="ByteDanceFirstLastFrameNode",
|
|
display_name="ByteDance First-Last-Frame to Video",
|
|
category="api node/video/ByteDance",
|
|
description="Generate video using prompt and first and last frames.",
|
|
inputs=[
|
|
IO.Combo.Input(
|
|
"model",
|
|
options=["seedance-1-5-pro-251215", "seedance-1-0-pro-250528", "seedance-1-0-lite-i2v-250428"],
|
|
default="seedance-1-0-lite-i2v-250428",
|
|
),
|
|
IO.String.Input(
|
|
"prompt",
|
|
multiline=True,
|
|
tooltip="The text prompt used to generate the video.",
|
|
),
|
|
IO.Image.Input(
|
|
"first_frame",
|
|
tooltip="First frame to be used for the video.",
|
|
),
|
|
IO.Image.Input(
|
|
"last_frame",
|
|
tooltip="Last frame to be used for the video.",
|
|
),
|
|
IO.Combo.Input(
|
|
"resolution",
|
|
options=["480p", "720p", "1080p"],
|
|
tooltip="The resolution of the output video.",
|
|
),
|
|
IO.Combo.Input(
|
|
"aspect_ratio",
|
|
options=["adaptive", "16:9", "4:3", "1:1", "3:4", "9:16", "21:9"],
|
|
tooltip="The aspect ratio of the output video.",
|
|
),
|
|
IO.Int.Input(
|
|
"duration",
|
|
default=5,
|
|
min=3,
|
|
max=12,
|
|
step=1,
|
|
tooltip="The duration of the output video in seconds.",
|
|
display_mode=IO.NumberDisplay.slider,
|
|
),
|
|
IO.Int.Input(
|
|
"seed",
|
|
default=0,
|
|
min=0,
|
|
max=2147483647,
|
|
step=1,
|
|
display_mode=IO.NumberDisplay.number,
|
|
control_after_generate=True,
|
|
tooltip="Seed to use for generation.",
|
|
optional=True,
|
|
),
|
|
IO.Boolean.Input(
|
|
"camera_fixed",
|
|
default=False,
|
|
tooltip="Specifies whether to fix the camera. The platform appends an instruction "
|
|
"to fix the camera to your prompt, but does not guarantee the actual effect.",
|
|
optional=True,
|
|
advanced=True,
|
|
),
|
|
IO.Boolean.Input(
|
|
"watermark",
|
|
default=False,
|
|
tooltip='Whether to add an "AI generated" watermark to the video.',
|
|
optional=True,
|
|
advanced=True,
|
|
),
|
|
IO.Boolean.Input(
|
|
"generate_audio",
|
|
default=False,
|
|
tooltip="This parameter is ignored for any model except seedance-1-5-pro.",
|
|
optional=True,
|
|
advanced=True,
|
|
),
|
|
],
|
|
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=PRICE_BADGE_VIDEO,
|
|
)
|
|
|
|
@classmethod
|
|
async def execute(
|
|
cls,
|
|
model: str,
|
|
prompt: str,
|
|
first_frame: Input.Image,
|
|
last_frame: Input.Image,
|
|
resolution: str,
|
|
aspect_ratio: str,
|
|
duration: int,
|
|
seed: int,
|
|
camera_fixed: bool,
|
|
watermark: bool,
|
|
generate_audio: bool = False,
|
|
) -> IO.NodeOutput:
|
|
if model == "seedance-1-5-pro-251215" and duration < 4:
|
|
raise ValueError("Minimum supported duration for Seedance 1.5 Pro is 4 seconds.")
|
|
validate_string(prompt, strip_whitespace=True, min_length=1)
|
|
raise_if_text_params(prompt, ["resolution", "ratio", "duration", "seed", "camerafixed", "watermark"])
|
|
for i in (first_frame, last_frame):
|
|
validate_image_dimensions(i, min_width=300, min_height=300, max_width=6000, max_height=6000)
|
|
validate_image_aspect_ratio(i, (2, 5), (5, 2), strict=False) # 0.4 to 2.5
|
|
|
|
download_urls = await upload_images_to_comfyapi(
|
|
cls,
|
|
image_tensor_pair_to_batch(first_frame, last_frame),
|
|
max_images=2,
|
|
mime_type="image/png",
|
|
)
|
|
|
|
prompt = (
|
|
f"{prompt} "
|
|
f"--resolution {resolution} "
|
|
f"--ratio {aspect_ratio} "
|
|
f"--duration {duration} "
|
|
f"--seed {seed} "
|
|
f"--camerafixed {str(camera_fixed).lower()} "
|
|
f"--watermark {str(watermark).lower()}"
|
|
)
|
|
|
|
return await process_video_task(
|
|
cls,
|
|
payload=Image2VideoTaskCreationRequest(
|
|
model=model,
|
|
content=[
|
|
TaskTextContent(text=prompt),
|
|
TaskImageContent(image_url=TaskImageContentUrl(url=str(download_urls[0])), role="first_frame"),
|
|
TaskImageContent(image_url=TaskImageContentUrl(url=str(download_urls[1])), role="last_frame"),
|
|
],
|
|
generate_audio=generate_audio if model == "seedance-1-5-pro-251215" else None,
|
|
),
|
|
estimated_duration=max(1, math.ceil(VIDEO_TASKS_EXECUTION_TIME[model][resolution] * (duration / 10.0))),
|
|
)
|
|
|
|
|
|
class ByteDanceImageReferenceNode(IO.ComfyNode):
|
|
|
|
@classmethod
|
|
def define_schema(cls):
|
|
return IO.Schema(
|
|
node_id="ByteDanceImageReferenceNode",
|
|
display_name="ByteDance Reference Images to Video",
|
|
category="api node/video/ByteDance",
|
|
description="Generate video using prompt and reference images.",
|
|
inputs=[
|
|
IO.Combo.Input(
|
|
"model",
|
|
options=["seedance-1-0-pro-250528", "seedance-1-0-lite-i2v-250428"],
|
|
default="seedance-1-0-lite-i2v-250428",
|
|
),
|
|
IO.String.Input(
|
|
"prompt",
|
|
multiline=True,
|
|
tooltip="The text prompt used to generate the video.",
|
|
),
|
|
IO.Image.Input(
|
|
"images",
|
|
tooltip="One to four images.",
|
|
),
|
|
IO.Combo.Input(
|
|
"resolution",
|
|
options=["480p", "720p"],
|
|
tooltip="The resolution of the output video.",
|
|
),
|
|
IO.Combo.Input(
|
|
"aspect_ratio",
|
|
options=["adaptive", "16:9", "4:3", "1:1", "3:4", "9:16", "21:9"],
|
|
tooltip="The aspect ratio of the output video.",
|
|
),
|
|
IO.Int.Input(
|
|
"duration",
|
|
default=5,
|
|
min=3,
|
|
max=12,
|
|
step=1,
|
|
tooltip="The duration of the output video in seconds.",
|
|
display_mode=IO.NumberDisplay.slider,
|
|
),
|
|
IO.Int.Input(
|
|
"seed",
|
|
default=0,
|
|
min=0,
|
|
max=2147483647,
|
|
step=1,
|
|
display_mode=IO.NumberDisplay.number,
|
|
control_after_generate=True,
|
|
tooltip="Seed to use for generation.",
|
|
optional=True,
|
|
),
|
|
IO.Boolean.Input(
|
|
"watermark",
|
|
default=False,
|
|
tooltip='Whether to add an "AI generated" watermark to the video.',
|
|
optional=True,
|
|
advanced=True,
|
|
),
|
|
],
|
|
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", "resolution"]),
|
|
expr="""
|
|
(
|
|
$priceByModel := {
|
|
"seedance-1-0-pro": {
|
|
"480p":[0.23,0.24],
|
|
"720p":[0.51,0.56]
|
|
},
|
|
"seedance-1-0-lite": {
|
|
"480p":[0.17,0.18],
|
|
"720p":[0.37,0.41]
|
|
}
|
|
};
|
|
$model := widgets.model;
|
|
$modelKey :=
|
|
$contains($model, "seedance-1-0-pro") ? "seedance-1-0-pro" :
|
|
"seedance-1-0-lite";
|
|
$resolution := widgets.resolution;
|
|
$resKey :=
|
|
$contains($resolution, "720") ? "720p" :
|
|
"480p";
|
|
$modelPrices := $lookup($priceByModel, $modelKey);
|
|
$baseRange := $lookup($modelPrices, $resKey);
|
|
$min10s := $baseRange[0];
|
|
$max10s := $baseRange[1];
|
|
$scale := widgets.duration / 10;
|
|
$minCost := $min10s * $scale;
|
|
$maxCost := $max10s * $scale;
|
|
($minCost = $maxCost)
|
|
? {"type":"usd","usd": $minCost}
|
|
: {"type":"range_usd","min_usd": $minCost, "max_usd": $maxCost}
|
|
)
|
|
""",
|
|
),
|
|
)
|
|
|
|
@classmethod
|
|
async def execute(
|
|
cls,
|
|
model: str,
|
|
prompt: str,
|
|
images: Input.Image,
|
|
resolution: str,
|
|
aspect_ratio: str,
|
|
duration: int,
|
|
seed: int,
|
|
watermark: bool,
|
|
) -> IO.NodeOutput:
|
|
validate_string(prompt, strip_whitespace=True, min_length=1)
|
|
raise_if_text_params(prompt, ["resolution", "ratio", "duration", "seed", "watermark"])
|
|
for image in images:
|
|
validate_image_dimensions(image, min_width=300, min_height=300, max_width=6000, max_height=6000)
|
|
validate_image_aspect_ratio(image, (2, 5), (5, 2), strict=False) # 0.4 to 2.5
|
|
|
|
image_urls = await upload_images_to_comfyapi(cls, images, max_images=4, mime_type="image/png")
|
|
prompt = (
|
|
f"{prompt} "
|
|
f"--resolution {resolution} "
|
|
f"--ratio {aspect_ratio} "
|
|
f"--duration {duration} "
|
|
f"--seed {seed} "
|
|
f"--watermark {str(watermark).lower()}"
|
|
)
|
|
x = [
|
|
TaskTextContent(text=prompt),
|
|
*[TaskImageContent(image_url=TaskImageContentUrl(url=str(i)), role="reference_image") for i in image_urls],
|
|
]
|
|
return await process_video_task(
|
|
cls,
|
|
payload=Image2VideoTaskCreationRequest(model=model, content=x, generate_audio=None),
|
|
estimated_duration=max(1, math.ceil(VIDEO_TASKS_EXECUTION_TIME[model][resolution] * (duration / 10.0))),
|
|
)
|
|
|
|
|
|
def raise_if_text_params(prompt: str, text_params: list[str]) -> None:
|
|
for i in text_params:
|
|
if f"--{i} " in prompt:
|
|
raise ValueError(
|
|
f"--{i} is not allowed in the prompt, use the appropriated widget input to change this value."
|
|
)
|
|
|
|
|
|
PRICE_BADGE_VIDEO = IO.PriceBadge(
|
|
depends_on=IO.PriceBadgeDepends(widgets=["model", "duration", "resolution", "generate_audio"]),
|
|
expr="""
|
|
(
|
|
$priceByModel := {
|
|
"seedance-1-5-pro": {
|
|
"480p":[0.12,0.12],
|
|
"720p":[0.26,0.26],
|
|
"1080p":[0.58,0.59]
|
|
},
|
|
"seedance-1-0-pro": {
|
|
"480p":[0.23,0.24],
|
|
"720p":[0.51,0.56],
|
|
"1080p":[1.18,1.22]
|
|
},
|
|
"seedance-1-0-pro-fast": {
|
|
"480p":[0.09,0.1],
|
|
"720p":[0.21,0.23],
|
|
"1080p":[0.47,0.49]
|
|
},
|
|
"seedance-1-0-lite": {
|
|
"480p":[0.17,0.18],
|
|
"720p":[0.37,0.41],
|
|
"1080p":[0.85,0.88]
|
|
}
|
|
};
|
|
$model := widgets.model;
|
|
$modelKey :=
|
|
$contains($model, "seedance-1-5-pro") ? "seedance-1-5-pro" :
|
|
$contains($model, "seedance-1-0-pro-fast") ? "seedance-1-0-pro-fast" :
|
|
$contains($model, "seedance-1-0-pro") ? "seedance-1-0-pro" :
|
|
"seedance-1-0-lite";
|
|
$resolution := widgets.resolution;
|
|
$resKey :=
|
|
$contains($resolution, "1080") ? "1080p" :
|
|
$contains($resolution, "720") ? "720p" :
|
|
"480p";
|
|
$modelPrices := $lookup($priceByModel, $modelKey);
|
|
$baseRange := $lookup($modelPrices, $resKey);
|
|
$min10s := $baseRange[0];
|
|
$max10s := $baseRange[1];
|
|
$scale := widgets.duration / 10;
|
|
$audioMultiplier := ($modelKey = "seedance-1-5-pro" and widgets.generate_audio) ? 2 : 1;
|
|
$minCost := $min10s * $scale * $audioMultiplier;
|
|
$maxCost := $max10s * $scale * $audioMultiplier;
|
|
($minCost = $maxCost)
|
|
? {"type":"usd","usd": $minCost, "format": { "approximate": true }}
|
|
: {"type":"range_usd","min_usd": $minCost, "max_usd": $maxCost, "format": { "approximate": true }}
|
|
)
|
|
""",
|
|
)
|
|
|
|
|
|
def _seedance2_text_inputs():
|
|
return [
|
|
IO.String.Input(
|
|
"prompt",
|
|
multiline=True,
|
|
default="",
|
|
tooltip="Text prompt for video generation.",
|
|
),
|
|
IO.Combo.Input(
|
|
"resolution",
|
|
options=["480p", "720p"],
|
|
tooltip="Resolution of the output video.",
|
|
),
|
|
IO.Combo.Input(
|
|
"ratio",
|
|
options=["16:9", "4:3", "1:1", "3:4", "9:16", "21:9", "adaptive"],
|
|
tooltip="Aspect ratio of the output video.",
|
|
),
|
|
IO.Int.Input(
|
|
"duration",
|
|
default=7,
|
|
min=4,
|
|
max=15,
|
|
step=1,
|
|
tooltip="Duration of the output video in seconds (4-15).",
|
|
display_mode=IO.NumberDisplay.slider,
|
|
),
|
|
IO.Boolean.Input(
|
|
"generate_audio",
|
|
default=True,
|
|
tooltip="Enable audio generation for the output video.",
|
|
),
|
|
]
|
|
|
|
|
|
class ByteDance2TextToVideoNode(IO.ComfyNode):
|
|
|
|
@classmethod
|
|
def define_schema(cls):
|
|
return IO.Schema(
|
|
node_id="ByteDance2TextToVideoNode",
|
|
display_name="ByteDance Seedance 2.0 Text to Video",
|
|
category="api node/video/ByteDance",
|
|
description="Generate video using Seedance 2.0 models based on a text prompt.",
|
|
inputs=[
|
|
IO.DynamicCombo.Input(
|
|
"model",
|
|
options=[
|
|
IO.DynamicCombo.Option("Seedance 2.0", _seedance2_text_inputs()),
|
|
IO.DynamicCombo.Option("Seedance 2.0 Fast", _seedance2_text_inputs()),
|
|
],
|
|
tooltip="Seedance 2.0 for maximum quality; Seedance 2.0 Fast for speed optimization.",
|
|
),
|
|
IO.Int.Input(
|
|
"seed",
|
|
default=0,
|
|
min=0,
|
|
max=2147483647,
|
|
step=1,
|
|
display_mode=IO.NumberDisplay.number,
|
|
control_after_generate=True,
|
|
tooltip="Seed controls whether the node should re-run; "
|
|
"results are non-deterministic regardless of seed.",
|
|
),
|
|
IO.Boolean.Input(
|
|
"watermark",
|
|
default=False,
|
|
tooltip="Whether to add a watermark to the video.",
|
|
advanced=True,
|
|
),
|
|
],
|
|
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", "model.resolution", "model.duration"]),
|
|
expr="""
|
|
(
|
|
$rate480 := 10044;
|
|
$rate720 := 21600;
|
|
$m := widgets.model;
|
|
$pricePer1K := $contains($m, "fast") ? 0.008008 : 0.01001;
|
|
$res := $lookup(widgets, "model.resolution");
|
|
$dur := $lookup(widgets, "model.duration");
|
|
$rate := $res = "720p" ? $rate720 : $rate480;
|
|
$cost := $dur * $rate * $pricePer1K / 1000;
|
|
{"type": "usd", "usd": $cost, "format": {"approximate": true}}
|
|
)
|
|
""",
|
|
),
|
|
)
|
|
|
|
@classmethod
|
|
async def execute(
|
|
cls,
|
|
model: dict,
|
|
seed: int,
|
|
watermark: bool,
|
|
) -> IO.NodeOutput:
|
|
validate_string(model["prompt"], strip_whitespace=True, min_length=1)
|
|
model_id = SEEDANCE_MODELS[model["model"]]
|
|
initial_response = await sync_op(
|
|
cls,
|
|
ApiEndpoint(path=BYTEPLUS_TASK_ENDPOINT, method="POST"),
|
|
data=Seedance2TaskCreationRequest(
|
|
model=model_id,
|
|
content=[TaskTextContent(text=model["prompt"])],
|
|
generate_audio=model["generate_audio"],
|
|
resolution=model["resolution"],
|
|
ratio=model["ratio"],
|
|
duration=model["duration"],
|
|
seed=seed,
|
|
watermark=watermark,
|
|
),
|
|
response_model=TaskCreationResponse,
|
|
)
|
|
response = await poll_op(
|
|
cls,
|
|
ApiEndpoint(path=f"{BYTEPLUS_SEEDANCE2_TASK_STATUS_ENDPOINT}/{initial_response.id}"),
|
|
response_model=TaskStatusResponse,
|
|
status_extractor=lambda r: r.status,
|
|
price_extractor=_seedance2_price_extractor(model_id, has_video_input=False),
|
|
poll_interval=9,
|
|
)
|
|
return IO.NodeOutput(await download_url_to_video_output(response.content.video_url))
|
|
|
|
|
|
class ByteDance2FirstLastFrameNode(IO.ComfyNode):
|
|
|
|
@classmethod
|
|
def define_schema(cls):
|
|
return IO.Schema(
|
|
node_id="ByteDance2FirstLastFrameNode",
|
|
display_name="ByteDance Seedance 2.0 First-Last-Frame to Video",
|
|
category="api node/video/ByteDance",
|
|
description="Generate video using Seedance 2.0 from a first frame image and optional last frame image.",
|
|
inputs=[
|
|
IO.DynamicCombo.Input(
|
|
"model",
|
|
options=[
|
|
IO.DynamicCombo.Option("Seedance 2.0", _seedance2_text_inputs()),
|
|
IO.DynamicCombo.Option("Seedance 2.0 Fast", _seedance2_text_inputs()),
|
|
],
|
|
tooltip="Seedance 2.0 for maximum quality; Seedance 2.0 Fast for speed optimization.",
|
|
),
|
|
IO.Image.Input(
|
|
"first_frame",
|
|
tooltip="First frame image for the video.",
|
|
),
|
|
IO.Image.Input(
|
|
"last_frame",
|
|
tooltip="Last frame image for the video.",
|
|
optional=True,
|
|
),
|
|
IO.Int.Input(
|
|
"seed",
|
|
default=0,
|
|
min=0,
|
|
max=2147483647,
|
|
step=1,
|
|
display_mode=IO.NumberDisplay.number,
|
|
control_after_generate=True,
|
|
tooltip="Seed controls whether the node should re-run; "
|
|
"results are non-deterministic regardless of seed.",
|
|
),
|
|
IO.Boolean.Input(
|
|
"watermark",
|
|
default=False,
|
|
tooltip="Whether to add a watermark to the video.",
|
|
advanced=True,
|
|
),
|
|
],
|
|
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", "model.resolution", "model.duration"]),
|
|
expr="""
|
|
(
|
|
$rate480 := 10044;
|
|
$rate720 := 21600;
|
|
$m := widgets.model;
|
|
$pricePer1K := $contains($m, "fast") ? 0.008008 : 0.01001;
|
|
$res := $lookup(widgets, "model.resolution");
|
|
$dur := $lookup(widgets, "model.duration");
|
|
$rate := $res = "720p" ? $rate720 : $rate480;
|
|
$cost := $dur * $rate * $pricePer1K / 1000;
|
|
{"type": "usd", "usd": $cost, "format": {"approximate": true}}
|
|
)
|
|
""",
|
|
),
|
|
)
|
|
|
|
@classmethod
|
|
async def execute(
|
|
cls,
|
|
model: dict,
|
|
first_frame: Input.Image,
|
|
seed: int,
|
|
watermark: bool,
|
|
last_frame: Input.Image | None = None,
|
|
) -> IO.NodeOutput:
|
|
validate_string(model["prompt"], strip_whitespace=True, min_length=1)
|
|
model_id = SEEDANCE_MODELS[model["model"]]
|
|
|
|
content: list[TaskTextContent | TaskImageContent] = [
|
|
TaskTextContent(text=model["prompt"]),
|
|
TaskImageContent(
|
|
image_url=TaskImageContentUrl(
|
|
url=await upload_image_to_comfyapi(cls, first_frame, wait_label="Uploading first frame.")
|
|
),
|
|
role="first_frame",
|
|
),
|
|
]
|
|
if last_frame is not None:
|
|
content.append(
|
|
TaskImageContent(
|
|
image_url=TaskImageContentUrl(
|
|
url=await upload_image_to_comfyapi(cls, last_frame, wait_label="Uploading last frame.")
|
|
),
|
|
role="last_frame",
|
|
),
|
|
)
|
|
|
|
initial_response = await sync_op(
|
|
cls,
|
|
ApiEndpoint(path=BYTEPLUS_TASK_ENDPOINT, method="POST"),
|
|
data=Seedance2TaskCreationRequest(
|
|
model=model_id,
|
|
content=content,
|
|
generate_audio=model["generate_audio"],
|
|
resolution=model["resolution"],
|
|
ratio=model["ratio"],
|
|
duration=model["duration"],
|
|
seed=seed,
|
|
watermark=watermark,
|
|
),
|
|
response_model=TaskCreationResponse,
|
|
)
|
|
response = await poll_op(
|
|
cls,
|
|
ApiEndpoint(path=f"{BYTEPLUS_SEEDANCE2_TASK_STATUS_ENDPOINT}/{initial_response.id}"),
|
|
response_model=TaskStatusResponse,
|
|
status_extractor=lambda r: r.status,
|
|
price_extractor=_seedance2_price_extractor(model_id, has_video_input=False),
|
|
poll_interval=9,
|
|
)
|
|
return IO.NodeOutput(await download_url_to_video_output(response.content.video_url))
|
|
|
|
|
|
def _seedance2_reference_inputs():
|
|
return [
|
|
*_seedance2_text_inputs(),
|
|
IO.Autogrow.Input(
|
|
"reference_images",
|
|
template=IO.Autogrow.TemplateNames(
|
|
IO.Image.Input("reference_image"),
|
|
names=[
|
|
"image_1",
|
|
"image_2",
|
|
"image_3",
|
|
"image_4",
|
|
"image_5",
|
|
"image_6",
|
|
"image_7",
|
|
"image_8",
|
|
"image_9",
|
|
],
|
|
min=0,
|
|
),
|
|
),
|
|
IO.Autogrow.Input(
|
|
"reference_videos",
|
|
template=IO.Autogrow.TemplateNames(
|
|
IO.Video.Input("reference_video"),
|
|
names=["video_1", "video_2", "video_3"],
|
|
min=0,
|
|
),
|
|
),
|
|
IO.Autogrow.Input(
|
|
"reference_audios",
|
|
template=IO.Autogrow.TemplateNames(
|
|
IO.Audio.Input("reference_audio"),
|
|
names=["audio_1", "audio_2", "audio_3"],
|
|
min=0,
|
|
),
|
|
),
|
|
]
|
|
|
|
|
|
class ByteDance2ReferenceNode(IO.ComfyNode):
|
|
|
|
@classmethod
|
|
def define_schema(cls):
|
|
return IO.Schema(
|
|
node_id="ByteDance2ReferenceNode",
|
|
display_name="ByteDance Seedance 2.0 Reference to Video",
|
|
category="api node/video/ByteDance",
|
|
description="Generate, edit, or extend video using Seedance 2.0 with reference images, "
|
|
"videos, and audio. Supports multimodal reference, video editing, and video extension.",
|
|
inputs=[
|
|
IO.DynamicCombo.Input(
|
|
"model",
|
|
options=[
|
|
IO.DynamicCombo.Option("Seedance 2.0", _seedance2_reference_inputs()),
|
|
IO.DynamicCombo.Option("Seedance 2.0 Fast", _seedance2_reference_inputs()),
|
|
],
|
|
tooltip="Seedance 2.0 for maximum quality; Seedance 2.0 Fast for speed optimization.",
|
|
),
|
|
IO.Int.Input(
|
|
"seed",
|
|
default=0,
|
|
min=0,
|
|
max=2147483647,
|
|
step=1,
|
|
display_mode=IO.NumberDisplay.number,
|
|
control_after_generate=True,
|
|
tooltip="Seed controls whether the node should re-run; "
|
|
"results are non-deterministic regardless of seed.",
|
|
),
|
|
IO.Boolean.Input(
|
|
"watermark",
|
|
default=False,
|
|
tooltip="Whether to add a watermark to the video.",
|
|
advanced=True,
|
|
),
|
|
],
|
|
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", "model.resolution", "model.duration"],
|
|
input_groups=["model.reference_videos"],
|
|
),
|
|
expr="""
|
|
(
|
|
$rate480 := 10044;
|
|
$rate720 := 21600;
|
|
$m := widgets.model;
|
|
$hasVideo := $lookup(inputGroups, "model.reference_videos") > 0;
|
|
$noVideoPricePer1K := $contains($m, "fast") ? 0.008008 : 0.01001;
|
|
$videoPricePer1K := $contains($m, "fast") ? 0.004719 : 0.006149;
|
|
$res := $lookup(widgets, "model.resolution");
|
|
$dur := $lookup(widgets, "model.duration");
|
|
$rate := $res = "720p" ? $rate720 : $rate480;
|
|
$noVideoCost := $dur * $rate * $noVideoPricePer1K / 1000;
|
|
$minVideoFactor := $ceil($dur * 5 / 3);
|
|
$minVideoCost := $minVideoFactor * $rate * $videoPricePer1K / 1000;
|
|
$maxVideoCost := (15 + $dur) * $rate * $videoPricePer1K / 1000;
|
|
$hasVideo
|
|
? {
|
|
"type": "range_usd",
|
|
"min_usd": $minVideoCost,
|
|
"max_usd": $maxVideoCost,
|
|
"format": {"approximate": true}
|
|
}
|
|
: {
|
|
"type": "usd",
|
|
"usd": $noVideoCost,
|
|
"format": {"approximate": true}
|
|
}
|
|
)
|
|
""",
|
|
),
|
|
)
|
|
|
|
@classmethod
|
|
async def execute(
|
|
cls,
|
|
model: dict,
|
|
seed: int,
|
|
watermark: bool,
|
|
) -> IO.NodeOutput:
|
|
validate_string(model["prompt"], strip_whitespace=True, min_length=1)
|
|
|
|
reference_images = model.get("reference_images", {})
|
|
reference_videos = model.get("reference_videos", {})
|
|
reference_audios = model.get("reference_audios", {})
|
|
|
|
if not reference_images and not reference_videos:
|
|
raise ValueError("At least one reference image or video is required.")
|
|
|
|
model_id = SEEDANCE_MODELS[model["model"]]
|
|
has_video_input = len(reference_videos) > 0
|
|
total_video_duration = 0.0
|
|
for i, key in enumerate(reference_videos, 1):
|
|
video = reference_videos[key]
|
|
_validate_ref_video_pixels(video, model_id, i)
|
|
try:
|
|
dur = video.get_duration()
|
|
if dur < 1.8:
|
|
raise ValueError(f"Reference video {i} is too short: {dur:.1f}s. Minimum duration is 1.8 seconds.")
|
|
total_video_duration += dur
|
|
except ValueError:
|
|
raise
|
|
except Exception:
|
|
pass
|
|
if total_video_duration > 15.1:
|
|
raise ValueError(f"Total reference video duration is {total_video_duration:.1f}s. Maximum is 15.1 seconds.")
|
|
|
|
total_audio_duration = 0.0
|
|
for i, key in enumerate(reference_audios, 1):
|
|
audio = reference_audios[key]
|
|
dur = int(audio["waveform"].shape[-1]) / int(audio["sample_rate"])
|
|
if dur < 1.8:
|
|
raise ValueError(f"Reference audio {i} is too short: {dur:.1f}s. Minimum duration is 1.8 seconds.")
|
|
total_audio_duration += dur
|
|
if total_audio_duration > 15.1:
|
|
raise ValueError(f"Total reference audio duration is {total_audio_duration:.1f}s. Maximum is 15.1 seconds.")
|
|
|
|
content: list[TaskTextContent | TaskImageContent | TaskVideoContent | TaskAudioContent] = [
|
|
TaskTextContent(text=model["prompt"]),
|
|
]
|
|
for i, key in enumerate(reference_images, 1):
|
|
content.append(
|
|
TaskImageContent(
|
|
image_url=TaskImageContentUrl(
|
|
url=await upload_image_to_comfyapi(
|
|
cls,
|
|
image=reference_images[key],
|
|
wait_label=f"Uploading image {i}",
|
|
),
|
|
),
|
|
role="reference_image",
|
|
),
|
|
)
|
|
for i, key in enumerate(reference_videos, 1):
|
|
content.append(
|
|
TaskVideoContent(
|
|
video_url=TaskVideoContentUrl(
|
|
url=await upload_video_to_comfyapi(
|
|
cls,
|
|
reference_videos[key],
|
|
wait_label=f"Uploading video {i}",
|
|
),
|
|
),
|
|
),
|
|
)
|
|
for key in reference_audios:
|
|
content.append(
|
|
TaskAudioContent(
|
|
audio_url=TaskAudioContentUrl(
|
|
url=await upload_audio_to_comfyapi(
|
|
cls,
|
|
reference_audios[key],
|
|
container_format="mp3",
|
|
codec_name="libmp3lame",
|
|
mime_type="audio/mpeg",
|
|
),
|
|
),
|
|
),
|
|
)
|
|
initial_response = await sync_op(
|
|
cls,
|
|
ApiEndpoint(path=BYTEPLUS_TASK_ENDPOINT, method="POST"),
|
|
data=Seedance2TaskCreationRequest(
|
|
model=model_id,
|
|
content=content,
|
|
generate_audio=model["generate_audio"],
|
|
resolution=model["resolution"],
|
|
ratio=model["ratio"],
|
|
duration=model["duration"],
|
|
seed=seed,
|
|
watermark=watermark,
|
|
),
|
|
response_model=TaskCreationResponse,
|
|
)
|
|
response = await poll_op(
|
|
cls,
|
|
ApiEndpoint(path=f"{BYTEPLUS_SEEDANCE2_TASK_STATUS_ENDPOINT}/{initial_response.id}"),
|
|
response_model=TaskStatusResponse,
|
|
status_extractor=lambda r: r.status,
|
|
price_extractor=_seedance2_price_extractor(model_id, has_video_input=has_video_input),
|
|
poll_interval=9,
|
|
)
|
|
return IO.NodeOutput(await download_url_to_video_output(response.content.video_url))
|
|
|
|
|
|
async def process_video_task(
|
|
cls: type[IO.ComfyNode],
|
|
payload: Text2VideoTaskCreationRequest | Image2VideoTaskCreationRequest,
|
|
estimated_duration: int | None,
|
|
) -> IO.NodeOutput:
|
|
if payload.model in DEPRECATED_MODELS:
|
|
logger.warning(
|
|
"Model '%s' is deprecated and will be deactivated on May 13, 2026. "
|
|
"Please switch to a newer model. Recommended: seedance-1-0-pro-fast-251015.",
|
|
payload.model,
|
|
)
|
|
initial_response = await sync_op(
|
|
cls,
|
|
ApiEndpoint(path=BYTEPLUS_TASK_ENDPOINT, method="POST"),
|
|
data=payload,
|
|
response_model=TaskCreationResponse,
|
|
)
|
|
response = await poll_op(
|
|
cls,
|
|
ApiEndpoint(path=f"{BYTEPLUS_TASK_STATUS_ENDPOINT}/{initial_response.id}"),
|
|
status_extractor=lambda r: r.status,
|
|
estimated_duration=estimated_duration,
|
|
response_model=TaskStatusResponse,
|
|
)
|
|
return IO.NodeOutput(await download_url_to_video_output(response.content.video_url))
|
|
|
|
|
|
class ByteDanceExtension(ComfyExtension):
|
|
@override
|
|
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
|
|
return [
|
|
ByteDanceImageNode,
|
|
ByteDanceSeedreamNode,
|
|
ByteDanceTextToVideoNode,
|
|
ByteDanceImageToVideoNode,
|
|
ByteDanceFirstLastFrameNode,
|
|
ByteDanceImageReferenceNode,
|
|
ByteDance2TextToVideoNode,
|
|
ByteDance2FirstLastFrameNode,
|
|
ByteDance2ReferenceNode,
|
|
]
|
|
|
|
|
|
async def comfy_entrypoint() -> ByteDanceExtension:
|
|
return ByteDanceExtension()
|