use new API client in Pixverse and Ideogram nodes (#10543)
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@@ -1,15 +1,12 @@
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from __future__ import annotations
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import aiohttp
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import mimetypes
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from typing import Optional, Union
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from comfy.utils import common_upscale
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from typing import Union
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from server import PromptServer
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from comfy.cli_args import args
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import numpy as np
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from PIL import Image
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import torch
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import math
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import base64
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from io import BytesIO
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@@ -60,85 +57,6 @@ async def validate_and_cast_response(
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return torch.stack(image_tensors, dim=0)
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def validate_aspect_ratio(
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aspect_ratio: str,
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minimum_ratio: float,
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maximum_ratio: float,
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minimum_ratio_str: str,
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maximum_ratio_str: str,
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) -> float:
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"""Validates and casts an aspect ratio string to a float.
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Args:
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aspect_ratio: The aspect ratio string to validate.
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minimum_ratio: The minimum aspect ratio.
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maximum_ratio: The maximum aspect ratio.
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minimum_ratio_str: The minimum aspect ratio string.
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maximum_ratio_str: The maximum aspect ratio string.
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Returns:
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The validated and cast aspect ratio.
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Raises:
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Exception: If the aspect ratio is not valid.
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"""
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# get ratio values
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numbers = aspect_ratio.split(":")
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if len(numbers) != 2:
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raise TypeError(
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f"Aspect ratio must be in the format X:Y, such as 16:9, but was {aspect_ratio}."
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)
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try:
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numerator = int(numbers[0])
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denominator = int(numbers[1])
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except ValueError as exc:
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raise TypeError(
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f"Aspect ratio must contain numbers separated by ':', such as 16:9, but was {aspect_ratio}."
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) from exc
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calculated_ratio = numerator / denominator
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# if not close to minimum and maximum, check bounds
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if not math.isclose(calculated_ratio, minimum_ratio) or not math.isclose(
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calculated_ratio, maximum_ratio
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):
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if calculated_ratio < minimum_ratio:
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raise TypeError(
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f"Aspect ratio cannot reduce to any less than {minimum_ratio_str} ({minimum_ratio}), but was {aspect_ratio} ({calculated_ratio})."
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)
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if calculated_ratio > maximum_ratio:
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raise TypeError(
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f"Aspect ratio cannot reduce to any greater than {maximum_ratio_str} ({maximum_ratio}), but was {aspect_ratio} ({calculated_ratio})."
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)
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return aspect_ratio
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async def download_url_to_bytesio(
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url: str, timeout: int = None, auth_kwargs: Optional[dict[str, str]] = None
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) -> BytesIO:
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"""Downloads content from a URL using requests and returns it as BytesIO.
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Args:
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url: The URL to download.
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timeout: Request timeout in seconds. Defaults to None (no timeout).
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Returns:
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BytesIO object containing the downloaded content.
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"""
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headers = {}
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if url.startswith("/proxy/"):
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url = str(args.comfy_api_base).rstrip("/") + url
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auth_token = auth_kwargs.get("auth_token")
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comfy_api_key = auth_kwargs.get("comfy_api_key")
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if auth_token:
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headers["Authorization"] = f"Bearer {auth_token}"
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elif comfy_api_key:
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headers["X-API-KEY"] = comfy_api_key
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timeout_cfg = aiohttp.ClientTimeout(total=timeout) if timeout else None
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async with aiohttp.ClientSession(timeout=timeout_cfg) as session:
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async with session.get(url, headers=headers) as resp:
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resp.raise_for_status() # Raises HTTPError for bad responses (4XX or 5XX)
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return BytesIO(await resp.read())
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def text_filepath_to_base64_string(filepath: str) -> str:
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"""Converts a text file to a base64 string."""
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with open(filepath, "rb") as f:
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@@ -153,28 +71,3 @@ def text_filepath_to_data_uri(filepath: str) -> str:
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if mime_type is None:
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mime_type = "application/octet-stream"
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return f"data:{mime_type};base64,{base64_string}"
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def resize_mask_to_image(
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mask: torch.Tensor,
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image: torch.Tensor,
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upscale_method="nearest-exact",
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crop="disabled",
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allow_gradient=True,
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add_channel_dim=False,
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):
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"""
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Resize mask to be the same dimensions as an image, while maintaining proper format for API calls.
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"""
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_, H, W, _ = image.shape
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mask = mask.unsqueeze(-1)
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mask = mask.movedim(-1, 1)
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mask = common_upscale(
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mask, width=W, height=H, upscale_method=upscale_method, crop=crop
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)
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mask = mask.movedim(1, -1)
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if not add_channel_dim:
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mask = mask.squeeze(-1)
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if not allow_gradient:
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mask = (mask > 0.5).float()
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return mask
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