convert nodes_openai.py to V3 schema (#10604)

comfy_api_nodes/apinode_utils.py

@@ -1,73 +0,0 @@
-from __future__ import annotations
-import aiohttp
-import mimetypes
-from typing import Union
-from server import PromptServer
-
-import numpy as np
-from PIL import Image
-import torch
-import base64
-from io import BytesIO
-
-
-async def validate_and_cast_response(
-    response, timeout: int = None, node_id: Union[str, None] = None
-) -> torch.Tensor:
-    """Validates and casts a response to a torch.Tensor.
-
-    Args:
-        response: The response to validate and cast.
-        timeout: Request timeout in seconds. Defaults to None (no timeout).
-
-    Returns:
-        A torch.Tensor representing the image (1, H, W, C).
-
-    Raises:
-        ValueError: If the response is not valid.
-    """
-    # validate raw JSON response
-    data = response.data
-    if not data or len(data) == 0:
-        raise ValueError("No images returned from API endpoint")
-
-    # Initialize list to store image tensors
-    image_tensors: list[torch.Tensor] = []
-
-    # Process each image in the data array
-    async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=timeout)) as session:
-        for img_data in data:
-            img_bytes: bytes
-            if img_data.b64_json:
-                img_bytes = base64.b64decode(img_data.b64_json)
-            elif img_data.url:
-                if node_id:
-                    PromptServer.instance.send_progress_text(f"Result URL: {img_data.url}", node_id)
-                async with session.get(img_data.url) as resp:
-                    if resp.status != 200:
-                        raise ValueError("Failed to download generated image")
-                    img_bytes = await resp.read()
-            else:
-                raise ValueError("Invalid image payload – neither URL nor base64 data present.")
-
-            pil_img = Image.open(BytesIO(img_bytes)).convert("RGBA")
-            arr = np.asarray(pil_img).astype(np.float32) / 255.0
-            image_tensors.append(torch.from_numpy(arr))
-
-    return torch.stack(image_tensors, dim=0)
-
-
-def text_filepath_to_base64_string(filepath: str) -> str:
-    """Converts a text file to a base64 string."""
-    with open(filepath, "rb") as f:
-        file_content = f.read()
-    return base64.b64encode(file_content).decode("utf-8")
-
-
-def text_filepath_to_data_uri(filepath: str) -> str:
-    """Converts a text file to a data URI."""
-    base64_string = text_filepath_to_base64_string(filepath)
-    mime_type, _ = mimetypes.guess_type(filepath)
-    if mime_type is None:
-        mime_type = "application/octet-stream"
-    return f"data:{mime_type};base64,{base64_string}"

comfy_api_nodes/util/__init__.py

@@ -18,6 +18,8 @@ from .conversions import (
     tensor_to_base64_string,
     tensor_to_bytesio,
     tensor_to_pil,
+    text_filepath_to_base64_string,
+    text_filepath_to_data_uri,
     trim_video,
     video_to_base64_string,
 )
@@ -75,6 +77,8 @@ __all__ = [
     "tensor_to_base64_string",
     "tensor_to_bytesio",
     "tensor_to_pil",
+    "text_filepath_to_base64_string",
+    "text_filepath_to_data_uri",
     "trim_video",
     "video_to_base64_string",
     # Validation utilities

comfy_api_nodes/util/conversions.py

@@ -1,6 +1,7 @@
 import base64
 import logging
 import math
+import mimetypes
 import uuid
 from io import BytesIO
 from typing import Optional
@@ -12,7 +13,7 @@ from PIL import Image
 
 from comfy.utils import common_upscale
 from comfy_api.latest import Input, InputImpl
-from comfy_api.util import VideoContainer, VideoCodec
+from comfy_api.util import VideoCodec, VideoContainer
 
 from ._helpers import mimetype_to_extension
 
@@ -451,3 +452,19 @@ def resize_mask_to_image(
     if not allow_gradient:
         mask = (mask > 0.5).float()
     return mask
+
+
+def text_filepath_to_base64_string(filepath: str) -> str:
+    """Converts a text file to a base64 string."""
+    with open(filepath, "rb") as f:
+        file_content = f.read()
+    return base64.b64encode(file_content).decode("utf-8")
+
+
+def text_filepath_to_data_uri(filepath: str) -> str:
+    """Converts a text file to a data URI."""
+    base64_string = text_filepath_to_base64_string(filepath)
+    mime_type, _ = mimetypes.guess_type(filepath)
+    if mime_type is None:
+        mime_type = "application/octet-stream"
+    return f"data:{mime_type};base64,{base64_string}"