Merge 40c61a257d into b633244635

* feat(api-nodes-bytedance): use the virtual portrait library for regular images

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* fix: include shape in image dedup hash

Signed-off-by: bigcat88 <bigcat88@icloud.com>

---------

Signed-off-by: bigcat88 <bigcat88@icloud.com>

comfy_api_nodes/apis/bytedance.py

@@ -157,6 +157,11 @@ class SeedanceCreateAssetResponse(BaseModel):
     asset_id: str = Field(...)
 
 
+class SeedanceVirtualLibraryCreateAssetRequest(BaseModel):
+    url: str = Field(..., description="Publicly accessible URL of the image asset to upload.")
+    hash: str = Field(..., description="Dedup key. Re-submitting the same hash returns the existing asset id.")
+
+
 # Dollars per 1K tokens, keyed by (model_id, has_video_input).
 SEEDANCE2_PRICE_PER_1K_TOKENS = {
     ("dreamina-seedance-2-0-260128", False): 0.007,

comfy_api_nodes/nodes_bytedance.py

@@ -1,3 +1,4 @@
+import hashlib
 import logging
 import math
 import re
@@ -20,6 +21,7 @@ from comfy_api_nodes.apis.bytedance import (
     SeedanceCreateAssetResponse,
     SeedanceCreateVisualValidateSessionResponse,
     SeedanceGetVisualValidateSessionResponse,
+    SeedanceVirtualLibraryCreateAssetRequest,
     Seedream4Options,
     Seedream4TaskCreationRequest,
     TaskAudioContent,
@@ -271,6 +273,30 @@ async def _wait_for_asset_active(cls: type[IO.ComfyNode], asset_id: str, group_i
     )
 
 
+async def _seedance_virtual_library_upload_image_asset(
+    cls: type[IO.ComfyNode],
+    image: torch.Tensor,
+    *,
+    wait_label: str = "Uploading image",
+) -> str:
+    """Upload an image into the caller's per-customer Seedance virtual library."""
+    public_url = await upload_image_to_comfyapi(cls, image, wait_label=wait_label)
+    normalized = image.detach().cpu().contiguous().to(torch.float32)
+    digest = hashlib.sha256()
+    digest.update(str(tuple(normalized.shape)).encode("utf-8"))
+    digest.update(b"\0")
+    digest.update(normalized.numpy().tobytes())
+    image_hash = digest.hexdigest()
+    create_resp = await sync_op(
+        cls,
+        ApiEndpoint(path="/proxy/seedance/virtual-library/assets", method="POST"),
+        response_model=SeedanceCreateAssetResponse,
+        data=SeedanceVirtualLibraryCreateAssetRequest(url=public_url, hash=image_hash),
+    )
+    await _wait_for_asset_active(cls, create_resp.asset_id, group_id="virtual-library")
+    return f"asset://{create_resp.asset_id}"
+
+
 def _seedance2_price_extractor(model_id: str, has_video_input: bool):
     """Returns a price_extractor closure for Seedance 2.0 poll_op."""
     rate = SEEDANCE2_PRICE_PER_1K_TOKENS.get((model_id, has_video_input))
@@ -1507,7 +1533,9 @@ class ByteDance2FirstLastFrameNode(IO.ComfyNode):
         if first_frame_asset_id:
             first_frame_url = image_assets[first_frame_asset_id]
         else:
-            first_frame_url = await upload_image_to_comfyapi(cls, first_frame, wait_label="Uploading first frame.")
+            first_frame_url = await _seedance_virtual_library_upload_image_asset(
+                cls, first_frame, wait_label="Uploading first frame."
+            )
 
         content: list[TaskTextContent | TaskImageContent] = [
             TaskTextContent(text=model["prompt"]),
@@ -1527,7 +1555,9 @@ class ByteDance2FirstLastFrameNode(IO.ComfyNode):
             content.append(
                 TaskImageContent(
                     image_url=TaskImageContentUrl(
-                        url=await upload_image_to_comfyapi(cls, last_frame, wait_label="Uploading last frame.")
+                        url=await _seedance_virtual_library_upload_image_asset(
+                            cls, last_frame, wait_label="Uploading last frame."
+                        )
                     ),
                     role="last_frame",
                 ),
@@ -1805,9 +1835,9 @@ class ByteDance2ReferenceNode(IO.ComfyNode):
             content.append(
                 TaskImageContent(
                     image_url=TaskImageContentUrl(
-                        url=await upload_image_to_comfyapi(
+                        url=await _seedance_virtual_library_upload_image_asset(
                             cls,
-                            image=reference_images[key],
+                            reference_images[key],
                             wait_label=f"Uploading image {i}",
                         ),
                     ),

comfy_api_nodes/nodes_openai.py

@@ -415,8 +415,9 @@ class OpenAIGPTImage1(IO.ComfyNode):
                         "1152x2048",
                         "3840x2160",
                         "2160x3840",
+                        "Custom",
                     ],
-                    tooltip="Image size",
+                    tooltip="Image size. Select 'Custom' to use the custom width and height (GPT Image 2 only).",
                     optional=True,
                 ),
                 IO.Int.Input(
@@ -445,6 +446,26 @@ class OpenAIGPTImage1(IO.ComfyNode):
                     default="gpt-image-2",
                     optional=True,
                 ),
+                IO.Int.Input(
+                    "custom_width",
+                    default=1024,
+                    min=1024,
+                    max=3840,
+                    step=16,
+                    tooltip="Used only when `size` is 'Custom'. Must be a multiple of 16 (GPT Image 2 only).",
+                    optional=True,
+                    advanced=True,
+                ),
+                IO.Int.Input(
+                    "custom_height",
+                    default=1024,
+                    min=1024,
+                    max=3840,
+                    step=16,
+                    tooltip="Used only when `size` is 'Custom'. Must be a multiple of 16 (GPT Image 2 only).",
+                    optional=True,
+                    advanced=True,
+                ),
             ],
             outputs=[
                 IO.Image.Output(),
@@ -471,9 +492,9 @@ class OpenAIGPTImage1(IO.ComfyNode):
                       "high":   [0.133, 0.22]
                     },
                     "gpt-image-2": {
-                      "low":    [0.0048, 0.012],
-                      "medium": [0.041, 0.112],
-                      "high":   [0.165, 0.43]
+                      "low":    [0.0048, 0.019],
+                      "medium": [0.041, 0.168],
+                      "high":   [0.165, 0.67]
                     }
                   };
                   $range := $lookup($lookup($ranges, widgets.model), widgets.quality);
@@ -503,6 +524,8 @@ class OpenAIGPTImage1(IO.ComfyNode):
         mask: Input.Image | None = None,
         n: int = 1,
         size: str = "1024x1024",
+        custom_width: int = 1024,
+        custom_height: int = 1024,
         model: str = "gpt-image-1",
     ) -> IO.NodeOutput:
         validate_string(prompt, strip_whitespace=False)
@@ -510,7 +533,25 @@ class OpenAIGPTImage1(IO.ComfyNode):
         if mask is not None and image is None:
             raise ValueError("Cannot use a mask without an input image")
 
-        if model in ("gpt-image-1", "gpt-image-1.5"):
+        if size == "Custom":
+            if model != "gpt-image-2":
+                raise ValueError("Custom resolution is only supported by GPT Image 2 model")
+            if custom_width % 16 != 0 or custom_height % 16 != 0:
+                raise ValueError(f"Custom width and height must be multiples of 16, got {custom_width}x{custom_height}")
+            if max(custom_width, custom_height) > 3840:
+                raise ValueError(f"Custom resolution max edge must be <= 3840, got {custom_width}x{custom_height}")
+            ratio = max(custom_width, custom_height) / min(custom_width, custom_height)
+            if ratio > 3:
+                raise ValueError(
+                    f"Custom resolution aspect ratio must not exceed 3:1, got {custom_width}x{custom_height}"
+                )
+            total_pixels = custom_width * custom_height
+            if not 655_360 <= total_pixels <= 8_294_400:
+                raise ValueError(
+                    f"Custom resolution total pixels must be between 655,360 and 8,294,400, got {total_pixels}"
+                )
+            size = f"{custom_width}x{custom_height}"
+        elif model in ("gpt-image-1", "gpt-image-1.5"):
             if size not in ("auto", "1024x1024", "1024x1536", "1536x1024"):
                 raise ValueError(f"Resolution {size} is only supported by GPT Image 2 model")
 

server.py

@@ -54,6 +54,31 @@ if args.enable_manager:
     import comfyui_manager
 
 
+def _make_content_disposition(filename: str, disposition: str = "inline") -> str:
+    """
+    Generate RFC 8187 compliant Content-Disposition header.
+    
+    According to RFC 8187, the filename parameter should use the extended notation
+    with 'filename*=' and 'utf-8'' language tag when the filename contains non-ASCII
+    characters or needs special encoding.
+    
+    Examples:
+        ASCII: inline; filename="test.png"; filename*=UTF-8''test.png
+        Unicode: inline; filename="__.png"; filename*=UTF-8''%E6%B5%8B%E8%AF%95.png
+    """
+    import urllib.parse
+    
+    # Create ASCII-safe fallback filename
+    fallback = "".join(
+        ch if 0x20 <= ord(ch) < 0x7F and ch not in {'"', '\\'} else "_"
+        for ch in filename
+    ) or "download"
+    
+    # Percent-encode the UTF-8 filename
+    encoded_filename = urllib.parse.quote(filename, safe='')
+    return f"{disposition}; filename=\"{fallback}\"; filename*=UTF-8''{encoded_filename}"
+
+
 def _remove_sensitive_from_queue(queue: list) -> list:
     """Remove sensitive data (index 5) from queue item tuples."""
     return [item[:5] for item in queue]
@@ -559,7 +584,7 @@ class PromptServer():
                             buffer.seek(0)
 
                             return web.Response(body=buffer.read(), content_type=f'image/{image_format}',
-                                                headers={"Content-Disposition": f"filename=\"{filename}\""})
+                                                headers={"Content-Disposition": _make_content_disposition(filename)})
 
                     if 'channel' not in request.rel_url.query:
                         channel = 'rgba'
@@ -579,7 +604,7 @@ class PromptServer():
                             buffer.seek(0)
 
                             return web.Response(body=buffer.read(), content_type='image/png',
-                                                headers={"Content-Disposition": f"filename=\"{filename}\""})
+                                                headers={"Content-Disposition": _make_content_disposition(filename)})
 
                     elif channel == 'a':
                         with Image.open(file) as img:
@@ -596,7 +621,7 @@ class PromptServer():
                             alpha_buffer.seek(0)
 
                             return web.Response(body=alpha_buffer.read(), content_type='image/png',
-                                                headers={"Content-Disposition": f"filename=\"{filename}\""})
+                                                headers={"Content-Disposition": _make_content_disposition(filename)})
                     else:
                         # Use the content type from asset resolution if available,
                         # otherwise guess from the filename.
@@ -613,7 +638,7 @@ class PromptServer():
                         return web.FileResponse(
                             file,
                             headers={
-                                "Content-Disposition": f"filename=\"{filename}\"",
+                                "Content-Disposition": _make_content_disposition(filename),
                                 "Content-Type": content_type
                             }
                         )