chore: format

backend/open_webui/retrieval/loaders/main.py

@@ -146,10 +146,7 @@ class DoclingLoader:
                 )
             }
 
-            params = {
-                "image_export_mode": "placeholder",
-                "table_mode": "accurate"
-            }
+            params = {"image_export_mode": "placeholder", "table_mode": "accurate"}
 
             if self.params:
                 if self.params.get("do_picture_description"):
@@ -293,8 +290,8 @@ class Loader:
                         "ocr_lang": self.kwargs.get("DOCLING_OCR_LANG"),
                         "do_picture_description": self.kwargs.get(
                             "DOCLING_DO_PICTURE_DESCRIPTION"
-                        )
-                    }
+                        ),
+                    },
                 )
         elif (
             self.engine == "document_intelligence"

backend/open_webui/routers/openai.py

@@ -886,15 +886,16 @@ async def generate_chat_completion(
                 r.close()
             await session.close()
 
+
 async def embeddings(request: Request, form_data: dict, user):
     """
     Calls the embeddings endpoint for OpenAI-compatible providers.
-    
+
     Args:
         request (Request): The FastAPI request context.
         form_data (dict): OpenAI-compatible embeddings payload.
         user (UserModel): The authenticated user.
-    
+
     Returns:
         dict: OpenAI-compatible embeddings response.
     """
@@ -928,7 +929,8 @@ async def embeddings(request: Request, form_data: dict, user):
                         "X-OpenWebUI-User-Email": user.email,
                         "X-OpenWebUI-User-Role": user.role,
                     }
-                    if ENABLE_FORWARD_USER_INFO_HEADERS and user else {}
+                    if ENABLE_FORWARD_USER_INFO_HEADERS and user
+                    else {}
                 ),
             },
         )
@@ -966,6 +968,7 @@ async def embeddings(request: Request, form_data: dict, user):
                 r.close()
             await session.close()
 
+
 @router.api_route("/{path:path}", methods=["GET", "POST", "PUT", "DELETE"])
 async def proxy(path: str, request: Request, user=Depends(get_verified_user)):
     """

backend/open_webui/utils/payload.py

@@ -341,9 +341,7 @@ def convert_embedding_payload_openai_to_ollama(openai_payload: dict) -> dict:
     Returns:
         dict: A payload compatible with the Ollama API embeddings endpoint.
     """
-    ollama_payload = {
-        "model": openai_payload.get("model")
-    }
+    ollama_payload = {"model": openai_payload.get("model")}
     input_value = openai_payload.get("input")
 
     # Ollama expects 'input' as a list, and 'prompt' as a single string.

backend/open_webui/utils/response.py

@@ -126,12 +126,13 @@ async def convert_streaming_response_ollama_to_openai(ollama_streaming_response)
 
     yield "data: [DONE]\n\n"
 
+
 def convert_embedding_response_ollama_to_openai(response) -> dict:
     """
     Convert the response from Ollama embeddings endpoint to the OpenAI-compatible format.
 
     Args:
-        response (dict): The response from the Ollama API, 
+        response (dict): The response from the Ollama API,
             e.g. {"embedding": [...], "model": "..."}
             or {"embeddings": [{"embedding": [...], "index": 0}, ...], "model": "..."}
 
@@ -150,11 +151,13 @@ def convert_embedding_response_ollama_to_openai(response) -> dict:
     if isinstance(response, dict) and "embeddings" in response:
         openai_data = []
         for i, emb in enumerate(response["embeddings"]):
-            openai_data.append({
-                "object": "embedding",
-                "embedding": emb.get("embedding"),
-                "index": emb.get("index", i),
-            })
+            openai_data.append(
+                {
+                    "object": "embedding",
+                    "embedding": emb.get("embedding"),
+                    "index": emb.get("index", i),
+                }
+            )
         return {
             "object": "list",
             "data": openai_data,
@@ -164,16 +167,22 @@ def convert_embedding_response_ollama_to_openai(response) -> dict:
     elif isinstance(response, dict) and "embedding" in response:
         return {
             "object": "list",
-            "data": [{
-                "object": "embedding",
-                "embedding": response["embedding"],
-                "index": 0,
-            }],
+            "data": [
+                {
+                    "object": "embedding",
+                    "embedding": response["embedding"],
+                    "index": 0,
+                }
+            ],
             "model": response.get("model"),
         }
     # Already OpenAI-compatible?
-    elif isinstance(response, dict) and "data" in response and isinstance(response["data"], list):
+    elif (
+        isinstance(response, dict)
+        and "data" in response
+        and isinstance(response["data"], list)
+    ):
         return response
 
     # Fallback: return as is if unrecognized
-    return response
+    return response