style: ruff autofix (auto)

Author: autofix-ci[bot]

src/api/v1/chat.py

@@ -4,6 +4,7 @@
 Provides chat functionality with streaming support and conversation history.
 Uses API key authentication. Routes through Langflow (chat_service.langflow_chat).
 """
+
 import json
 from typing import Any
 
@@ -38,13 +39,15 @@ def _extract_sources(item: dict) -> list[dict]:
     sources = []
     for result in item.get("results", []):
         if isinstance(result, dict) and "text" in result:
-            sources.append({
-                "filename": result.get("filename", ""),
-                "text": result.get("text", ""),
-                "score": result.get("score", 0),
-                "page": result.get("page"),
-                "mimetype": result.get("mimetype"),
-            })
+            sources.append(
+                {
+                    "filename": result.get("filename", ""),
+                    "text": result.get("text", ""),
+                    "score": result.get("score", 0),
+                    "page": result.get("page"),
+                    "mimetype": result.get("mimetype"),
+                }
+            )
     return sources
 
 
@@ -121,6 +124,7 @@ async def chat_create_endpoint(
     jwt_token = user.jwt_token
     if body.chat_id:
         from api.chat import _assert_owns
+
         await _assert_owns(body.chat_id, storage_user_id)
 
     if body.filters:
@@ -146,7 +150,11 @@ async def chat_create_endpoint(
         return StreamingResponse(
             _transform_stream_to_sse(raw_stream, chat_id_container),
             media_type="text/event-stream",
-            headers={"Cache-Control": "no-cache", "Connection": "keep-alive", "X-Accel-Buffering": "no"},
+            headers={
+                "Cache-Control": "no-cache",
+                "Connection": "keep-alive",
+                "X-Accel-Buffering": "no",
+            },
         )
     else:
         result = await chat_service.langflow_chat(
@@ -161,11 +169,13 @@ async def chat_create_endpoint(
             owner_email=user.email,
             storage_user_id=storage_user_id,
         )
-        return JSONResponse({
-            "response": result.get("response", ""),
-            "chat_id": result.get("response_id"),
-            "sources": result.get("sources", []),
-        })
+        return JSONResponse(
+            {
+                "response": result.get("response", ""),
+                "chat_id": result.get("response_id"),
+                "sources": result.get("sources", []),
+            }
+        )
 
 
 async def chat_list_endpoint(
@@ -218,20 +228,28 @@ async def chat_get_endpoint(
                 "timestamp": msg.get("timestamp"),
             }
             # Include token usage if available (from Responses API)
-            usage = msg.get("response_data", {}).get("usage") if isinstance(msg.get("response_data"), dict) else None
+            usage = (
+                msg.get("response_data", {}).get("usage")
+                if isinstance(msg.get("response_data"), dict)
+                else None
+            )
             if usage:
                 message_data["usage"] = usage
             messages.append(message_data)
 
-        return JSONResponse({
-            "chat_id": conversation.get("response_id"),
-            "title": conversation.get("title", ""),
-            "created_at": conversation.get("created_at"),
-            "last_activity": conversation.get("last_activity"),
-            "messages": messages,
-        })
+        return JSONResponse(
+            {
+                "chat_id": conversation.get("response_id"),
+                "title": conversation.get("title", ""),
+                "created_at": conversation.get("created_at"),
+                "last_activity": conversation.get("last_activity"),
+                "messages": messages,
+            }
+        )
     except Exception as e:
-        logger.error("Failed to get conversation", error=str(e), user_id=user.user_id, chat_id=chat_id)
+        logger.error(
+            "Failed to get conversation", error=str(e), user_id=user.user_id, chat_id=chat_id
+        )
         return JSONResponse({"error": f"Failed to get conversation: {str(e)}"}, status_code=500)
 
 
@@ -243,6 +261,7 @@ async def chat_delete_endpoint(
     """Delete a conversation. DELETE /v1/chat/{chat_id}"""
     try:
         from api.chat import _assert_owns
+
         storage_user_id = _openrag_user_id(user)
         await _assert_owns(chat_id, storage_user_id)
         result = await chat_service.delete_session(storage_user_id, chat_id)
@@ -258,5 +277,7 @@ async def chat_delete_endpoint(
     except HTTPException:
         raise
     except Exception as e:
-        logger.error("Failed to delete conversation", error=str(e), user_id=user.user_id, chat_id=chat_id)
+        logger.error(
+            "Failed to delete conversation", error=str(e), user_id=user.user_id, chat_id=chat_id
+        )
         return JSONResponse({"error": f"Failed to delete conversation: {str(e)}"}, status_code=500)

src/api/v1/knowledge_filters.py

@@ -5,6 +5,7 @@
 Uses API key authentication — delegates to the main api/knowledge_filter.py handlers
 but overrides the user dependency to use API keys.
 """
+
 from fastapi import Depends
 
 from api import knowledge_filter

src/api/v1/models.py

@@ -4,6 +4,7 @@
 Lists available LLM and embedding models per provider.
 Uses API key authentication. Uses stored credentials from config.
 """
+
 from fastapi import Depends
 from fastapi.responses import JSONResponse
 
@@ -22,21 +23,27 @@ async def _fetch_models(provider, config, models_service):
     if provider == "openai":
         api_key = config.providers.openai.api_key
         if not api_key:
-            return None, JSONResponse({"error": "OpenAI API key not configured. Set it in Settings."}, status_code=400)
+            return None, JSONResponse(
+                {"error": "OpenAI API key not configured. Set it in Settings."}, status_code=400
+            )
         models = await models_service.get_openai_models(api_key=api_key)
         return models, None
 
     if provider == "anthropic":
         api_key = config.providers.anthropic.api_key
         if not api_key:
-            return None, JSONResponse({"error": "Anthropic API key not configured. Set it in Settings."}, status_code=400)
+            return None, JSONResponse(
+                {"error": "Anthropic API key not configured. Set it in Settings."}, status_code=400
+            )
         models = await models_service.get_anthropic_models(api_key=api_key)
         return models, None
 
     if provider == "ollama":
         endpoint = config.providers.ollama.endpoint
         if not endpoint:
-            return None, JSONResponse({"error": "Ollama endpoint not configured. Set it in Settings."}, status_code=400)
+            return None, JSONResponse(
+                {"error": "Ollama endpoint not configured. Set it in Settings."}, status_code=400
+            )
         models = await models_service.get_ollama_models(endpoint=endpoint)
         return models, None
 
@@ -45,12 +52,20 @@ async def _fetch_models(provider, config, models_service):
     endpoint = config.providers.watsonx.endpoint
     project_id = config.providers.watsonx.project_id
     if not api_key:
-        return None, JSONResponse({"error": "WatsonX API key not configured. Set it in Settings."}, status_code=400)
+        return None, JSONResponse(
+            {"error": "WatsonX API key not configured. Set it in Settings."}, status_code=400
+        )
     if not endpoint:
-        return None, JSONResponse({"error": "WatsonX endpoint not configured. Set it in Settings."}, status_code=400)
+        return None, JSONResponse(
+            {"error": "WatsonX endpoint not configured. Set it in Settings."}, status_code=400
+        )
     if not project_id:
-        return None, JSONResponse({"error": "WatsonX project ID not configured. Set it in Settings."}, status_code=400)
-    models = await models_service.get_ibm_models(endpoint=endpoint, api_key=api_key, project_id=project_id)
+        return None, JSONResponse(
+            {"error": "WatsonX project ID not configured. Set it in Settings."}, status_code=400
+        )
+    models = await models_service.get_ibm_models(
+        endpoint=endpoint, api_key=api_key, project_id=project_id
+    )
     return models, None
 
 

src/api/v1/search.py

@@ -4,6 +4,7 @@
 Provides semantic search functionality.
 Uses API key authentication.
 """
+
 from typing import Any
 
 from fastapi import Depends

src/api/v1/settings.py

@@ -22,11 +22,13 @@
 
 logger = get_logger(__name__)
 
+
 class AgentSettings(BaseModel):
     llm_provider: str | None = None
     llm_model: str | None = None
     system_prompt: str | None = None
 
+
 class KnowledgeSettings(BaseModel):
     embedding_provider: str | None = None
     embedding_model: str | None = None
@@ -36,10 +38,12 @@ class KnowledgeSettings(BaseModel):
     ocr: bool | None = None
     picture_descriptions: bool | None = None
 
+
 class SettingsResponse(BaseModel):
     agent: AgentSettings
     knowledge: KnowledgeSettings
 
+
 async def get_settings_endpoint(
     user: User = Depends(get_api_key_user_async),
 ) -> SettingsResponse:
@@ -76,4 +80,6 @@ async def update_settings_endpoint(
     """Update OpenRAG configuration settings. POST /v1/settings"""
     from api.settings import update_settings
 
-    return await update_settings(body=body, session_manager=session_manager, user=user, models_service=models_service)
+    return await update_settings(
+        body=body, session_manager=session_manager, user=user, models_service=models_service
+    )