feat: voice mode

src/backend/base/langflow/api/v1/__init__.py

@@ -7,11 +7,11 @@
 from langflow.api.v1.login import router as login_router
 from langflow.api.v1.monitor import router as monitor_router
 from langflow.api.v1.starter_projects import router as starter_projects_router
-from langflow.api.v1.voice_mode import router as voice_mode_router
 from langflow.api.v1.store import router as store_router
 from langflow.api.v1.users import router as users_router
 from langflow.api.v1.validate import router as validate_router
 from langflow.api.v1.variable import router as variables_router
+from langflow.api.v1.voice_mode import router as voice_mode_router
 
 __all__ = [
     "api_key_router",

src/backend/base/langflow/api/v1/voice_mode.py

@@ -1,29 +1,27 @@
 import asyncio
-import os
 import json
-from typing import Annotated
+import os
 from uuid import UUID, uuid4
 
-from fastapi import APIRouter, BackgroundTasks, Depends
 import websockets
-from starlette.websockets import WebSocket, WebSocketDisconnect
+from fastapi import APIRouter, BackgroundTasks
 from loguru import logger
+from sqlalchemy import select
+from starlette.websockets import WebSocket, WebSocketDisconnect
 
 from langflow.api.utils import CurrentActiveUser, DbSession
 from langflow.api.v1.chat import build_flow
 from langflow.api.v1.schemas import InputValueRequest
-from langflow.services.auth.utils import get_current_user_for_websocket, get_current_user_by_jwt
-from langflow.services.database.models import User
+from langflow.services.auth.utils import get_current_user_by_jwt
 from langflow.services.database.models.flow.model import Flow
 from langflow.services.deps import async_session_scope
-from sqlalchemy import select
 
 router = APIRouter(prefix="/voice", tags=["Voice"])
 
 SILENCE_THRESHOLD = 0.5
 PREFIX_PADDING_MS = 300
 SILENCE_DURATION_MS = 500
 SESSION_INSTRUCTIONS = "Always call the execute_flow function with the user's question as the input parameter and use that to craft your responses."
 
 
 async def get_flow_desc_from_db(flow_id: str) -> Flow:
@@ -33,7 +31,7 @@
         result = await session.exec(stmt)
         flow = result.scalar_one_or_none()
         if not flow:
             raise ValueError(f"Flow {flow_id} not found")
         return flow.description
 
 
@@ -94,15 +92,15 @@
         await openai_ws.send(json.dumps(function_output))
         await openai_ws.send(json.dumps({"type": "response.create"}))
 
     except Exception as e:
-        logger.error(f"Error executing flow: {str(e)}")
+        logger.error(f"Error executing flow: {e!s}")
         # Send error back to OpenAI with correct format
         function_output = {
             "type": "conversation.item.create",
             "item": {
                 "type": "function_call_output",
                 "call_id": function_call.get("call_id"),
-                "output": f"Error executing flow: {str(e)}",
+                "output": f"Error executing flow: {e!s}",
             },
         }
         await openai_ws.send(json.dumps(function_output))
@@ -116,7 +114,7 @@
     session: DbSession,
 ):
     # Generate a unique session ID for this conversation
     conversation_id = str(uuid4())  # renamed to avoid confusion with session param
     current_user = await get_current_user_by_jwt(websocket.cookies.get("access_token_lf"), session)
     await websocket.accept()
 
@@ -136,8 +134,8 @@
             },
         }
         # }
     except Exception as e:
-        await websocket.send_json({"error": f"Failed to load flow: {str(e)}"})
+        await websocket.send_json({"error": f"Failed to load flow: {e!s}"})
         logger.error(e)
         return