Upload src\api\chat_router.py with huggingface_hub

src//api//chat_router.py

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+from fastapi import APIRouter, HTTPException, Depends, BackgroundTasks, File, UploadFile
+from typing import Optional, Dict, Any
+import uuid
+from datetime import datetime
+import os
+from pathlib import Path
+
+from models.message import Message, MessageCreate, MessageRead
+from models.conversation import Conversation
+from services.translation_service import translation_service, Language
+from services.voice_processing_service import voice_processing_service
+from services.chat_service import chat_service
+from tools.mcp_server import execute_mcp_tool
+from middleware.auth import get_optional_user, get_current_user
+from models.user import User
+
+router = APIRouter(prefix="/api", tags=["chat"])
+
+# Audio endpoint for serving synthesized voice files
+@router.get("/audio/{filename}")
+async def get_audio_file(filename: str):
+    """Serve audio files generated by voice synthesis"""
+    import tempfile
+    temp_dir = Path(tempfile.gettempdir())
+    file_path = temp_dir / filename
+
+    if not file_path.exists():
+        raise HTTPException(status_code=404, detail="Audio file not found")
+
+    from fastapi.responses import FileResponse
+    return FileResponse(
+        path=file_path,
+        media_type="audio/mpeg",
+        filename=filename
+    )
+
+
+@router.post("/chat", response_model=Dict[str, Any])
+async def process_chat_message(
+    message: str,
+    conversation_id: Optional[str] = None,
+    message_type: str = "text",
+    language: str = "en",
+    user_preferences: Optional[Dict[str, Any]] = None,
+    current_user: User = Depends(get_current_user)
+):
+    """
+    Process chat message and return AI response
+    Handles both text and voice input, processes through the AI system, and returns appropriate response
+    """
+    try:
+        # Validate inputs
+        if not message.strip():
+            raise HTTPException(status_code=400, detail="Message cannot be empty")
+
+        # Process the message using the chat service
+        response_obj = await chat_service.process_user_message(
+            message=message,
+            conversation_id=conversation_id,
+            message_type=message_type,
+            language=language,
+            user_preferences=user_preferences,
+            user_id=current_user.id if current_user else None
+        )
+
+        return response_obj
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Error processing chat message: {str(e)}")
+
+
+# Additional endpoints for conversation management
+@router.get("/conversations", response_model=Dict[str, Any])
+async def list_conversations():
+    """List user's conversations"""
+    # In a real implementation, this would fetch from database
+    return {"conversations": []}
+
+
+@router.get("/conversations/{conversation_id}", response_model=Dict[str, Any])
+async def get_conversation_history(conversation_id: str):
+    """Get conversation history"""
+    # In a real implementation, this would fetch from database
+    return {
+        "conversation": {"id": conversation_id, "title": "Sample Conversation"},
+        "messages": []
+    }