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questrag-backend

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# """
# FastAPI Main Application Entry Point

# Banking RAG Chatbot API with JWT Authentication

# This file:
# 1. Creates the FastAPI app
# 2. Configures CORS middleware
# 3. Connects to MongoDB on startup/shutdown
# 4. Includes API routers (auth + chat)
# 5. Provides health check endpoints
# """

# from fastapi import FastAPI, Request
# from fastapi.middleware.cors import CORSMiddleware
# from fastapi.responses import JSONResponse
# from contextlib import asynccontextmanager

# from app.config import settings
# from app.db.mongodb import connect_to_mongo, close_mongo_connection

# # ============================================================================
# # LIFESPAN MANAGER (Startup & Shutdown)
# # ============================================================================

# @asynccontextmanager
# async def lifespan(app: FastAPI):
#     """
#     Manage application lifespan events.
    
#     Startup:
#     - Connect to MongoDB Atlas
#     - ML models load lazily on first use
    
#     Shutdown:
#     - Close MongoDB connection
#     - Cleanup resources
#     """
#     # ========================================================================
#     # STARTUP
#     # ========================================================================
#     print("\n" + "=" * 80)
#     print("🚀 STARTING BANKING RAG CHATBOT API")
#     print("=" * 80)
#     print(f"Environment: {settings.ENVIRONMENT}")
#     print(f"Debug Mode: {settings.DEBUG}")
#     print("=" * 80)
    
#     # Connect to MongoDB
#     await connect_to_mongo()
    
#     print("\n💡 ML Models Info:")
#     print("   Policy Network: Loads on first chat request (lazy loading)")
#     print("   Retriever Model: Loads on first retrieval (lazy loading)")
#     print("   LLM: Groq (ChatGroq) with HuggingFace fallback")
#     print("\n🤖 LLM Configuration:")
#     print(f"   Chat Model: {settings.GROQ_CHAT_MODEL} (Llama 3 8B)")
#     print(f"   Eval Model: {settings.GROQ_EVAL_MODEL} (Llama 3 70B)")
#     print(f"   Groq API Keys: {len(settings.get_groq_api_keys())} configured")
#     print(f"   HuggingFace Tokens: {len(settings.get_hf_tokens())} configured")
#     print(f"   Fallback: Groq → HuggingFace")
    
#     print("\n✅ Backend startup complete!")
#     print("=" * 80)
#     print(f"📖 API Docs: https://eeshanyaj-questrag-backend.hf.space/docs")
#     print(f"🏥 Health Check: https://eeshanyaj-questrag-backend.hf.space/health")
#     print(f"🧠 Backend Link: https://eeshanyaj-questrag-backend.hf.space/")
#     # print(f"🔑 Login: POST http://localhost:8000/api/v1/auth/login")
#     print("=" * 80 + "\n")
    
#     yield  # Application runs here
    
#     # ========================================================================
#     # SHUTDOWN
#     # ========================================================================
#     print("\n" + "=" * 80)
#     print("🛑 SHUTTING DOWN API")
#     print("=" * 80)
    
#     # Close MongoDB connection
#     await close_mongo_connection()
    
#     print("✅ Shutdown complete")
#     print("=" * 80 + "\n")

# # ============================================================================
# # CREATE FASTAPI APPLICATION
# # ============================================================================

# app = FastAPI(
#     title="Banking RAG Chatbot API",
#     description="""
# 🤖 AI-powered Banking Assistant with:

# **Features:**
# - 🔐 JWT Authentication (Sign up, Login, Protected routes)
# - 💬 RAG (Retrieval-Augmented Generation)
# - 🧠 RL-based Policy Network (BERT)
# - 🔍 Custom E5 Retriever
# - ⚡ Groq LLM with HuggingFace Fallback (Llama 3 models)

# **Capabilities:**
# - Intelligent document retrieval
# - Context-aware responses
# - Conversation history
# - Real-time chat
# - User authentication & authorization
# - Multi-provider LLM with automatic fallback
#     """,
#     version="1.0.0",
#     docs_url="/docs",
#     redoc_url="/redoc",
#     lifespan=lifespan
# )

# # ============================================================================
# # CORS MIDDLEWARE
# # ============================================================================

# allowed_origins = settings.get_allowed_origins()
# print("\n🌐 CORS Configuration:")
# print(f"   Allowed Origins: {allowed_origins}")

# app.add_middleware(
#     CORSMiddleware,
#     allow_origins=allowed_origins,
#     allow_credentials=True,
#     allow_methods=["*"],
#     allow_headers=["*"],
# )

# # ============================================================================
# # INCLUDE API ROUTERS
# # ============================================================================

# from app.api.v1 import chat, auth

# # Auth router (public endpoints - register, login)
# app.include_router(
#     auth.router,
#     prefix="/api/v1/auth",
#     tags=["🔐 Authentication"]
# )

# # Chat router (protected endpoints - requires JWT token)
# app.include_router(
#     chat.router,
#     prefix="/api/v1/chat",
#     tags=["💬 Chat"]
# )

# # ============================================================================
# # ROOT ENDPOINTS
# # ============================================================================

# @app.get("/", tags=["📍 Root"])
# async def root():
#     """
#     Root endpoint - API information and available endpoints
#     """
#     return {
#         "message": "Banking RAG Chatbot API with Authentication",
#         "version": "1.0.0",
#         "status": "online",
#         "authentication": "JWT Bearer Token Required for chat endpoints",
#         "llm_provider": "Groq (ChatGroq) with HuggingFace fallback",
#         "models": {
#             "chat": settings.GROQ_CHAT_MODEL,
#             "evaluation": settings.GROQ_EVAL_MODEL
#         },
#         "documentation": {
#             "swagger_ui": "/docs",
#             "redoc": "/redoc"
#         },
#         "endpoints": {
#             "auth": {
#                 "register": "POST /api/v1/auth/register",
#                 "login": "POST /api/v1/auth/login",
#                 "me": "GET /api/v1/auth/me (requires token)",
#                 "logout": "POST /api/v1/auth/logout (requires token)"
#             },
#             "chat": {
#                 "send_message": "POST /api/v1/chat/ (requires token)",
#                 "get_history": "GET /api/v1/chat/history/{conversation_id} (requires token)",
#                 "list_conversations": "GET /api/v1/chat/conversations (requires token)",
#                 "delete_conversation": "DELETE /api/v1/chat/conversation/{conversation_id} (requires token)"
#             },
#             "health": "GET /health"
#         }
#     }

# @app.get("/health", tags=["🏥 Health"])
# async def health_check():
#     """
#     Comprehensive health check endpoint
    
#     Checks status of:
#     - API service
#     - MongoDB connection
#     - ML models (lazy loaded)
#     - Authentication system
#     - LLM providers (Groq & HuggingFace)
    
#     Returns:
#         dict: Health status of all components
#     """
#     from app.db.mongodb import get_database
    
#     # Check MongoDB
#     mongodb_status = "connected" if get_database() is not None else "disconnected"
    
#     # Check ML models (don't load them, just check readiness)
#     ml_models_status = {
#         "policy_network": "ready (lazy load)",
#         "retriever": "ready (lazy load)",
#         "llm": "ready (API-based)"
#     }
    
#     # Check LLM providers
#     llm_providers = {
#         "groq": {
#             "enabled": settings.is_groq_enabled(),
#             "api_keys_configured": len(settings.get_groq_api_keys()),
#             "chat_model": settings.GROQ_CHAT_MODEL,
#             "eval_model": settings.GROQ_EVAL_MODEL
#         },
#         "huggingface": {
#             "enabled": settings.is_hf_enabled(),
#             "tokens_configured": len(settings.get_hf_tokens()),
#             "chat_model": settings.HF_CHAT_MODEL,
#             "eval_model": settings.HF_EVAL_MODEL
#         }
#     }
    
#     # Check authentication
#     auth_status = {
#         "jwt_enabled": bool(settings.SECRET_KEY and settings.SECRET_KEY != "your-secret-key-change-in-production"),
#         "algorithm": settings.ALGORITHM,
#         "token_expiry_minutes": settings.ACCESS_TOKEN_EXPIRE_MINUTES
#     }
    
#     # Overall health
#     is_healthy = (
#         mongodb_status == "connected" and 
#         auth_status["jwt_enabled"] and
#         (llm_providers["groq"]["enabled"] or llm_providers["huggingface"]["enabled"])
#     )
    
#     return {
#         "status": "healthy" if is_healthy else "degraded",
#         "api": "online",
#         "mongodb": mongodb_status,
#         "authentication": auth_status,
#         "llm_providers": llm_providers,
#         "ml_models": ml_models_status,
#         "environment": settings.ENVIRONMENT,
#         "debug_mode": settings.DEBUG
#     }

# # ============================================================================
# # GLOBAL EXCEPTION HANDLER
# # ============================================================================

# @app.exception_handler(Exception)
# async def global_exception_handler(request: Request, exc: Exception):
#     """
#     Global exception handler for unhandled errors
#     """
#     print(f"\n❌ Unhandled Exception:")
#     print(f"   Path: {request.url.path}")
#     print(f"   Error: {str(exc)}")
    
#     if settings.DEBUG:
#         import traceback
#         traceback.print_exc()
    
#     return JSONResponse(
#         status_code=500,
#         content={
#             "error": "Internal Server Error",
#             "detail": str(exc) if settings.DEBUG else "An unexpected error occurred",
#             "path": str(request.url.path)
#         }
#     )

# # ============================================================================
# # MAIN ENTRY POINT (for direct execution)
# # ============================================================================

# if __name__ == "__main__":
#     import uvicorn
    
#     print("\n🚀 Starting server directly...")
#     print("   Note: For production, use: uvicorn app.main:app --host 0.0.0.0 --port 8000")
    
#     uvicorn.run(
#         "app.main:app",
#         host="0.0.0.0",
#         port=8000,
#         reload=settings.DEBUG  # Auto-reload only in debug mode
#     )