src/apis/create_app.py

from fastapi import FastAPI, APIRouter
from fastapi.middleware.cors import CORSMiddleware
from contextlib import asynccontextmanager
from src.apis.routes.user_route import router as router_user
from src.apis.routes.chat_route import router as router_chat
from src.apis.routes.lesson_route import router as router_lesson
from src.apis.routes.evaluation_route import router as router_evaluation
from src.apis.routes.pronunciation_route import router as router_pronunciation
from src.apis.routes.speaking_route import router as router_speaking, preload_whisper_model
from src.apis.routes.ipa_route import router as router_ipa
from loguru import logger
import time

api_router = APIRouter(prefix="/api")
api_router.include_router(router_user)
api_router.include_router(router_chat)
api_router.include_router(router_lesson)
api_router.include_router(router_evaluation)
api_router.include_router(router_pronunciation)
api_router.include_router(router_speaking)
api_router.include_router(router_ipa)


@asynccontextmanager
async def lifespan(app: FastAPI):
    """
    FastAPI lifespan context manager for startup and shutdown events
    Preloads Whisper model during startup for faster first inference
    """
    # Startup
    logger.info("🚀 Starting English Tutor API...")
    startup_start = time.time()
    
    try:
        # Preload Whisper model during startup
        logger.info("📦 Preloading Whisper model for pronunciation assessment...")
        success = preload_whisper_model(whisper_model="base.en")
        
        if success:
            logger.info("✅ Whisper model preloaded successfully!")
            logger.info("🎯 First pronunciation assessment will be much faster!")
        else:
            logger.warning("⚠️  Failed to preload Whisper model, will load on first request")
            
    except Exception as e:
        logger.error(f"❌ Error during Whisper preloading: {e}")
        logger.warning("⚠️  Continuing without preload, model will load on first request")
    
    startup_time = time.time() - startup_start
    logger.info(f"🎯 English Tutor API startup completed in {startup_time:.2f}s")
    logger.info("🌟 API is ready to serve pronunciation assessments!")
    
    yield  # Application runs here
    
    # Shutdown
    logger.info("🛑 Shutting down English Tutor API...")


def create_app():
    app = FastAPI(
        docs_url="/", 
        title="English Tutor API with Optimized Whisper",
        description="Pronunciation assessment API with preloaded Whisper for faster inference",
        version="2.1.0",
        lifespan=lifespan  # Enable preloading during startup
    )

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

    # Add health check endpoint for monitoring Whisper status
    @app.get("/health")
    async def health_check():
        """Health check endpoint that also verifies Whisper is loaded"""
        try:
            from src.apis.routes.speaking_route import global_assessor
            
            whisper_loaded = global_assessor is not None
            model_name = global_assessor.asr.whisper_model_name if whisper_loaded else None
            
            return {
                "status": "healthy",
                "whisper_preloaded": whisper_loaded,
                "whisper_model": model_name,
                "api_version": "2.1.0",
                "message": "English Tutor API is running" + (" with preloaded Whisper!" if whisper_loaded else "")
            }
        except Exception as e:
            return {
                "status": "healthy", 
                "whisper_preloaded": False,
                "error": str(e),
                "api_version": "2.1.0"
            }

    return app