example_app_with_preload.py

"""
Example: How to integrate Whisper preloading in FastAPI app startup

This shows how to preload Whisper model during FastAPI startup 
so the first inference will be much faster.
"""

from fastapi import FastAPI
from contextlib import asynccontextmanager
from src.apis.routes.speaking_route import router as speaking_router, preload_whisper_model
from loguru import logger
import time


@asynccontextmanager
async def lifespan(app: FastAPI):
    """
    FastAPI lifespan context manager for startup and shutdown events
    """
    # Startup
    logger.info("🚀 Starting FastAPI application...")
    startup_start = time.time()
    
    # Preload Whisper model during startup
    logger.info("📦 Preloading Whisper model...")
    success = preload_whisper_model(whisper_model="base.en")
    
    if success:
        logger.info("✅ Whisper model preloaded successfully!")
    else:
        logger.warning("⚠️  Failed to preload Whisper model, will load on first request")
    
    startup_time = time.time() - startup_start
    logger.info(f"🎯 FastAPI startup completed in {startup_time:.2f}s")
    
    yield  # Application runs here
    
    # Shutdown
    logger.info("🛑 Shutting down FastAPI application...")


# Create FastAPI app with lifespan
app = FastAPI(
    title="English Tutor API with Whisper Preloading",
    description="Pronunciation assessment API with optimized Whisper startup",
    version="2.0.0",
    lifespan=lifespan  # This enables the startup preloading
)

# Include speaking routes
app.include_router(speaking_router)


@app.get("/")
async def root():
    return {"message": "English Tutor API with Whisper preloaded!", "status": "ready"}


@app.get("/health")
async def health_check():
    """Health check endpoint that also verifies Whisper is loaded"""
    from src.apis.routes.speaking_route import global_assessor
    
    whisper_loaded = global_assessor is not None
    
    return {
        "status": "healthy",
        "whisper_preloaded": whisper_loaded,
        "model": global_assessor.asr.whisper_model_name if whisper_loaded else None
    }


if __name__ == "__main__":
    import uvicorn
    
    # Run with uvicorn
    uvicorn.run(
        "example_app_with_preload:app",
        host="0.0.0.0",
        port=8000,
        reload=False,  # Set to False for production to avoid reloading and losing preloaded model
        log_level="info"
    )