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"""Main FastAPI application entry point"""
import sys
from pathlib import Path
# Add the app directory to Python path to ensure imports work
app_dir = Path(__file__).parent
if str(app_dir) not in sys.path:
sys.path.insert(0, str(app_dir))
from contextlib import asynccontextmanager
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
import logging
from config import (
API_TITLE,
API_DESCRIPTION,
API_VERSION,
STANCE_MODEL_ID,
HUGGINGFACE_API_KEY,
HUGGINGFACE_STANCE_MODEL_ID,
HOST,
PORT,
RELOAD,
CORS_ORIGINS,
CORS_CREDENTIALS,
CORS_METHODS,
CORS_HEADERS,
)
from services import stance_model_manager
from routes import api_router
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
@asynccontextmanager
async def lifespan(app: FastAPI):
"""Load models on startup and cleanup on shutdown"""
# Startup: Load all models
logger.info("Loading models on startup...")
# Load stance detection model
try:
logger.info(f"Loading stance model from Hugging Face: {HUGGINGFACE_STANCE_MODEL_ID}")
stance_model_manager.load_model(HUGGINGFACE_STANCE_MODEL_ID, HUGGINGFACE_API_KEY)
except Exception as e:
logger.error(f"✗ Failed to load stance model: {str(e)}")
logger.error("⚠️ Stance detection endpoints will not work!")
logger.info("✓ API startup complete")
logger.info("https://nlp-debater-project-fastapi-backend-models.hf.space/docs")
yield # Application runs here
# Shutdown: Cleanup (if needed)
# Currently no cleanup needed, but you can add it here if necessary
# Create FastAPI application
app = FastAPI(
title=API_TITLE,
description=API_DESCRIPTION,
version=API_VERSION,
docs_url="/docs",
redoc_url="/redoc",
lifespan=lifespan,
)
# Add CORS middleware
app.add_middleware(
CORSMiddleware,
allow_origins=CORS_ORIGINS,
allow_credentials=CORS_CREDENTIALS,
allow_methods=CORS_METHODS,
allow_headers=CORS_HEADERS,
)
# Include API routes
app.include_router(api_router)
if __name__ == "__main__":
# Run the API server
# Access at: http://localhost:8000
# API docs at: http://localhost:8000/docs
# Run the API server
uvicorn.run(
"main:app",
host=HOST,
port=PORT,
reload=RELOAD,
log_level="info"
)
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