"""
LLM Inference Server main application using LitServe framework.
"""
import litserve as ls
import yaml
import logging
import multiprocessing as mp
from pathlib import Path
from fastapi.middleware.cors import CORSMiddleware
from .routes import router, init_router
from .api import InferenceApi

# Store process list globally so it doesn't get garbage collected
_WORKER_PROCESSES = []
_MANAGER = None

def setup_logging():
    """Set up basic logging configuration"""
    logging.basicConfig(
        level=logging.INFO,
        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
    )
    return logging.getLogger(__name__)

def load_config():
    """Load configuration from config.yaml"""
    config_path = Path(__file__).parent / "config.yaml"
    with open(config_path) as f:
        return yaml.safe_load(f)

def create_app():
    """Create and configure the application instance."""
    global _WORKER_PROCESSES, _MANAGER

    logger = setup_logging()
    config = load_config()
    server_config = config.get('server', {})

    # Initialize API with config
    api = InferenceApi(config)

    # Initialize router with API instance
    init_router(api)

    # Create LitServer instance
    server = ls.LitServer(
        api,
        timeout=server_config.get('timeout', 60),
        max_batch_size=server_config.get('max_batch_size', 1),
        track_requests=True
    )

    # Launch inference workers (assuming single uvicorn worker for now)
    _MANAGER, _WORKER_PROCESSES = server.launch_inference_worker(num_uvicorn_servers=1)

    # Get the FastAPI app
    app = server.app

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

    # Add routes with configured prefix
    api_prefix = config.get('llm_server', {}).get('api_prefix', '/api/v1')
    app.include_router(router, prefix=api_prefix)

    # Set the response queue ID for the app
    app.response_queue_id = 0  # Since we're using a single worker

    return app

# Create the app instance for uvicorn
app = create_app()