#!/usr/bin/env python3
"""
Base Service Class for AI Model Services

Provides common functionality for all model services:
- Health check endpoint
- Graceful shutdown handling
- Logging configuration
- Standard FastAPI setup
"""

import asyncio
import logging
import os
import signal
import sys
from abc import ABC, abstractmethod
from typing import Optional

from fastapi import FastAPI
import uvicorn


class BaseService(ABC):
    """Abstract base class for all AI model services"""

    def __init__(self, name: str, port: int, host: str = "0.0.0.0"):
        """
        Initialize base service

        Args:
            name: Service name (for logging)
            port: Port to run service on
            host: Host to bind to (default: 0.0.0.0)
        """
        self.name = name
        self.port = port
        self.host = host
        self.app = FastAPI(title=f"{name} Service", version="1.0.0")
        self.logger = self._setup_logging()
        self.shutdown_event = asyncio.Event()

        # Register standard endpoints
        self._register_health_endpoint()

        # Register signal handlers for graceful shutdown
        self._register_signal_handlers()

        # Allow subclasses to add custom routes
        self.create_app()

    def _setup_logging(self) -> logging.Logger:
        """Configure logging for the service"""
        logging.basicConfig(
            level=logging.INFO,
            format=f'%(asctime)s - {self.name} - %(levelname)s - %(message)s',
            handlers=[
                logging.StreamHandler(sys.stdout)
            ]
        )
        return logging.getLogger(self.name)

    def _register_health_endpoint(self):
        """Register standard health check endpoint"""
        @self.app.get("/health")
        async def health_check():
            """Health check endpoint"""
            return {
                "status": "healthy",
                "service": self.name,
                "port": self.port
            }

    def _register_signal_handlers(self):
        """Register signal handlers for graceful shutdown"""
        def signal_handler(sig, frame):
            self.logger.info(f"Received signal {sig}, initiating graceful shutdown...")
            self.shutdown_event.set()

        signal.signal(signal.SIGINT, signal_handler)
        signal.signal(signal.SIGTERM, signal_handler)

    @abstractmethod
    def create_app(self):
        """
        Create FastAPI routes for this service.
        Subclasses must implement this to add their specific endpoints.

        Example:
            @self.app.post("/v1/generate")
            async def generate(request: MyRequest):
                return await self.model.generate(request)
        """
        pass

    async def initialize(self):
        """
        Initialize the service (load models, etc.).
        Subclasses can override this for custom initialization.
        """
        self.logger.info(f"Initializing {self.name} service...")

    async def cleanup(self):
        """
        Cleanup resources on shutdown.
        Subclasses can override this for custom cleanup.
        """
        self.logger.info(f"Cleaning up {self.name} service...")

    def run(self):
        """
        Run the service.
        This is the main entry point that starts the FastAPI server.
        """
        try:
            self.logger.info(f"Starting {self.name} service on {self.host}:{self.port}")

            # Run initialization
            asyncio.run(self.initialize())

            # Start uvicorn server
            config = uvicorn.Config(
                app=self.app,
                host=self.host,
                port=self.port,
                log_level="info",
                access_log=True
            )
            server = uvicorn.Server(config)

            # Run server
            asyncio.run(server.serve())

        except KeyboardInterrupt:
            self.logger.info("Keyboard interrupt received")
        except Exception as e:
            self.logger.error(f"Error running service: {e}", exc_info=True)
            sys.exit(1)
        finally:
            # Cleanup
            asyncio.run(self.cleanup())
            self.logger.info(f"{self.name} service stopped")


class GPUService(BaseService):
    """
    Base class for GPU-accelerated services.
    Provides additional GPU-specific functionality.
    """

    def __init__(self, name: str, port: int, host: str = "0.0.0.0"):
        super().__init__(name, port, host)
        self._check_gpu_availability()

    def _check_gpu_availability(self):
        """Check if GPU is available"""
        try:
            import torch
            if torch.cuda.is_available():
                gpu_count = torch.cuda.device_count()
                gpu_name = torch.cuda.get_device_name(0)
                self.logger.info(f"GPU available: {gpu_name} (count: {gpu_count})")
            else:
                self.logger.warning("No GPU available - service may run slowly")
        except ImportError:
            self.logger.warning("PyTorch not installed - cannot check GPU availability")