import os
from fastapi import FastAPI, Request, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from linebot import LineBotApi, WebhookHandler
from linebot.exceptions import InvalidSignatureError
from linebot.models import MessageEvent, TextMessage, TextSendMessage
import logging
from backend.services.nlp_service import NLPService
from backend.services.database_service import DatabaseService
from backend.config import settings
from backend.database.connection import test_database_connection

# 設定日誌
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

app = FastAPI(title="LINE Bot API", version="1.0.0")

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

# LINE Bot 初始化
line_bot_api = LineBotApi(settings.LINE_CHANNEL_ACCESS_TOKEN)
handler = WebhookHandler(settings.LINE_CHANNEL_SECRET)

# 服務初始化
nlp_service = NLPService()
db_service = DatabaseService()

@app.get("/")
def greet_json():
    return {"Hello": "LINE Bot API is running!"}

@app.get("/health")
def health_check():
    # 檢查資料庫連線
    db_status = "connected" if test_database_connection() else "disconnected"
    
    return {
        "status": "healthy", 
        "message": "LINE Bot API is operational",
        "database": db_status,
        "database_url": f"postgresql://{settings.DB_HOST}:{settings.DB_PORT}/{settings.DB_NAME}"
    }

@app.post("/webhook")
async def callback(request: Request):
    """LINE Bot Webhook 端點"""
    signature = request.headers.get('X-Line-Signature', '')
    body = await request.body()
    
    try:
        handler.handle(body.decode('utf-8'), signature)
    except InvalidSignatureError:
        logger.error("Invalid signature")
        raise HTTPException(status_code=400, detail="Invalid signature")
    
    return {"status": "ok"}

@handler.add(MessageEvent, message=TextMessage)
def handle_message(event):
    """處理 LINE 訊息"""
    try:
        user_message = event.message.text
        user_id = event.source.user_id
        
        logger.info(f"收到訊息: {user_message} from {user_id}")
        
        # 使用 NLP 服務分析訊息
        analysis_result = nlp_service.analyze_message(user_message)
        
        # 根據分析結果調用對應的資料庫方法
        response_data = db_service.execute_query(analysis_result)
        
        # 格式化回應訊息
        reply_message = nlp_service.format_response(response_data, analysis_result, user_message)
        
        # 回覆訊息
        line_bot_api.reply_message(
            event.reply_token,
            TextSendMessage(text=reply_message)
        )
        
    except Exception as e:
        logger.error(f"處理訊息時發生錯誤: {str(e)}")
        line_bot_api.reply_message(
            event.reply_token,
            TextSendMessage(text="抱歉，處理您的訊息時發生錯誤，請稍後再試。")
        )

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=7860)