backend/services/line_bot_service.py

"""
LINE Bot 服務 - 整合業務查詢功能
處理來自 LINE 官方帳號的用戶訊息
"""

import logging
from typing import Dict, Any, Optional
from backend.services.business_query_service import BusinessQueryService
from backend.services.database_service import DatabaseService

logger = logging.getLogger(__name__)

class LineBotService:
    """LINE Bot 服務類"""
    
    def __init__(self):
        self.business_query_service = BusinessQueryService()
        self.db_service = DatabaseService()
    
    def handle_text_message(self, user_id: str, message_text: str, display_name: str = None) -> Dict[str, Any]:
        """
        處理 LINE 用戶的文字訊息
        
        Args:
            user_id: LINE 用戶ID
            message_text: 用戶發送的訊息內容
            display_name: 用戶顯示名稱（可選）
            
        Returns:
            包含回應訊息和相關資料的字典
        """
        try:
            # 記錄用戶訊息
            logger.info(f"收到來自用戶 {user_id} 的訊息: {message_text}")
            
            # 🔧 後門測試：直接與 DeepSeek V3 聊天
            if message_text.startswith('##test##'):
                return self._handle_deepseek_test(user_id, message_text[8:].strip())
            
            # 檢查是否為特殊指令
            if message_text.lower() in ['help', '幫助', '說明', '指令']:
                return self._handle_help_command(user_id)
            
            elif message_text.lower() in ['menu', '選單', '功能']:
                return self._handle_menu_command(user_id)
            
            # 確保用戶資料存在
            self._ensure_user_profile(user_id, display_name)
            
            # 處理業務查詢
            query_result = self.business_query_service.process_user_query(message_text, user_id)
            
            # 準備回應
            response = {
                "type": "text",
                "text": query_result["response_message"],
                "user_id": user_id,
                "success": query_result["success"],
                "intent": query_result["intent"],
                "confidence": query_result["confidence"]
            }
            
            # 如果查詢成功且有資料，可以添加快速回覆按鈕
            if query_result["success"] and query_result["data"]:
                response["quick_reply"] = self._generate_quick_reply_buttons(query_result["intent"])
            
            return response
            
        except Exception as e:
            logger.error(f"處理 LINE 訊息時發生錯誤: {str(e)}")
            return {
                "type": "text",
                "text": "抱歉，系統暫時無法處理您的請求，請稍後再試。",
                "user_id": user_id,
                "success": False,
                "error": str(e)
            }
    
    def _handle_help_command(self, user_id: str) -> Dict[str, Any]:
        """處理幫助指令"""
        help_message = self.business_query_service.get_help_message()
        
        return {
            "type": "text",
            "text": help_message,
            "user_id": user_id,
            "success": True,
            "intent": "help"
        }
    
    def _handle_menu_command(self, user_id: str) -> Dict[str, Any]:
        """處理選單指令"""
        menu_message = """
🏪 智能查詢系統主選單

請選擇您需要的功能：

1️⃣ 商品查詢
   輸入：查詢商品 [商品名稱]

2️⃣ 庫存查詢  
   輸入：庫存查詢 [商品名稱]

3️⃣ 訂單查詢
   輸入：我的訂單

4️⃣ 低庫存警告
   輸入：低庫存商品

5️⃣ 業務統計
   輸入：業務摘要

💡 您也可以直接用自然語言提問！
例如：「iPhone 還有多少庫存？」

輸入「幫助」查看詳細說明
        """
        
        return {
            "type": "text", 
            "text": menu_message.strip(),
            "user_id": user_id,
            "success": True,
            "intent": "menu",
            "quick_reply": {
                "items": [
                    {"type": "action", "action": {"type": "message", "label": "商品查詢", "text": "查詢商品"}},
                    {"type": "action", "action": {"type": "message", "label": "庫存查詢", "text": "庫存查詢"}},
                    {"type": "action", "action": {"type": "message", "label": "我的訂單", "text": "我的訂單"}},
                    {"type": "action", "action": {"type": "message", "label": "低庫存", "text": "低庫存商品"}},
                    {"type": "action", "action": {"type": "message", "label": "業務統計", "text": "業務摘要"}}
                ]
            }
        }
    
    def _ensure_user_profile(self, user_id: str, display_name: str = None):
        """確保用戶資料存在於資料庫中"""
        try:
            # 檢查用戶是否已存在
            existing_user = self.db_service.get_user_profile(user_id)
            
            if not existing_user:
                # 建立新用戶資料
                user_data = {
                    "user_id": user_id,
                    "display_name": display_name or f"用戶_{user_id[:8]}",
                    "created_at": "now()"
                }
                
                success = self.db_service.create_user_profile(user_data)
                if success:
                    logger.info(f"已建立新用戶資料: {user_id}")
                else:
                    logger.warning(f"建立用戶資料失敗: {user_id}")
                    
        except Exception as e:
            logger.error(f"處理用戶資料時發生錯誤: {str(e)}")
    
    def _generate_quick_reply_buttons(self, intent: str) -> Dict[str, Any]:
        """根據查詢意圖生成快速回覆按鈕"""
        
        if intent == "product_search":
            return {
                "items": [
                    {"type": "action", "action": {"type": "message", "label": "查看庫存", "text": "庫存查詢"}},
                    {"type": "action", "action": {"type": "message", "label": "相關商品", "text": "查詢商品"}},
                    {"type": "action", "action": {"type": "message", "label": "主選單", "text": "選單"}}
                ]
            }
        
        elif intent == "inventory_check":
            return {
                "items": [
                    {"type": "action", "action": {"type": "message", "label": "低庫存警告", "text": "低庫存商品"}},
                    {"type": "action", "action": {"type": "message", "label": "商品詳情", "text": "查詢商品"}},
                    {"type": "action", "action": {"type": "message", "label": "主選單", "text": "選單"}}
                ]
            }
        
        elif intent == "order_search":
            return {
                "items": [
                    {"type": "action", "action": {"type": "message", "label": "業務統計", "text": "業務摘要"}},
                    {"type": "action", "action": {"type": "message", "label": "主選單", "text": "選單"}}
                ]
            }
        
        else:
            return {
                "items": [
                    {"type": "action", "action": {"type": "message", "label": "商品查詢", "text": "查詢商品"}},
                    {"type": "action", "action": {"type": "message", "label": "庫存查詢", "text": "庫存查詢"}},
                    {"type": "action", "action": {"type": "message", "label": "主選單", "text": "選單"}}
                ]
            }
    
    def handle_postback_action(self, user_id: str, postback_data: str) -> Dict[str, Any]:
        """處理 Postback 動作（按鈕點擊等）"""
        try:
            # 解析 postback 資料
            if postback_data.startswith("query_"):
                query_type = postback_data.replace("query_", "")
                
                if query_type == "products":
                    return self.handle_text_message(user_id, "查詢商品")
                elif query_type == "inventory":
                    return self.handle_text_message(user_id, "庫存查詢")
                elif query_type == "orders":
                    return self.handle_text_message(user_id, "我的訂單")
                elif query_type == "summary":
                    return self.handle_text_message(user_id, "業務摘要")
            
            # 預設回應
            return self._handle_menu_command(user_id)
            
        except Exception as e:
            logger.error(f"處理 Postback 動作時發生錯誤: {str(e)}")
            return {
                "type": "text",
                "text": "抱歉，無法處理此操作。",
                "user_id": user_id,
                "success": False,
                "error": str(e)
            }
    
    def get_user_activity_summary(self, user_id: str, days: int = 7) -> Dict[str, Any]:
        """取得用戶活動摘要"""
        try:
            # 這裡可以實作用戶活動統計
            # 例如：查詢次數、常用功能等
            
            summary = {
                "user_id": user_id,
                "period_days": days,
                "total_queries": 0,  # 從資料庫查詢
                "most_used_features": [],  # 最常使用的功能
                "last_activity": None  # 最後活動時間
            }
            
            return {
                "success": True,
                "data": summary
            }
            
        except Exception as e:
            logger.error(f"取得用戶活動摘要時發生錯誤: {str(e)}")
            return {
                "success": False,
                "error": str(e)
            }

        def _handle_deepseek_test(self, user_id: str, test_message: str) -> Dict[str, Any]:
            """
            🔧 後門測試：直接與 DeepSeek V3 聊天
            使用方式：在 LINE 中發送 "##test##你好" 
            """
            try:
                import asyncio
                import httpx
                from backend.config import settings
                
                if not test_message:
                    return {
                        "type": "text",
                        "text": "🔧 DeepSeek V3 測試模式\n\n使用方式：##test##[您的訊息]\n\n範例：##test##你好，請介紹一下自己",
                        "user_id": user_id,
                        "success": True,
                        "intent": "deepseek_test"
                    }
                
                # 同步調用異步函數的方法
                def sync_call_deepseek():
                    return asyncio.run(self._call_deepseek_api(test_message))
                
                try:
                    response_text = sync_call_deepseek()
                    
                    return {
                        "type": "text",
                        "text": f"🤖 DeepSeek V3 回應：\n\n{response_text}",
                        "user_id": user_id,
                        "success": True,
                        "intent": "deepseek_test"
                    }
                    
                except Exception as api_error:
                    return {
                        "type": "text",
                        "text": f"❌ DeepSeek V3 API 錯誤：\n{str(api_error)}\n\n請檢查：\n1. API Key 設定\n2. 網路連線\n3. OpenRouter 服務狀態",
                        "user_id": user_id,
                        "success": False,
                        "intent": "deepseek_test",
                        "error": str(api_error)
                    }
                    
            except Exception as e:
                logger.error(f"DeepSeek 測試錯誤: {str(e)}")
                return {
                    "type": "text",
                    "text": f"❌ 測試功能錯誤：{str(e)}",
                    "user_id": user_id,
                    "success": False,
                    "intent": "deepseek_test",
                    "error": str(e)
                }

        async def _call_deepseek_api(self, message: str) -> str:
            """
            直接調用 DeepSeek V3 API
            """
            from backend.config import settings
            
            api_key = settings.OPENROUTER_API_KEY
            model = settings.OPENROUTER_MODEL
            
            if not api_key:
                return "❌ OPENROUTER_API_KEY 未設定"
            
            headers = {
                "Authorization": f"Bearer {api_key}",
                "Content-Type": "application/json",
                "HTTP-Referer": "https://huggingface.co/spaces",
                "X-Title": "LINE Bot DeepSeek Test"
            }
            
            try:
                async with httpx.AsyncClient(timeout=30.0) as client:
                    response = await client.post(
                        "https://openrouter.ai/api/v1/chat/completions",
                        headers=headers,
                        json={
                            "model": model,
                            "messages": [
                                {
                                    "role": "system",
                                    "content": "你是 DeepSeek V3，一個強大的中文 AI 助手。請用繁體中文回應，並在回應開頭說明你是 DeepSeek V3。"
                                },
                                {
                                    "role": "user",
                                    "content": message
                                }
                            ],
                            "temperature": 0.7,
                            "max_tokens": 500
                        }
                    )
                
                if response.status_code == 200:
                    result = response.json()
                    content = result["choices"][0]["message"]["content"]
                    return content
                else:
                    return f"❌ API 錯誤 {response.status_code}: {response.text}"
                    
            except httpx.TimeoutException:
                return "❌ API 請求超時，請稍後再試"
            except Exception as e:
                return f"❌ 網路錯誤: {str(e)}"