import logging from typing import Dict, List, Optional, Any from datetime import datetime import json from ..core.database import db_manager from ..core.models import WorkOrder, Conversation from ..core.llm_client import QwenClient from ..knowledge_base.knowledge_manager import KnowledgeManager from ..vehicle.vehicle_data_manager import VehicleDataManager logger = logging.getLogger(__name__) class DialogueManager: """对话管理器""" def __init__(self): self.llm_client = QwenClient() self.knowledge_manager = KnowledgeManager() self.vehicle_manager = VehicleDataManager() self.conversation_history = {} # 存储对话历史 def process_user_message( self, user_message: str, work_order_id: Optional[int] = None, user_id: Optional[str] = None, vehicle_id: Optional[str] = None ) -> Dict[str, Any]: """处理用户消息""" try: # 搜索相关知识库（只搜索已验证的） knowledge_results = self.knowledge_manager.search_knowledge( user_message, top_k=3, verified_only=True ) # 获取车辆实时数据 vehicle_data = None if vehicle_id: vehicle_data = self.vehicle_manager.get_latest_vehicle_data(vehicle_id) # 构建上下文 context = self._build_context(work_order_id, user_id) # 准备知识库信息 knowledge_context = "" if knowledge_results: knowledge_context = "相关知识库信息:\n" for i, result in enumerate(knowledge_results[:2], 1): knowledge_context += f"{i}. 问题: {result['question']}\n" knowledge_context += f" 答案: {result['answer']}\n" knowledge_context += f" 置信度: {result['confidence_score']:.2f}\n\n" # 准备车辆数据信息 vehicle_context = "" if vehicle_data: vehicle_context = "车辆实时数据:\n" for data_type, data_info in vehicle_data.items(): vehicle_context += f"- {data_type}: {json.dumps(data_info['value'], ensure_ascii=False)}\n" vehicle_context += f" 更新时间: {data_info['timestamp']}\n" vehicle_context += "\n" # 生成回复 response_result = self.llm_client.generate_response( user_message=user_message, context=context, knowledge_base=[knowledge_context] if knowledge_context else None, vehicle_data=[vehicle_context] if vehicle_context else None ) if "error" in response_result: return response_result # 保存对话记录 conversation_id = self._save_conversation( work_order_id=work_order_id, user_message=user_message, assistant_response=response_result["response"], knowledge_used=json.dumps([r["id"] for r in knowledge_results], ensure_ascii=False) ) # 更新对话历史 if user_id: if user_id not in self.conversation_history: self.conversation_history[user_id] = [] self.conversation_history[user_id].append({ "role": "user", "content": user_message, "timestamp": datetime.now().isoformat() }) self.conversation_history[user_id].append({ "role": "assistant", "content": response_result["response"], "timestamp": datetime.now().isoformat() }) # 保持历史记录在限制范围内 if len(self.conversation_history[user_id]) > 20: # 10轮对话 self.conversation_history[user_id] = self.conversation_history[user_id][-20:] return { "response": response_result["response"], "conversation_id": conversation_id, "knowledge_used": knowledge_results, "confidence_score": self._calculate_confidence(knowledge_results), "timestamp": datetime.now().isoformat() } except Exception as e: logger.error(f"处理用户消息失败: {e}") return {"error": f"处理失败: {str(e)}"} def _build_context(self, work_order_id: Optional[int], user_id: Optional[str]) -> str: """构建对话上下文""" context_parts = [] # 添加工单信息 if work_order_id: try: with db_manager.get_session() as session: work_order = session.query(WorkOrder).filter( WorkOrder.id == work_order_id ).first() if work_order: context_parts.append(f"当前工单信息:") context_parts.append(f"工单号: {work_order.order_id}") context_parts.append(f"标题: {work_order.title}") context_parts.append(f"描述: {work_order.description}") context_parts.append(f"类别: {work_order.category}") context_parts.append(f"优先级: {work_order.priority}") context_parts.append(f"状态: {work_order.status}") except Exception as e: logger.error(f"获取工单信息失败: {e}") # 添加用户历史对话 if user_id and user_id in self.conversation_history: recent_history = self.conversation_history[user_id][-6:] # 最近3轮对话 if recent_history: context_parts.append("最近的对话历史:") for msg in recent_history: role = "用户" if msg["role"] == "user" else "助手" context_parts.append(f"{role}: {msg['content']}") return "\n".join(context_parts) if context_parts else "" def _save_conversation( self, work_order_id: Optional[int], user_message: str, assistant_response: str, knowledge_used: str ) -> int: """保存对话记录""" try: with db_manager.get_session() as session: conversation = Conversation( work_order_id=work_order_id, user_message=user_message, assistant_response=assistant_response, knowledge_used=knowledge_used, timestamp=datetime.now() ) session.add(conversation) session.commit() return conversation.id except Exception as e: logger.error(f"保存对话记录失败: {e}") return 0 def _calculate_confidence(self, knowledge_results: List[Dict[str, Any]]) -> float: """计算回复置信度""" if not knowledge_results: return 0.5 # 默认置信度 # 基于知识库匹配度和置信度计算 max_similarity = max(result.get("similarity_score", 0) for result in knowledge_results) avg_confidence = sum(result.get("confidence_score", 0) for result in knowledge_results) / len(knowledge_results) # 综合评分 confidence = (max_similarity * 0.6 + avg_confidence * 0.4) return min(confidence, 1.0) def create_work_order( self, title: str, description: str, category: str, priority: str = "medium" ) -> Dict[str, Any]: """创建工单""" try: with db_manager.get_session() as session: work_order = WorkOrder( order_id=f"WO{datetime.now().strftime('%Y%m%d%H%M%S')}", title=title, description=description, category=category, priority=priority, status="open", created_at=datetime.now() ) session.add(work_order) session.commit() logger.info(f"创建工单成功: {work_order.order_id}") return { "work_order_id": work_order.id, "order_id": work_order.order_id, "status": "success" } except Exception as e: logger.error(f"创建工单失败: {e}") return {"error": f"创建失败: {str(e)}"} def update_work_order( self, work_order_id: int, status: Optional[str] = None, resolution: Optional[str] = None, satisfaction_score: Optional[float] = None ) -> bool: """更新工单""" try: with db_manager.get_session() as session: work_order = session.query(WorkOrder).filter( WorkOrder.id == work_order_id ).first() if not work_order: return False if status: work_order.status = status if resolution: work_order.resolution = resolution if satisfaction_score is not None: work_order.satisfaction_score = satisfaction_score work_order.updated_at = datetime.now() session.commit() # 如果工单已解决，学习知识 if status == "resolved" and resolution: self.knowledge_manager.learn_from_work_order(work_order_id) logger.info(f"更新工单成功: {work_order_id}") return True except Exception as e: logger.error(f"更新工单失败: {e}") return False def get_conversation_history(self, work_order_id: int) -> List[Dict[str, Any]]: """获取工单对话历史""" try: with db_manager.get_session() as session: conversations = session.query(Conversation).filter( Conversation.work_order_id == work_order_id ).order_by(Conversation.timestamp).all() return [ { "id": conv.id, "user_message": conv.user_message, "assistant_response": conv.assistant_response, "timestamp": conv.timestamp.isoformat(), "confidence_score": conv.confidence_score } for conv in conversations ] except Exception as e: logger.error(f"获取对话历史失败: {e}") return []