系统架构概览
1. 多轮对话管理设计
多轮对话管理是智能客服系统的核心,良好的对话管理可以让系统"记住"上下文,提供连贯的对话体验。
from typing import Dict, List, Optional
from dataclasses import dataclass
from datetime import datetime
@dataclass
class DialogueContext:
session_id: str
user_id: str
start_time: datetime
last_update: datetime
conversation_history: List[Dict]
current_intent: Optional[str] = None
entities: Dict = None
sentiment: float = 0.0
class DialogueManager:
def __init__(self, llm_service, knowledge_base):
self.llm = llm_service
self.kb = knowledge_base
self.sessions: Dict[str, DialogueContext] = {}
async def handle_message(self, session_id: str, message: str) -> str:
"""处理用户消息"""
# 获取或创建会话上下文
context = self._get_or_create_session(session_id)
# 更新对话历史
context.conversation_history.append({
"role": "user",
"content": message,
"timestamp": datetime.now()
})
# 意图识别
intent = await self._identify_intent(message, context)
context.current_intent = intent
# 实体提取
entities = await self._extract_entities(message, context)
context.entities.update(entities)
# 情绪分析
sentiment = await self._analyze_sentiment(message)
context.sentiment = sentiment
# 生成响应
response = await self._generate_response(context)
# 更新对话历史
context.conversation_history.append({
"role": "assistant",
"content": response,
"timestamp": datetime.now()
})
return response
async def _identify_intent(self, message: str, context: DialogueContext) -> str:
"""意图识别"""
prompt = f"""
对话历史:{context.conversation_history[-3:]}
当前用户消息:{message}
请识别用户意图,可能的意图包括:
- inquiry_product: 产品咨询
- technical_support: 技术支持
- complaint: 投诉
- general_chat: 闲聊
- other: 其他
仅返回意图标识符。
"""
return await self.llm.generate(prompt)
标签:context,客服,self,await,Agent,从零开始,str,._,response From: https://www.cnblogs.com/muzinan110/p/18554709