140 lines
5.2 KiB
Python
140 lines
5.2 KiB
Python
"""
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对话 Agent：Facade，内部委托 ChatOrchestrator + ProfileAgent + InterviewAgent
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保留原有对外 API，供 router 等调用方兼容使用
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"""
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from datetime import datetime
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from typing import Any, Dict, List, Optional
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from app.agents.chat.orchestrator import ChatOrchestrator
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from app.agents.chat.prompts_conversation import ConversationStage
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from app.agents.state_schema import MemoirStateSchema
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from app.core.redis import redis_service
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class ConversationAgent:
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"""对话 Agent Facade，委托 ChatOrchestrator 实现多 Agent 协同"""
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def __init__(self):
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self._orchestrator = ChatOrchestrator()
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async def extract_profile_from_message(
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self,
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user_message: str,
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missing_fields: List[str],
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conversation_id: Optional[str] = None,
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) -> Dict[str, Any]:
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"""委托 ChatOrchestrator/ProfileAgent 提取资料"""
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return await self._orchestrator.extract_profile_from_message(
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user_message, missing_fields, conversation_id=conversation_id
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)
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async def generate_profile_followup(
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self,
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conversation_id: str,
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user_message: str,
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missing_fields: List[str],
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filled_fields: Dict[str, str],
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nickname: str = "",
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is_from_voice: bool = False,
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voice_session_id: str | None = None,
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user_message_timestamp: datetime | None = None,
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) -> List[str]:
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"""委托 ChatOrchestrator/ProfileAgent 生成资料追问"""
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return await self._orchestrator.generate_profile_followup(
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conversation_id=conversation_id,
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user_message=user_message,
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missing_fields=missing_fields,
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filled_fields=filled_fields,
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nickname=nickname,
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is_from_voice=is_from_voice,
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voice_session_id=voice_session_id,
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user_message_timestamp=user_message_timestamp,
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)
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async def generate_profile_greeting(
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self,
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conversation_id: str,
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missing_fields: List[str],
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nickname: str = "",
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) -> List[str]:
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"""委托 ChatOrchestrator/ProfileAgent 生成资料收集开场白"""
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return await self._orchestrator.generate_profile_greeting(
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conversation_id=conversation_id,
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missing_fields=missing_fields,
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nickname=nickname,
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)
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async def generate_response_with_state(
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self,
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conversation_id: str,
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user_message: str,
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memoir_state: MemoirStateSchema,
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user_profile_context: str = "",
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is_from_voice: bool = False,
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voice_session_id: str | None = None,
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user_message_timestamp: datetime | None = None,
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) -> List[str]:
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"""委托 ChatOrchestrator/InterviewAgent 生成访谈回复"""
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return await self._orchestrator.generate_response_with_state(
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conversation_id=conversation_id,
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user_message=user_message,
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memoir_state=memoir_state,
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user_profile_context=user_profile_context,
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is_from_voice=is_from_voice,
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voice_session_id=voice_session_id,
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user_message_timestamp=user_message_timestamp,
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)
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async def generate_opening_message(
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self,
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conversation_id: str,
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memoir_state: MemoirStateSchema,
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user_profile_context: str = "",
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) -> List[str]:
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"""委托 ChatOrchestrator/InterviewAgent 生成开场白"""
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return await self._orchestrator.generate_opening_message(
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conversation_id=conversation_id,
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memoir_state=memoir_state,
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user_profile_context=user_profile_context,
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)
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async def generate_response(
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self,
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conversation_id: str,
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user_message: str,
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current_stage: Optional[ConversationStage] = None,
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covered_topics: Optional[List[str]] = None,
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) -> str:
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"""兼容旧 API：生成简单回复（无状态感知），委托 InterviewAgent 的等价逻辑"""
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from app.agents.state_schema import default_state
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state = default_state()
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state.current_stage = (current_stage or ConversationStage.CHILDHOOD).value
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state.covered_stages = covered_topics or []
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responses = await self._orchestrator.generate_response_with_state(
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conversation_id=conversation_id,
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user_message=user_message,
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memoir_state=state,
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user_profile_context="",
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)
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return responses[0] if responses else ""
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def detect_stage(self, conversation_id: str, user_message: str) -> ConversationStage:
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"""根据关键词检测用户阶段（兼容 API）"""
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detected = self._orchestrator.detect_user_stage(user_message)
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if detected == "childhood":
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return ConversationStage.CHILDHOOD
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if detected == "education":
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return ConversationStage.EDUCATION
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if detected == "career":
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return ConversationStage.CAREER
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if detected == "family":
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return ConversationStage.FAMILY
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if detected == "belief":
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return ConversationStage.BELIEFS
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return ConversationStage.CHILDHOOD
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async def clear_memory(self, conversation_id: str) -> None:
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"""清除 Redis 中的对话历史"""
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await redis_service.clear_conversation_history(conversation_id)
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