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life-echo/api/app/agents/chat/orchestrator.py

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"""
ChatOrchestratorAI 回复用户模块的编排层
负责路由Profile vs Interview调用 Specialist Agent统一 Redis 持久化与错误处理
"""
from datetime import datetime
from typing import TYPE_CHECKING, List, Optional
from sqlalchemy.ext.asyncio import AsyncSession
from app.agents.chat.helpers import save_message
from app.agents.chat.interview_agent import InterviewAgent
from app.agents.chat.profile_agent import ProfileAgent
from app.agents.state_schema import MemoirStateSchema
from app.core.logging import get_logger
from app.features.memoir.state_service import get_or_create_state
if TYPE_CHECKING:
from app.features.user.models import User
logger = get_logger(__name__)
class ChatOrchestrator:
"""
聊天编排器根据用户资料完成度路由到 ProfileAgent InterviewAgent
统一管理 Redis 写入
"""
def __init__(self):
self.profile_agent = ProfileAgent()
self.interview_agent = InterviewAgent()
async def process_user_message(
self,
conversation_id: str,
user_message: str,
user: Optional["User"],
conversation, # 用于更新 conversation_stage
is_from_voice: bool,
voice_session_id: Optional[str],
db: AsyncSession,
apply_extracted_profile_fn,
get_missing_profile_fields_fn,
get_filled_profile_fields_fn,
user_message_timestamp: Optional[datetime] = None,
) -> List[str]:
"""
处理用户消息返回 AI 回复列表
根据 missing_fields 路由到 ProfileAgent InterviewAgent
统一写入 Redis
"""
# --- 资料收集模式 ---
if user:
missing = get_missing_profile_fields_fn(user)
if missing:
try:
extracted = await self.profile_agent.extract_profile_from_message(
user_message, missing, conversation_id=conversation_id
)
if extracted:
await apply_extracted_profile_fn(user, extracted, db)
remaining = get_missing_profile_fields_fn(user)
filled = get_filled_profile_fields_fn(user)
responses = await self.profile_agent.generate_profile_followup(
conversation_id=conversation_id,
user_message=user_message,
missing_fields=remaining,
filled_fields=filled,
nickname=user.nickname or "",
)
await self._save_messages(
conversation_id=conversation_id,
user_message=user_message,
response_text="\n\n".join(responses),
is_from_voice=is_from_voice,
voice_session_id=voice_session_id,
user_message_timestamp=user_message_timestamp,
)
return responses
except Exception as e:
logger.error(f"资料收集处理失败: {e}", exc_info=True)
# --- 正式访谈模式 ---
user_id = user.id if user else None
if not user_id:
return ["抱歉,无法识别用户。"]
state = await get_or_create_state(user_id, db)
if conversation and conversation.conversation_stage != state.current_stage:
conversation.conversation_stage = state.current_stage
await db.commit()
from app.agents.chat.prompts_profile import format_user_profile_context
user_profile_context = ""
if user:
user_profile_context = format_user_profile_context(
birth_year=user.birth_year,
birth_place=user.birth_place,
grew_up_place=user.grew_up_place,
occupation=user.occupation,
)
responses = await self.interview_agent.generate_response_with_state(
conversation_id=conversation_id,
user_message=user_message,
memoir_state=state,
user_profile_context=user_profile_context,
)
await self._save_messages(
conversation_id=conversation_id,
user_message=user_message,
response_text="\n\n".join(responses),
is_from_voice=is_from_voice,
voice_session_id=voice_session_id,
user_message_timestamp=user_message_timestamp,
)
return responses
async def _save_messages(
self,
conversation_id: str,
user_message: str,
response_text: str,
is_from_voice: bool = False,
voice_session_id: Optional[str] = None,
user_message_timestamp: Optional[datetime] = None,
) -> None:
"""统一写入 Human + AI 消息到 Redis"""
human_msg_type = "audio" if is_from_voice else "text"
await save_message(
conversation_id,
"human",
user_message,
message_type=human_msg_type,
voice_session_id=voice_session_id,
timestamp=user_message_timestamp,
)
await save_message(conversation_id, "ai", response_text)
async def extract_profile_from_message(
self,
user_message: str,
missing_fields: List[str],
conversation_id: Optional[str] = None,
):
"""委托 ProfileAgent 提取资料"""
return await self.profile_agent.extract_profile_from_message(
user_message, missing_fields, conversation_id=conversation_id
)
async def generate_profile_followup(
self,
conversation_id: str,
user_message: str,
missing_fields: List[str],
filled_fields: dict,
nickname: str = "",
is_from_voice: bool = False,
voice_session_id: str | None = None,
user_message_timestamp: datetime | None = None,
) -> List[str]:
"""委托 ProfileAgent 生成资料追问,并写入 Redis"""
responses = await self.profile_agent.generate_profile_followup(
conversation_id=conversation_id,
user_message=user_message,
missing_fields=missing_fields,
filled_fields=filled_fields,
nickname=nickname,
)
response_text = "\n\n".join(responses)
await self._save_messages(
conversation_id=conversation_id,
user_message=user_message,
response_text=response_text,
is_from_voice=is_from_voice,
voice_session_id=voice_session_id,
user_message_timestamp=user_message_timestamp,
)
return responses
async def generate_profile_greeting(
self,
conversation_id: str,
missing_fields: List[str],
nickname: str = "",
) -> List[str]:
"""委托 ProfileAgent 生成资料收集开场白,并写入 Redis"""
responses = await self.profile_agent.generate_profile_greeting(
conversation_id=conversation_id,
missing_fields=missing_fields,
nickname=nickname,
)
response_text = "\n\n".join(responses)
await save_message(conversation_id, "ai", response_text)
return responses
async def generate_response_with_state(
self,
conversation_id: str,
user_message: str,
memoir_state: MemoirStateSchema,
user_profile_context: str = "",
is_from_voice: bool = False,
voice_session_id: str | None = None,
user_message_timestamp: datetime | None = None,
) -> List[str]:
"""委托 InterviewAgent 生成访谈回复,并写入 Redis"""
responses = await self.interview_agent.generate_response_with_state(
conversation_id=conversation_id,
user_message=user_message,
memoir_state=memoir_state,
user_profile_context=user_profile_context,
)
response_text = "\n\n".join(responses)
await self._save_messages(
conversation_id=conversation_id,
user_message=user_message,
response_text=response_text,
is_from_voice=is_from_voice,
voice_session_id=voice_session_id,
user_message_timestamp=user_message_timestamp,
)
return responses
def detect_user_stage(self, user_message: str) -> str:
"""委托 InterviewAgent 检测用户阶段"""
return self.interview_agent._detect_user_stage(user_message)
async def generate_opening_message(
self,
conversation_id: str,
memoir_state: MemoirStateSchema,
user_profile_context: str = "",
) -> List[str]:
"""委托 InterviewAgent 生成开场白,并写入 Redis"""
responses = await self.interview_agent.generate_opening_message(
conversation_id=conversation_id,
memoir_state=memoir_state,
user_profile_context=user_profile_context,
)
response_text = "\n\n".join(responses)
await save_message(conversation_id, "ai", response_text)
return responses