刘金宝
76 lines
3.1 KiB
Python
76 lines
3.1 KiB
Python
from collections.abc import AsyncIterator
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from app.agents.llm_adapter import LLMResponse, LLMStreamChunk
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from app.agents.hint_agent import HintAgent
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from app.agents.patient_agent import PatientAgent
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from app.agents.report_agent import ReportAgent
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from app.agents.scoring_agent import ScoringAgent
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from app.models.source_case import CaseBase
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from app.models.training import SessionOrder, SessionSubmission, TrainingSession
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class MedicalConsultationOrchestrator:
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"""主编排器：统一调度 Patient、Scoring、Report 等子 Agent。"""
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def __init__(self) -> None:
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self.patient_agent = PatientAgent()
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self.hint_agent = HintAgent()
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self.scoring_agent = ScoringAgent()
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self.report_agent = ReportAgent()
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async def patient_reply(self, session: TrainingSession, case: CaseBase, memory_messages: list[dict], message: str) -> LLMResponse:
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"""问诊编排：调用 Patient Agent 生成 AI 病人回复。"""
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return await self.patient_agent.reply(case, memory_messages, message, session.mode, self._patient_config(session))
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async def patient_stream_reply(
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self,
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session: TrainingSession,
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case: CaseBase,
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memory_messages: list[dict],
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message: str,
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) -> AsyncIterator[LLMStreamChunk]:
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"""流式问诊编排：调用 Patient Agent 并返回流式片段。"""
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async for chunk in self.patient_agent.stream_reply(case, memory_messages, message, session.mode, self._patient_config(session)):
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yield chunk
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async def evaluate(
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self,
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session: TrainingSession,
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case: CaseBase,
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memory_messages: list[dict],
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orders: list[SessionOrder],
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submission: SessionSubmission,
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rubric: object | None,
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guideline_refs: list[dict],
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scoring_rules: list | None = None,
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) -> dict:
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"""评价编排：调用 Scoring Agent 后交给 Report Agent 整理报告。"""
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scoring_result = await self.scoring_agent.score(
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session=session,
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case=case,
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memory_messages=memory_messages,
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orders=orders,
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submission=submission,
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rubric=rubric,
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guideline_refs=guideline_refs,
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scoring_rules=scoring_rules or [],
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)
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return self.report_agent.build_report(scoring_result)
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async def generate_hints(
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self,
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session: TrainingSession,
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case: CaseBase,
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memory_messages: list[dict],
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orders: list[SessionOrder],
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last_user_message: str | None = None,
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) -> dict:
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"""新手提示编排：基于当前会话上下文生成轻量训练提醒。"""
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return await self.hint_agent.generate(session, case, memory_messages, orders, last_user_message)
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def _patient_config(self, session: TrainingSession) -> dict | None:
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"""病人配置：从会话 metadata 读取训练页初始化配置，传递给 Patient Agent。"""
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metadata = session.metadata_ or {}
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patient_config = metadata.get("patient_config") if isinstance(metadata, dict) else None
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return patient_config if isinstance(patient_config, dict) else None
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