add training configuration APIs

app/services/session_service.py

@@ -28,6 +28,7 @@ from app.schemas.session import (
 )
 from app.services.audit_service import AuditService
 from app.services.runtime_memory import runtime_memory
+from app.services.training_config_service import TrainingConfigService
 
 logger = logging.getLogger(__name__)
 
@@ -48,6 +49,7 @@ class SessionService:
         if not case:
             raise AppError("CASE_NOT_FOUND", "case not found or inactive", 404)
 
+        patient_config = TrainingConfigService(self.db).normalize_patient_config(payload.patient_config)
         session_code = f"sess_{datetime.utcnow().strftime('%Y%m%d%H%M%S')}_{uuid.uuid4().hex[:8]}"
         memory_key = f"mem:{session_code}"
         session = self.session_repo.create_session(
@@ -64,7 +66,7 @@ class SessionService:
                 status="inquiry",
                 started_at=datetime.utcnow(),
                 memory_key=memory_key,
-                metadata_={"source": "demo"},
+                metadata_={"source": "demo", "patient_config": patient_config},
             )
         )
         patient_opening = case.patient_opening or "家长：医生，孩子这几天不舒服，想请您看看。"
@@ -75,6 +77,7 @@ class SessionService:
             session_code=session.session_code,
             status=session.status,
             patient_opening=patient_opening,
+            patient_config=patient_config,
         )
 
     async def chat(self, ctx: UserContext, session_id: int, message: str) -> ChatResponse:
@@ -225,6 +228,61 @@ class SessionService:
         self.audit.log(ctx, "session.hints", "training_session", str(session.id), session.id)
         return HintResponse(**result)
 
+    async def stream_hints(self, ctx: UserContext, session_id: int, payload: HintRequest) -> AsyncIterator[str]:
+        """流式练习提示：把结构化提示压缩成一句话并用 SSE 返回给前端。"""
+        started_at = time.perf_counter()
+        try:
+            hint_result = await self.generate_hints(ctx, session_id, payload)
+            sentence = self._build_hint_sentence(hint_result)
+        except AppError as exc:
+            error_message = exc.message
+            error_code = exc.code
+
+            async def app_error_generator() -> AsyncIterator[str]:
+                yield self._sse_error(error_message, error_code)
+
+            return app_error_generator()
+        except Exception:
+            logger.exception("hint_stream.failed session_id=%s", session_id)
+
+            async def error_generator() -> AsyncIterator[str]:
+                yield self._sse_error("练习提示生成失败，请稍后重试", "HINT_STREAM_FAILED")
+
+            return error_generator()
+
+        async def event_generator() -> AsyncIterator[str]:
+            if not sentence:
+                yield self._sse_error("当前没有生成有效提示，请继续问诊后再试", "HINT_EMPTY")
+                return
+            for chunk in self._chunk_text(sentence, size=12):
+                payload_text = json.dumps({"delta": chunk}, ensure_ascii=False)
+                yield f"event: hint_delta\ndata: {payload_text}\n\n"
+                await asyncio.sleep(0)
+            done_payload = json.dumps({"latency_ms": int((time.perf_counter() - started_at) * 1000)}, ensure_ascii=False)
+            yield f"event: hint_done\ndata: {done_payload}\n\n"
+
+        return event_generator()
+
+    def _build_hint_sentence(self, hint_result: HintResponse) -> str:
+        """提示压缩：从结构化提示中提炼适合前端流式展示的一句话。"""
+        parts: list[str] = []
+        if hint_result.missing_dimensions:
+            parts.append(f"当前可补充{ '、'.join(hint_result.missing_dimensions[:3]) }")
+        if hint_result.next_questions:
+            parts.append(f"下一步可问：{hint_result.next_questions[0]}")
+        elif hint_result.hints:
+            parts.append(hint_result.hints[0])
+        if hint_result.recommended_orders:
+            order = hint_result.recommended_orders[0]
+            item_code = order.get("item_code") or order.get("item_name") or "关键检查"
+            reason = order.get("reason") or "用于完善病情判断"
+            parts.append(f"可考虑申请{item_code}，{reason}")
+        return "；".join(parts) + ("。" if parts else "")
+
+    def _chunk_text(self, text: str, size: int) -> list[str]:
+        """文本切片：把一句练习提示拆成短片段，便于前端按 SSE 渐进展示。"""
+        return [text[index : index + size] for index in range(0, len(text), size)]
+
     def complete_inquiry(self, ctx: UserContext, session_id: int) -> SessionStatusResponse:
         """完成问诊：校验至少一轮医生问诊后进入诊断阶段。"""
         session = self._get_session(session_id, ctx.user_id)