修复一些已知问题

api/app/agents/chat/interview_agent.py

@@ -5,6 +5,7 @@ InterviewAgent：正式访谈 Specialist
 
 from typing import Any, List
 
+from app.agents.chat.agent_turn import AgentChatTurn
 from app.core.dependencies import get_llm_provider
 from app.core.logging import get_logger
 
@@ -18,6 +19,9 @@ from app.agents.state_schema import MemoirStateSchema
 
 logger = get_logger(__name__)
 
+# LLM 不可用或调用失败时对用户展示（不暴露异常细节、不触发 TTS）
+_FALLBACK_REPLY = "刚才网络不太稳，没接上。你可以再说一遍，或稍后再试。"
+
 
 def _get_langchain_llm():
     try:
@@ -149,12 +153,11 @@ class InterviewAgent:
         user_message: str,
         memoir_state: MemoirStateSchema,
         user_profile_context: str = "",
-    ) -> List[str]:
+    ) -> AgentChatTurn:
         """生成状态感知的访谈回复，不持久化（由 Orchestrator 负责）"""
         if not self.llm:
-            return [
-                "抱歉，LLM 服务未配置。请设置 DEEPSEEK_API_KEY 或 LLM_API_KEY 环境变量。"
-            ]
+            logger.warning("InterviewAgent: LLM 未配置，返回兜底文案")
+            return AgentChatTurn(messages=[_FALLBACK_REPLY], skip_tts=True)
         try:
             empty_slots = memoir_state.empty_slots_for_current_stage()
             filled_slots = {
@@ -191,10 +194,11 @@ class InterviewAgent:
             messages = [
                 msg.strip() for msg in response_text.split("[SPLIT]") if msg.strip()
             ]
-            return messages[:3] if messages else [response_text]
+            out = messages[:3] if messages else [response_text]
+            return AgentChatTurn(messages=out, skip_tts=False)
         except Exception as e:
-            logger.error("生成回应失败: %s", e)
-            return [f"抱歉，生成回应时出现错误: {str(e)}"]
+            logger.error("生成回应失败: %s", e, exc_info=True)
+            return AgentChatTurn(messages=[_FALLBACK_REPLY], skip_tts=True)
 
     async def generate_opening_message(
         self,