修复一些已知问题

api/app/agents/chat/agent_turn.py

@@ -0,0 +1,14 @@
+"""一轮 AI 对话输出：分段文案 + 是否整轮跳过 TTS（如失败兜底）。"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import List
+
+
+@dataclass(frozen=True)
+class AgentChatTurn:
+    """与 WebSocket pipeline 对齐：messages 为气泡分段；skip_tts 为 True 时不合成语音。"""
+
+    messages: List[str]
+    skip_tts: bool = False

api/app/agents/chat/conversation_agent.py

@@ -6,6 +6,7 @@
 from datetime import datetime
 from typing import Any, Dict, List, Optional
 
+from app.agents.chat.agent_turn import AgentChatTurn
 from app.agents.chat.orchestrator import ChatOrchestrator
 from app.agents.chat.prompts_conversation import ConversationStage
 from app.agents.state_schema import MemoirStateSchema
@@ -77,7 +78,7 @@ class ConversationAgent:
         voice_session_id: str | None = None,
         user_message_timestamp: datetime | None = None,
         audio_duration_seconds: int | None = None,
-    ) -> List[str]:
+    ) -> AgentChatTurn:
         """委托 ChatOrchestrator/InterviewAgent 生成访谈回复"""
         return await self._orchestrator.generate_response_with_state(
             conversation_id=conversation_id,
@@ -116,13 +117,13 @@ class ConversationAgent:
         state = default_state()
         state.current_stage = (current_stage or ConversationStage.CHILDHOOD).value
         state.covered_stages = covered_topics or []
-        responses = await self._orchestrator.generate_response_with_state(
+        turn = await self._orchestrator.generate_response_with_state(
             conversation_id=conversation_id,
             user_message=user_message,
             memoir_state=state,
             user_profile_context="",
         )
-        return responses[0] if responses else ""
+        return turn.messages[0] if turn.messages else ""
 
     def detect_stage(
         self, conversation_id: str, user_message: str

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,

api/app/agents/chat/orchestrator.py

@@ -8,6 +8,7 @@ from typing import TYPE_CHECKING, List, Optional
 
 from sqlalchemy.ext.asyncio import AsyncSession
 
+from app.agents.chat.agent_turn import AgentChatTurn
 from app.agents.chat.helpers import save_message
 from app.agents.chat.interview_agent import InterviewAgent
 from app.agents.chat.profile_agent import ProfileAgent
@@ -20,6 +21,10 @@ if TYPE_CHECKING:
 
 logger = get_logger(__name__)
 
+_UNAUTH_TURN = AgentChatTurn(
+    messages=["暂时没法继续对话，请先登录后再试。"], skip_tts=True
+)
+
 
 class ChatOrchestrator:
     """
@@ -45,9 +50,9 @@ class ChatOrchestrator:
         get_filled_profile_fields_fn,
         user_message_timestamp: Optional[datetime] = None,
         audio_duration_seconds: Optional[int] = None,
-    ) -> List[str]:
+    ) -> AgentChatTurn:
         """
-        处理用户消息，返回 AI 回复列表。
+        处理用户消息，返回 AI 回复（分段 + 是否跳过 TTS）。
         根据 missing_fields 路由到 ProfileAgent 或 InterviewAgent，
         统一写入 Redis。
         """
@@ -81,14 +86,14 @@ class ChatOrchestrator:
                         user_message_timestamp=user_message_timestamp,
                         audio_duration_seconds=audio_duration_seconds,
                     )
-                    return responses
+                    return AgentChatTurn(messages=responses, skip_tts=False)
                 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。"]
+            return _UNAUTH_TURN
 
         state = await get_or_create_state(user_id, db)
         if conversation and conversation.conversation_stage != state.current_stage:
@@ -106,7 +111,7 @@ class ChatOrchestrator:
                 occupation=user.occupation,
             )
 
-        responses = await self.interview_agent.generate_response_with_state(
+        turn = await self.interview_agent.generate_response_with_state(
             conversation_id=conversation_id,
             user_message=user_message,
             memoir_state=state,
@@ -115,13 +120,13 @@ class ChatOrchestrator:
         await self._save_messages(
             conversation_id=conversation_id,
             user_message=user_message,
-            response_text="\n\n".join(responses),
+            response_text="\n\n".join(turn.messages),
             is_from_voice=is_from_voice,
             voice_session_id=voice_session_id,
             user_message_timestamp=user_message_timestamp,
             audio_duration_seconds=audio_duration_seconds,
         )
-        return responses
+        return turn
 
     async def _save_messages(
         self,
@@ -222,15 +227,15 @@ class ChatOrchestrator:
         voice_session_id: str | None = None,
         user_message_timestamp: datetime | None = None,
         audio_duration_seconds: int | None = None,
-    ) -> List[str]:
+    ) -> AgentChatTurn:
         """委托 InterviewAgent 生成访谈回复，并写入 Redis"""
-        responses = await self.interview_agent.generate_response_with_state(
+        turn = 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)
+        response_text = "\n\n".join(turn.messages)
         await self._save_messages(
             conversation_id=conversation_id,
             user_message=user_message,
@@ -240,7 +245,7 @@ class ChatOrchestrator:
             user_message_timestamp=user_message_timestamp,
             audio_duration_seconds=audio_duration_seconds,
         )
-        return responses
+        return turn
 
     def detect_user_stage(self, user_message: str) -> str:
         """委托 InterviewAgent 检测用户阶段"""