feat & refactor: 重构agents目录结构；AI回复模块agent结构封装

api/app/features/conversation/ws/pipeline.py

@@ -14,8 +14,8 @@ from sqlalchemy import select
 from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.agents import ConversationAgent, MemoryAgent
-from app.agents.memoir_processor import BackgroundTaskRunner
-from app.agents.prompts.profile_prompts import format_user_profile_context
+from app.agents.chat import ChatOrchestrator
+from app.agents.memoir import BackgroundTaskRunner
 from app.core.db import AsyncSessionLocal
 from app.features.conversation.models import Conversation, Segment
 from app.features.conversation.ws.connection_manager import manager
@@ -28,7 +28,6 @@ from app.features.conversation.ws.profile_collector import (
 from app.features.user.models import User
 from app.core.config import settings
 from app.core.dependencies import get_asr_provider, get_tts_provider
-from app.features.memoir.state_service import get_or_create_state
 
 logger = get_logger(__name__)
 
@@ -53,6 +52,7 @@ async def _send_tts_audio(conversation_id: str, text: str) -> None:
 
 # ── Agent 实例（从 ConnectionManager 移出） ─────────────────────
 conversation_agent = ConversationAgent()
+chat_orchestrator = ChatOrchestrator()
 memory_agent = MemoryAgent()
 background_runner = BackgroundTaskRunner()
 
@@ -429,82 +429,21 @@ async def process_user_message(
     user: User = None,
     user_message_timestamp: Optional[datetime] = None,
 ) -> None:
-    """处理用户消息，生成 Agent 回应。支持资料收集模式和正式访谈模式。"""
-    agent = conversation_agent
-
-    if user:
-        missing = get_missing_profile_fields(user)
-        if missing:
-            try:
-                extracted = await agent.extract_profile_from_message(
-                    user_message, missing, conversation_id=conversation_id
-                )
-                if extracted:
-                    await apply_extracted_profile(user, extracted, db)
-
-                remaining = get_missing_profile_fields(user)
-                filled = get_filled_profile_fields(user)
-                is_from_voice = bool(segment.audio_url)
-                responses = await agent.generate_profile_followup(
-                    conversation_id=conversation_id,
-                    user_message=user_message,
-                    missing_fields=remaining,
-                    filled_fields=filled,
-                    nickname=user.nickname or "",
-                    is_from_voice=is_from_voice,
-                    voice_session_id=_voice_session_id_from_audio_url(segment.audio_url),
-                    user_message_timestamp=user_message_timestamp,
-                )
-
-                segment.agent_response = "\n\n".join(responses)
-                _mark_conversation_active(conversation)
-                await db.commit()
-
-                for i, response_text in enumerate(responses):
-                    await manager.send_message(conversation_id, {
-                        "type": MessageType.AGENT_RESPONSE,
-                        "conversation_id": conversation_id,
-                        "data": {"text": response_text, "index": i, "total": len(responses)},
-                        "timestamp": datetime.now(timezone.utc).isoformat(),
-                    })
-                    await _send_tts_audio(conversation_id, response_text)
-                    if i < len(responses) - 1:
-                        await asyncio.sleep(0.5)
-                return
-            except Exception as e:
-                logger.error(f"资料收集处理失败: {e}", exc_info=True)
-
-    state = await get_or_create_state(conversation.user_id, db)
-
-    if conversation.conversation_stage != state.current_stage:
-        conversation.conversation_stage = state.current_stage
-        await db.commit()
-
-    stmt_segments = select(Segment).where(
-        Segment.conversation_id == conversation_id
-    ).order_by(Segment.created_at)
-    result_segments = await db.execute(stmt_segments)
-    previous_segments = result_segments.scalars().all()
-    covered_topics = [seg.topic_category for seg in previous_segments if seg.topic_category]
-
-    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,
-        )
-
+    """处理用户消息，生成 Agent 回应。由 ChatOrchestrator 路由到 ProfileAgent 或 InterviewAgent。"""
     try:
         is_from_voice = bool(segment.audio_url)
-        responses = await agent.generate_response_with_state(
+        voice_session_id = _voice_session_id_from_audio_url(segment.audio_url)
+        responses = await chat_orchestrator.process_user_message(
             conversation_id=conversation_id,
             user_message=user_message,
-            memoir_state=state,
-            user_profile_context=user_profile_context,
+            user=user,
+            conversation=conversation,
             is_from_voice=is_from_voice,
-            voice_session_id=_voice_session_id_from_audio_url(segment.audio_url),
+            voice_session_id=voice_session_id,
+            db=db,
+            apply_extracted_profile_fn=apply_extracted_profile,
+            get_missing_profile_fields_fn=get_missing_profile_fields,
+            get_filled_profile_fields_fn=get_filled_profile_fields,
             user_message_timestamp=user_message_timestamp,
         )