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refactor(api,expo): 多智能体与会话收敛、回忆录兼容层移除、后端测试集大幅删减

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- 对齐「多智能体收敛」与「回忆录 stories-first / markdown-first」方向：收紧运行时契约、
  删除过渡兼容路径与双轨逻辑，并同步更新客户端与文档。

- Chat：以 ChatOrchestrator 为实时编排入口；删除独立 conversation_agent，精简 prompts。
- Memoir：删除 memory_agent；MemoirOrchestrator、classification / story_route 与 prompts 收敛到
  prepare_batches + run_story_pipeline_for_category_batch 主链路。
- 将 agents 侧 processor 迁入 feature 层为 background_runner，并移除 features 下重复/过时
  processor 封装。

- 新增 history_store，强化「conversation_messages 为 DB 真源、Redis 为缓存」模型。
- 调整 models、repo、service、session_history；精简 WS message_types，重构 pipeline 与 router。

- 移除章节占位、整章再生等旧路径；章节列表与封面逻辑要求 story 关联；收紧 cover 资格与
  enqueue。
- helpers、repo、service、router、reading_segment_materialize、story_pipeline_sync、pdf_service
  等按 canonical markdown / cover_asset_id 收缩；删除 memoir_images/provider 等冗余。
- tasks：memoir_tasks、chapter_cover_tasks 等大幅瘦身；story_image_tasks 等与当前图片任务对齐。

- core：config、logging、redis、task_tracker 小幅调整。
- auth / user / payment / quota：路由或服务侧删减过时接口或逻辑（如 payment router 行数减少）。

- pyproject.toml、development.sh、.env.example / .env.production、README 等同步说明或变量。

- Alembic 0001_initial_schema 微调（与当前 schema 叙事一致的小改动）。

- 回忆录：types / mappers / api、章节页与 memoir 页与后端契约对齐；markdown-renderer 调整。
- 语音：删除 voice/player，voice-segment-store 相应精简。

- api/tests：删除 conftest 及绝大部分既有测试文件（websocket_baseline、conversation、memoir
  图片、PDF、SMS 等），属有意收缩/待按 backend-test-system 重建的信号。
- docs：新增多智能体收敛与移除兼容层计划摘要；更新 story-first 设计、backend-test-system、
  multi-agent-refactor-plan、实施总结等。

BREAKING CHANGE: 后端对外契约、回忆录章节字段与若干路由/任务行为已变更；大量 API 测试被移除，
  CI 若依赖这些用例需按新策略补测或调整流水线。
This commit is contained in:
Kevin
2026-03-22 16:45:57 +08:00
parent 70070216c4
commit 786ebf8ae6
122 changed files with 2802 additions and 7941 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
api/app/features/conversation/ws/message_types.py
View File

@@ -2,8 +2,6 @@
from enum import Enum
LEGACY_VOICE_SESSION_ID = "legacy"
class MessageType(str, Enum):
"""WebSocket 消息类型"""

94
api/app/features/conversation/ws/pipeline.py
View File

@@ -15,24 +15,20 @@ if TYPE_CHECKING:
from sqlalchemy import select, update
from sqlalchemy.ext.asyncio import AsyncSession
from app.agents import ConversationAgent, MemoryAgent
from app.agents.chat import ChatOrchestrator
from app.agents.memoir import BackgroundTaskRunner
from app.core.config import settings
from app.core.db import AsyncSessionLocal
from app.core.dependencies import get_asr_provider, get_object_storage, get_tts_provider
from app.core.redis import redis_service
from app.features.conversation.history_store import ConversationHistoryStore
from app.features.conversation.models import Conversation, Segment
from app.features.conversation.ws.connection_manager import manager
from app.features.conversation.ws.message_types import (
LEGACY_VOICE_SESSION_ID,
MessageType,
)
from app.features.conversation.ws.message_types import MessageType
from app.features.conversation.ws.profile_collector import (
apply_extracted_profile,
get_filled_profile_fields,
get_missing_profile_fields,
)
from app.features.memoir.background_runner import BackgroundTaskRunner
from app.features.user.models import User
logger = get_logger(__name__)
@@ -77,9 +73,6 @@ async def _send_tts_audio(
storage = get_object_storage()
key = f"conversations/{conversation_id}/tts/{uuid.uuid4().hex}.{ext}"
public_url = storage.upload(key, audio_bytes, content_type)
await redis_service.append_tts_audio_url_to_last_ai_message(
conversation_id, public_url
)
await manager.send_message(
conversation_id,
{
@@ -109,9 +102,7 @@ async def _send_tts_audio(
# ── Agent 实例（从 ConnectionManager 移出） ─────────────────────
conversation_agent = ConversationAgent()
chat_orchestrator = ChatOrchestrator()
memory_agent = MemoryAgent()
background_runner = BackgroundTaskRunner()
@@ -197,12 +188,6 @@ def _mark_conversation_active(
return activity_time
def _normalize_voice_session_id(voice_session_id: Optional[str]) -> str:
if voice_session_id:
return str(voice_session_id)
return LEGACY_VOICE_SESSION_ID
def _voice_session_id_from_client_segment_id(
client_segment_id: Optional[str],
) -> Optional[str]:
@@ -220,19 +205,19 @@ def _build_segment_audio_url(voice_session_id: str, segment_index: int) -> str:
def _extract_segment_scope(audio_url: Optional[str]) -> Optional[Tuple[str, int]]:
"""从 audio_url 中解析 voice_session_id 与 segment_index。兼容旧格式 audio-segment:{index}。"""
"""从 audio_url 解析 voice_session_id 与 segment_index（audio-segment:{session_id}:{index}）。"""
prefix = "audio-segment:"
if not audio_url or not audio_url.startswith(prefix):
return None
payload = audio_url[len(prefix) :]
voice_session_id_raw, separator, segment_index_raw = payload.rpartition(":")
if not separator:
return None
try:
if separator:
return (
_normalize_voice_session_id(voice_session_id_raw),
int(segment_index_raw),
)
return (LEGACY_VOICE_SESSION_ID, int(payload))
sid = str(voice_session_id_raw).strip()
if not sid:
return None
return (sid, int(segment_index_raw))
except ValueError:
return None
@@ -452,9 +437,14 @@ async def process_audio_segment(
if existing_segment:
async with state.lock:
state.processed_indices.add(segment_index)
logger.info(
"分段已存在，按幂等处理跳过: "
f"conversation_id={conversation_id}, voice_session_id={voice_session_id}, segment_index={segment_index}"
logger.debug(
"分段已存在，按幂等跳过: conversation_id=%s voice_session_id=%s "
"segment_index=%s segment_id=%s transcript=%s",
conversation_id,
voice_session_id,
segment_index,
existing_segment.id,
existing_segment.transcript_text or "",
)
return
else:
@@ -535,6 +525,8 @@ async def process_user_message(
user_message_timestamp: Optional[datetime] = None,
) -> None:
"""处理用户消息，生成 Agent 回应。由 ChatOrchestrator 路由到 ProfileAgent 或 InterviewAgent。"""
store = ConversationHistoryStore(db)
tts_urls: list[str] = []
try:
is_from_voice = bool(segment.audio_url)
voice_session_id = _voice_session_id_from_audio_url(segment.audio_url)
@@ -558,9 +550,18 @@ async def process_user_message(
segment.agent_response = "\n\n".join(responses)
_mark_conversation_active(conversation)
await db.commit()
await store.record_human_ai_turn(
conversation_id=conversation_id,
user_message=user_message,
responses=responses,
user_message_timestamp=user_message_timestamp,
is_from_voice=is_from_voice,
voice_session_id=voice_session_id,
audio_duration_seconds=audio_dur,
tts_audio_urls=None,
segment_id=segment.id,
)
tts_urls: list[str] = []
n = len(responses)
for i, response_text in enumerate(responses):
await manager.send_message(
@@ -589,14 +590,35 @@ async def process_user_message(
if i < n - 1:
await asyncio.sleep(0.5)
await db.execute(
update(Segment)
.where(Segment.id == segment.id)
.values(tts_audio_urls=tts_urls if tts_urls else None)
)
await db.commit()
if tts_urls:
await store.attach_ai_tts_audio_urls(
conversation_id,
tts_audio_urls=tts_urls,
segment_id=segment.id,
)
await db.execute(
update(Segment)
.where(Segment.id == segment.id)
.values(tts_audio_urls=tts_urls)
)
await db.commit()
except Exception as e:
if tts_urls:
try:
await store.attach_ai_tts_audio_urls(
conversation_id,
tts_audio_urls=tts_urls,
segment_id=segment.id,
)
await db.execute(
update(Segment)
.where(Segment.id == segment.id)
.values(tts_audio_urls=tts_urls)
)
await db.commit()
except Exception as persist_error:
logger.warning("补写 TTS 元数据失败: %s", persist_error)
logger.error(f"处理用户消息失败: {e}", exc_info=True)
if conversation_id in manager.active_connections:
try:

95
api/app/features/conversation/ws/router.py
View File

@@ -16,19 +16,18 @@ from app.core.db import AsyncSessionLocal
from app.core.dependencies import get_asr_provider
from app.core.logging import get_logger
from app.core.security import verify_token
from app.features.conversation.history_store import ConversationHistoryStore
from app.features.conversation.models import Conversation, Segment
from app.features.conversation.service import ConversationService
from app.features.conversation.ws.connection_manager import manager
from app.features.conversation.ws.message_types import MessageType
from app.features.conversation.ws.pipeline import (
SegmentStreamState, # noqa: F401 — re-export for test backward compat
_delayed_listening_feedback,
_mark_conversation_active,
_normalize_voice_session_id,
_voice_session_id_from_client_segment_id,
background_runner,
chat_orchestrator,
cleanup_segment_states,
conversation_agent,
get_or_create_segment_state,
process_audio_segment,
process_conversation_segments,
@@ -144,18 +143,21 @@ async def websocket_endpoint(
)
return
history = await conversation_service.ensure_redis_history_from_segments(
history = await conversation_service.ensure_redis_history_from_db(
conversation_id
)
if not history:
missing_profile = get_missing_profile_fields(user)
if missing_profile:
try:
greetings = await conversation_agent.generate_profile_greeting(
greetings = await chat_orchestrator.generate_profile_greeting(
conversation_id=conversation_id,
missing_fields=missing_profile,
nickname=user.nickname or "",
)
await ConversationHistoryStore(db).record_ai_only_turn(
conversation_id, greetings
)
for i, text in enumerate(greetings):
await manager.send_message(
conversation_id,
@@ -184,12 +186,15 @@ async def websocket_endpoint(
occupation=user.occupation,
)
opening_messages = (
await conversation_agent.generate_opening_message(
await chat_orchestrator.generate_opening_message(
conversation_id=conversation_id,
memoir_state=state,
user_profile_context=user_profile_context,
)
)
await ConversationHistoryStore(db).record_ai_only_turn(
conversation_id, opening_messages
)
for i, text in enumerate(opening_messages):
await manager.send_message(
conversation_id,
@@ -212,8 +217,9 @@ async def websocket_endpoint(
while True:
try:
if websocket.application_state != WebSocketState.CONNECTED:
logger.info(
f"WebSocket 已非连接状态，退出循环: conversation_id={conversation_id}"
logger.debug(
"WebSocket 已非连接状态，退出循环: conversation_id=%s",
conversation_id,
)
break
message = await websocket.receive_json()
@@ -271,9 +277,18 @@ async def websocket_endpoint(
elif msg_type == MessageType.RECORDING_STARTED:
data = message.get("data", {})
voice_session_id = _normalize_voice_session_id(
data.get("voice_session_id")
)
raw_vs = data.get("voice_session_id")
if not raw_vs or not str(raw_vs).strip():
await manager.send_message(
conversation_id,
{
"type": MessageType.ERROR,
"data": {"message": "缺少 voice_session_id"},
"timestamp": datetime.now(timezone.utc).isoformat(),
},
)
continue
voice_session_id = str(raw_vs).strip()
segment_state = get_or_create_segment_state(
conversation_id,
voice_session_id,
@@ -298,12 +313,24 @@ async def websocket_endpoint(
data = message.get("data", {})
audio_base64 = data.get("audio_base64", "")
segment_index_raw = data.get("segment_index")
voice_session_id = _normalize_voice_session_id(
data.get("voice_session_id")
or _voice_session_id_from_client_segment_id(
resolved_vs = data.get("voice_session_id") or (
_voice_session_id_from_client_segment_id(
data.get("client_segment_id")
)
)
if not resolved_vs or not str(resolved_vs).strip():
await manager.send_message(
conversation_id,
{
"type": MessageType.ERROR,
"data": {
"message": "缺少 voice_session_id 或有效的 client_segment_id"
},
"timestamp": datetime.now(timezone.utc).isoformat(),
},
)
continue
voice_session_id = str(resolved_vs).strip()
is_last = bool(data.get("is_last", False))
audio_duration = int(data.get("duration", 0) or 0)
@@ -386,9 +413,14 @@ async def websocket_endpoint(
should_process = True
if not should_process:
logger.info(
"收到重复分段，跳过处理: "
f"conversation_id={conversation_id}, voice_session_id={voice_session_id}, segment_index={segment_index}"
logger.debug(
"收到重复分段，跳过: conversation_id=%s voice_session_id=%s "
"segment_index=%s audio_b64_len=%s duration=%s",
conversation_id,
voice_session_id,
segment_index,
len(audio_base64 or ""),
audio_duration,
)
continue
@@ -437,7 +469,11 @@ async def websocket_endpoint(
)
continue
logger.info(f"收到音频消息，时长: {audio_duration}s")
logger.debug(
"收到音频消息: conversation_id=%s duration_s=%s",
conversation_id,
audio_duration,
)
try:
asr = get_asr_provider()
@@ -445,7 +481,16 @@ async def websocket_endpoint(
transcript_text = await asr.transcribe(
audio_bytes, "m4a"
)
logger.info("ASR 转写结果: %s", transcript_text)
logger.debug(
"ASR 转写完成: conversation_id=%s chars=%s",
conversation_id,
len(transcript_text or ""),
)
logger.debug(
"ASR 转写全文: conversation_id=%s text=%s",
conversation_id,
transcript_text,
)
await manager.send_message(
conversation_id,
@@ -591,8 +636,10 @@ async def websocket_endpoint(
or "accept" in error_msg.lower()
and "not connected" in error_msg.lower()
):
logger.info(
f"WebSocket 连接已断开或未就绪: conversation_id={conversation_id}, error={error_msg}"
logger.debug(
"WebSocket 连接已断开或未就绪: conversation_id=%s error=%s",
conversation_id,
error_msg,
)
break
else:
@@ -613,8 +660,8 @@ async def websocket_endpoint(
logger.warning(f"发送错误消息失败: {send_error}")
break
except WebSocketDisconnect:
logger.info(
f"WebSocket 断开连接: conversation_id={conversation_id}"
logger.debug(
"WebSocket 断开连接: conversation_id=%s", conversation_id
)
break
except Exception as e:
@@ -634,7 +681,7 @@ async def websocket_endpoint(
break
except WebSocketDisconnect:
logger.info(f"WebSocket 断开连接: conversation_id={conversation_id}")
logger.debug("WebSocket 断开连接: conversation_id=%s", conversation_id)
await manager.disconnect(conversation_id)
cleanup_segment_states(conversation_id)
except Exception as e: