- 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。
145 lines
4.9 KiB
Python
145 lines
4.9 KiB
Python
"""Durable conversation turn persistence + Redis cache sync (feature layer)."""
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from __future__ import annotations
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import uuid
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from datetime import datetime, timedelta, timezone
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from typing import Any
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core import redis as redis_core
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from app.core.logging import get_logger
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from app.features.conversation import repo
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from app.features.conversation.models import ConversationMessage
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from app.features.conversation.session_history import (
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conversation_messages_to_redis_history,
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)
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logger = get_logger(__name__)
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def _utc_now() -> datetime:
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return datetime.now(timezone.utc)
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class ConversationHistoryStore:
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def __init__(self, db: AsyncSession):
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self._db = db
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async def load_canonical_history(
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self, conversation_id: str
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) -> list[dict[str, Any]]:
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rows = await repo.get_conversation_messages(conversation_id, self._db)
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return conversation_messages_to_redis_history(rows)
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async def _touch_conversation(
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self, conversation_id: str, *, occurred_at: datetime
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) -> None:
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conversation = await repo.get_conversation(conversation_id, self._db)
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if conversation is None:
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return
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current = getattr(conversation, "last_message_at", None)
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if current is None or current < occurred_at:
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conversation.last_message_at = occurred_at
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async def _sync_redis_from_db(self, conversation_id: str) -> None:
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hist = await self.load_canonical_history(conversation_id)
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await redis_core.redis_service.set_conversation_history(conversation_id, hist)
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async def _sync_redis_best_effort(self, conversation_id: str) -> None:
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try:
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await self._sync_redis_from_db(conversation_id)
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except Exception as exc:
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logger.warning("conversation history cache sync skipped: %s", exc)
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async def record_ai_only_turn(
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self, conversation_id: str, responses: list[str]
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) -> None:
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if not responses:
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return
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combined = "\n\n".join(responses)
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created_at = _utc_now()
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msg = ConversationMessage(
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id=str(uuid.uuid4()),
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conversation_id=conversation_id,
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role="ai",
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content=combined,
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message_type="text",
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created_at=created_at,
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)
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repo.add_conversation_message(msg, self._db)
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await self._touch_conversation(conversation_id, occurred_at=created_at)
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await self._db.commit()
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await self._sync_redis_best_effort(conversation_id)
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async def record_human_ai_turn(
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self,
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conversation_id: str,
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user_message: str,
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responses: list[str],
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*,
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user_message_timestamp: datetime | None,
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is_from_voice: bool,
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voice_session_id: str | None,
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audio_duration_seconds: int | None,
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tts_audio_urls: list[str] | None,
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segment_id: str | None,
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) -> None:
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if not responses:
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return
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human_ts = user_message_timestamp or _utc_now()
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if human_ts.tzinfo is None:
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human_ts = human_ts.replace(tzinfo=timezone.utc)
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ai_ts = human_ts + timedelta(microseconds=1)
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human_type = "audio" if is_from_voice else "text"
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human = ConversationMessage(
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id=str(uuid.uuid4()),
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conversation_id=conversation_id,
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role="human",
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content=user_message,
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message_type=human_type,
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voice_session_id=voice_session_id,
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duration_seconds=audio_duration_seconds
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if audio_duration_seconds is not None and audio_duration_seconds > 0
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else None,
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segment_id=segment_id,
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created_at=human_ts,
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)
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combined = "\n\n".join(responses)
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ai = ConversationMessage(
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id=str(uuid.uuid4()),
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conversation_id=conversation_id,
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role="ai",
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content=combined,
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message_type="text",
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tts_audio_urls=tts_audio_urls if tts_audio_urls else None,
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segment_id=segment_id,
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created_at=ai_ts,
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)
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repo.add_conversation_message(human, self._db)
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repo.add_conversation_message(ai, self._db)
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await self._touch_conversation(conversation_id, occurred_at=ai_ts)
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await self._db.commit()
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await self._sync_redis_best_effort(conversation_id)
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async def attach_ai_tts_audio_urls(
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self,
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conversation_id: str,
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*,
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tts_audio_urls: list[str],
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segment_id: str | None = None,
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) -> None:
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if not tts_audio_urls:
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return
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row = await repo.set_latest_ai_message_tts_audio_urls(
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conversation_id,
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self._db,
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tts_audio_urls=tts_audio_urls,
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segment_id=segment_id,
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)
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if row is None:
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return
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await self._db.commit()
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await self._sync_redis_best_effort(conversation_id)
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