- 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。
77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
from sqlalchemy import (
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JSON,
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Boolean,
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Column,
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DateTime,
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ForeignKey,
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Integer,
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String,
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Text,
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)
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from sqlalchemy.orm import relationship
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from app.core.db import Base, utc_now
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class Conversation(Base):
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__tablename__ = "conversations"
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id = Column(String, primary_key=True)
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user_id = Column(String, ForeignKey("users.id"), nullable=False)
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started_at = Column(DateTime(timezone=True), default=utc_now)
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last_message_at = Column(DateTime(timezone=True), nullable=True)
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ended_at = Column(DateTime(timezone=True), nullable=True)
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duration_seconds = Column(Integer, default=0)
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summary = Column(Text, nullable=True)
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status = Column(String, default="active")
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current_topic = Column(String, nullable=True)
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conversation_stage = Column(String, nullable=True)
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deleted_at = Column(DateTime(timezone=True), nullable=True)
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user = relationship("User", back_populates="conversations")
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segments = relationship(
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"Segment", back_populates="conversation", cascade="all, delete-orphan"
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)
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messages = relationship(
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"ConversationMessage",
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back_populates="conversation",
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cascade="all, delete-orphan",
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)
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class Segment(Base):
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__tablename__ = "segments"
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id = Column(String, primary_key=True)
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conversation_id = Column(String, ForeignKey("conversations.id"), nullable=False)
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audio_url = Column(String, nullable=True)
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transcript_text = Column(Text, nullable=False)
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audio_duration_seconds = Column(Integer, nullable=True)
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created_at = Column(DateTime(timezone=True), default=utc_now)
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processed = Column(Boolean, default=False)
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topic_category = Column(String, nullable=True)
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agent_response = Column(Text, nullable=True)
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tts_audio_urls = Column(JSON, nullable=True)
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conversation = relationship("Conversation", back_populates="segments")
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class ConversationMessage(Base):
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"""durable turn log aligned with Redis history shape (canonical chat source of truth)."""
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__tablename__ = "conversation_messages"
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id = Column(String, primary_key=True)
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conversation_id = Column(String, ForeignKey("conversations.id"), nullable=False)
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role = Column(String, nullable=False) # human / ai
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content = Column(Text, nullable=False)
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message_type = Column(String, nullable=False, default="text")
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voice_session_id = Column(String, nullable=True)
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duration_seconds = Column(Integer, nullable=True)
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tts_audio_urls = Column(JSON, nullable=True)
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segment_id = Column(String, ForeignKey("segments.id"), nullable=True)
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created_at = Column(DateTime(timezone=True), default=utc_now)
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conversation = relationship("Conversation", back_populates="messages")
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segment = relationship("Segment", foreign_keys=[segment_id])
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