78b61c076e
在 conversations 表增加 playground_conversation_judge_json，流式/非流式对话评审结束后写入最近一次快照（整体分、逐轮分、对比文案、错误与基线文件名等）。新增只读 GET 供前端按会话拉取；评测台 Playground 切换会话时自动恢复，并提示基线是否和当时一致。
93 lines
3.8 KiB
Python
93 lines
3.8 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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# 内部评测 Playground：最近一次 GLM 对话评分快照（含逐轮分与对比文案）
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playground_conversation_judge_json = Column(JSON, 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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# 用户输入正文：语音 ASR 结果或键盘输入（历史列名 transcript_text）
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user_input_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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# Phase 1 分类结果（回忆录 chapter 类目）；非空表示 Phase 1 已完成
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topic_category = Column(String, nullable=True)
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# Phase 2 已消费该段并完成叙事落库
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narrated = Column(Boolean, default=False, server_default="false")
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# Phase 1 判定无需进故事管线（无 slots 且 LLM 判 none）
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skip_narrative = Column(Boolean, default=False, server_default="false")
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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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# 用户轮次 durable message id（与 lineage_json 同步；便于查询）
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user_message_id = Column(
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String, ForeignKey("conversation_messages.id", ondelete="SET NULL"), nullable=True
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)
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# DialogueLineage JSON（schema 见 conversation.lineage_schemas）
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lineage_json = 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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# 本轮（与用户句配对）助手生成前检索到的 memory 证据 id 快照；Phase 8 可追溯
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memory_retrieval_trace_json = Column(JSON, nullable=True)
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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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