life-echo/api/app/features/conversation/models.py

from sqlalchemy import (
    JSON,
    Boolean,
    Column,
    DateTime,
    ForeignKey,
    Integer,
    String,
    Text,
)
from sqlalchemy.orm import relationship

from app.core.db import Base, utc_now


class Conversation(Base):
    __tablename__ = "conversations"

    id = Column(String, primary_key=True)
    user_id = Column(String, ForeignKey("users.id"), nullable=False)
    started_at = Column(DateTime(timezone=True), default=utc_now)
    last_message_at = Column(DateTime(timezone=True), nullable=True)
    ended_at = Column(DateTime(timezone=True), nullable=True)
    duration_seconds = Column(Integer, default=0)
    summary = Column(Text, nullable=True)
    status = Column(String, default="active")
    current_topic = Column(String, nullable=True)
    conversation_stage = Column(String, nullable=True)
    deleted_at = Column(DateTime(timezone=True), nullable=True)
    # 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）
    playground_conversation_judge_json = Column(JSON, nullable=True)

    user = relationship("User", back_populates="conversations")
    segments = relationship(
        "Segment", back_populates="conversation", cascade="all, delete-orphan"
    )
    messages = relationship(
        "ConversationMessage",
        back_populates="conversation",
        cascade="all, delete-orphan",
    )


class Segment(Base):
    __tablename__ = "segments"

    id = Column(String, primary_key=True)
    conversation_id = Column(String, ForeignKey("conversations.id"), nullable=False)
    audio_url = Column(String, nullable=True)
    # 用户输入正文：语音 ASR 结果或键盘输入（历史列名 transcript_text）
    user_input_text = Column(Text, nullable=False)
    audio_duration_seconds = Column(Integer, nullable=True)
    created_at = Column(DateTime(timezone=True), default=utc_now)
    processed = Column(Boolean, default=False)
    # Phase 1 分类结果（回忆录 chapter 类目）；非空表示 Phase 1 已完成
    topic_category = Column(String, nullable=True)
    # Phase 2 已消费该段并完成叙事落库
    narrated = Column(Boolean, default=False, server_default="false")
    # Phase 1 判定无需进故事管线（无 slots 且 LLM 判 none）
    skip_narrative = Column(Boolean, default=False, server_default="false")
    # Phase 2 路由低置信延迟：到期前不消费；新同类目素材到达可清空。
    narrative_deferred_until = Column(DateTime(timezone=True), nullable=True)
    narrative_defer_count = Column(
        Integer, nullable=False, default=0, server_default="0"
    )
    narrative_defer_reason = Column(String, nullable=True)
    narrative_last_attempt_at = Column(DateTime(timezone=True), nullable=True)
    agent_response = Column(Text, nullable=True)
    tts_audio_urls = Column(JSON, nullable=True)
    # 用户轮次 durable message id（与 lineage_json 同步；便于查询）
    user_message_id = Column(
        String,
        ForeignKey("conversation_messages.id", ondelete="SET NULL"),
        nullable=True,
    )
    # DialogueLineage JSON（schema 见 conversation.lineage_schemas）
    lineage_json = Column(JSON, nullable=True)

    conversation = relationship("Conversation", back_populates="segments")


class ConversationMessage(Base):
    """durable turn log aligned with Redis history shape (canonical chat source of truth)."""

    __tablename__ = "conversation_messages"

    id = Column(String, primary_key=True)
    conversation_id = Column(String, ForeignKey("conversations.id"), nullable=False)
    role = Column(String, nullable=False)  # human / ai
    content = Column(Text, nullable=False)
    message_type = Column(String, nullable=False, default="text")
    voice_session_id = Column(String, nullable=True)
    duration_seconds = Column(Integer, nullable=True)
    tts_audio_urls = Column(JSON, nullable=True)
    segment_id = Column(String, ForeignKey("segments.id"), nullable=True)
    created_at = Column(DateTime(timezone=True), default=utc_now)
    # 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
    memory_retrieval_trace_json = Column(JSON, nullable=True)

    conversation = relationship("Conversation", back_populates="messages")
    segment = relationship("Segment", foreign_keys=[segment_id])