309a051038
数据库与模型：新增多版迁移（章节证据快照、对话血缘、记忆事实/时间线 lineage 等），把「成稿 ↔ 对话/记忆」的溯源信息落到表结构里。 业务链路：会话与 WS、回忆录/故事流水线、记忆写入与 enrichment 等跟着接上线索与快照；新增章节证据快照与评测侧 EvalTraceService 等模块，方便组评审用的证据包。 内部评测：自动化 run 与手工 memoir 评审共用可追溯证据；rubric/ judge 相关脚本与文档有配套调整。 app-eval-web：Memoir/实验详情里能展开看证据摘要与 evidence_trace（含对话轮次 id）；Vite 代理与 development.sh 注入的 API 端口与当前默认内部评测端口一致，避免改端口后页面连错服务。 工程杂项：GitHub Actions / 仓库说明有更新；各适配器与支付/配额/plan 等多处为小改动或跟随主改动的收尾；新增/扩充了?
91 lines
3.7 KiB
Python
91 lines
3.7 KiB
Python
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)
|
||
|
||
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")
|
||
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])
|