DESKTOP-72TV0V4\caoxiaozhu
3ee825aa90
Normalize uploaded documents into structured markdown, add clearer parser errors for missing dependencies, and cover the ingestion flow with backend tests. This also replaces deprecated UTC timestamp helpers in the touched backend paths so the knowledge pipeline stays warning-free. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
35 lines
1.6 KiB
Python
35 lines
1.6 KiB
Python
from sqlalchemy import Column, String, Text, Integer, ForeignKey, Boolean, DateTime, Enum as SQLEnum
|
|
from app.models.base import BaseModel, utc_now
|
|
|
|
|
|
class MemorySummary(BaseModel):
|
|
"""
|
|
对话摘要 — 中期记忆
|
|
当一段对话超过阈值轮数时，自动生成摘要存入此表
|
|
"""
|
|
__tablename__ = "memory_summaries"
|
|
|
|
user_id = Column(String(36), ForeignKey("users.id"), nullable=False, index=True)
|
|
conversation_id = Column(String(36), ForeignKey("conversations.id"), nullable=False, index=True)
|
|
summary_text = Column(Text, nullable=False) # 摘要内容
|
|
turn_count = Column(Integer, default=0) # 摘要时累计轮数
|
|
summary_at = Column(DateTime, default=utc_now, nullable=False)
|
|
|
|
|
|
class UserMemory(BaseModel):
|
|
"""
|
|
用户画像记忆 — 长期记忆
|
|
从对话中提取的用户事实、偏好、目标
|
|
"""
|
|
__tablename__ = "user_memories"
|
|
|
|
user_id = Column(String(36), ForeignKey("users.id"), nullable=False, index=True)
|
|
memory_type = Column(String(50), nullable=False) # fact | preference | goal | habit | other
|
|
content = Column(Text, nullable=False) # 记忆内容
|
|
importance = Column(Integer, default=5) # 重要程度 1-10
|
|
is_recalled = Column(Boolean, default=False) # 是否在当前对话中被召回
|
|
recall_count = Column(Integer, default=0) # 被召回次数
|
|
source_conversation_id = Column(String(36), nullable=True) # 来源对话
|
|
extracted_at = Column(DateTime, default=utc_now, nullable=False)
|
|
last_recalled_at = Column(DateTime, nullable=True)
|