Simon
ead5f83bee
dependencies.py 拆分为 dependencies/ 包; 新增 vision/ragflow_ingestion/neo4j 客户端与 h5_ai_task; alembic 045 图置信度迁移; 响应契约统一收尾。
260 lines
8.0 KiB
Python
260 lines
8.0 KiB
Python
# =============================================================================
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# 企微IT智能服务台 — 知识库优化建议模型
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# =============================================================================
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# 说明：对应数据库 knowledge_suggestions 表
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# 存储AI分析生成的优化建议，用于知识库迭代
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# 分析维度：错误标注高频问题、未命中知识库的会话、AI不确定回复
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# =============================================================================
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import uuid
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from datetime import datetime
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from typing import Any, Dict, List, Optional
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from sqlalchemy import Boolean, DateTime, Float, Index, JSON, String, Text
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from sqlalchemy.orm import Mapped, mapped_column
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from app.database import Base
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class KnowledgeSuggestion(Base):
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"""知识库优化建议模型 — 对应 knowledge_suggestions 表。
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存储AI自动分析生成的优化建议，用于知识库持续迭代。
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Attributes:
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id: 建议ID（UUID）
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suggestion_type: 建议类型（new_faq=新增FAQ/update=更新/outdated=标记过时）
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status: 状态（pending=待审核/approved=已通过/rejected=已拒绝/applied=已应用）
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title: 建议标题（新增/更新的FAQ标题）
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content: 建议内容（答案内容）
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category: 分类
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tags: 标签列表（JSON数组）
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source_type: 分析来源（annotation=标注数据/conversation=会话数据/ai_uncertain=AI不确定）
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source_data: 来源数据（JSON，存储相关会话ID或标注ID列表）
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reason: 生成理由（AI分析的理由）
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reject_reason: 拒绝理由（审核拒绝时填写）
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reviewer_id: 审核人ID
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reviewed_at: 审核时间
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created_at: 创建时间
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updated_at: 更新时间
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"""
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# 表名
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__tablename__ = "knowledge_suggestions"
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# --------------------------------------------------------------------------
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# 字段定义
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# --------------------------------------------------------------------------
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# 主键
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id: Mapped[str] = mapped_column(
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String(36),
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primary_key=True,
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default=lambda: str(uuid.uuid4()),
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)
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# 建议类型
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suggestion_type: Mapped[str] = mapped_column(
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String(20),
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nullable=False,
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default="new_faq",
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comment="new_faq=新增FAQ/update=更新/outdated=标记过时",
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)
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# 状态
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status: Mapped[str] = mapped_column(
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String(20),
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nullable=False,
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default="pending",
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index=True,
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comment="pending=待审核/approved=已通过/rejected=已拒绝/applied=已应用",
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)
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# 建议标题
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title: Mapped[str] = mapped_column(
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String(256),
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nullable=False,
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comment="新增/更新的FAQ标题",
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)
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# 建议内容
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content: Mapped[str] = mapped_column(
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Text,
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nullable=False,
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comment="答案内容",
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)
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# 分类
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category: Mapped[str] = mapped_column(
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String(64),
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nullable=False,
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default="其他",
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comment="分类：硬件/软件/网络/安全/账号/其他",
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)
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# 标签列表
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tags: Mapped[List[str]] = mapped_column(
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JSON,
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nullable=False,
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default=list,
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comment="标签列表",
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)
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# 分析来源
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source_type: Mapped[str] = mapped_column(
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String(30),
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nullable=False,
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comment="annotation=标注数据/conversation=会话数据/ai_uncertain=AI不确定",
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)
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# 来源数据（JSON）
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source_data: Mapped[Optional[List[str]]] = mapped_column(
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JSON,
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nullable=True,
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comment="相关会话ID或标注ID列表",
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)
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# --------------------------------------------------------------------------
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# Tier0 扩展字段 — 图结构 + 置信度 + 受众 + 状态（D1/D3/D7/D8）
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# --------------------------------------------------------------------------
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# AI 生成置信度（0.0-1.0，D3 门控阈值 0.7）
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confidence: Mapped[Optional[float]] = mapped_column(
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Float,
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nullable=True,
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comment="AI 生成置信度（0.0-1.0）",
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)
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# 受众类型（D8：employee_quick_reply / engineer_workguide）
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audience: Mapped[Optional[str]] = mapped_column(
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String(30),
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nullable=True,
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comment="受众类型：employee_quick_reply / engineer_workguide",
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)
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# 图结构字段 — 问题名称（对应 Neo4j Issue.name）
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issue: Mapped[Optional[str]] = mapped_column(
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String(256),
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nullable=True,
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comment="图节点：问题名称",
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)
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# 图结构字段 — 动作名称（对应 Neo4j Action.name）
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action: Mapped[Optional[str]] = mapped_column(
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String(256),
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nullable=True,
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comment="图节点：动作名称",
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)
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# 图关系类型（LEADS_TO / RELATES_TO / CAN_JUMP_TO）
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relation_type: Mapped[Optional[str]] = mapped_column(
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String(30),
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nullable=True,
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comment="图关系类型",
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)
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# 父 Issue 名称（用于构建 Issue→Issue 关系）
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parent_issue: Mapped[Optional[str]] = mapped_column(
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String(256),
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nullable=True,
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comment="父 Issue 名称",
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)
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# 图结构扩展元数据（JSON，存放额外的图属性）
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graph_meta: Mapped[Optional[Dict[str, Any]]] = mapped_column(
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JSON,
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nullable=True,
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comment="图结构扩展元数据",
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)
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# 图同步状态（pending / synced / failed）
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graph_sync_status: Mapped[str] = mapped_column(
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String(20),
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nullable=False,
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default="pending",
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comment="图同步状态：pending / synced / failed",
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)
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# AI 生成失败标记（Dify 不可用或置信度不足时置 True）
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source_failed: Mapped[bool] = mapped_column(
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Boolean,
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nullable=False,
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default=False,
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comment="AI 生成失败标记",
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)
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# 入队列时间
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queued_at: Mapped[Optional[datetime]] = mapped_column(
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DateTime(timezone=True),
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nullable=True,
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comment="入独立队列时间",
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)
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# 应用到 KB 的时间
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applied_at: Mapped[Optional[datetime]] = mapped_column(
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DateTime(timezone=True),
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nullable=True,
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comment="应用到 KB 的时间",
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)
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# 生成理由
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reason: Mapped[Optional[str]] = mapped_column(
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Text,
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nullable=True,
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comment="AI分析的理由",
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)
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# 拒绝理由
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reject_reason: Mapped[Optional[str]] = mapped_column(
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Text,
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nullable=True,
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comment="审核拒绝时填写",
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)
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# 审核人ID
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reviewer_id: Mapped[Optional[str]] = mapped_column(
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String(36),
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nullable=True,
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comment="审核人ID",
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)
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# 审核时间
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reviewed_at: Mapped[Optional[datetime]] = mapped_column(
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DateTime(timezone=True),
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nullable=True,
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comment="审核时间",
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)
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# 创建时间
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created_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True),
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nullable=False,
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default=datetime.now,
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comment="创建时间",
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)
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# 更新时间
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updated_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True),
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nullable=False,
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default=datetime.now,
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onupdate=datetime.now,
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comment="更新时间",
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)
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# --------------------------------------------------------------------------
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# 索引定义
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# --------------------------------------------------------------------------
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__table_args__ = (
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Index("idx_suggestion_status", "status"),
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Index("idx_suggestion_type", "suggestion_type"),
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Index("idx_suggestion_created", "created_at"),
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Index("idx_suggestion_audience", "audience"),
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Index("idx_suggestion_confidence", "confidence"),
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Index("idx_suggestion_graph_sync", "graph_sync_status"),
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)
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def __repr__(self) -> str:
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"""建议对象的字符串表示。"""
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return f"<KnowledgeSuggestion(id={self.id}, type={self.suggestion_type}, status={self.status})>"
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