1. 新增 resolve_tenant_by_chat_id() 根据飞书群 chat_id 查找绑定的租户 2. 新增 get_tenant_feishu_config() 获取租户级飞书凭证 3. FeishuService 支持传入自定义 app_id/app_secret(租户级别) 4. feishu_bot.py 收到消息时自动解析租户,使用租户凭证回复 5. feishu_longconn_service.py 同样按 chat_id 解析租户并传递 tenant_id 6. 租户管理 UI 新增飞书配置字段:App ID、App Secret、绑定群 Chat ID 7. 租户列表展示飞书绑定状态和群数量 8. 保存租户时同步更新飞书配置到 config JSON
90 lines
2.8 KiB
Python
90 lines
2.8 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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知识库体检脚本
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对 KnowledgeEntry 做简单统计,供 kb-audit Skill 调用。
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"""
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import sys
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from datetime import datetime, timedelta
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from pathlib import Path
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def add_project_root_to_path():
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# 假定脚本位于 .claude/skills/kb-audit/scripts/ 下
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script_path = Path(__file__).resolve()
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project_root = script_path.parents[4]
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if str(project_root) not in sys.path:
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sys.path.insert(0, str(project_root))
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def main():
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add_project_root_to_path()
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from src.core.database import db_manager
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from src.core.models import KnowledgeEntry
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print("=== 知识库健康检查 ===\n")
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with db_manager.get_session() as session:
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total = session.query(KnowledgeEntry).count()
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print(f"知识条目总数: {total}")
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# 低置信度(<0.7)
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low_conf = (
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session.query(KnowledgeEntry)
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.filter(KnowledgeEntry.confidence_score.isnot(None))
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.filter(KnowledgeEntry.confidence_score < 0.7)
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.count()
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)
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print(f"低置信度条目数 (confidence_score < 0.7): {low_conf}")
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# 使用次数极低(usage_count < 3 或为 NULL)
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low_usage = (
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session.query(KnowledgeEntry)
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.filter(
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(KnowledgeEntry.usage_count.is_(None))
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| (KnowledgeEntry.usage_count < 3)
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)
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.count()
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)
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print(f"使用次数极低条目数 (usage_count < 3 或空): {low_usage}")
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# 长期未更新(> 90 天)
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cutoff = datetime.now() - timedelta(days=90)
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old_entries = (
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session.query(KnowledgeEntry)
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.filter(
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(KnowledgeEntry.updated_at.isnot(None))
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& (KnowledgeEntry.updated_at < cutoff)
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)
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.count()
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)
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print(f"长期未更新条目数 (updated_at > 90 天未更新): {old_entries}")
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print("\n示例问题条目(不含完整答案,仅展示前若干个):")
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sample_entries = (
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session.query(KnowledgeEntry)
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.order_by(KnowledgeEntry.created_at.desc())
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.limit(5)
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.all()
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)
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for e in sample_entries:
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q_preview = (e.question or "")[:40]
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print(
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f" ID={e.id}, category={e.category}, "
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f"confidence={e.confidence_score}, usage={e.usage_count}, "
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f"Q='{q_preview}...'"
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)
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print("\n提示:")
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print(" - 建议优先审查低置信度且 usage_count 较高的条目;")
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print(" - 对长期未更新且 usage_count 较高的条目,可考虑人工复查内容是否过时;")
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print(" - 对 usage_count 极低且从未触发的条目,可考虑合并或归档。")
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if __name__ == "__main__":
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main()
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