K2Cr2O1
fbeceb4dc9
- 为 AI 聊天和知识库插件添加元信息配置 - 简化插件命令配置，移除冗余别名 - 更新 Discord 适配器的 Redis 频道名称 - 增强向量数据库管理器的日志信息
93 lines
3.1 KiB
Python
93 lines
3.1 KiB
Python
# -*- coding: utf-8 -*-
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"""
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群聊知识库插件，支持向量数据库检索
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"""
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import time
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import uuid
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from core.managers.command_manager import matcher
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from models.events.message import GroupMessageEvent
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from core.managers.vectordb_manager import vectordb_manager
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from core.utils.logger import ModuleLogger
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from core.permission import Permission
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logger = ModuleLogger("GroupKnowledgeBase")
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__plugin_meta__ = {
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"name": "群聊知识库",
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"description": "基于向量数据库的群聊知识库，支持语义检索",
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"usage": "/kb_add <问题> <答案> - 添加知识库条目 (仅管理员)\n/kb_search <关键词> - 搜索知识库"
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}
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@matcher.command("kb_add", permission=Permission.ADMIN)
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async def kb_add_command(event: GroupMessageEvent, args: list[str]):
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"""添加知识库条目"""
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if len(args) < 2:
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await event.reply("用法: /kb_add <问题> <答案>")
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return
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question = args[0]
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answer = " ".join(args[1:])
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group_id = event.group_id
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try:
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collection_name = f"knowledge_base_{group_id}"
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doc_id = str(uuid.uuid4())
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text_to_embed = f"问题: {question}\n答案: {answer}"
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metadata = {
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"group_id": group_id,
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"question": question,
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"answer": answer,
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"added_by": event.user_id,
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"timestamp": int(time.time())
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}
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success = vectordb_manager.add_texts(
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collection_name=collection_name,
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texts=[text_to_embed],
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metadatas=[metadata],
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ids=[doc_id]
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)
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if success:
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await event.reply(f"知识库条目添加成功！\n问题: {question}")
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else:
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await event.reply("知识库条目添加失败，请查看日志。")
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except Exception as e:
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logger.error(f"添加知识库失败: {e}")
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await event.reply(f"添加失败: {str(e)}")
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@matcher.command("kb_search")
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async def kb_search_command(event: GroupMessageEvent, args: list[str]):
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"""搜索知识库条目"""
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if not args:
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await event.reply("用法: /kb_search <关键词>")
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return
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query = " ".join(args)
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group_id = event.group_id
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try:
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collection_name = f"knowledge_base_{group_id}"
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results = vectordb_manager.query_texts(
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collection_name=collection_name,
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query_texts=[query],
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n_results=3
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)
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if not results or not results.get("documents") or not results["documents"][0]:
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await event.reply("未找到相关的知识库条目。")
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return
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reply_msg = f"为您找到以下相关知识：\n"
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for i, metadata in enumerate(results["metadatas"][0], 1):
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question = metadata.get("question", "")
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answer = metadata.get("answer", "")
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reply_msg += f"\n{i}. Q: {question}\n A: {answer}"
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await event.reply(reply_msg)
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except Exception as e:
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logger.error(f"搜索知识库失败: {e}")
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await event.reply(f"搜索失败: {str(e)}")
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