feat(vectordb): 添加向量数据库支持及集成功能

新增向量数据库管理器模块，支持文本的存储、检索和相似度查询添加知识库插件和AI聊天插件，利用向量数据库实现记忆功能优化跨平台翻译模块，集成向量数据库存储历史翻译记录改进消息处理逻辑，优先使用用户显示名称
2026-03-24 14:32:36 +08:00
parent 23eabf6bde
commit d6623e2cc8
10 changed files with 415 additions and 6 deletions
--- a/plugins/knowledge_base.py
+++ b/plugins/knowledge_base.py
@@ -0,0 +1,86 @@
+# -*- coding: utf-8 -*-
+"""
+群聊知识库插件，支持向量数据库检索
+"""
+import time
+import uuid
+from core.managers.command_manager import matcher
+from models.events.message import GroupMessageEvent
+from core.managers.vectordb_manager import vectordb_manager
+from core.utils.logger import ModuleLogger
+from core.permission import Permission
+
+logger = ModuleLogger("GroupKnowledgeBase")
+
+@matcher.command("kb_add", "添加知识库", permission=Permission.ADMIN)
+async def kb_add_command(event: GroupMessageEvent, args: list[str]):
+    """添加知识库条目"""
+    if len(args) < 2:
+        await event.reply("用法: /kb_add <问题> <答案>")
+        return
+        
+    question = args[0]
+    answer = " ".join(args[1:])
+    group_id = event.group_id
+    
+    try:
+        collection_name = f"knowledge_base_{group_id}"
+        doc_id = str(uuid.uuid4())
+        
+        text_to_embed = f"问题: {question}\n答案: {answer}"
+        metadata = {
+            "group_id": group_id,
+            "question": question,
+            "answer": answer,
+            "added_by": event.user_id,
+            "timestamp": int(time.time())
+        }
+        
+        success = vectordb_manager.add_texts(
+            collection_name=collection_name,
+            texts=[text_to_embed],
+            metadatas=[metadata],
+            ids=[doc_id]
+        )
+        
+        if success:
+            await event.reply(f"知识库条目添加成功！\n问题: {question}")
+        else:
+            await event.reply("知识库条目添加失败，请查看日志。")
+    except Exception as e:
+        logger.error(f"添加知识库失败: {e}")
+        await event.reply(f"添加失败: {str(e)}")
+
+@matcher.command("kb_search", "搜索知识库")
+async def kb_search_command(event: GroupMessageEvent, args: list[str]):
+    """搜索知识库条目"""
+    if not args:
+        await event.reply("用法: /kb_search <关键词>")
+        return
+        
+    query = " ".join(args)
+    group_id = event.group_id
+    
+    try:
+        collection_name = f"knowledge_base_{group_id}"
+        
+        results = vectordb_manager.query_texts(
+            collection_name=collection_name,
+            query_texts=[query],
+            n_results=3
+        )
+        
+        if not results or not results.get("documents") or not results["documents"][0]:
+            await event.reply("未找到相关的知识库条目。")
+            return
+            
+        reply_msg = f"为您找到以下相关知识：\n"
+        for i, metadata in enumerate(results["metadatas"][0], 1):
+            question = metadata.get("question", "")
+            answer = metadata.get("answer", "")
+            reply_msg += f"\n{i}. Q: {question}\n   A: {answer}"
+            
+        await event.reply(reply_msg)
+    except Exception as e:
+        logger.error(f"搜索知识库失败: {e}")
+        await event.reply(f"搜索失败: {str(e)}")