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

adapters/router.py

@@ -356,7 +356,8 @@ class DiscordToOneBotConverter:
         
         # 注入 Discord 特定信息（用于跨平台插件识别）
         discord_channel_id = discord_message.channel.id if not isinstance(discord_message.channel, discord.DMChannel) else None
-        discord_username = discord_message.author.name
+        # 使用 global_name (显示名称/昵称) 如果存在，否则使用 name (用户名)
+        discord_username = getattr(discord_message.author, 'global_name', None) or discord_message.author.name
         discord_discriminator = f"#{discord_message.author.discriminator}" if discord_message.author.discriminator != "0" else ""
         
         if is_private:

core/managers/__init__.py

@@ -0,0 +1,60 @@
+"""
+管理器包
+
+这个包集中了机器人核心的单例管理器。
+通过从这里导入，可以确保在整个应用中访问到的都是同一个实例。
+"""
+from .command_manager import matcher as command_manager
+from .permission_manager import PermissionManager
+from .plugin_manager import PluginManager
+from .redis_manager import RedisManager
+from .mysql_manager import MySQLManager
+from .browser_manager import BrowserManager
+from .image_manager import ImageManager
+from .reverse_ws_manager import ReverseWSManager
+from .thread_manager import thread_manager
+from .vectordb_manager import vectordb_manager
+
+# --- 实例化所有单例管理器 ---
+
+# 权限管理器（包含了管理员管理功能）
+permission_manager = PermissionManager()
+
+# 命令与事件管理器 (别名 matcher)
+matcher = command_manager
+
+# 插件管理器
+plugin_manager = PluginManager(command_manager)
+# plugin_manager.load_all_plugins()
+
+# Redis 管理器
+redis_manager = RedisManager()
+
+# MySQL 管理器
+mysql_manager = MySQLManager()
+
+# 浏览器管理器
+browser_manager = BrowserManager()
+
+# 图片管理器
+image_manager = ImageManager()
+
+# 反向 WebSocket 管理器
+reverse_ws_manager = ReverseWSManager()
+
+# 线程管理器
+thread_manager.start()
+
+__all__ = [
+    "permission_manager",
+    "command_manager",
+    "matcher",
+    "plugin_manager",
+    "redis_manager",
+    "mysql_manager",
+    "browser_manager",
+    "image_manager",
+    "reverse_ws_manager",
+    "thread_manager",
+    "vectordb_manager",
+]

plugins/ai_chat.py

@@ -0,0 +1,113 @@
+# -*- coding: utf-8 -*-
+"""
+AI 聊天插件，支持向量数据库记忆功能
+"""
+import time
+import uuid
+from core.managers.command_manager import matcher
+from models.events.message import GroupMessageEvent, PrivateMessageEvent
+from core.managers.vectordb_manager import vectordb_manager
+from core.utils.logger import ModuleLogger
+from core.config_loader import global_config
+
+logger = ModuleLogger("AIChat")
+
+# 尝试导入 OpenAI 客户端
+try:
+    from openai import AsyncOpenAI
+    OPENAI_AVAILABLE = True
+except ImportError:
+    OPENAI_AVAILABLE = False
+
+async def get_ai_response(user_id: int, group_id: int, user_message: str) -> str:
+    """获取 AI 回复，包含向量数据库记忆"""
+    if not OPENAI_AVAILABLE:
+        return "请先安装 openai 库: pip install openai"
+        
+    # 从配置中获取 DeepSeek API 配置（复用跨平台插件的配置或全局配置）
+    api_key = getattr(global_config.cross_platform, 'deepseek_api_key', None) or "your-api-key"
+    api_url = getattr(global_config.cross_platform, 'deepseek_api_url', "https://api.deepseek.com/v1")
+    model = getattr(global_config.cross_platform, 'deepseek_model', "deepseek-chat")
+    
+    if api_key == "your-api-key":
+        return "请先在配置中设置 DeepSeek API Key"
+        
+    # 1. 从向量数据库检索相关记忆
+    collection_name = f"chat_memory_{user_id}"
+    memory_context = ""
+    
+    try:
+        results = vectordb_manager.query_texts(
+            collection_name=collection_name,
+            query_texts=[user_message],
+            n_results=3
+        )
+        
+        if results and results.get("documents") and results["documents"][0]:
+            memory_context = "\n\n相关历史记忆：\n"
+            for i, doc in enumerate(results["documents"][0], 1):
+                memory_context += f"{i}. {doc}\n"
+    except Exception as e:
+        logger.error(f"检索聊天记忆失败: {e}")
+        
+    # 2. 构建 Prompt
+    system_prompt = f"""你是一个友好的 AI 助手。请根据用户的输入进行回复。
+如果提供了相关历史记忆，请参考这些记忆来保持对话的连贯性。{memory_context}"""
+
+    try:
+        client = AsyncOpenAI(
+            api_key=api_key,
+            base_url=api_url.replace("/chat/completions", "")
+        )
+        
+        response = await client.chat.completions.create(
+            model=model,
+            messages=[
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": user_message}
+            ],
+            temperature=0.7,
+            max_tokens=1000
+        )
+        
+        ai_reply = response.choices[0].message.content
+        
+        # 3. 将本次对话存入向量数据库
+        if ai_reply:
+            try:
+                doc_id = str(uuid.uuid4())
+                text_to_embed = f"用户: {user_message}\nAI: {ai_reply}"
+                metadata = {
+                    "user_id": user_id,
+                    "group_id": group_id,
+                    "timestamp": int(time.time())
+                }
+                
+                vectordb_manager.add_texts(
+                    collection_name=collection_name,
+                    texts=[text_to_embed],
+                    metadatas=[metadata],
+                    ids=[doc_id]
+                )
+            except Exception as e:
+                logger.error(f"保存聊天记忆失败: {e}")
+                
+        return ai_reply
+    except Exception as e:
+        logger.error(f"AI 聊天请求失败: {e}")
+        return f"请求失败: {str(e)}"
+
+@matcher.command("chat", "聊天")
+async def chat_command(event: GroupMessageEvent | PrivateMessageEvent, args: list[str]):
+    """AI 聊天命令"""
+    if not args:
+        await event.reply("请提供要聊天的内容，例如：/chat 你好")
+        return
+        
+    user_message = " ".join(args)
+    user_id = event.user_id
+    group_id = getattr(event, 'group_id', 0)
+    
+    await event.reply("正在思考中...")
+    reply = await get_ai_response(user_id, group_id, user_message)
+    await event.reply(reply)

plugins/discord-cross/handlers.py

@@ -148,7 +148,7 @@ async def handle_qq_group_message(event: GroupMessageEvent):
             group_name = f"群{group_id}"
         
         await handle_qq_message(
-            nickname=event.sender.nickname or event.sender.card or str(event.user_id),
+            nickname=event.sender.card or event.sender.nickname or str(event.user_id),
             user_id=event.user_id,
             group_name=group_name,
             group_id=group_id,

src/neobot/adapters/discord_adapter.py

@@ -112,7 +112,8 @@ class DiscordAdapter(discord.Client if DISCORD_AVAILABLE else object):
                     try:
                         data = json.loads(message["data"])
                         if data.get("type") == "send_message":
-                            await self.handle_send_message(data)
+                            # 使用 asyncio.create_task 异步处理消息，避免阻塞订阅循环
+                            asyncio.create_task(self.handle_send_message(data))
                     except json.JSONDecodeError as e:
                         self.logger.error(f"[DiscordAdapter] 解析 Redis 消息失败: {e}")
                     except Exception as e: