feat(ai_chat): 添加Markdown渲染和图片生成功能

支持将AI回复的Markdown内容转换为HTML并渲染为美观的图片格式返回，提升聊天体验
```

```msg
feat(knowledge_base): 扩展知识库支持个人和群聊独立记忆

- 新增个人知识库功能，支持独立记忆
- 添加清除个人/群聊记忆命令
- 优化知识搜索逻辑，优先搜索个人记忆
- 更新插件帮助信息

plugins/ai_chat.py

@@ -4,9 +4,12 @@ AI 聊天插件，支持向量数据库记忆功能
 """
 import time
 import uuid
+import markdown
 from core.managers.command_manager import matcher
 from models.events.message import GroupMessageEvent, PrivateMessageEvent
+from models.message import MessageSegment
 from core.managers.vectordb_manager import vectordb_manager
+from core.managers.image_manager import image_manager
 from core.utils.logger import ModuleLogger
 from core.config_loader import global_config
 
@@ -113,7 +116,38 @@ async def chat_command(event: GroupMessageEvent | PrivateMessageEvent, args: lis
     user_message = " ".join(args)
     user_id = event.user_id
     group_id = getattr(event, 'group_id', 0)
+    user_name = event.sender.nickname or event.sender.card or str(user_id)
     
     await event.reply("正在思考中...")
     reply = await get_ai_response(user_id, group_id, user_message)
-    await event.reply(reply)
+    
+    # 将 Markdown 转换为 HTML
+    try:
+        # 启用扩展以支持代码块、表格等
+        html_reply = markdown.markdown(reply, extensions=['fenced_code', 'tables', 'nl2br'])
+    except Exception as e:
+        logger.error(f"Markdown 转换失败: {e}")
+        html_reply = reply.replace('\n', '<br>')
+    
+    # 渲染图片
+    try:
+        template_data = {
+            "user_name": user_name,
+            "user_message": user_message,
+            "ai_reply": html_reply
+        }
+        
+        base64_img = await image_manager.render_template_to_base64(
+            template_name="ai_chat.html",
+            data=template_data,
+            output_name=f"chat_{user_id}_{int(time.time())}.png",
+            image_type="png"
+        )
+        
+        if base64_img:
+            await event.reply(MessageSegment.image(f"base64://{base64_img}"))
+        else:
+            await event.reply("图片生成失败，返回文本：\n" + reply)
+    except Exception as e:
+        logger.error(f"渲染聊天图片失败: {e}")
+        await event.reply("图片生成失败，返回文本：\n" + reply)

plugins/knowledge_base.py

@@ -5,7 +5,7 @@
 import time
 import uuid
 from core.managers.command_manager import matcher
-from models.events.message import GroupMessageEvent
+from models.events.message import GroupMessageEvent, PrivateMessageEvent
 from core.managers.vectordb_manager import vectordb_manager
 from core.utils.logger import ModuleLogger
 from core.permission import Permission
@@ -13,24 +13,62 @@ from core.permission import Permission
 logger = ModuleLogger("GroupKnowledgeBase")
 
 __plugin_meta__ = {
-    "name": "群聊知识库",
-    "description": "基于向量数据库的群聊知识库，支持语义检索",
-    "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"
+    "name": "知识库",
+    "description": "基于向量数据库的知识库，支持个人和群聊独立记忆",
+    "usage": "/kb_add <问题> <答案> - 添加个人知识库\n/kb_add_group <问题> <答案> - 添加群聊知识库 (仅管理员)\n/kb_search <关键词> - 搜索知识库\n/kb_remove_person - 清除个人所有记忆\n/kb_remove_group - 清除群聊所有记忆 (仅管理员)"
 }
 
-@matcher.command("kb_add", permission=Permission.ADMIN)
-async def kb_add_command(event: GroupMessageEvent, args: list[str]):
-    """添加知识库条目"""
+@matcher.command("kb_add")
+async def kb_add_person_command(event: GroupMessageEvent | PrivateMessageEvent, args: list[str]):
+    """添加个人知识库条目"""
     if len(args) < 2:
         await event.reply("用法: /kb_add <问题> <答案>")
         return
         
+    question = args[0]
+    answer = " ".join(args[1:])
+    user_id = event.user_id
+    
+    try:
+        collection_name = f"knowledge_base_user_{user_id}"
+        doc_id = str(uuid.uuid4())
+        
+        text_to_embed = f"问题: {question}\n答案: {answer}"
+        metadata = {
+            "user_id": user_id,
+            "question": question,
+            "answer": answer,
+            "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"个人知识库条目添加成功！\n问题: {question}")
+        else:
+            await event.reply("个人知识库条目添加失败，请查看日志。")
+    except Exception as e:
+        logger.error(f"添加个人知识库失败: {e}")
+        await event.reply(f"添加失败: {str(e)}")
+
+@matcher.command("kb_add_group", permission=Permission.ADMIN)
+async def kb_add_group_command(event: GroupMessageEvent, args: list[str]):
+    """添加群聊知识库条目"""
+    if len(args) < 2:
+        await event.reply("用法: /kb_add_group <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}"
+        collection_name = f"knowledge_base_group_{group_id}"
         doc_id = str(uuid.uuid4())
         
         text_to_embed = f"问题: {question}\n答案: {answer}"
@@ -50,43 +88,109 @@ async def kb_add_command(event: GroupMessageEvent, args: list[str]):
         )
         
         if success:
-            await event.reply(f"知识库条目添加成功！\n问题: {question}")
+            await event.reply(f"群聊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。")
+            await event.reply("群聊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}")
+        logger.error(f"添加群聊知识库失败: {e}")
         await event.reply(f"添加失败: {str(e)}")
 
 @matcher.command("kb_search")
-async def kb_search_command(event: GroupMessageEvent, args: list[str]):
-    """搜索知识库条目"""
+async def kb_search_command(event: GroupMessageEvent | PrivateMessageEvent, args: list[str]):
+    """搜索知识库条目（优先搜索个人，再搜索群聊）"""
     if not args:
         await event.reply("用法: /kb_search <关键词>")
         return
         
     query = " ".join(args)
-    group_id = event.group_id
+    user_id = event.user_id
+    group_id = getattr(event, 'group_id', None)
     
     try:
-        collection_name = f"knowledge_base_{group_id}"
+        reply_msg = f"为您找到以下相关知识：\n"
+        found = False
         
-        results = vectordb_manager.query_texts(
-            collection_name=collection_name,
+        # 1. 搜索个人知识库
+        person_collection = f"knowledge_base_user_{user_id}"
+        person_results = vectordb_manager.query_texts(
+            collection_name=person_collection,
             query_texts=[query],
-            n_results=3
+            n_results=2
         )
         
-        if not results or not results.get("documents") or not results["documents"][0]:
+        if person_results and person_results.get("documents") and person_results["documents"][0]:
+            reply_msg += "\n【个人记忆】"
+            for i, metadata in enumerate(person_results["metadatas"][0], 1):
+                question = metadata.get("question", "")
+                answer = metadata.get("answer", "")
+                reply_msg += f"\n{i}. Q: {question}\n   A: {answer}"
+            found = True
+            
+        # 2. 搜索群聊知识库
+        if group_id:
+            group_collection = f"knowledge_base_group_{group_id}"
+            group_results = vectordb_manager.query_texts(
+                collection_name=group_collection,
+                query_texts=[query],
+                n_results=2
+            )
+            
+            if group_results and group_results.get("documents") and group_results["documents"][0]:
+                reply_msg += "\n\n【群聊记忆】"
+                for i, metadata in enumerate(group_results["metadatas"][0], 1):
+                    question = metadata.get("question", "")
+                    answer = metadata.get("answer", "")
+                    reply_msg += f"\n{i}. Q: {question}\n   A: {answer}"
+                found = True
+                
+        if not found:
             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)}")
+
+@matcher.command("kb_remove_person")
+async def kb_remove_person_command(event: GroupMessageEvent | PrivateMessageEvent):
+    """清除个人所有记忆"""
+    user_id = event.user_id
+    collection_name = f"knowledge_base_user_{user_id}"
+    
+    try:
+        # ChromaDB 不支持直接删除整个 collection 的所有数据，最简单的方法是删除 collection
+        if vectordb_manager._client:
+            try:
+                vectordb_manager._client.delete_collection(collection_name)
+                if collection_name in vectordb_manager._collections:
+                    del vectordb_manager._collections[collection_name]
+                await event.reply("已成功清除您的所有个人记忆。")
+            except ValueError:
+                await event.reply("您还没有任何个人记忆。")
+        else:
+            await event.reply("向量数据库未初始化。")
+    except Exception as e:
+        logger.error(f"清除个人记忆失败: {e}")
+        await event.reply(f"清除失败: {str(e)}")
+
+@matcher.command("kb_remove_group", permission=Permission.ADMIN)
+async def kb_remove_group_command(event: GroupMessageEvent):
+    """清除群聊所有记忆"""
+    group_id = event.group_id
+    collection_name = f"knowledge_base_group_{group_id}"
+    
+    try:
+        if vectordb_manager._client:
+            try:
+                vectordb_manager._client.delete_collection(collection_name)
+                if collection_name in vectordb_manager._collections:
+                    del vectordb_manager._collections[collection_name]
+                await event.reply("已成功清除本群的所有群聊记忆。")
+            except ValueError:
+                await event.reply("本群还没有任何群聊记忆。")
+        else:
+            await event.reply("向量数据库未初始化。")
+    except Exception as e:
+        logger.error(f"清除群聊记忆失败: {e}")
+        await event.reply(f"清除失败: {str(e)}")