remove：移除了冗余代码

src/chat/replyer/default_generator.py

@@ -354,9 +354,18 @@ class DefaultReplyer:
         # 动态构建expression habits块
         expression_habits_block = ""
         if style_habits_str.strip():
-            expression_habits_block += f"你可以参考以下的语言习惯，如果情景合适就使用，不要盲目使用,不要生硬使用，而是结合到表达中：\n{style_habits_str}\n\n"
+            expression_habits_title = "你可以参考以下的语言习惯，当情景合适就使用，但不要生硬使用，以合理的方式结合到你的回复中："
+            expression_habits_block += f"{style_habits_str}\n"
         if grammar_habits_str.strip():
-            expression_habits_block += f"请你根据情景使用以下句法：\n{grammar_habits_str}\n"
+            expression_habits_title = "你可以选择下面的句法进行回复，如果情景合适就使用，不要盲目使用,不要生硬使用，以合理的方式使用："
+            expression_habits_block += f"{grammar_habits_str}\n"
+            
+        if style_habits_str.strip() and grammar_habits_str.strip():
+            expression_habits_title = "你可以参考以下的语言习惯和句法，如果情景合适就使用，不要盲目使用,不要生硬使用，以合理的方式结合到你的回复中："
+            
+        expression_habits_block = f"{expression_habits_title}\n{expression_habits_block}"
+            
+            
 
         return expression_habits_block
 
@@ -428,6 +437,7 @@ class DefaultReplyer:
 
                 tool_info_str += "以上是你获取到的实时信息，请在回复时参考这些信息。"
                 logger.info(f"获取到 {len(tool_results)} 个工具结果")
+                
                 return tool_info_str
             else:
                 logger.debug(f"未获取到任何工具结果")
@@ -505,7 +515,9 @@ class DefaultReplyer:
         for msg_dict in message_list_before_now:
             try:
                 msg_user_id = str(msg_dict.get("user_id"))
-                if msg_user_id == bot_id or msg_user_id == target_user_id:
+                reply_to = msg_dict.get("reply_to", "")
+                _platform, reply_to_user_id = self._parse_reply_target(reply_to)
+                if (msg_user_id == bot_id and reply_to_user_id == target_user_id) or msg_user_id == target_user_id:
                     # bot 和目标用户的对话
                     core_dialogue_list.append(msg_dict)
                 else:
@@ -517,7 +529,7 @@ class DefaultReplyer:
         # 构建背景对话 prompt
         background_dialogue_prompt = ""
         if background_dialogue_list:
-            latest_25_msgs = background_dialogue_list[-int(global_config.chat.max_context_size * 0.6) :]
+            latest_25_msgs = background_dialogue_list[-int(global_config.chat.max_context_size * 0.5) :]
             background_dialogue_prompt_str = build_readable_messages(
                 latest_25_msgs,
                 replace_bot_name=True,
@@ -544,6 +556,34 @@ class DefaultReplyer:
 
         return core_dialogue_prompt, background_dialogue_prompt
 
+    def build_mai_think_context(
+        self,
+        chat_id: str,
+        memory_block: str,
+        relation_info: str,
+        time_block: str,
+        chat_target_1: str,
+        chat_target_2: str,
+        mood_prompt: str,
+        identity_block: str,
+        sender: str,
+        target: str,
+        chat_info: str,
+    ):
+        """构建 mai_think 上下文信息"""
+        mai_think = mai_thinking_manager.get_mai_think(chat_id)
+        mai_think.memory_block = memory_block
+        mai_think.relation_info_block = relation_info
+        mai_think.time_block = time_block
+        mai_think.chat_target = chat_target_1
+        mai_think.chat_target_2 = chat_target_2
+        mai_think.chat_info = chat_info
+        mai_think.mood_state = mood_prompt
+        mai_think.identity = identity_block
+        mai_think.sender = sender
+        mai_think.target = target
+        return mai_think
+
     async def build_prompt_reply_context(
         self,
         reply_data: Dict[str, Any],
@@ -623,7 +663,7 @@ class DefaultReplyer:
             show_actions=True,
         )
 
-        # 并行执行四个构建任务
+        # 并行执行五个构建任务
         task_results = await asyncio.gather(
             self._time_and_run_task(
                 self.build_expression_habits(chat_talking_prompt_short, target), "expression_habits"
@@ -635,6 +675,9 @@ class DefaultReplyer:
             self._time_and_run_task(
                 self.build_tool_info(chat_talking_prompt_short, reply_data, enable_tool=enable_tool), "tool_info"
             ),
+            self._time_and_run_task(
+                get_prompt_info(target, threshold=0.38), "prompt_info"
+            ),
         )
 
         # 任务名称中英文映射
@@ -642,7 +685,8 @@ class DefaultReplyer:
             "expression_habits": "选取表达方式",
             "relation_info": "感受关系", 
             "memory_block": "回忆",
-            "tool_info": "使用工具"
+            "tool_info": "使用工具",
+            "prompt_info": "获取知识"
         }
 
         # 处理结果
@@ -660,16 +704,10 @@ class DefaultReplyer:
         relation_info = results_dict["relation_info"]
         memory_block = results_dict["memory_block"]
         tool_info = results_dict["tool_info"]
+        prompt_info = results_dict["prompt_info"]  # 直接使用格式化后的结果
 
         keywords_reaction_prompt = await self.build_keywords_reaction_prompt(target)
 
-        if tool_info:
-            tool_info_block = (
-                f"以下是你了解的额外信息信息，现在请你阅读以下内容，进行决策\n{tool_info}\n以上是一些额外的信息。"
-            )
-        else:
-            tool_info_block = ""
-
         if extra_info_block:
             extra_info_block = f"以下是你在回复时需要参考的信息，现在请你阅读以下内容，进行决策\n{extra_info_block}\n以上是你在回复时需要参考的信息，现在请你阅读以下内容，进行决策"
         else:
@@ -703,10 +741,6 @@ class DefaultReplyer:
         else:
             reply_target_block = ""
 
-        prompt_info = await get_prompt_info(target, threshold=0.38)
-        if prompt_info:
-            prompt_info = await global_prompt_manager.format_prompt("knowledge_prompt", prompt_info=prompt_info)
-
         template_name = "default_generator_prompt"
         if is_group_chat:
             chat_target_1 = await global_prompt_manager.get_prompt_async("chat_target_group1")
@@ -746,24 +780,24 @@ class DefaultReplyer:
                 message_list_before_now_long, target_user_id
             )
             
-            mai_think = mai_thinking_manager.get_mai_think(chat_id)
-            mai_think.memory_block = memory_block
-            mai_think.relation_info_block = relation_info
-            mai_think.time_block = time_block
-            mai_think.chat_target = chat_target_1
-            mai_think.chat_target_2 = chat_target_2
-            # mai_think.chat_info = chat_talking_prompt
-            mai_think.mood_state = mood_prompt
-            mai_think.identity = identity_block
-            mai_think.sender = sender
-            mai_think.target = target
-            
-            mai_think.chat_info = f"""
+            self.build_mai_think_context(
+                chat_id=chat_id,
+                memory_block=memory_block,
+                relation_info=relation_info,
+                time_block=time_block,
+                chat_target_1=chat_target_1,
+                chat_target_2=chat_target_2,
+                mood_prompt=mood_prompt,
+                identity_block=identity_block,
+                sender=sender,
+                target=target,
+                chat_info=f"""
 {background_dialogue_prompt}
 --------------------------------
 {time_block}
 这是你和{sender}的对话，你们正在交流中：
 {core_dialogue_prompt}"""
+            )
             
 
             # 使用 s4u 风格的模板
@@ -772,7 +806,7 @@ class DefaultReplyer:
             return await global_prompt_manager.format_prompt(
                 template_name,
                 expression_habits_block=expression_habits_block,
-                tool_info_block=tool_info_block,
+                tool_info_block=tool_info,
                 knowledge_prompt=prompt_info,
                 memory_block=memory_block,
                 relation_info_block=relation_info,
@@ -791,17 +825,19 @@ class DefaultReplyer:
                 moderation_prompt=moderation_prompt_block,
             )
         else:
-            mai_think = mai_thinking_manager.get_mai_think(chat_id)
-            mai_think.memory_block = memory_block
-            mai_think.relation_info_block = relation_info
-            mai_think.time_block = time_block
-            mai_think.chat_target = chat_target_1
-            mai_think.chat_target_2 = chat_target_2
-            mai_think.chat_info = chat_talking_prompt
-            mai_think.mood_state = mood_prompt
-            mai_think.identity = identity_block
-            mai_think.sender = sender
-            mai_think.target = target
+            self.build_mai_think_context(
+                chat_id=chat_id,
+                memory_block=memory_block,
+                relation_info=relation_info,
+                time_block=time_block,
+                chat_target_1=chat_target_1,
+                chat_target_2=chat_target_2,
+                mood_prompt=mood_prompt,
+                identity_block=identity_block,
+                sender=sender,
+                target=target,
+                chat_info=chat_talking_prompt
+            )
             
             # 使用原有的模式
             return await global_prompt_manager.format_prompt(
@@ -810,7 +846,7 @@ class DefaultReplyer:
                 chat_target=chat_target_1,
                 chat_info=chat_talking_prompt,
                 memory_block=memory_block,
-                tool_info_block=tool_info_block,
+                tool_info_block=tool_info,
                 knowledge_prompt=prompt_info,
                 extra_info_block=extra_info_block,
                 relation_info_block=relation_info,
@@ -1016,7 +1052,10 @@ async def get_prompt_info(message: str, threshold: float):
             related_info += found_knowledge_from_lpmm
             logger.debug(f"获取知识库内容耗时: {(end_time - start_time):.3f}秒")
             logger.debug(f"获取知识库内容，相关信息：{related_info[:100]}...，信息长度: {len(related_info)}")
-            return related_info
+            
+            # 格式化知识信息
+            formatted_prompt_info = await global_prompt_manager.format_prompt("knowledge_prompt", prompt_info=related_info)
+            return formatted_prompt_info
         else:
             logger.debug("从LPMM知识库获取知识失败，可能是从未导入过知识，返回空知识...")
             return ""

src/config/official_configs.py

@@ -17,6 +17,9 @@ from src.config.config_base import ConfigBase
 @dataclass
 class BotConfig(ConfigBase):
     """QQ机器人配置类"""
+    
+    platform: str
+    """平台"""
 
     qq_account: str
     """QQ账号"""

src/individuality/individuality.py

@@ -2,6 +2,7 @@ import ast
 import json
 import os
 import hashlib
+import time
 
 from src.common.logger import get_logger
 from src.config.config import global_config
@@ -9,8 +10,6 @@ from src.llm_models.utils_model import LLMRequest
 from src.person_info.person_info import get_person_info_manager
 from rich.traceback import install
 
-from .personality import Personality
-
 install(extra_lines=3)
 
 logger = get_logger("individuality")
@@ -20,12 +19,10 @@ class Individuality:
     """个体特征管理类"""
 
     def __init__(self):
-        # 正常初始化实例属性
-        self.personality: Personality = None  # type: ignore
-
         self.name = ""
         self.bot_person_id = ""
         self.meta_info_file_path = "data/personality/meta.json"
+        self.personality_data_file_path = "data/personality/personality_data.json"
 
         self.model = LLMRequest(
             model=global_config.model.utils,
@@ -33,14 +30,7 @@ class Individuality:
         )
 
     async def initialize(self) -> None:
-        """初始化个体特征
-
-        Args:
-            bot_nickname: 机器人昵称
-            personality_core: 人格核心特点
-            personality_side: 人格侧面描述
-            identity: 身份细节描述
-        """
+        """初始化个体特征"""
         bot_nickname = global_config.bot.nickname
         personality_core = global_config.personality.personality_core
         personality_side = global_config.personality.personality_side
@@ -56,124 +46,58 @@ class Individuality:
             bot_nickname, personality_core, personality_side, identity
         )
 
-        # 初始化人格（现在包含身份）
-        self.personality = Personality.initialize(
-            bot_nickname=bot_nickname,
-            personality_core=personality_core,
-            personality_side=personality_side,
-            identity=identity,
-            compress_personality=global_config.personality.compress_personality,
-            compress_identity=global_config.personality.compress_identity,
-        )
+        logger.info("正在构建人设信息")
 
-        logger.info("正在将所有人设写入impression")
-        # 将所有人设写入impression
-        impression_parts = []
-        if personality_core:
-            impression_parts.append(f"核心人格: {personality_core}")
-        if personality_side:
-            impression_parts.append(f"人格侧面: {personality_side}")
-        if identity:
-            impression_parts.append(f"身份: {identity}")
-        logger.info(f"impression_parts: {impression_parts}")
+        # 如果配置有变化，重新生成压缩版本
+        if personality_changed or identity_changed:
+            logger.info("检测到配置变化，重新生成压缩版本")
+            personality_result = await self._create_personality(personality_core, personality_side)
+            identity_result = await self._create_identity(identity)
+        else:
+            logger.info("配置未变化，使用缓存版本")
+            # 从文件中获取已有的结果
+            personality_result, identity_result = self._get_personality_from_file()
+            if not personality_result or not identity_result:
+                logger.info("未找到有效缓存，重新生成")
+                personality_result = await self._create_personality(personality_core, personality_side)
+                identity_result = await self._create_identity(identity)
 
-        impression_text = "。".join(impression_parts)
-        if impression_text:
-            impression_text += "。"
+        # 保存到文件
+        if personality_result and identity_result:
+            self._save_personality_to_file(personality_result, identity_result)
+            logger.info("已将人设构建并保存到文件")
+        else:
+            logger.error("人设构建失败")
 
-        if impression_text:
+        # 如果任何一个发生变化，都需要清空数据库中的info_list（因为这影响整体人设）
+        if personality_changed or identity_changed:
+            logger.info("将清空数据库中原有的关键词缓存")
             update_data = {
                 "platform": "system",
                 "user_id": "bot_id",
                 "person_name": self.name,
                 "nickname": self.name,
             }
-
-            await person_info_manager.update_one_field(
-                self.bot_person_id, "impression", impression_text, data=update_data
-            )
-            logger.debug("已将完整人设更新到bot的impression中")
-
-        # 根据变化情况决定是否重新创建
-        personality_result = None
-        identity_result = None
-
-        if personality_changed:
-            logger.info("检测到人格配置变化，重新生成压缩版本")
-            personality_result = await self._create_personality(personality_core, personality_side)
-        else:
-            logger.info("人格配置未变化，使用缓存版本")
-            # 从缓存中获取已有的personality结果
-            existing_short_impression = await person_info_manager.get_value(self.bot_person_id, "short_impression")
-            if existing_short_impression:
-                try:
-                    existing_data = ast.literal_eval(existing_short_impression)  # type: ignore
-                    if isinstance(existing_data, list) and len(existing_data) >= 1:
-                        personality_result = existing_data[0]
-                except (json.JSONDecodeError, TypeError, IndexError):
-                    logger.warning("无法解析现有的short_impression，将重新生成人格部分")
-                    personality_result = await self._create_personality(personality_core, personality_side)
-            else:
-                logger.info("未找到现有的人格缓存，重新生成")
-                personality_result = await self._create_personality(personality_core, personality_side)
-
-        if identity_changed:
-            logger.info("检测到身份配置变化，重新生成压缩版本")
-            identity_result = await self._create_identity(identity)
-        else:
-            logger.info("身份配置未变化，使用缓存版本")
-            # 从缓存中获取已有的identity结果
-            existing_short_impression = await person_info_manager.get_value(self.bot_person_id, "short_impression")
-            if existing_short_impression:
-                try:
-                    existing_data = ast.literal_eval(existing_short_impression)  # type: ignore
-                    if isinstance(existing_data, list) and len(existing_data) >= 2:
-                        identity_result = existing_data[1]
-                except (json.JSONDecodeError, TypeError, IndexError):
-                    logger.warning("无法解析现有的short_impression，将重新生成身份部分")
-                    identity_result = await self._create_identity(identity)
-            else:
-                logger.info("未找到现有的身份缓存，重新生成")
-                identity_result = await self._create_identity(identity)
-
-        result = [personality_result, identity_result]
-
-        # 更新short_impression字段
-        if personality_result and identity_result:
-            person_info_manager = get_person_info_manager()
-            await person_info_manager.update_one_field(self.bot_person_id, "short_impression", result)
-            logger.info("已将人设构建")
-        else:
-            logger.error("人设构建失败")
+            await person_info_manager.update_one_field(self.bot_person_id, "info_list", [], data=update_data)
 
     async def get_personality_block(self) -> str:
-        person_info_manager = get_person_info_manager()
-        bot_person_id = person_info_manager.get_person_id("system", "bot_id")
-
         bot_name = global_config.bot.nickname
         if global_config.bot.alias_names:
             bot_nickname = f",也有人叫你{','.join(global_config.bot.alias_names)}"
         else:
             bot_nickname = ""
-        short_impression = await person_info_manager.get_value(bot_person_id, "short_impression")
-        # 解析字符串形式的Python列表
-        try:
-            if isinstance(short_impression, str) and short_impression.strip():
-                short_impression = ast.literal_eval(short_impression)
-            elif not short_impression:
-                logger.warning("short_impression为空，使用默认值")
-                short_impression = ["友好活泼", "人类"]
-        except (ValueError, SyntaxError) as e:
-            logger.error(f"解析short_impression失败: {e}, 原始值: {short_impression}")
-            short_impression = ["友好活泼", "人类"]
+        
+        # 从文件获取 short_impression
+        personality, identity = self._get_personality_from_file()
+        
         # 确保short_impression是列表格式且有足够的元素
-        if not isinstance(short_impression, list) or len(short_impression) < 2:
-            logger.warning(f"short_impression格式不正确: {short_impression}, 使用默认值")
-            short_impression = ["友好活泼", "人类"]
-        personality = short_impression[0]
-        identity = short_impression[1]
-        prompt_personality = f"{personality}，{identity}"
-        return f"你的名字是{bot_name}{bot_nickname}，你{prompt_personality}："
+        if not personality or not identity:
+            logger.warning(f"personality或identity为空: {personality}, {identity}, 使用默认值")
+            personality = "友好活泼"
+            identity = "人类"
+        
+        prompt_personality = f"{personality}\n{identity}"
+        return f"你的名字是{bot_name}{bot_nickname}，你{prompt_personality}"
 
     def _get_config_hash(
         self, bot_nickname: str, personality_core: str, personality_side: str, identity: str
@@ -188,7 +112,7 @@ class Individuality:
             "nickname": bot_nickname,
             "personality_core": personality_core,
             "personality_side": personality_side,
-            "compress_personality": self.personality.compress_personality if self.personality else True,
+            "compress_personality": global_config.personality.compress_personality,
         }
         personality_str = json.dumps(personality_config, sort_keys=True)
         personality_hash = hashlib.md5(personality_str.encode("utf-8")).hexdigest()
@@ -196,7 +120,7 @@ class Individuality:
         # 身份配置哈希
         identity_config = {
             "identity": identity,
-            "compress_identity": self.personality.compress_identity if self.personality else True,
+            "compress_identity": global_config.personality.compress_identity,
         }
         identity_str = json.dumps(identity_config, sort_keys=True)
         identity_hash = hashlib.md5(identity_str.encode("utf-8")).hexdigest()
@@ -269,6 +193,53 @@ class Individuality:
         except IOError as e:
             logger.error(f"保存meta_info文件失败: {e}")
 
+    def _load_personality_data(self) -> dict:
+        """从JSON文件中加载personality数据"""
+        if os.path.exists(self.personality_data_file_path):
+            try:
+                with open(self.personality_data_file_path, "r", encoding="utf-8") as f:
+                    return json.load(f)
+            except (json.JSONDecodeError, IOError) as e:
+                logger.error(f"读取personality_data文件失败: {e}, 将创建新文件。")
+                return {}
+        return {}
+
+    def _save_personality_data(self, personality_data: dict):
+        """将personality数据保存到JSON文件"""
+        try:
+            os.makedirs(os.path.dirname(self.personality_data_file_path), exist_ok=True)
+            with open(self.personality_data_file_path, "w", encoding="utf-8") as f:
+                json.dump(personality_data, f, ensure_ascii=False, indent=2)
+            logger.debug(f"已保存personality数据到文件: {self.personality_data_file_path}")
+        except IOError as e:
+            logger.error(f"保存personality_data文件失败: {e}")
+
+    def _get_personality_from_file(self) -> tuple[str, str]:
+        """从文件获取personality数据
+        
+        Returns:
+            tuple: (personality, identity)
+        """
+        personality_data = self._load_personality_data()
+        personality = personality_data.get("personality", "友好活泼")
+        identity = personality_data.get("identity", "人类")
+        return personality, identity
+
+    def _save_personality_to_file(self, personality: str, identity: str):
+        """保存personality数据到文件
+        
+        Args:
+            personality: 压缩后的人格描述
+            identity: 压缩后的身份描述
+        """
+        personality_data = {
+            "personality": personality,
+            "identity": identity,
+            "bot_nickname": self.name,
+            "last_updated": int(time.time())
+        }
+        self._save_personality_data(personality_data)
+
     async def _create_personality(self, personality_core: str, personality_side: str) -> str:
         # sourcery skip: merge-list-append, move-assign
         """使用LLM创建压缩版本的impression
@@ -288,7 +259,7 @@ class Individuality:
             personality_parts.append(f"{personality_core}")
 
         # 准备需要压缩的内容
-        if self.personality.compress_personality:
+        if global_config.personality.compress_personality:
             personality_to_compress = f"人格特质: {personality_side}"
 
             prompt = f"""请将以下人格信息进行简洁压缩，保留主要内容，用简练的中文表达：
@@ -323,7 +294,7 @@ class Individuality:
         """使用LLM创建压缩版本的impression"""
         logger.info("正在构建身份.........")
 
-        if self.personality.compress_identity:
+        if global_config.personality.compress_identity:
             identity_to_compress = f"身份背景: {identity}"
 
             prompt = f"""请将以下身份信息进行简洁压缩，保留主要内容，用简练的中文表达：

src/individuality/personality.py

@@ -1,90 +0,0 @@
-from dataclasses import dataclass
-from typing import Dict, Optional
-
-
-@dataclass
-class Personality:
-    """人格特质类"""
-
-    bot_nickname: str  # 机器人昵称
-    personality_core: str  # 人格核心特点
-    personality_side: str  # 人格侧面描述
-    identity: Optional[str]  # 身份细节描述
-    compress_personality: bool  # 是否压缩人格
-    compress_identity: bool  # 是否压缩身份
-
-    _instance = None
-
-    def __new__(cls, *args, **kwargs):
-        if cls._instance is None:
-            cls._instance = super().__new__(cls)
-        return cls._instance
-
-    def __init__(self, personality_core: str = "", personality_side: str = "", identity: Optional[str] = None):
-        self.personality_core = personality_core
-        self.personality_side = personality_side
-        self.identity = identity
-        self.compress_personality = True
-        self.compress_identity = True
-
-    @classmethod
-    def get_instance(cls) -> "Personality":
-        """获取Personality单例实例
-
-        Returns:
-            Personality: 单例实例
-        """
-        if cls._instance is None:
-            cls._instance = cls()
-        return cls._instance
-
-    @classmethod
-    def initialize(
-        cls,
-        bot_nickname: str,
-        personality_core: str,
-        personality_side: str,
-        identity: Optional[str] = None,
-        compress_personality: bool = True,
-        compress_identity: bool = True,
-    ) -> "Personality":
-        """初始化人格特质
-
-        Args:
-            bot_nickname: 机器人昵称
-            personality_core: 人格核心特点
-            personality_side: 人格侧面描述
-            identity: 身份细节描述
-            compress_personality: 是否压缩人格
-            compress_identity: 是否压缩身份
-
-        Returns:
-            Personality: 初始化后的人格特质实例
-        """
-        instance = cls.get_instance()
-        instance.bot_nickname = bot_nickname
-        instance.personality_core = personality_core
-        instance.personality_side = personality_side
-        instance.identity = identity
-        instance.compress_personality = compress_personality
-        instance.compress_identity = compress_identity
-        return instance
-
-    def to_dict(self) -> Dict:
-        """将人格特质转换为字典格式"""
-        return {
-            "bot_nickname": self.bot_nickname,
-            "personality_core": self.personality_core,
-            "personality_side": self.personality_side,
-            "identity": self.identity,
-            "compress_personality": self.compress_personality,
-            "compress_identity": self.compress_identity,
-        }
-
-    @classmethod
-    def from_dict(cls, data: Dict) -> "Personality":
-        """从字典创建人格特质实例"""
-        instance = cls.get_instance()
-        for key, value in data.items():
-            setattr(instance, key, value)
-        return instance

template/bot_config_template.toml

@@ -1,5 +1,5 @@
 [inner]
-version = "4.4.7"
+version = "4.4.8"
 
 #----以下是给开发人员阅读的，如果你只是部署了麦麦，不需要阅读----
 #如果你想要修改配置文件，请在修改后将version的值进行变更
@@ -13,6 +13,7 @@ version = "4.4.7"
 #----以上是给开发人员阅读的，如果你只是部署了麦麦，不需要阅读----
 
 [bot]
+platform = "qq" 
 qq_account = 1145141919810 # 麦麦的QQ账号
 nickname = "麦麦" # 麦麦的昵称
 alias_names = ["麦叠", "牢麦"] # 麦麦的别名