better 优化logger输出，清洁cmd

src/plugins/chat/bot.py

@@ -12,7 +12,6 @@ from nonebot.adapters.onebot.v11 import (
     FriendRecallNoticeEvent,
 )
 
-from src.common.logger import get_module_logger
 from ..memory_system.memory import hippocampus
 from ..moods.moods import MoodManager  # 导入情绪管理器
 from .config import global_config
@@ -33,7 +32,16 @@ from .utils_user import get_user_nickname, get_user_cardname, get_groupname
 from ..willing.willing_manager import willing_manager  # 导入意愿管理器
 from .message_base import UserInfo, GroupInfo, Seg
 
-logger = get_module_logger("chat_bot")
+from src.common.logger import get_module_logger, CHAT_STYLE_CONFIG, LogConfig
+# 定义日志配置
+chat_config = LogConfig(
+    # 使用消息发送专用样式
+    console_format=CHAT_STYLE_CONFIG["console_format"],
+    file_format=CHAT_STYLE_CONFIG["file_format"]
+)
+
+# 配置主程序日志格式
+logger = get_module_logger("chat_bot", config=chat_config)
 
 
 class ChatBot:

src/plugins/chat/message_sender.py

@@ -69,7 +69,7 @@ class Message_Sender:
                             message=message_send.raw_message,
                             auto_escape=False,
                         )
-                        logger.success(f"[调试] 发送消息“{message_preview}”成功")
+                        logger.success(f"发送消息“{message_preview}”成功")
                     except Exception as e:
                         logger.error(f"[调试] 发生错误 {e}")
                         logger.error(f"[调试] 发送消息“{message_preview}”失败")
@@ -81,7 +81,7 @@ class Message_Sender:
                             message=message_send.raw_message,
                             auto_escape=False,
                         )
-                        logger.success(f"[调试] 发送消息“{message_preview}”成功")
+                        logger.success(f"发送消息“{message_preview}”成功")
                     except Exception as e:
                         logger.error(f"[调试] 发生错误 {e}")
                         logger.error(f"[调试] 发送消息“{message_preview}”失败")

src/plugins/memory_system/memory.py

@@ -826,7 +826,7 @@ class Hippocampus:
 
     async def memory_activate_value(self, text: str, max_topics: int = 5, similarity_threshold: float = 0.3) -> int:
         """计算输入文本对记忆的激活程度"""
-        logger.info(f"[激活] 识别主题: {await self._identify_topics(text)}")
+        logger.info(f"识别主题: {await self._identify_topics(text)}")
 
         # 识别主题
         identified_topics = await self._identify_topics(text)
@@ -858,7 +858,7 @@ class Hippocampus:
 
             activation = int(score * 50 * penalty)
             logger.info(
-                f"[激活] 单主题「{topic}」- 相似度: {score:.3f}, 内容数: {content_count}, 激活值: {activation}")
+                f"单主题「{topic}」- 相似度: {score:.3f}, 内容数: {content_count}, 激活值: {activation}")
             return activation
 
         # 计算关键词匹配率，同时考虑内容数量
@@ -895,7 +895,7 @@ class Hippocampus:
         # 计算最终激活值
         activation = int((topic_match + average_similarities) / 2 * 100)
         logger.info(
-            f"[激活] 匹配率: {topic_match:.3f}, 平均相似度: {average_similarities:.3f}, 激活值: {activation}")
+            f"匹配率: {topic_match:.3f}, 平均相似度: {average_similarities:.3f}, 激活值: {activation}")
 
         return activation
 

src/plugins/models/utils_model.py

@@ -103,7 +103,7 @@ class LLM_request:
                 "timestamp": datetime.now(),
             }
             db.llm_usage.insert_one(usage_data)
-            logger.info(
+            logger.debug(
                 f"Token使用情况 - 模型: {self.model_name}, "
                 f"用户: {user_id}, 类型: {request_type}, "
                 f"提示词: {prompt_tokens}, 完成: {completion_tokens}, "

src/plugins/utils/typo_generator.py

@@ -42,7 +42,7 @@ class ChineseTypoGenerator:
         
         # 加载数据
         # print("正在加载汉字数据库，请稍候...")
-        logger.info("正在加载汉字数据库，请稍候...")
+        # logger.info("正在加载汉字数据库，请稍候...")
         
         self.pinyin_dict = self._create_pinyin_dict()
         self.char_frequency = self._load_or_create_char_frequency()