fix: 修复神秘formatter

src/plugins/chat/llm_generator.py

@@ -23,96 +23,65 @@ class ResponseGenerator:
     def __init__(self):
         self.model_r1 = LLM_request(model=global_config.llm_reasoning, temperature=0.7)
         self.model_v3 = LLM_request(model=global_config.llm_normal, temperature=0.7)
-        self.model_r1_distill = LLM_request(
-            model=global_config.llm_reasoning_minor, temperature=0.7
-        )
+        self.model_r1_distill = LLM_request(model=global_config.llm_reasoning_minor, temperature=0.7)
         self.db = Database.get_instance()
-        self.current_model_type = "r1"  # 默认使用 R1
+        self.current_model_type = 'r1'  # 默认使用 R1
 
-    async def generate_response(
-        self, message: Message
-    ) -> Optional[Union[str, List[str]]]:
+    async def generate_response(self, message: Message) -> Optional[Union[str, List[str]]]:
         """根据当前模型类型选择对应的生成函数"""
         # 从global_config中获取模型概率值并选择模型
         rand = random.random()
         if rand < global_config.MODEL_R1_PROBABILITY:
-            self.current_model_type = "r1"
+            self.current_model_type = 'r1'
             current_model = self.model_r1
-        elif (
-            rand
-            < global_config.MODEL_R1_PROBABILITY + global_config.MODEL_V3_PROBABILITY
-        ):
-            self.current_model_type = "v3"
+        elif rand < global_config.MODEL_R1_PROBABILITY + global_config.MODEL_V3_PROBABILITY:
+            self.current_model_type = 'v3'
             current_model = self.model_v3
         else:
-            self.current_model_type = "r1_distill"
+            self.current_model_type = 'r1_distill'
             current_model = self.model_r1_distill
 
-        print(
-            f"+++++++++++++++++{global_config.BOT_NICKNAME}{self.current_model_type}思考中+++++++++++++++++"
-        )
-
-        model_response = await self._generate_response_with_model(
-            message, current_model
-        )
-
+        print(f"+++++++++++++++++{global_config.BOT_NICKNAME}{self.current_model_type}思考中+++++++++++++++++")
+        
+        model_response = await self._generate_response_with_model(message, current_model)
+        
         if model_response:
-            print(f"{global_config.BOT_NICKNAME}的回复是：{model_response}")
+            print(f'{global_config.BOT_NICKNAME}的回复是：{model_response}')
             model_response, emotion = await self._process_response(model_response)
             if model_response:
                 print(f"为 '{model_response}' 获取到的情感标签为：{emotion}")
-                valuedict = {
-                    "happy": 0.5,
-                    "angry": -1,
-                    "sad": -0.5,
-                    "surprised": 0.5,
-                    "disgusted": -1.5,
-                    "fearful": -0.25,
-                    "neutral": 0.25,
+                valuedict={
+                'happy':0.5,'angry':-1,'sad':-0.5,'surprised':0.5,'disgusted':-1.5,'fearful':-0.25,'neutral':0.25
                 }
-                await relationship_manager.update_relationship_value(
-                    message.user_id, relationship_value=valuedict[emotion[0]]
-                )
+                await relationship_manager.update_relationship_value(message.user_id, relationship_value=valuedict[emotion[0]])
 
             return model_response, emotion
         return None, []
 
-    async def _generate_response_with_model(
-        self, message: Message, model: LLM_request
-    ) -> Optional[str]:
+    async def _generate_response_with_model(self, message: Message, model: LLM_request) -> Optional[str]:
         """使用指定的模型生成回复"""
         sender_name = message.user_nickname or f"用户{message.user_id}"
         if message.user_cardname:
-            sender_name = (
-                f"[({message.user_id}){message.user_nickname}]{message.user_cardname}"
-            )
-
+            sender_name=f"[({message.user_id}){message.user_nickname}]{message.user_cardname}"
+        
         # 获取关系值
-        relationship_value = (
-            relationship_manager.get_relationship(message.user_id).relationship_value
-            if relationship_manager.get_relationship(message.user_id)
-            else 0.0
-        )
+        relationship_value = relationship_manager.get_relationship(message.user_id).relationship_value if relationship_manager.get_relationship(message.user_id) else 0.0
         if relationship_value != 0.0:
-            print(
-                f"\033[1;32m[关系管理]\033[0m 回复中_当前关系值: {relationship_value}"
-            )
-
+            print(f"\033[1;32m[关系管理]\033[0m 回复中_当前关系值: {relationship_value}")
+        
         # 构建prompt
         prompt, prompt_check = prompt_builder._build_prompt(
             message_txt=message.processed_plain_text,
             sender_name=sender_name,
             relationship_value=relationship_value,
-            group_id=message.group_id,
+            group_id=message.group_id
         )
 
         # 读空气模块
         if global_config.enable_kuuki_read:
-            content_check, reasoning_content_check = (
-                await self.model_v3.generate_response(prompt_check)
-            )
+            content_check, reasoning_content_check = await self.model_v3.generate_response(prompt_check)
             print(f"\033[1;32m[读空气]\033[0m 读空气结果为{content_check}")
-            if "yes" not in content_check.lower() and random.random() < 0.3:
+            if 'yes' not in content_check.lower() and random.random() < 0.3:
                 self._save_to_db(
                     message=message,
                     sender_name=sender_name,
@@ -121,13 +90,13 @@ class ResponseGenerator:
                     content="",
                     content_check=content_check,
                     reasoning_content="",
-                    reasoning_content_check=reasoning_content_check,
+                    reasoning_content_check=reasoning_content_check
                 )
                 return None
 
         # 生成回复
         content, reasoning_content = await model.generate_response(prompt)
-
+        
         # 保存到数据库
         self._save_to_db(
             message=message,
@@ -137,65 +106,52 @@ class ResponseGenerator:
             content=content,
             content_check=content_check if global_config.enable_kuuki_read else "",
             reasoning_content=reasoning_content,
-            reasoning_content_check=(
-                reasoning_content_check if global_config.enable_kuuki_read else ""
-            ),
+            reasoning_content_check=reasoning_content_check if global_config.enable_kuuki_read else ""
         )
-
+        
         return content
 
-    def _save_to_db(
-        self,
-        message: Message,
-        sender_name: str,
-        prompt: str,
-        prompt_check: str,
-        content: str,
-        content_check: str,
-        reasoning_content: str,
-        reasoning_content_check: str,
-    ):
+    def _save_to_db(self, message: Message, sender_name: str, prompt: str, prompt_check: str,
+                    content: str, content_check: str, reasoning_content: str, reasoning_content_check: str):
         """保存对话记录到数据库"""
-        self.db.db.reasoning_logs.insert_one(
-            {
-                "time": time.time(),
-                "group_id": message.group_id,
-                "user": sender_name,
-                "message": message.processed_plain_text,
-                "model": self.current_model_type,
-                "reasoning_check": reasoning_content_check,
-                "response_check": content_check,
-                "reasoning": reasoning_content,
-                "response": content,
-                "prompt": prompt,
-                "prompt_check": prompt_check,
-            }
-        )
+        self.db.db.reasoning_logs.insert_one({
+            'time': time.time(),
+            'group_id': message.group_id,
+            'user': sender_name,
+            'message': message.processed_plain_text,
+            'model': self.current_model_type,
+            'reasoning_check': reasoning_content_check,
+            'response_check': content_check,
+            'reasoning': reasoning_content,
+            'response': content,
+            'prompt': prompt,
+            'prompt_check': prompt_check
+        })
 
     async def _get_emotion_tags(self, content: str) -> List[str]:
         """提取情感标签"""
         try:
-            prompt = f"""请从以下内容中，从"happy,angry,sad,surprised,disgusted,fearful,neutral"中选出最匹配的1个情感标签并输出
+            prompt = f'''请从以下内容中，从"happy,angry,sad,surprised,disgusted,fearful,neutral"中选出最匹配的1个情感标签并输出
             只输出标签就好，不要输出其他内容:
             内容：{content}
             输出：
-            """
-
+            '''
+            
             content, _ = await self.model_v3.generate_response(prompt)
             return [content.strip()] if content else ["neutral"]
-
+            
         except Exception as e:
             print(f"获取情感标签时出错: {e}")
             return ["neutral"]
-
+    
     async def _process_response(self, content: str) -> Tuple[List[str], List[str]]:
         """处理响应内容，返回处理后的内容和情感标签"""
         if not content:
             return None, []
-
+        
         emotion_tags = await self._get_emotion_tags(content)
         processed_response = process_llm_response(content)
-
+        
         return processed_response, emotion_tags
 
 

src/plugins/chat/topic_identifier.py

@@ -8,8 +8,7 @@ from snownlp import SnowNLP
 from ..models.utils_model import LLM_request
 
 driver = get_driver()
-config = driver.config
-
+config = driver.config  
 
 class TopicIdentifier:
     def __init__(self):
@@ -18,11 +17,11 @@ class TopicIdentifier:
     async def identify_topic_llm(self, text: str) -> Optional[List[str]]:
         """识别消息主题，返回主题列表"""
 
-        prompt = f"""判断这条消息的主题，如果没有明显主题请回复"无主题"，要求：\
-            1. 主题通常2-4个字，必须简短，要求精准概括，不要太具体。\
-            2. 建议给出多个主题，之间用英文逗号分割。只输出主题本身就好，不要有前后缀。\
-            3. 这里是
-            消息内容：{text}"""
+        prompt = f"""判断这条消息的主题，如果没有明显主题请回复"无主题"，要求：
+1. 主题通常2-4个字，必须简短，要求精准概括，不要太具体。
+2. 建议给出多个主题，之间用英文逗号分割。只输出主题本身就好，不要有前后缀。
+
+消息内容：{text}"""
 
         # 使用 LLM_request 类进行请求
         topic, _ = await self.llm_client.generate_response(prompt)
@@ -44,181 +43,25 @@ class TopicIdentifier:
         words = jieba.lcut(text)
         # 去除停用词和标点符号
         stop_words = {
-            "的",
-            "了",
-            "和",
-            "是",
-            "就",
-            "都",
-            "而",
-            "及",
-            "与",
-            "这",
-            "那",
-            "但",
-            "然",
-            "却",
-            "因为",
-            "所以",
-            "如果",
-            "虽然",
-            "一个",
-            "我",
-            "你",
-            "他",
-            "她",
-            "它",
-            "我们",
-            "你们",
-            "他们",
-            "在",
-            "有",
-            "个",
-            "把",
-            "被",
-            "让",
-            "给",
-            "从",
-            "向",
-            "到",
-            "又",
-            "也",
-            "很",
-            "啊",
-            "吧",
-            "呢",
-            "吗",
-            "呀",
-            "哦",
-            "哈",
-            "么",
-            "嘛",
-            "啦",
-            "哎",
-            "唉",
-            "哇",
-            "嗯",
-            "哼",
-            "哪",
-            "什么",
-            "怎么",
-            "为什么",
-            "怎样",
-            "如何",
-            "什么样",
-            "这样",
-            "那样",
-            "这么",
-            "那么",
-            "多少",
-            "几",
-            "谁",
-            "哪里",
-            "哪儿",
-            "什么时候",
-            "何时",
-            "为何",
-            "怎么办",
-            "怎么样",
-            "这些",
-            "那些",
-            "一些",
-            "一点",
-            "一下",
-            "一直",
-            "一定",
-            "一般",
-            "一样",
-            "一会儿",
-            "一边",
-            "一起",
+            '的', '了', '和', '是', '就', '都', '而', '及', '与', '这', '那', '但', '然', '却', 
+            '因为', '所以', '如果', '虽然', '一个', '我', '你', '他', '她', '它', '我们', '你们', 
+            '他们', '在', '有', '个', '把', '被', '让', '给', '从', '向', '到', '又', '也', '很', 
+            '啊', '吧', '呢', '吗', '呀', '哦', '哈', '么', '嘛', '啦', '哎', '唉', '哇', '嗯', 
+            '哼', '哪', '什么', '怎么', '为什么', '怎样', '如何', '什么样', '这样', '那样', '这么', 
+            '那么', '多少', '几', '谁', '哪里', '哪儿', '什么时候', '何时', '为何', '怎么办', 
+            '怎么样', '这些', '那些', '一些', '一点', '一下', '一直', '一定', '一般', '一样', 
+            '一会儿', '一边', '一起',
             # 添加更多量词
-            "个",
-            "只",
-            "条",
-            "张",
-            "片",
-            "块",
-            "本",
-            "册",
-            "页",
-            "幅",
-            "面",
-            "篇",
-            "份",
-            "朵",
-            "颗",
-            "粒",
-            "座",
-            "幢",
-            "栋",
-            "间",
-            "层",
-            "家",
-            "户",
-            "位",
-            "名",
-            "群",
-            "双",
-            "对",
-            "打",
-            "副",
-            "套",
-            "批",
-            "组",
-            "串",
-            "包",
-            "箱",
-            "袋",
-            "瓶",
-            "罐",
+            '个', '只', '条', '张', '片', '块', '本', '册', '页', '幅', '面', '篇', '份', 
+            '朵', '颗', '粒', '座', '幢', '栋', '间', '层', '家', '户', '位', '名', '群',
+            '双', '对', '打', '副', '套', '批', '组', '串', '包', '箱', '袋', '瓶', '罐',
             # 添加更多介词
-            "按",
-            "按照",
-            "把",
-            "被",
-            "比",
-            "比如",
-            "除",
-            "除了",
-            "当",
-            "对",
-            "对于",
-            "根据",
-            "关于",
-            "跟",
-            "和",
-            "将",
-            "经",
-            "经过",
-            "靠",
-            "连",
-            "论",
-            "通过",
-            "同",
-            "往",
-            "为",
-            "为了",
-            "围绕",
-            "于",
-            "由",
-            "由于",
-            "与",
-            "在",
-            "沿",
-            "沿着",
-            "依",
-            "依照",
-            "以",
-            "因",
-            "因为",
-            "用",
-            "由",
-            "与",
-            "自",
-            "自从",
+            '按', '按照', '把', '被', '比', '比如', '除', '除了', '当', '对', '对于', 
+            '根据', '关于', '跟', '和', '将', '经', '经过', '靠', '连', '论', '通过',
+            '同', '往', '为', '为了', '围绕', '于', '由', '由于', '与', '在', '沿', '沿着',
+            '依', '依照', '以', '因', '因为', '用', '由', '与', '自', '自从'
         }
-
+        
         # 过滤掉停用词和标点符号,只保留名词和动词
         filtered_words = []
         for word in words:
@@ -231,16 +74,16 @@ class TopicIdentifier:
                 '≈', '∈', '∉', '⊆', '⊇', '⊂', '⊃', '∪', '∩', '∧', '∨'
             }:
                 filtered_words.append(word)
-
+        
         # 统计词频
         word_freq = {}
         for word in filtered_words:
             word_freq[word] = word_freq.get(word, 0) + 1
-
+        
         # 按词频排序，取前3个
         sorted_words = sorted(word_freq.items(), key=lambda x: x[1], reverse=True)
         top_words = [word for word, freq in sorted_words[:3]]
-
+        
         return top_words if top_words else None
 
     def identify_topic_snownlp(self, text: str) -> Optional[List[str]]:
@@ -264,4 +107,4 @@ class TopicIdentifier:
             print(f"\033[1;31m[错误]\033[0m SnowNLP 处理失败: {str(e)}")
             return None
 
-topic_identifier = TopicIdentifier()
+topic_identifier = TopicIdentifier()