feat: 增加ban words

config/bot_config.toml

@@ -6,6 +6,7 @@ nickname = "麦麦"
 min_text_length = 2 # 与麦麦聊天时麦麦只会回答文本大于等于此数的消息
 max_context_size = 15 # 麦麦获得的上下文数量，超出数量后自动丢弃
 emoji_chance = 0.2 # 麦麦使用表情包的概率
+ban_words = ["打胶"]
 
 [emoji]
 check_interval = 120 # 检查表情包的时间间隔

src/plugins/chat/bot.py

@@ -95,6 +95,13 @@ class ChatBot:
             reply_message=event.reply,
         )
 
+        # 过滤词
+        for word in global_config.ban_words:
+            if word in message.detailed_plain_text:
+                print(f"\033[1;32m[{current_time}][{message.group_name}]{message.user_nickname}:\033[0m {message.processed_plain_text}")
+                print(f"\033[1;32m[过滤词识别]\033[0m 消息中含有{word}，filtered")
+                return
+        
         current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(message.time))
 
         topic1 = topic_identifier.identify_topic_jieba(message.processed_plain_text)

src/plugins/chat/config.py

@@ -32,11 +32,14 @@ class BotConfig:
     EMOJI_CHECK_INTERVAL: int = 120  # 表情包检查间隔（分钟）
     EMOJI_REGISTER_INTERVAL: int = 10  # 表情包注册间隔（分钟）
 
+    ban_words: list[str] = [] #违禁词
+    
     # 模型配置
     llm_reasoning: Dict[str, str] = field(default_factory=lambda: {})
     llm_reasoning_minor: Dict[str, str] = field(default_factory=lambda: {})
     llm_normal: Dict[str, str] = field(default_factory=lambda: {})
     llm_normal_minor: Dict[str, str] = field(default_factory=lambda: {})
+    embedding: Dict[str, str] = field(default_factory=lambda: {})
     vlm: Dict[str, str] = field(default_factory=lambda: {})
     
     API_USING: str = "siliconflow"  # 使用的API
@@ -126,6 +129,7 @@ class BotConfig:
                 config.MIN_TEXT_LENGTH = msg_config.get("min_text_length", config.MIN_TEXT_LENGTH)
                 config.MAX_CONTEXT_SIZE = msg_config.get("max_context_size", config.MAX_CONTEXT_SIZE)
                 config.emoji_chance = msg_config.get("emoji_chance", config.emoji_chance)
+                config.ban_words=msg_config.get("banwords",config.ban_words)
 
             if "memory" in toml_dict:
                 memory_config = toml_dict["memory"]