ruff

src/plugin_system/base/base_action.py

@@ -1,16 +1,17 @@
 from abc import ABC, abstractmethod
-from typing import Tuple, Dict, Any, Optional
+from typing import Tuple
 from src.common.logger_manager import get_logger
 from src.plugin_system.apis.plugin_api import PluginAPI
 from src.plugin_system.base.component_types import ActionActivationType, ChatMode, ActionInfo, ComponentType
 
 logger = get_logger("base_action")
 
+
 class BaseAction(ABC):
     """Action组件基类
-    
+
     Action是插件的一种组件类型，用于处理聊天中的动作逻辑
-    
+
     子类可以通过类属性定义激活条件：
     - focus_activation_type: 专注模式激活类型
     - normal_activation_type: 普通模式激活类型
@@ -21,7 +22,7 @@ class BaseAction(ABC):
     - random_activation_probability: 随机激活概率
     - llm_judge_prompt: LLM判断提示词
     """
-    
+
     # 默认激活设置（子类可以覆盖）
     focus_activation_type: ActionActivationType = ActionActivationType.NEVER
     normal_activation_type: ActionActivationType = ActionActivationType.NEVER
@@ -31,15 +32,10 @@ class BaseAction(ABC):
     parallel_action: bool = True
     random_activation_probability: float = 0.0
     llm_judge_prompt: str = ""
-    
-    def __init__(self, 
-                 action_data: dict, 
-                 reasoning: str, 
-                 cycle_timers: dict, 
-                 thinking_id: str,
-                 **kwargs):
+
+    def __init__(self, action_data: dict, reasoning: str, cycle_timers: dict, thinking_id: str, **kwargs):
         """初始化Action组件
-        
+
         Args:
             action_data: 动作数据
             reasoning: 执行该动作的理由
@@ -51,51 +47,50 @@ class BaseAction(ABC):
         self.reasoning = reasoning
         self.cycle_timers = cycle_timers
         self.thinking_id = thinking_id
-        
+
         # 创建API实例
         self.api = PluginAPI(
             chat_stream=kwargs.get("chat_stream"),
-            expressor=kwargs.get("expressor"), 
+            expressor=kwargs.get("expressor"),
             replyer=kwargs.get("replyer"),
             observations=kwargs.get("observations"),
-            log_prefix=kwargs.get("log_prefix", "")
+            log_prefix=kwargs.get("log_prefix", ""),
         )
-        
+
         self.log_prefix = kwargs.get("log_prefix", "")
-        
+
         logger.debug(f"{self.log_prefix} Action组件初始化完成")
-    
+
     async def send_reply(self, content: str) -> bool:
         """发送回复消息
-        
+
         Args:
             content: 回复内容
-            
+
         Returns:
             bool: 是否发送成功
         """
         return await self.api.send_message("text", content)
-    
+
     @classmethod
-    def get_action_info(cls, name: str = None, description: str = None) -> 'ActionInfo':
+    def get_action_info(cls, name: str = None, description: str = None) -> "ActionInfo":
         """从类属性生成ActionInfo
-        
+
         Args:
             name: Action名称，如果不提供则使用类名
             description: Action描述，如果不提供则使用类文档字符串
-            
+
         Returns:
             ActionInfo: 生成的Action信息对象
         """
 
-        
         # 自动生成名称和描述
         if name is None:
-            name = cls.__name__.lower().replace('action', '')
+            name = cls.__name__.lower().replace("action", "")
         if description is None:
             description = cls.__doc__ or f"{cls.__name__} Action组件"
-            description = description.strip().split('\n')[0]  # 取第一行作为描述
-        
+            description = description.strip().split("\n")[0]  # 取第一行作为描述
+
         return ActionInfo(
             name=name,
             component_type=ComponentType.ACTION,
@@ -107,14 +102,14 @@ class BaseAction(ABC):
             mode_enable=cls.mode_enable,
             parallel_action=cls.parallel_action,
             random_activation_probability=cls.random_activation_probability,
-            llm_judge_prompt=cls.llm_judge_prompt
+            llm_judge_prompt=cls.llm_judge_prompt,
         )
-    
+
     @abstractmethod
     async def execute(self) -> Tuple[bool, str]:
         """执行Action的抽象方法，子类必须实现
-        
+
         Returns:
             Tuple[bool, str]: (是否执行成功, 回复文本)
         """
-        pass 
+        pass