ruff fix

src/common/message_repository.py

@@ -1,7 +1,7 @@
 from src.common.database import db
 from src.common.logger import get_module_logger
 import traceback
-from typing import List, Dict, Any, Optional
+from typing import List, Any, Optional
 
 logger = get_module_logger(__name__)
 

src/do_tool/not_used/change_relationship.py

@@ -1,4 +1,4 @@
-from typing import Dict, Any
+from typing import Any
 from src.common.logger_manager import get_logger
 from src.do_tool.tool_can_use.base_tool import BaseTool
 

src/do_tool/not_used/send_emoji.py

@@ -1,7 +1,7 @@
 from src.do_tool.tool_can_use.base_tool import BaseTool
 from src.common.logger import get_module_logger
 
-from typing import Dict, Any
+from typing import Any
 
 logger = get_module_logger("send_emoji_tool")
 

src/do_tool/tool_can_use/base_tool.py

@@ -1,4 +1,4 @@
-from typing import Dict, List, Any, Optional, Type
+from typing import List, Any, Optional, Type
 import inspect
 import importlib
 import pkgutil

src/heart_flow/background_tasks.py

@@ -250,14 +250,10 @@ class BackgroundTaskManager:
 
     # --- Specific Task Runners --- #
     async def _run_state_update_cycle(self, interval: int):
-        await _run_periodic_loop(
+        await _run_periodic_loop(task_name="State Update", interval=interval, task_func=self._perform_state_update_work)
-            task_name="State Update", interval=interval, task_func=self._perform_state_update_work
-        )
 
     async def _run_absent_into_chat(self, interval: int):
-        await _run_periodic_loop(
+        await _run_periodic_loop(task_name="Into Chat", interval=interval, task_func=self._perform_absent_into_chat)
-            task_name="Into Chat", interval=interval, task_func=self._perform_absent_into_chat
-        )
 
     async def _run_normal_chat_timeout_check_cycle(self, interval: int):
         await _run_periodic_loop(

src/individuality/scene.py

@@ -30,7 +30,7 @@ def get_scene_by_factor(factor: str) -> dict | None:
     Returns:
         dict: 包含情景描述的字典
     """
-    return PERSONALITY_SCENES.get(factor,None)
+    return PERSONALITY_SCENES.get(factor, None)
 
 
 def get_all_scenes() -> dict:

src/plugins/chat/message.py

@@ -116,8 +116,6 @@ class MessageRecv(Message):
         self.processed_plain_text = await self._process_message_segments(self.message_segment)
         self.detailed_plain_text = self._generate_detailed_text()
 
-
-
     async def _process_single_segment(self, seg: Seg) -> str:
         """处理单个消息段
 

src/plugins/chat/message_sender.py

@@ -4,7 +4,6 @@ import time
 from typing import Union
 
 # from ...common.database import db # 数据库依赖似乎不需要了，注释掉
-from ..message.api import global_api
 from .message import MessageSending, MessageThinking, MessageSet
 
 from ..storage.storage import MessageStorage

src/plugins/chat/utils.py

@@ -34,7 +34,7 @@ def db_message_to_str(message_dict: dict) -> str:
             message_dict.get("user_nickname", ""),
             message_dict.get("user_cardname", ""),
         )
-    except Exception as e:
+    except Exception:
         name = message_dict.get("user_nickname", "") or f"用户{message_dict['user_id']}"
     content = message_dict.get("processed_plain_text", "")
     result = f"[{time_str}] {name}: {content}\n"
@@ -76,7 +76,7 @@ def is_mentioned_bot_in_message(message: MessageRecv) -> tuple[bool, float]:
         if not is_mentioned:
             # 判断是否被回复
             if re.match(
-                f"\[回复 [\s\S]*?\({str(global_config.BOT_QQ)}\)：[\s\S]*?]，说：" , message.processed_plain_text
+                f"\[回复 [\s\S]*?\({str(global_config.BOT_QQ)}\)：[\s\S]*?]，说：", message.processed_plain_text
             ):
                 is_mentioned = True
             else:

src/plugins/heartFC_chat/heartFC_sender.py

@@ -1,7 +1,6 @@
 # src/plugins/heartFC_chat/heartFC_sender.py
 import asyncio  # 重新导入 asyncio
 from typing import Dict, Optional  # 重新导入类型
-from ..message.api import global_api
 from ..chat.message import MessageSending, MessageThinking  # 只保留 MessageSending 和 MessageThinking
 from ..storage.storage import MessageStorage
 from ..chat.utils import truncate_message

src/plugins/heartFC_chat/heartflow_prompt_builder.py

@@ -151,9 +151,7 @@ JSON 结构如下，包含三个字段 "action", "reasoning", "emoji_query":
     Prompt("\n你有以下这些**知识**：\n{prompt_info}\n请你**记住上面的知识**，之后可能会用到。\n", "knowledge_prompt")
 
 
-async def _build_prompt_focus(
+async def _build_prompt_focus(reason, current_mind_info, structured_info, chat_stream, sender_name) -> tuple[str, str]:
-        reason, current_mind_info, structured_info, chat_stream, sender_name
-) -> tuple[str, str]:
     individuality = Individuality.get_instance()
     prompt_personality = individuality.get_prompt(x_person=0, level=2)
     # 日程构建

src/plugins/respon_info_catcher/info_catcher.py

@@ -185,18 +185,25 @@ class InfoCatcher:
         try:
             # 将消息对象转换为可序列化的字典喵~
 
-            thinking_log_data = {"chat_id": self.chat_id, "trigger_text": self.trigger_response_text,
+            thinking_log_data = {
-                                 "response_text": self.response_text, "trigger_info": {
+                "chat_id": self.chat_id,
+                "trigger_text": self.trigger_response_text,
+                "response_text": self.response_text,
+                "trigger_info": {
                     "time": self.trigger_response_time,
                     "message": self.message_to_dict(self.trigger_response_message),
-                }, "response_info": {
+                },
+                "response_info": {
                     "time": self.response_time,
                     "message": self.response_messages,
-                }, "timing_results": self.timing_results, "chat_history": self.message_list_to_dict(self.chat_history),
+                },
+                "timing_results": self.timing_results,
+                "chat_history": self.message_list_to_dict(self.chat_history),
                 "chat_history_in_thinking": self.message_list_to_dict(self.chat_history_in_thinking),
-                                 "chat_history_after_response": self.message_list_to_dict(
+                "chat_history_after_response": self.message_list_to_dict(self.chat_history_after_response),
-                                     self.chat_history_after_response), "heartflow_data": self.heartflow_data,
+                "heartflow_data": self.heartflow_data,
-                                 "reasoning_data": self.reasoning_data}
+                "reasoning_data": self.reasoning_data,
+            }
 
             # 根据不同的响应模式添加相应的数据喵~ # 现在直接都加上去好了喵~
             # if self.response_mode == "heart_flow":