ruff，私聊视为提及了bot

bot.py

@@ -34,6 +34,7 @@ script_dir = os.path.dirname(os.path.abspath(__file__))
 os.chdir(script_dir)
 logger.info(f"已设置工作目录为: {script_dir}")
 
+
 # 检查并创建.env文件
 def ensure_env_file():
     """确保.env文件存在，如果不存在则从模板创建"""
@@ -44,6 +45,7 @@ def ensure_env_file():
         if template_env.exists():
             logger.info("未找到.env文件，正在从模板创建...")
             import shutil
+
             shutil.copy(template_env, env_file)
             logger.info("已从template/template.env创建.env文件")
             logger.warning("请编辑.env文件，将EULA_CONFIRMED设置为true并配置其他必要参数")
@@ -51,6 +53,7 @@ def ensure_env_file():
             logger.error("未找到.env文件和template.env模板文件")
             sys.exit(1)
 
+
 # 确保环境文件存在
 ensure_env_file()
 
@@ -130,9 +133,9 @@ async def graceful_shutdown():
 def check_eula():
     """检查EULA和隐私条款确认状态 - 环境变量版（类似Minecraft）"""
     # 检查环境变量中的EULA确认
-    eula_confirmed = os.getenv('EULA_CONFIRMED', '').lower()
+    eula_confirmed = os.getenv("EULA_CONFIRMED", "").lower()
 
-    if eula_confirmed == 'true':
+    if eula_confirmed == "true":
         logger.info("EULA已通过环境变量确认")
         return
 
@@ -148,8 +151,8 @@ def check_eula():
         try:
             load_dotenv(override=True)  # 重新加载.env文件
 
-            eula_confirmed = os.getenv('EULA_CONFIRMED', '').lower()
+            eula_confirmed = os.getenv("EULA_CONFIRMED", "").lower()
-            if eula_confirmed == 'true':
+            if eula_confirmed == "true":
                 confirm_logger.info("EULA确认成功，感谢您的同意")
                 return
 

scripts/update_prompt_imports.py

@@ -20,16 +20,17 @@ files_to_update = [
     "src/mais4u/mais4u_chat/s4u_mood_manager.py",
     "src/plugin_system/core/tool_use.py",
     "src/chat/memory_system/memory_activator.py",
-    "src/chat/utils/smart_prompt.py"
+    "src/chat/utils/smart_prompt.py",
 ]
 
+
 def update_prompt_imports(file_path):
     """更新文件中的Prompt导入"""
     if not os.path.exists(file_path):
         print(f"文件不存在: {file_path}")
         return False
 
-    with open(file_path, 'r', encoding='utf-8') as f:
+    with open(file_path, "r", encoding="utf-8") as f:
         content = f.read()
 
     # 替换导入语句
@@ -38,7 +39,7 @@ def update_prompt_imports(file_path):
 
     if old_import in content:
         new_content = content.replace(old_import, new_import)
-        with open(file_path, 'w', encoding='utf-8') as f:
+        with open(file_path, "w", encoding="utf-8") as f:
             f.write(new_content)
         print(f"已更新: {file_path}")
         return True
@@ -46,6 +47,7 @@ def update_prompt_imports(file_path):
         print(f"无需更新: {file_path}")
         return False
 
+
 def main():
     """主函数"""
     updated_count = 0
@@ -55,5 +57,6 @@ def main():
 
     print(f"\n更新完成！共更新了 {updated_count} 个文件")
 
+
 if __name__ == "__main__":
     main()

src/chat/affinity_flow/__init__.py

@@ -5,4 +5,4 @@
 
 from src.chat.affinity_flow.afc_manager import afc_manager
 
-__all__ = ['afc_manager', 'AFCManager', 'AffinityFlowChatter']
+__all__ = ["afc_manager", "AFCManager", "AffinityFlowChatter"]

src/chat/affinity_flow/afc_manager.py

@@ -2,6 +2,7 @@
 亲和力聊天处理流管理器
 管理不同聊天流的亲和力聊天处理流，统一获取新消息并分发到对应的亲和力聊天处理流
 """
+
 import time
 import traceback
 from typing import Dict, Optional, List
@@ -20,7 +21,7 @@ class AFCManager:
 
     def __init__(self):
         self.affinity_flow_chatters: Dict[str, "AffinityFlowChatter"] = {}
-        '''所有聊天流的亲和力聊天处理流，stream_id -> affinity_flow_chatter'''
+        """所有聊天流的亲和力聊天处理流，stream_id -> affinity_flow_chatter"""
 
         # 动作管理器
         self.action_manager = ActionManager()
@@ -40,11 +41,7 @@ class AFCManager:
             # 创建增强版规划器
             planner = ActionPlanner(stream_id, self.action_manager)
 
-            chatter = AffinityFlowChatter(
+            chatter = AffinityFlowChatter(stream_id=stream_id, planner=planner, action_manager=self.action_manager)
-                stream_id=stream_id,
-                planner=planner,
-                action_manager=self.action_manager
-            )
             self.affinity_flow_chatters[stream_id] = chatter
             logger.info(f"创建新的亲和力聊天处理器: {stream_id}")
 
@@ -74,7 +71,6 @@ class AFCManager:
                 "executed_count": 0,
             }
 
-
     def get_chatter_stats(self, stream_id: str) -> Optional[Dict[str, any]]:
         """获取聊天处理器统计"""
         if stream_id in self.affinity_flow_chatters:
@@ -131,4 +127,5 @@ class AFCManager:
             self.affinity_flow_chatters[stream_id].update_interest_keywords(new_keywords)
             logger.info(f"已更新聊天流 {stream_id} 的兴趣关键词: {list(new_keywords.keys())}")
 
+
 afc_manager = AFCManager()

src/chat/affinity_flow/chatter.py

@@ -2,6 +2,7 @@
 亲和力聊天处理器
 单个聊天流的处理器，负责处理特定聊天流的完整交互流程
 """
+
 import time
 import traceback
 from datetime import datetime
@@ -57,10 +58,7 @@ class AffinityFlowChatter:
             unread_messages = context.get_unread_messages()
 
             # 使用增强版规划器处理消息
-            actions, target_message = await self.planner.plan(
+            actions, target_message = await self.planner.plan(mode=ChatMode.FOCUS, context=context)
-                mode=ChatMode.FOCUS,
-                context=context
-            )
             self.stats["plans_created"] += 1
 
             # 执行动作（如果规划器返回了动作）
@@ -84,7 +82,9 @@ class AffinityFlowChatter:
                 **execution_result,
             }
 
-            logger.info(f"聊天流 {self.stream_id} StreamContext处理成功: 动作数={result['actions_count']}, 未读消息={result['unread_messages_processed']}")
+            logger.info(
+                f"聊天流 {self.stream_id} StreamContext处理成功: 动作数={result['actions_count']}, 未读消息={result['unread_messages_processed']}"
+            )
 
             return result
 
@@ -197,7 +197,9 @@ class AffinityFlowChatter:
 
     def __repr__(self) -> str:
         """详细字符串表示"""
-        return (f"AffinityFlowChatter(stream_id={self.stream_id}, "
+        return (
-                f"messages_processed={self.stats['messages_processed']}, "
+            f"AffinityFlowChatter(stream_id={self.stream_id}, "
-                f"plans_created={self.stats['plans_created']}, "
+            f"messages_processed={self.stats['messages_processed']}, "
-                f"last_activity={datetime.fromtimestamp(self.last_activity_time)})")
+            f"plans_created={self.stats['plans_created']}, "
+            f"last_activity={datetime.fromtimestamp(self.last_activity_time)})"
+        )

src/chat/affinity_flow/interest_scoring.py

@@ -38,7 +38,9 @@ class InterestScoringSystem:
         # 连续不回复概率提升
         self.no_reply_count = 0
         self.max_no_reply_count = affinity_config.max_no_reply_count
-        self.probability_boost_per_no_reply = affinity_config.no_reply_threshold_adjustment / affinity_config.max_no_reply_count  # 每次不回复增加的概率
+        self.probability_boost_per_no_reply = (
+            affinity_config.no_reply_threshold_adjustment / affinity_config.max_no_reply_count
+        )  # 每次不回复增加的概率
 
         # 用户关系数据
         self.user_relationships: Dict[str, float] = {}  # user_id -> relationship_score
@@ -153,7 +155,9 @@ class InterestScoringSystem:
 
                 # 返回匹配分数，考虑置信度和匹配标签数量
                 affinity_config = global_config.affinity_flow
-                match_count_bonus = min(len(match_result.matched_tags) * affinity_config.match_count_bonus, affinity_config.max_match_bonus)
+                match_count_bonus = min(
+                    len(match_result.matched_tags) * affinity_config.match_count_bonus, affinity_config.max_match_bonus
+                )
                 final_score = match_result.overall_score * 1.15 * match_result.confidence + match_count_bonus
                 logger.debug(
                     f"⚖️  最终分数计算: 总分({match_result.overall_score:.3f}) × 1.3 × 置信度({match_result.confidence:.3f}) + 标签数量奖励({match_count_bonus:.3f}) = {final_score:.3f}"
@@ -263,7 +267,17 @@ class InterestScoringSystem:
         if not msg.processed_plain_text:
             return 0.0
 
-        if msg.is_mentioned or (bot_nickname and bot_nickname in msg.processed_plain_text):
+        # 检查是否被提及
+        is_mentioned = msg.is_mentioned or (bot_nickname and bot_nickname in msg.processed_plain_text)
+
+        # 检查是否为私聊（group_info为None表示私聊）
+        is_private_chat = msg.group_info is None
+
+        # 如果被提及或是私聊，都视为提及了bot
+        if is_mentioned or is_private_chat:
+            logger.debug(f"🔍 提及检测 - 被提及: {is_mentioned}, 私聊: {is_private_chat}")
+            if is_private_chat and not is_mentioned:
+                logger.debug("💬 私聊消息自动视为提及bot")
             return global_config.affinity_flow.mention_bot_interest_score
 
         return 0.0
@@ -282,7 +296,9 @@ class InterestScoringSystem:
         logger.debug(f"📋 基础阈值: {base_threshold:.3f}")
 
         # 如果被提及，降低阈值
-        if score.mentioned_score >= global_config.affinity_flow.mention_bot_interest_score * 0.5:  # 使用提及bot兴趣分的一半作为判断阈值
+        if (
+            score.mentioned_score >= global_config.affinity_flow.mention_bot_interest_score * 0.5
+        ):  # 使用提及bot兴趣分的一半作为判断阈值
             base_threshold = self.mention_threshold
             logger.debug(f"📣 消息提及了机器人，使用降低阈值: {base_threshold:.3f}")
 
@@ -325,7 +341,9 @@ class InterestScoringSystem:
 
     def update_user_relationship(self, user_id: str, relationship_change: float):
         """更新用户关系"""
-        old_score = self.user_relationships.get(user_id, global_config.affinity_flow.base_relationship_score)  # 默认新用户分数
+        old_score = self.user_relationships.get(
+            user_id, global_config.affinity_flow.base_relationship_score
+        )  # 默认新用户分数
         new_score = max(0.0, min(1.0, old_score + relationship_change))
 
         self.user_relationships[user_id] = new_score

src/chat/affinity_flow/relationship_tracker.py

@@ -116,6 +116,7 @@ class UserRelationshipTracker:
         try:
             # 获取bot人设信息
             from src.individuality.individuality import Individuality
+
             individuality = Individuality()
             bot_personality = await individuality.get_personality_block()
 
@@ -168,7 +169,17 @@ class UserRelationshipTracker:
                     # 清理LLM响应，移除可能的格式标记
                     cleaned_response = self._clean_llm_json_response(llm_response)
                     response_data = json.loads(cleaned_response)
-                    new_score = max(0.0, min(1.0, float(response_data.get("new_relationship_score", global_config.affinity_flow.base_relationship_score))))
+                    new_score = max(
+                        0.0,
+                        min(
+                            1.0,
+                            float(
+                                response_data.get(
+                                    "new_relationship_score", global_config.affinity_flow.base_relationship_score
+                                )
+                            ),
+                        ),
+                    )
 
                     if self.interest_scoring_system:
                         self.interest_scoring_system.update_user_relationship(
@@ -295,7 +306,9 @@ class UserRelationshipTracker:
             # 更新缓存
             self.user_relationship_cache[user_id] = {
                 "relationship_text": relationship_data.get("relationship_text", ""),
-                "relationship_score": relationship_data.get("relationship_score", global_config.affinity_flow.base_relationship_score),
+                "relationship_score": relationship_data.get(
+                    "relationship_score", global_config.affinity_flow.base_relationship_score
+                ),
                 "last_tracked": time.time(),
             }
             return relationship_data.get("relationship_score", global_config.affinity_flow.base_relationship_score)
@@ -386,7 +399,11 @@ class UserRelationshipTracker:
 
             # 获取当前关系数据
             current_relationship = self._get_user_relationship_from_db(user_id)
-            current_score = current_relationship.get("relationship_score", global_config.affinity_flow.base_relationship_score) if current_relationship else global_config.affinity_flow.base_relationship_score
+            current_score = (
+                current_relationship.get("relationship_score", global_config.affinity_flow.base_relationship_score)
+                if current_relationship
+                else global_config.affinity_flow.base_relationship_score
+            )
             current_text = current_relationship.get("relationship_text", "新用户") if current_relationship else "新用户"
 
             # 使用LLM分析并更新关系
@@ -501,6 +518,7 @@ class UserRelationshipTracker:
 
             # 获取bot人设信息
             from src.individuality.individuality import Individuality
+
             individuality = Individuality()
             bot_personality = await individuality.get_personality_block()
 

src/chat/emoji_system/emoji_history.py

@@ -2,6 +2,7 @@
 """
 表情包发送历史记录模块
 """
+
 import os
 from typing import List, Dict
 from collections import deque

src/chat/emoji_system/emoji_manager.py

@@ -477,7 +477,7 @@ class EmojiManager:
             emoji_options_str = ""
             for i, emoji in enumerate(candidate_emojis):
                 # 为每个表情包创建一个编号和它的详细描述
-                emoji_options_str += f"编号: {i+1}\n描述: {emoji.description}\n\n"
+                emoji_options_str += f"编号: {i + 1}\n描述: {emoji.description}\n\n"
 
             # 精心设计的prompt，引导LLM做出选择
             prompt = f"""
@@ -524,9 +524,7 @@ class EmojiManager:
             self.record_usage(selected_emoji.hash)
             _time_end = time.time()
 
-            logger.info(
+            logger.info(f"找到匹配描述的表情包: {selected_emoji.description}, 耗时: {(_time_end - _time_start):.2f}s")
-                f"找到匹配描述的表情包: {selected_emoji.description}, 耗时: {(_time_end - _time_start):.2f}s"
-            )
 
             # 8. 返回选中的表情包信息
             return selected_emoji.full_path, f"[表情包：{selected_emoji.description}]", text_emotion
@@ -627,8 +625,9 @@ class EmojiManager:
 
             # 无论steal_emoji是否开启，都检查emoji文件夹以支持手动注册
             # 只有在需要腾出空间或填充表情库时，才真正执行注册
-            if (self.emoji_num > self.emoji_num_max and global_config.emoji.do_replace) or \
+            if (self.emoji_num > self.emoji_num_max and global_config.emoji.do_replace) or (
-               (self.emoji_num < self.emoji_num_max):
+                self.emoji_num < self.emoji_num_max
+            ):
                 try:
                     # 获取目录下所有图片文件
                     files_to_process = [
@@ -931,16 +930,21 @@ class EmojiManager:
                 image_base64 = image_base64.encode("ascii", errors="ignore").decode("ascii")
             image_bytes = base64.b64decode(image_base64)
             image_hash = hashlib.md5(image_bytes).hexdigest()
-            image_format = Image.open(io.BytesIO(image_bytes)).format.lower() if Image.open(io.BytesIO(image_bytes)).format else "jpeg"
+            image_format = (
-
+                Image.open(io.BytesIO(image_bytes)).format.lower()
+                if Image.open(io.BytesIO(image_bytes)).format
+                else "jpeg"
+            )
 
             # 2. 检查数据库中是否已存在该表情包的描述，实现复用
             existing_description = None
             try:
                 with get_db_session() as session:
-                    existing_image = session.query(Images).filter(
+                    existing_image = (
-                        (Images.emoji_hash == image_hash) & (Images.type == "emoji")
+                        session.query(Images)
-                    ).one_or_none()
+                        .filter((Images.emoji_hash == image_hash) & (Images.type == "emoji"))
+                        .one_or_none()
+                    )
                     if existing_image and existing_image.description:
                         existing_description = existing_image.description
                         logger.info(f"[复用描述] 找到已有详细描述: {existing_description[:50]}...")

src/chat/frequency_analyzer/analyzer.py

@@ -14,6 +14,7 @@ Chat Frequency Analyzer
 - MIN_CHATS_FOR_PEAK: 在一个窗口内需要多少次聊天才能被认为是高峰时段。
 - MIN_GAP_BETWEEN_PEAKS_HOURS: 两个独立高峰时段之间的最小间隔（小时）。
 """
+
 import time as time_module
 from datetime import datetime, timedelta, time
 from typing import List, Tuple, Optional
@@ -71,7 +72,9 @@ class ChatFrequencyAnalyzer:
                 current_window_end = datetimes[i]
 
                 # 合并重叠或相邻的高峰时段
-                if peak_windows and current_window_start - peak_windows[-1][1] < timedelta(hours=MIN_GAP_BETWEEN_PEAKS_HOURS):
+                if peak_windows and current_window_start - peak_windows[-1][1] < timedelta(
+                    hours=MIN_GAP_BETWEEN_PEAKS_HOURS
+                ):
                     # 扩展上一个窗口的结束时间
                     peak_windows[-1] = (peak_windows[-1][0], current_window_end)
                 else:

src/chat/frequency_analyzer/trigger.py

@@ -14,6 +14,7 @@ Frequency-Based Proactive Trigger
 - TRIGGER_CHECK_INTERVAL_SECONDS: 触发器检查的周期（秒）。
 - COOLDOWN_HOURS: 在同一个高峰时段内触发一次后的冷却时间（小时）。
 """
+
 import asyncio
 import time
 from datetime import datetime
@@ -21,6 +22,7 @@ from typing import Dict, Optional
 
 from src.common.logger import get_logger
 from src.chat.affinity_flow.afc_manager import afc_manager
+
 # TODO: 需要重新实现主动思考和睡眠管理功能
 from .analyzer import chat_frequency_analyzer
 
@@ -74,7 +76,6 @@ class FrequencyBasedTrigger:
 
                     # 4. 检查当前是否是该用户的高峰聊天时间
                     if chat_frequency_analyzer.is_in_peak_time(chat_id, now):
-                        
                         # 5. 检查用户当前是否已有活跃的处理任务
                         #    亲和力流系统不直接提供循环状态，通过检查最后活动时间来判断是否忙碌
                         chatter = afc_manager.get_or_create_chatter(chat_id)

src/chat/interest_system/__init__.py

@@ -4,14 +4,12 @@
 """
 
 from .bot_interest_manager import BotInterestManager, bot_interest_manager
-from src.common.data_models.bot_interest_data_model import (
+from src.common.data_models.bot_interest_data_model import BotInterestTag, BotPersonalityInterests, InterestMatchResult
-    BotInterestTag, BotPersonalityInterests, InterestMatchResult
-)
 
 __all__ = [
     "BotInterestManager",
     "bot_interest_manager",
     "BotInterestTag",
     "BotPersonalityInterests",
-    "InterestMatchResult"
+    "InterestMatchResult",
 ]

src/chat/interest_system/bot_interest_manager.py

@@ -2,6 +2,7 @@
 机器人兴趣标签管理系统
 基于人设生成兴趣标签，并使用embedding计算匹配度
 """
+
 import orjson
 import traceback
 from typing import List, Dict, Optional, Any
@@ -10,9 +11,7 @@ import numpy as np
 
 from src.common.logger import get_logger
 from src.config.config import global_config
-from src.common.data_models.bot_interest_data_model import (
+from src.common.data_models.bot_interest_data_model import BotPersonalityInterests, BotInterestTag, InterestMatchResult
-    BotPersonalityInterests, BotInterestTag, InterestMatchResult
-)
 
 logger = get_logger("bot_interest_manager")
 
@@ -87,7 +86,7 @@ class BotInterestManager:
         logger.debug("✅ 成功导入embedding相关模块")
 
         # 检查embedding配置是否存在
-        if not hasattr(model_config.model_task_config, 'embedding'):
+        if not hasattr(model_config.model_task_config, "embedding"):
             raise RuntimeError("❌ 未找到embedding模型配置")
 
         logger.info("📋 找到embedding模型配置")
@@ -101,7 +100,7 @@ class BotInterestManager:
         logger.info(f"🔗 客户端类型: {type(self.embedding_request).__name__}")
 
         # 获取第一个embedding模型的ModelInfo
-        if hasattr(self.embedding_config, 'model_list') and self.embedding_config.model_list:
+        if hasattr(self.embedding_config, "model_list") and self.embedding_config.model_list:
             first_model_name = self.embedding_config.model_list[0]
             logger.info(f"🎯 使用embedding模型: {first_model_name}")
         else:
@@ -127,7 +126,9 @@ class BotInterestManager:
             # 生成新的兴趣标签
             logger.info("🆕 数据库中未找到兴趣标签，开始生成新的...")
             logger.info("🤖 正在调用LLM生成个性化兴趣标签...")
-            generated_interests = await self._generate_interests_from_personality(personality_description, personality_id)
+            generated_interests = await self._generate_interests_from_personality(
+                personality_description, personality_id
+            )
 
             if generated_interests:
                 self.current_interests = generated_interests
@@ -140,14 +141,16 @@ class BotInterestManager:
             else:
                 raise RuntimeError("❌ 兴趣标签生成失败")
 
-    async def _generate_interests_from_personality(self, personality_description: str, personality_id: str) -> Optional[BotPersonalityInterests]:
+    async def _generate_interests_from_personality(
+        self, personality_description: str, personality_id: str
+    ) -> Optional[BotPersonalityInterests]:
         """根据人设生成兴趣标签"""
         try:
             logger.info("🎨 开始根据人设生成兴趣标签...")
             logger.info(f"📝 人设长度: {len(personality_description)} 字符")
 
             # 检查embedding客户端是否可用
-            if not hasattr(self, 'embedding_request'):
+            if not hasattr(self, "embedding_request"):
                 raise RuntimeError("❌ Embedding客户端未初始化，无法生成兴趣标签")
 
             # 构建提示词
@@ -190,8 +193,7 @@ class BotInterestManager:
             interests_data = orjson.loads(response)
 
             bot_interests = BotPersonalityInterests(
-                personality_id=personality_id,
+                personality_id=personality_id, personality_description=personality_description
-                personality_description=personality_description
             )
 
             # 解析生成的兴趣标签
@@ -202,10 +204,7 @@ class BotInterestManager:
                 tag_name = tag_data.get("name", f"标签_{i}")
                 weight = tag_data.get("weight", 0.5)
 
-                tag = BotInterestTag(
+                tag = BotInterestTag(tag_name=tag_name, weight=weight)
-                    tag_name=tag_name,
-                    weight=weight
-                )
                 bot_interests.interest_tags.append(tag)
 
                 logger.debug(f"   🏷️  {tag_name} (权重: {weight:.2f})")
@@ -225,7 +224,6 @@ class BotInterestManager:
             traceback.print_exc()
             raise
 
-    
     async def _call_llm_for_interest_generation(self, prompt: str) -> Optional[str]:
         """调用LLM生成兴趣标签"""
         try:
@@ -252,12 +250,14 @@ class BotInterestManager:
                 model_config=replyer_config,
                 request_type="interest_generation",
                 temperature=0.7,
-                max_tokens=2000
+                max_tokens=2000,
             )
 
             if success and response:
                 logger.info(f"✅ LLM响应成功，模型: {model_name}, 响应长度: {len(response)} 字符")
-                logger.debug(f"📄 LLM响应内容: {response[:200]}..." if len(response) > 200 else f"📄 LLM响应内容: {response}")
+                logger.debug(
+                    f"📄 LLM响应内容: {response[:200]}..." if len(response) > 200 else f"📄 LLM响应内容: {response}"
+                )
                 if reasoning_content:
                     logger.debug(f"🧠 推理内容: {reasoning_content[:100]}...")
 
@@ -279,14 +279,14 @@ class BotInterestManager:
         import re
 
         # 移除 ```json 和 ``` 标记
-        cleaned = re.sub(r'```json\s*', '', response)
+        cleaned = re.sub(r"```json\s*", "", response)
-        cleaned = re.sub(r'\s*```', '', cleaned)
+        cleaned = re.sub(r"\s*```", "", cleaned)
 
         # 移除可能的多余空格和换行
         cleaned = cleaned.strip()
 
         # 尝试提取JSON对象（如果响应中有其他文本）
-        json_match = re.search(r'\{.*\}', cleaned, re.DOTALL)
+        json_match = re.search(r"\{.*\}", cleaned, re.DOTALL)
         if json_match:
             cleaned = json_match.group(0)
 
@@ -295,7 +295,7 @@ class BotInterestManager:
 
     async def _generate_embeddings_for_tags(self, interests: BotPersonalityInterests):
         """为所有兴趣标签生成embedding"""
-        if not hasattr(self, 'embedding_request'):
+        if not hasattr(self, "embedding_request"):
             raise RuntimeError("❌ Embedding客户端未初始化，无法生成embedding")
 
         total_tags = len(interests.interest_tags)
@@ -342,7 +342,7 @@ class BotInterestManager:
 
     async def _get_embedding(self, text: str) -> List[float]:
         """获取文本的embedding向量"""
-        if not hasattr(self, 'embedding_request'):
+        if not hasattr(self, "embedding_request"):
             raise RuntimeError("❌ Embedding请求客户端未初始化")
 
         # 检查缓存
@@ -376,7 +376,9 @@ class BotInterestManager:
         logger.debug(f"✅ 消息embedding生成成功，维度: {len(embedding)}")
         return embedding
 
-    async def _calculate_similarity_scores(self, result: InterestMatchResult, message_embedding: List[float], keywords: List[str]):
+    async def _calculate_similarity_scores(
+        self, result: InterestMatchResult, message_embedding: List[float], keywords: List[str]
+    ):
         """计算消息与兴趣标签的相似度分数"""
         try:
             if not self.current_interests:
@@ -397,7 +399,9 @@ class BotInterestManager:
                     # 设置相似度阈值为0.3
                     if similarity > 0.3:
                         result.add_match(tag.tag_name, weighted_score, keywords)
-                        logger.debug(f"   🏷️  '{tag.tag_name}': 相似度={similarity:.3f}, 权重={tag.weight:.2f}, 加权分数={weighted_score:.3f}")
+                        logger.debug(
+                            f"   🏷️  '{tag.tag_name}': 相似度={similarity:.3f}, 权重={tag.weight:.2f}, 加权分数={weighted_score:.3f}"
+                        )
 
         except Exception as e:
             logger.error(f"❌ 计算相似度分数失败: {e}")
@@ -455,7 +459,9 @@ class BotInterestManager:
                     match_count += 1
                     high_similarity_count += 1
                     result.add_match(tag.tag_name, enhanced_score, [tag.tag_name])
-                    logger.debug(f"   🏷️  '{tag.tag_name}': 相似度={similarity:.3f}, 权重={tag.weight:.2f}, 基础分数={weighted_score:.3f}, 增强分数={enhanced_score:.3f} [高匹配]")
+                    logger.debug(
+                        f"   🏷️  '{tag.tag_name}': 相似度={similarity:.3f}, 权重={tag.weight:.2f}, 基础分数={weighted_score:.3f}, 增强分数={enhanced_score:.3f} [高匹配]"
+                    )
 
                 elif similarity > medium_threshold:
                     # 中相似度：中等加成
@@ -463,7 +469,9 @@ class BotInterestManager:
                     match_count += 1
                     medium_similarity_count += 1
                     result.add_match(tag.tag_name, enhanced_score, [tag.tag_name])
-                    logger.debug(f"   🏷️  '{tag.tag_name}': 相似度={similarity:.3f}, 权重={tag.weight:.2f}, 基础分数={weighted_score:.3f}, 增强分数={enhanced_score:.3f} [中匹配]")
+                    logger.debug(
+                        f"   🏷️  '{tag.tag_name}': 相似度={similarity:.3f}, 权重={tag.weight:.2f}, 基础分数={weighted_score:.3f}, 增强分数={enhanced_score:.3f} [中匹配]"
+                    )
 
                 elif similarity > low_threshold:
                     # 低相似度：轻微加成
@@ -471,7 +479,9 @@ class BotInterestManager:
                     match_count += 1
                     low_similarity_count += 1
                     result.add_match(tag.tag_name, enhanced_score, [tag.tag_name])
-                    logger.debug(f"   🏷️  '{tag.tag_name}': 相似度={similarity:.3f}, 权重={tag.weight:.2f}, 基础分数={weighted_score:.3f}, 增强分数={enhanced_score:.3f} [低匹配]")
+                    logger.debug(
+                        f"   🏷️  '{tag.tag_name}': 相似度={similarity:.3f}, 权重={tag.weight:.2f}, 基础分数={weighted_score:.3f}, 增强分数={enhanced_score:.3f} [低匹配]"
+                    )
 
         logger.info(f"📈 匹配统计: {match_count}/{len(active_tags)} 个标签超过阈值")
         logger.info(f"🔥 高相似度匹配(>{high_threshold}): {high_similarity_count} 个")
@@ -488,7 +498,9 @@ class BotInterestManager:
                 original_score = result.match_scores[tag_name]
                 bonus = keyword_bonus[tag_name]
                 result.match_scores[tag_name] = original_score + bonus
-                logger.debug(f"   🏷️  '{tag_name}': 原始分数={original_score:.3f}, 奖励={bonus:.3f}, 最终分数={result.match_scores[tag_name]:.3f}")
+                logger.debug(
+                    f"   🏷️  '{tag_name}': 原始分数={original_score:.3f}, 奖励={bonus:.3f}, 最终分数={result.match_scores[tag_name]:.3f}"
+                )
 
         # 计算总体分数
         result.calculate_overall_score()
@@ -499,10 +511,11 @@ class BotInterestManager:
             result.top_tag = top_tag_name
             logger.info(f"🏆 最佳匹配标签: '{top_tag_name}' (分数: {result.match_scores[top_tag_name]:.3f})")
 
-        logger.info(f"📊 最终结果: 总分={result.overall_score:.3f}, 置信度={result.confidence:.3f}, 匹配标签数={len(result.matched_tags)}")
+        logger.info(
+            f"📊 最终结果: 总分={result.overall_score:.3f}, 置信度={result.confidence:.3f}, 匹配标签数={len(result.matched_tags)}"
+        )
         return result
 
-    
     def _calculate_keyword_match_bonus(self, keywords: List[str], matched_tags: List[str]) -> Dict[str, float]:
         """计算关键词直接匹配奖励"""
         if not keywords or not matched_tags:
@@ -522,17 +535,25 @@ class BotInterestManager:
                 # 完全匹配
                 if keyword_lower == tag_name_lower:
                     bonus += affinity_config.high_match_interest_threshold * 0.6  # 使用高匹配阈值的60%作为完全匹配奖励
-                    logger.debug(f"   🎯 关键词完全匹配: '{keyword}' == '{tag_name}' (+{affinity_config.high_match_interest_threshold * 0.6:.3f})")
+                    logger.debug(
+                        f"   🎯 关键词完全匹配: '{keyword}' == '{tag_name}' (+{affinity_config.high_match_interest_threshold * 0.6:.3f})"
+                    )
 
                 # 包含匹配
                 elif keyword_lower in tag_name_lower or tag_name_lower in keyword_lower:
-                    bonus += affinity_config.medium_match_interest_threshold * 0.3  # 使用中匹配阈值的30%作为包含匹配奖励
+                    bonus += (
-                    logger.debug(f"   🎯 关键词包含匹配: '{keyword}' ⊃ '{tag_name}' (+{affinity_config.medium_match_interest_threshold * 0.3:.3f})")
+                        affinity_config.medium_match_interest_threshold * 0.3
+                    )  # 使用中匹配阈值的30%作为包含匹配奖励
+                    logger.debug(
+                        f"   🎯 关键词包含匹配: '{keyword}' ⊃ '{tag_name}' (+{affinity_config.medium_match_interest_threshold * 0.3:.3f})"
+                    )
 
                 # 部分匹配（编辑距离）
                 elif self._calculate_partial_match(keyword_lower, tag_name_lower):
                     bonus += affinity_config.low_match_interest_threshold * 0.4  # 使用低匹配阈值的40%作为部分匹配奖励
-                    logger.debug(f"   🎯 关键词部分匹配: '{keyword}' ≈ '{tag_name}' (+{affinity_config.low_match_interest_threshold * 0.4:.3f})")
+                    logger.debug(
+                        f"   🎯 关键词部分匹配: '{keyword}' ≈ '{tag_name}' (+{affinity_config.low_match_interest_threshold * 0.4:.3f})"
+                    )
 
             if bonus > 0:
                 bonus_dict[tag_name] = min(bonus, affinity_config.max_match_bonus)  # 使用配置的最大奖励限制
@@ -608,12 +629,12 @@ class BotInterestManager:
 
             with get_db_session() as session:
                 # 查询最新的兴趣标签配置
-                db_interests = session.query(DBBotPersonalityInterests).filter(
+                db_interests = (
-                    DBBotPersonalityInterests.personality_id == personality_id
+                    session.query(DBBotPersonalityInterests)
-                ).order_by(
+                    .filter(DBBotPersonalityInterests.personality_id == personality_id)
-                    DBBotPersonalityInterests.version.desc(),
+                    .order_by(DBBotPersonalityInterests.version.desc(), DBBotPersonalityInterests.last_updated.desc())
-                    DBBotPersonalityInterests.last_updated.desc()
+                    .first()
-                ).first()
+                )
 
                 if db_interests:
                     logger.info(f"✅ 找到数据库中的兴趣标签配置，版本: {db_interests.version}")
@@ -631,7 +652,7 @@ class BotInterestManager:
                             personality_description=db_interests.personality_description,
                             embedding_model=db_interests.embedding_model,
                             version=db_interests.version,
-                            last_updated=db_interests.last_updated
+                            last_updated=db_interests.last_updated,
                         )
 
                         # 解析兴趣标签
@@ -639,10 +660,14 @@ class BotInterestManager:
                             tag = BotInterestTag(
                                 tag_name=tag_data.get("tag_name", ""),
                                 weight=tag_data.get("weight", 0.5),
-                                created_at=datetime.fromisoformat(tag_data.get("created_at", datetime.now().isoformat())),
+                                created_at=datetime.fromisoformat(
-                                updated_at=datetime.fromisoformat(tag_data.get("updated_at", datetime.now().isoformat())),
+                                    tag_data.get("created_at", datetime.now().isoformat())
+                                ),
+                                updated_at=datetime.fromisoformat(
+                                    tag_data.get("updated_at", datetime.now().isoformat())
+                                ),
                                 is_active=tag_data.get("is_active", True),
-                                embedding=tag_data.get("embedding")
+                                embedding=tag_data.get("embedding"),
                             )
                             interests.interest_tags.append(tag)
 
@@ -685,7 +710,7 @@ class BotInterestManager:
                     "created_at": tag.created_at.isoformat(),
                     "updated_at": tag.updated_at.isoformat(),
                     "is_active": tag.is_active,
-                    "embedding": tag.embedding
+                    "embedding": tag.embedding,
                 }
                 tags_data.append(tag_dict)
 
@@ -694,9 +719,11 @@ class BotInterestManager:
 
             with get_db_session() as session:
                 # 检查是否已存在相同personality_id的记录
-                existing_record = session.query(DBBotPersonalityInterests).filter(
+                existing_record = (
-                    DBBotPersonalityInterests.personality_id == interests.personality_id
+                    session.query(DBBotPersonalityInterests)
-                ).first()
+                    .filter(DBBotPersonalityInterests.personality_id == interests.personality_id)
+                    .first()
+                )
 
                 if existing_record:
                     # 更新现有记录
@@ -718,7 +745,7 @@ class BotInterestManager:
                         interest_tags=json_data,
                         embedding_model=interests.embedding_model,
                         version=interests.version,
-                        last_updated=interests.last_updated
+                        last_updated=interests.last_updated,
                     )
                     session.add(new_record)
                     session.commit()
@@ -728,9 +755,11 @@ class BotInterestManager:
 
             # 验证保存是否成功
             with get_db_session() as session:
-                saved_record = session.query(DBBotPersonalityInterests).filter(
+                saved_record = (
-                    DBBotPersonalityInterests.personality_id == interests.personality_id
+                    session.query(DBBotPersonalityInterests)
-                ).first()
+                    .filter(DBBotPersonalityInterests.personality_id == interests.personality_id)
+                    .first()
+                )
                 session.commit()
                 if saved_record:
                     logger.info(f"✅ 验证成功：数据库中存在personality_id为 {interests.personality_id} 的记录")
@@ -760,7 +789,7 @@ class BotInterestManager:
             "total_tags": len(active_tags),
             "embedding_model": self.current_interests.embedding_model,
             "last_updated": self.current_interests.last_updated.isoformat(),
-            "cache_size": len(self.embedding_cache)
+            "cache_size": len(self.embedding_cache),
         }
 
     async def update_interest_tags(self, new_personality_description: str = None):
@@ -775,8 +804,7 @@ class BotInterestManager:
 
             # 重新生成兴趣标签
             new_interests = await self._generate_interests_from_personality(
-                self.current_interests.personality_description,
+                self.current_interests.personality_description, self.current_interests.personality_id
-                self.current_interests.personality_id
             )
 
             if new_interests:

src/chat/message_manager/__init__.py

@@ -4,13 +4,11 @@
 """
 
 from .message_manager import MessageManager, message_manager
-from src.common.data_models.message_manager_data_model import StreamContext, MessageStatus, MessageManagerStats, StreamStats
+from src.common.data_models.message_manager_data_model import (
+    StreamContext,
+    MessageStatus,
+    MessageManagerStats,
+    StreamStats,
+)
 
-__all__ = [
+__all__ = ["MessageManager", "message_manager", "StreamContext", "MessageStatus", "MessageManagerStats", "StreamStats"]
-    "MessageManager",
-    "message_manager",
-    "StreamContext",
-    "MessageStatus",
-    "MessageManagerStats",
-    "StreamStats"
-]

src/chat/message_manager/message_manager.py

@@ -2,6 +2,7 @@
 消息管理模块
 管理每个聊天流的上下文信息，包含历史记录和未读消息，定期检查并处理新消息
 """
+
 import asyncio
 import time
 import traceback
@@ -100,9 +101,7 @@ class MessageManager:
 
                 # 如果没有处理任务，创建一个
                 if not context.processing_task or context.processing_task.done():
-                    context.processing_task = asyncio.create_task(
+                    context.processing_task = asyncio.create_task(self._process_stream_messages(stream_id))
-                        self._process_stream_messages(stream_id)
-                    )
 
         # 更新统计
         self.stats.active_streams = active_streams
@@ -175,7 +174,7 @@ class MessageManager:
             unread_count=len(context.get_unread_messages()),
             history_count=len(context.history_messages),
             last_check_time=context.last_check_time,
-            has_active_task=context.processing_task and not context.processing_task.done()
+            has_active_task=context.processing_task and not context.processing_task.done(),
         )
 
     def get_manager_stats(self) -> Dict[str, Any]:
@@ -186,7 +185,7 @@ class MessageManager:
             "total_unread_messages": self.stats.total_unread_messages,
             "total_processed_messages": self.stats.total_processed_messages,
             "uptime": self.stats.uptime,
-            "start_time": self.stats.start_time
+            "start_time": self.stats.start_time,
         }
 
     def cleanup_inactive_streams(self, max_inactive_hours: int = 24):
@@ -196,8 +195,7 @@ class MessageManager:
 
         inactive_streams = []
         for stream_id, context in self.stream_contexts.items():
-            if (current_time - context.last_check_time > max_inactive_seconds and
+            if current_time - context.last_check_time > max_inactive_seconds and not context.get_unread_messages():
-                not context.get_unread_messages()):
                 inactive_streams.append(stream_id)
 
         for stream_id in inactive_streams:

src/chat/message_receive/bot.py

@@ -17,6 +17,7 @@ from src.plugin_system.core import component_registry, event_manager, global_ann
 from src.plugin_system.base import BaseCommand, EventType
 from src.mais4u.mais4u_chat.s4u_msg_processor import S4UMessageProcessor
 from src.chat.utils.utils import is_mentioned_bot_in_message
+
 # 导入反注入系统
 from src.chat.antipromptinjector import initialize_anti_injector
 
@@ -511,7 +512,7 @@ class ChatBot:
                     chat_info_user_id=message.chat_stream.user_info.user_id,
                     chat_info_user_nickname=message.chat_stream.user_info.user_nickname,
                     chat_info_user_cardname=message.chat_stream.user_info.user_cardname,
-                    chat_info_user_platform=message.chat_stream.user_info.platform
+                    chat_info_user_platform=message.chat_stream.user_info.platform,
                 )
 
                 # 如果是群聊，添加群组信息

src/chat/message_receive/chat_stream.py

@@ -84,7 +84,9 @@ class ChatStream:
         self.saved = False
         self.context: ChatMessageContext = None  # type: ignore # 用于存储该聊天的上下文信息
         # 从配置文件中读取focus_value，如果没有则使用默认值1.0
-        self.focus_energy = data.get("focus_energy", global_config.chat.focus_value) if data else global_config.chat.focus_value
+        self.focus_energy = (
+            data.get("focus_energy", global_config.chat.focus_value) if data else global_config.chat.focus_value
+        )
         self.no_reply_consecutive = 0
         self.breaking_accumulated_interest = 0.0
 

src/chat/planner_actions/action_manager.py

@@ -168,7 +168,12 @@ class ActionManager:
 
             if not chat_stream:
                 logger.error(f"{log_prefix} 无法找到chat_id对应的chat_stream: {chat_id}")
-                return {"action_type": action_name, "success": False, "reply_text": "", "error": "chat_stream not found"}
+                return {
+                    "action_type": action_name,
+                    "success": False,
+                    "reply_text": "",
+                    "error": "chat_stream not found",
+                }
 
             if action_name == "no_action":
                 return {"action_type": "no_action", "success": True, "reply_text": "", "command": ""}

src/chat/planner_actions/plan_generator.py

@@ -1,6 +1,7 @@
 """
 PlanGenerator: 负责搜集和汇总所有决策所需的信息，生成一个未经筛选的“原始计划” (Plan)。
 """
+
 import time
 from typing import Dict
 
@@ -35,6 +36,7 @@ class PlanGenerator:
             chat_id (str): 当前聊天的 ID。
         """
         from src.chat.planner_actions.action_manager import ActionManager
+
         self.chat_id = chat_id
         # 注意：ActionManager 可能需要根据实际情况初始化
         self.action_manager = ActionManager()
@@ -65,7 +67,6 @@ class PlanGenerator:
         )
         chat_history = [DatabaseMessages(**msg) for msg in chat_history_raw]
 
-
         plan = Plan(
             chat_id=self.chat_id,
             mode=mode,
@@ -86,7 +87,7 @@ class PlanGenerator:
             Dict[str, "ActionInfo"]: 一个字典，键是动作名称，值是 ActionInfo 对象。
         """
         current_available_actions_dict = self.action_manager.get_using_actions()
-        all_registered_actions: Dict[str, ActionInfo] = component_registry.get_components_by_type( # type: ignore
+        all_registered_actions: Dict[str, ActionInfo] = component_registry.get_components_by_type(  # type: ignore
             ComponentType.ACTION
         )
 
@@ -99,16 +100,13 @@ class PlanGenerator:
             name="reply",
             component_type=ComponentType.ACTION,
             description="系统级动作：选择回复消息的决策",
-            action_parameters={
+            action_parameters={"content": "回复的文本内容", "reply_to_message_id": "要回复的消息ID"},
-                "content": "回复的文本内容",
-                "reply_to_message_id": "要回复的消息ID"
-            },
             action_require=[
                 "你想要闲聊或者随便附和",
                 "当用户提到你或艾特你时",
                 "当需要回答用户的问题时",
                 "当你想参与对话时",
-                "当用户分享有趣的内容时"
+                "当用户分享有趣的内容时",
             ],
             activation_type=ActionActivationType.ALWAYS,
             activation_keywords=[],

src/chat/planner_actions/planner.py

@@ -109,9 +109,7 @@ class ActionPlanner:
             self.planner_stats["failed_plans"] += 1
             return [], None
 
-    async def _enhanced_plan_flow(
+    async def _enhanced_plan_flow(self, mode: ChatMode, context: StreamContext) -> Tuple[List[Dict], Optional[Dict]]:
-        self, mode: ChatMode, context: StreamContext
-    ) -> Tuple[List[Dict], Optional[Dict]]:
         """执行增强版规划流程"""
         try:
             # 1. 生成初始 Plan
@@ -137,7 +135,9 @@ class ActionPlanner:
             # 检查兴趣度是否达到非回复动作阈值
             non_reply_action_interest_threshold = global_config.affinity_flow.non_reply_action_interest_threshold
             if score < non_reply_action_interest_threshold:
-                logger.info(f"❌ 兴趣度不足非回复动作阈值: {score:.3f} < {non_reply_action_interest_threshold:.3f}，直接返回no_action")
+                logger.info(
+                    f"❌ 兴趣度不足非回复动作阈值: {score:.3f} < {non_reply_action_interest_threshold:.3f}，直接返回no_action"
+                )
                 logger.info(f"📊 最低要求: {non_reply_action_interest_threshold:.3f}")
                 # 直接返回 no_action
                 from src.common.data_models.info_data_model import ActionPlannerInfo

src/chat/replyer/default_generator.py

@@ -598,6 +598,7 @@ class DefaultReplyer:
     def _parse_reply_target(self, target_message: str) -> Tuple[str, str]:
         """解析回复目标消息 - 使用共享工具"""
         from src.chat.utils.prompt import Prompt
+
         if target_message is None:
             logger.warning("target_message为None，返回默认值")
             return "未知用户", "(无消息内容)"
@@ -704,21 +705,23 @@ class DefaultReplyer:
                 unread_history_prompt = ""
                 if unread_messages:
                     # 尝试获取兴趣度评分
-                    interest_scores = await self._get_interest_scores_for_messages([msg.flatten() for msg in unread_messages])
+                    interest_scores = await self._get_interest_scores_for_messages(
+                        [msg.flatten() for msg in unread_messages]
+                    )
 
                     unread_lines = []
                     for msg in unread_messages:
                         msg_id = msg.message_id
-                        msg_time = time.strftime('%H:%M:%S', time.localtime(msg.time))
+                        msg_time = time.strftime("%H:%M:%S", time.localtime(msg.time))
                         msg_content = msg.processed_plain_text
 
                         # 使用与已读历史消息相同的方法获取用户名
                         from src.person_info.person_info import PersonInfoManager, get_person_info_manager
 
                         # 获取用户信息
-                        user_info = getattr(msg, 'user_info', {})
+                        user_info = getattr(msg, "user_info", {})
-                        platform = getattr(user_info, 'platform', '') or getattr(msg, 'platform', '')
+                        platform = getattr(user_info, "platform", "") or getattr(msg, "platform", "")
-                        user_id = getattr(user_info, 'user_id', '') or getattr(msg, 'user_id', '')
+                        user_id = getattr(user_info, "user_id", "") or getattr(msg, "user_id", "")
 
                         # 获取用户名
                         if platform and user_id:
@@ -808,7 +811,7 @@ class DefaultReplyer:
             unread_lines = []
             for msg in unread_messages:
                 msg_id = msg.get("message_id", "")
-                msg_time = time.strftime('%H:%M:%S', time.localtime(msg.get("time", time.time())))
+                msg_time = time.strftime("%H:%M:%S", time.localtime(msg.get("time", time.time())))
                 msg_content = msg.get("processed_plain_text", "")
 
                 # 使用与已读历史消息相同的方法获取用户名
@@ -834,7 +837,9 @@ class DefaultReplyer:
                 unread_lines.append(f"{msg_time} {sender_name}: {msg_content}{interest_text}")
 
             unread_history_prompt_str = "\n".join(unread_lines)
-            unread_history_prompt = f"这是未读历史消息，包含兴趣度评分，请优先对兴趣值高的消息做出动作：\n{unread_history_prompt_str}"
+            unread_history_prompt = (
+                f"这是未读历史消息，包含兴趣度评分，请优先对兴趣值高的消息做出动作：\n{unread_history_prompt_str}"
+            )
         else:
             unread_history_prompt = "暂无未读历史消息"
 
@@ -1052,6 +1057,7 @@ class DefaultReplyer:
             target_user_info = await person_info_manager.get_person_info_by_name(sender)
 
         from src.chat.utils.prompt import Prompt
+
         # 并行执行六个构建任务
         task_results = await asyncio.gather(
             self._time_and_run_task(
@@ -1127,6 +1133,7 @@ class DefaultReplyer:
         schedule_block = ""
         if global_config.planning_system.schedule_enable:
             from src.schedule.schedule_manager import schedule_manager
+
             current_activity = schedule_manager.get_current_activity()
             if current_activity:
                 schedule_block = f"你当前正在：{current_activity}。"
@@ -1139,7 +1146,7 @@ class DefaultReplyer:
         safety_guidelines = global_config.personality.safety_guidelines
         safety_guidelines_block = ""
         if safety_guidelines:
-            guidelines_text = "\n".join(f"{i+1}. {line}" for i, line in enumerate(safety_guidelines))
+            guidelines_text = "\n".join(f"{i + 1}. {line}" for i, line in enumerate(safety_guidelines))
             safety_guidelines_block = f"""### 安全与互动底线
 在任何情况下，你都必须遵守以下由你的设定者为你定义的原则：
 {guidelines_text}

src/chat/utils/chat_message_builder.py

@@ -821,7 +821,7 @@ def build_pic_mapping_info(pic_id_mapping: Dict[str, str]) -> str:
         try:
             with get_db_session() as session:
                 image = session.execute(select(Images).where(Images.image_id == pic_id)).scalar_one_or_none()
-                if image and image.description: # type: ignore
+                if image and image.description:  # type: ignore
                     description = image.description
         except Exception:
             # 如果查询失败，保持默认描述

src/chat/utils/prompt.py

@@ -235,7 +235,7 @@ class Prompt:
         template: str,
         name: Optional[str] = None,
         parameters: Optional[PromptParameters] = None,
-        should_register: bool = True
+        should_register: bool = True,
     ):
         """
         初始化统一提示词
@@ -420,17 +420,19 @@ class Prompt:
             await self._build_normal_chat_context(context_data)
 
         # 补充基础信息
-        context_data.update({
+        context_data.update(
-            "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt,
+            {
-            "extra_info_block": self.parameters.extra_info_block,
+                "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt,
-            "time_block": self.parameters.time_block or f"当前时间：{time.strftime('%Y-%m-%d %H:%M:%S')}",
+                "extra_info_block": self.parameters.extra_info_block,
-            "identity": self.parameters.identity_block,
+                "time_block": self.parameters.time_block or f"当前时间：{time.strftime('%Y-%m-%d %H:%M:%S')}",
-            "schedule_block": self.parameters.schedule_block,
+                "identity": self.parameters.identity_block,
-            "moderation_prompt": self.parameters.moderation_prompt_block,
+                "schedule_block": self.parameters.schedule_block,
-            "reply_target_block": self.parameters.reply_target_block,
+                "moderation_prompt": self.parameters.moderation_prompt_block,
-            "mood_state": self.parameters.mood_prompt,
+                "reply_target_block": self.parameters.reply_target_block,
-            "action_descriptions": self.parameters.action_descriptions,
+                "mood_state": self.parameters.mood_prompt,
-        })
+                "action_descriptions": self.parameters.action_descriptions,
+            }
+        )
 
         total_time = time.time() - start_time
         logger.debug(f"上下文构建完成，总耗时: {total_time:.2f}s")
@@ -446,7 +448,7 @@ class Prompt:
             self.parameters.message_list_before_now_long,
             self.parameters.target_user_info.get("user_id") if self.parameters.target_user_info else "",
             self.parameters.sender,
-            self.parameters.chat_id
+            self.parameters.chat_id,
         )
 
         context_data["read_history_prompt"] = read_history_prompt
@@ -476,8 +478,6 @@ class Prompt:
         except Exception as e:
             logger.error(f"构建S4U历史消息prompt失败: {e}")
 
-
-    
     async def _build_expression_habits(self) -> Dict[str, Any]:
         """构建表达习惯"""
         if not global_config.expression.enable_expression:
@@ -491,10 +491,7 @@ class Prompt:
             if self.parameters.message_list_before_now_long:
                 recent_messages = self.parameters.message_list_before_now_long[-10:]
                 chat_history = build_readable_messages(
-                    recent_messages,
+                    recent_messages, replace_bot_name=True, timestamp_mode="normal", truncate=True
-                    replace_bot_name=True,
-                    timestamp_mode="normal",
-                    truncate=True
                 )
 
             # 创建表情选择器
@@ -505,7 +502,7 @@ class Prompt:
                 chat_history=chat_history,
                 current_message=self.parameters.target,
                 emotional_tone="neutral",
-                topic_type="general"
+                topic_type="general",
             )
 
             # 构建表达习惯块
@@ -535,17 +532,13 @@ class Prompt:
             if self.parameters.message_list_before_now_long:
                 recent_messages = self.parameters.message_list_before_now_long[-20:]
                 chat_history = build_readable_messages(
-                    recent_messages,
+                    recent_messages, replace_bot_name=True, timestamp_mode="normal", truncate=True
-                    replace_bot_name=True,
-                    timestamp_mode="normal",
-                    truncate=True
                 )
 
             # 激活长期记忆
             memory_activator = MemoryActivator()
             running_memories = await memory_activator.activate_memory_with_chat_history(
-                target_message=self.parameters.target,
+                target_message=self.parameters.target, chat_history_prompt=chat_history
-                chat_history_prompt=chat_history
             )
 
             # 获取即时记忆
@@ -593,10 +586,7 @@ class Prompt:
             if self.parameters.message_list_before_now_long:
                 recent_messages = self.parameters.message_list_before_now_long[-15:]
                 chat_history = build_readable_messages(
-                    recent_messages,
+                    recent_messages, replace_bot_name=True, timestamp_mode="normal", truncate=True
-                    replace_bot_name=True,
-                    timestamp_mode="normal",
-                    truncate=True
                 )
 
             # 创建工具执行器
@@ -607,12 +597,12 @@ class Prompt:
                 sender=self.parameters.sender,
                 target_message=self.parameters.target,
                 chat_history=chat_history,
-                return_details=False
+                return_details=False,
             )
 
             # 构建工具信息块
             if tool_results:
-                tool_info_parts = ["## 工具信息","以下是你通过工具获取到的实时信息："]
+                tool_info_parts = ["## 工具信息", "以下是你通过工具获取到的实时信息："]
                 for tool_result in tool_results:
                     tool_name = tool_result.get("tool_name", "unknown")
                     content = tool_result.get("content", "")
@@ -649,15 +639,12 @@ class Prompt:
 
             # 搜索相关知识
             knowledge_results = await qa_manager.get_knowledge(
-                question=question,
+                question=question, chat_id=self.parameters.chat_id, max_results=5, min_similarity=0.5
-                chat_id=self.parameters.chat_id,
-                max_results=5,
-                min_similarity=0.5
             )
 
             # 构建知识块
             if knowledge_results and knowledge_results.get("knowledge_items"):
-                knowledge_parts = ["## 知识库信息","以下是与你当前对话相关的知识信息："]
+                knowledge_parts = ["## 知识库信息", "以下是与你当前对话相关的知识信息："]
 
                 for item in knowledge_results["knowledge_items"]:
                     content = item.get("content", "")
@@ -725,9 +712,11 @@ class Prompt:
             "time_block": context_data.get("time_block", ""),
             "reply_target_block": context_data.get("reply_target_block", ""),
             "reply_style": global_config.personality.reply_style,
-            "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt or context_data.get("keywords_reaction_prompt", ""),
+            "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt
+            or context_data.get("keywords_reaction_prompt", ""),
             "moderation_prompt": self.parameters.moderation_prompt_block or context_data.get("moderation_prompt", ""),
-            "safety_guidelines_block": self.parameters.safety_guidelines_block or context_data.get("safety_guidelines_block", ""),
+            "safety_guidelines_block": self.parameters.safety_guidelines_block
+            or context_data.get("safety_guidelines_block", ""),
         }
 
     def _prepare_normal_params(self, context_data: Dict[str, Any]) -> Dict[str, Any]:
@@ -749,9 +738,11 @@ class Prompt:
             "reply_target_block": context_data.get("reply_target_block", ""),
             "config_expression_style": global_config.personality.reply_style,
             "mood_state": self.parameters.mood_prompt or context_data.get("mood_state", ""),
-            "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt or context_data.get("keywords_reaction_prompt", ""),
+            "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt
+            or context_data.get("keywords_reaction_prompt", ""),
             "moderation_prompt": self.parameters.moderation_prompt_block or context_data.get("moderation_prompt", ""),
-            "safety_guidelines_block": self.parameters.safety_guidelines_block or context_data.get("safety_guidelines_block", ""),
+            "safety_guidelines_block": self.parameters.safety_guidelines_block
+            or context_data.get("safety_guidelines_block", ""),
         }
 
     def _prepare_default_params(self, context_data: Dict[str, Any]) -> Dict[str, Any]:
@@ -769,9 +760,11 @@ class Prompt:
             "reason": "",
             "mood_state": self.parameters.mood_prompt or context_data.get("mood_state", ""),
             "reply_style": global_config.personality.reply_style,
-            "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt or context_data.get("keywords_reaction_prompt", ""),
+            "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt
+            or context_data.get("keywords_reaction_prompt", ""),
             "moderation_prompt": self.parameters.moderation_prompt_block or context_data.get("moderation_prompt", ""),
-            "safety_guidelines_block": self.parameters.safety_guidelines_block or context_data.get("safety_guidelines_block", ""),
+            "safety_guidelines_block": self.parameters.safety_guidelines_block
+            or context_data.get("safety_guidelines_block", ""),
         }
 
     def format(self, *args, **kwargs) -> str:
@@ -872,9 +865,7 @@ class Prompt:
         return await relationship_fetcher.build_relation_info(person_id, points_num=5)
 
     @staticmethod
-    async def build_cross_context(
+    async def build_cross_context(chat_id: str, prompt_mode: str, target_user_info: Optional[Dict[str, Any]]) -> str:
-        chat_id: str, prompt_mode: str, target_user_info: Optional[Dict[str, Any]]
-    ) -> str:
         """
         构建跨群聊上下文 - 统一实现
 
@@ -937,10 +928,7 @@ class Prompt:
 
 # 工厂函数
 def create_prompt(
-    template: str,
+    template: str, name: Optional[str] = None, parameters: Optional[PromptParameters] = None, **kwargs
-    name: Optional[str] = None,
-    parameters: Optional[PromptParameters] = None,
-    **kwargs
 ) -> Prompt:
     """快速创建Prompt实例的工厂函数"""
     if parameters is None:
@@ -949,14 +937,10 @@ def create_prompt(
 
 
 async def create_prompt_async(
-    template: str,
+    template: str, name: Optional[str] = None, parameters: Optional[PromptParameters] = None, **kwargs
-    name: Optional[str] = None,
-    parameters: Optional[PromptParameters] = None,
-    **kwargs
 ) -> Prompt:
     """异步创建Prompt实例"""
     prompt = create_prompt(template, name, parameters, **kwargs)
     if global_prompt_manager._context._current_context:
         await global_prompt_manager._context.register_async(prompt)
     return prompt
-

src/chat/utils/utils.py

@@ -343,7 +343,7 @@ def process_llm_response(text: str, enable_splitter: bool = True, enable_chinese
             if split_mode == "llm":
                 logger.debug("未检测到 [SPLIT] 标记，本次不进行分割。")
                 split_sentences = [cleaned_text]
-            else: # mode == "punctuation"
+            else:  # mode == "punctuation"
                 logger.debug("使用基于标点的传统模式进行分割。")
                 split_sentences = split_into_sentences_w_remove_punctuation(cleaned_text)
     else:

src/common/data_models/__init__.py

@@ -6,6 +6,7 @@ class BaseDataModel:
     def deepcopy(self):
         return copy.deepcopy(self)
 
+
 def temporarily_transform_class_to_dict(obj: Any) -> Any:
     # sourcery skip: assign-if-exp, reintroduce-else
     """

src/common/data_models/bot_interest_data_model.py

@@ -2,6 +2,7 @@
 机器人兴趣标签数据模型
 定义机器人的兴趣标签和相关的embedding数据结构
 """
+
 from dataclasses import dataclass, field
 from typing import List, Dict, Optional, Any
 from datetime import datetime
@@ -12,6 +13,7 @@ from . import BaseDataModel
 @dataclass
 class BotInterestTag(BaseDataModel):
     """机器人兴趣标签"""
+
     tag_name: str
     weight: float = 1.0  # 权重，表示对这个兴趣的喜好程度 (0.0-1.0)
     embedding: Optional[List[float]] = None  # 标签的embedding向量
@@ -27,7 +29,7 @@ class BotInterestTag(BaseDataModel):
             "embedding": self.embedding,
             "created_at": self.created_at.isoformat(),
             "updated_at": self.updated_at.isoformat(),
-            "is_active": self.is_active
+            "is_active": self.is_active,
         }
 
     @classmethod
@@ -39,13 +41,14 @@ class BotInterestTag(BaseDataModel):
             embedding=data.get("embedding"),
             created_at=datetime.fromisoformat(data["created_at"]) if data.get("created_at") else datetime.now(),
             updated_at=datetime.fromisoformat(data["updated_at"]) if data.get("updated_at") else datetime.now(),
-            is_active=data.get("is_active", True)
+            is_active=data.get("is_active", True),
         )
 
 
 @dataclass
 class BotPersonalityInterests(BaseDataModel):
     """机器人人格化兴趣配置"""
+
     personality_id: str
     personality_description: str  # 人设描述文本
     interest_tags: List[BotInterestTag] = field(default_factory=list)
@@ -57,7 +60,6 @@ class BotPersonalityInterests(BaseDataModel):
         """获取活跃的兴趣标签"""
         return [tag for tag in self.interest_tags if tag.is_active]
 
-
     def to_dict(self) -> Dict[str, Any]:
         """转换为字典格式"""
         return {
@@ -66,7 +68,7 @@ class BotPersonalityInterests(BaseDataModel):
             "interest_tags": [tag.to_dict() for tag in self.interest_tags],
             "embedding_model": self.embedding_model,
             "last_updated": self.last_updated.isoformat(),
-            "version": self.version
+            "version": self.version,
         }
 
     @classmethod
@@ -78,13 +80,14 @@ class BotPersonalityInterests(BaseDataModel):
             interest_tags=[BotInterestTag.from_dict(tag_data) for tag_data in data.get("interest_tags", [])],
             embedding_model=data.get("embedding_model", "text-embedding-ada-002"),
             last_updated=datetime.fromisoformat(data["last_updated"]) if data.get("last_updated") else datetime.now(),
-            version=data.get("version", 1)
+            version=data.get("version", 1),
         )
 
 
 @dataclass
 class InterestMatchResult(BaseDataModel):
     """兴趣匹配结果"""
+
     message_id: str
     matched_tags: List[str] = field(default_factory=list)
     match_scores: Dict[str, float] = field(default_factory=dict)  # tag_name -> score
@@ -120,7 +123,9 @@ class InterestMatchResult(BaseDataModel):
         # 计算置信度（基于匹配标签数量和分数分布）
         if len(self.match_scores) > 0:
             avg_score = self.overall_score
-            score_variance = sum((score - avg_score) ** 2 for score in self.match_scores.values()) / len(self.match_scores)
+            score_variance = sum((score - avg_score) ** 2 for score in self.match_scores.values()) / len(
+                self.match_scores
+            )
             # 分数越集中，置信度越高
             self.confidence = max(0.0, 1.0 - score_variance)
         else:

src/common/data_models/database_data_model.py

@@ -208,6 +208,7 @@ class DatabaseMessages(BaseDataModel):
             "chat_info_user_cardname": self.chat_info.user_info.user_cardname,
         }
 
+
 @dataclass(init=False)
 class DatabaseActionRecords(BaseDataModel):
     def __init__(

src/common/data_models/info_data_model.py

@@ -28,6 +28,7 @@ class ActionPlannerInfo(BaseDataModel):
 @dataclass
 class InterestScore(BaseDataModel):
     """兴趣度评分结果"""
+
     message_id: str
     total_score: float
     interest_match_score: float
@@ -41,6 +42,7 @@ class Plan(BaseDataModel):
     """
     统一规划数据模型
     """
+
     chat_id: str
     mode: "ChatMode"
 

src/common/data_models/llm_data_model.py

@@ -2,9 +2,11 @@ from dataclasses import dataclass
 from typing import Optional, List, Tuple, TYPE_CHECKING, Any
 
 from . import BaseDataModel
+
 if TYPE_CHECKING:
     from src.llm_models.payload_content.tool_option import ToolCall
 
+
 @dataclass
 class LLMGenerationDataModel(BaseDataModel):
     content: Optional[str] = None

src/common/data_models/message_manager_data_model.py

@@ -2,6 +2,7 @@
 消息管理模块数据模型
 定义消息管理器使用的数据结构
 """
+
 import asyncio
 import time
 from dataclasses import dataclass, field
@@ -16,14 +17,16 @@ if TYPE_CHECKING:
 
 class MessageStatus(Enum):
     """消息状态枚举"""
-    UNREAD = "unread"    # 未读消息
+
-    READ = "read"        # 已读消息
+    UNREAD = "unread"  # 未读消息
+    READ = "read"  # 已读消息
     PROCESSING = "processing"  # 处理中
 
 
 @dataclass
 class StreamContext(BaseDataModel):
     """聊天流上下文信息"""
+
     stream_id: str
     unread_messages: List["DatabaseMessages"] = field(default_factory=list)
     history_messages: List["DatabaseMessages"] = field(default_factory=list)
@@ -59,6 +62,7 @@ class StreamContext(BaseDataModel):
 @dataclass
 class MessageManagerStats(BaseDataModel):
     """消息管理器统计信息"""
+
     total_streams: int = 0
     active_streams: int = 0
     total_unread_messages: int = 0
@@ -74,6 +78,7 @@ class MessageManagerStats(BaseDataModel):
 @dataclass
 class StreamStats(BaseDataModel):
     """聊天流统计信息"""
+
     stream_id: str
     is_active: bool
     unread_count: int

src/common/remote.py

@@ -31,7 +31,9 @@ class TelemetryHeartBeatTask(AsyncTask):
         self.client_uuid: str | None = local_storage["mofox_uuid"] if "mofox_uuid" in local_storage else None  # type: ignore
         """客户端UUID"""
 
-        self.private_key_pem: str | None = local_storage["mofox_private_key"] if "mofox_private_key" in local_storage else None  # type: ignore
+        self.private_key_pem: str | None = (
+            local_storage["mofox_private_key"] if "mofox_private_key" in local_storage else None
+        )  # type: ignore
         """客户端私钥"""
 
         self.info_dict = self._get_sys_info()
@@ -75,10 +77,7 @@ class TelemetryHeartBeatTask(AsyncTask):
         sign_data = f"{self.client_uuid}:{timestamp}:{json.dumps(request_body, separators=(',', ':'))}"
 
         # 加载私钥
-        private_key = serialization.load_pem_private_key(
+        private_key = serialization.load_pem_private_key(self.private_key_pem.encode("utf-8"), password=None)
-            self.private_key_pem.encode('utf-8'),
-            password=None
-        )
 
         # 确保是RSA私钥
         if not isinstance(private_key, rsa.RSAPrivateKey):
@@ -86,16 +85,13 @@ class TelemetryHeartBeatTask(AsyncTask):
 
         # 生成签名
         signature = private_key.sign(
-            sign_data.encode('utf-8'),
+            sign_data.encode("utf-8"),
-            padding.PSS(
+            padding.PSS(mgf=padding.MGF1(hashes.SHA256()), salt_length=padding.PSS.MAX_LENGTH),
-                mgf=padding.MGF1(hashes.SHA256()),
+            hashes.SHA256(),
-                salt_length=padding.PSS.MAX_LENGTH
-            ),
-            hashes.SHA256()
         )
 
         # Base64编码
-        signature_b64 = base64.b64encode(signature).decode('utf-8')
+        signature_b64 = base64.b64encode(signature).decode("utf-8")
 
         return timestamp, signature_b64
 
@@ -113,10 +109,7 @@ class TelemetryHeartBeatTask(AsyncTask):
             raise ValueError("私钥未初始化")
 
         # 加载私钥
-        private_key = serialization.load_pem_private_key(
+        private_key = serialization.load_pem_private_key(self.private_key_pem.encode("utf-8"), password=None)
-            self.private_key_pem.encode('utf-8'),
-            password=None
-        )
 
         # 确保是RSA私钥
         if not isinstance(private_key, rsa.RSAPrivateKey):
@@ -125,14 +118,10 @@ class TelemetryHeartBeatTask(AsyncTask):
         # 解密挑战数据
         decrypted_bytes = private_key.decrypt(
             base64.b64decode(challenge_b64),
-            padding.OAEP(
+            padding.OAEP(mgf=padding.MGF1(hashes.SHA256()), algorithm=hashes.SHA256(), label=None),
-                mgf=padding.MGF1(hashes.SHA256()),
-                algorithm=hashes.SHA256(),
-                label=None
-            )
         )
 
-        return decrypted_bytes.decode('utf-8')
+        return decrypted_bytes.decode("utf-8")
 
     async def _req_uuid(self) -> bool:
         """
@@ -155,14 +144,12 @@ class TelemetryHeartBeatTask(AsyncTask):
 
                         if response.status != 200:
                             response_text = await response.text()
-                            logger.error(
+                            logger.error(f"注册步骤1失败，状态码: {response.status}, 响应内容: {response_text}")
-                                f"注册步骤1失败，状态码: {response.status}, 响应内容: {response_text}"
-                            )
                             raise aiohttp.ClientResponseError(
                                 request_info=response.request_info,
                                 history=response.history,
                                 status=response.status,
-                                message=f"Step1 failed: {response_text}"
+                                message=f"Step1 failed: {response_text}",
                             )
 
                         step1_data = await response.json()
@@ -195,10 +182,7 @@ class TelemetryHeartBeatTask(AsyncTask):
                     # Step 2: 发送解密结果完成注册
                     async with session.post(
                         f"{TELEMETRY_SERVER_URL}/stat/reg_client_step2",
-                        json={
+                        json={"temp_uuid": temp_uuid, "decrypted_uuid": decrypted_uuid},
-                            "temp_uuid": temp_uuid,
-                            "decrypted_uuid": decrypted_uuid
-                        },
                         timeout=aiohttp.ClientTimeout(total=5),
                     ) as response:
                         logger.debug(f"Step2 Response status: {response.status}")
@@ -225,23 +209,19 @@ class TelemetryHeartBeatTask(AsyncTask):
                             raise ValueError(f"Step2失败: {response_text}")
                         else:
                             response_text = await response.text()
-                            logger.error(
+                            logger.error(f"注册步骤2失败，状态码: {response.status}, 响应内容: {response_text}")
-                                f"注册步骤2失败，状态码: {response.status}, 响应内容: {response_text}"
-                            )
                             raise aiohttp.ClientResponseError(
                                 request_info=response.request_info,
                                 history=response.history,
                                 status=response.status,
-                                message=f"Step2 failed: {response_text}"
+                                message=f"Step2 failed: {response_text}",
                             )
 
             except Exception as e:
                 import traceback
 
                 error_msg = str(e) or "未知错误"
-                logger.warning(
+                logger.warning(f"注册客户端出错，不过你还是可以正常使用墨狐: {type(e).__name__}: {error_msg}")
-                    f"注册客户端出错，不过你还是可以正常使用墨狐: {type(e).__name__}: {error_msg}"
-                )
                 logger.debug(f"完整错误信息: {traceback.format_exc()}")
 
             # 请求失败，重试次数+1
@@ -270,7 +250,7 @@ class TelemetryHeartBeatTask(AsyncTask):
                 "X-mofox-Signature": signature,
                 "X-mofox-Timestamp": timestamp,
                 "User-Agent": f"MofoxClient/{self.client_uuid[:8]}",
-                "Content-Type": "application/json"
+                "Content-Type": "application/json",
             }
 
             logger.debug(f"正在发送心跳到服务器: {self.server_url}")

src/common/server.py

@@ -99,7 +99,6 @@ def get_global_server() -> Server:
     """获取全局服务器实例"""
     global global_server
     if global_server is None:
-        
         host = os.getenv("HOST", "127.0.0.1")
         port_str = os.getenv("PORT", "8000")
 

src/config/config.py

@@ -44,7 +44,7 @@ from src.config.official_configs import (
     PermissionConfig,
     CommandConfig,
     PlanningSystemConfig,
-    AffinityFlowConfig
+    AffinityFlowConfig,
 )
 
 from .api_ada_configs import (
@@ -399,9 +399,7 @@ class Config(ValidatedConfigBase):
     cross_context: CrossContextConfig = Field(
         default_factory=lambda: CrossContextConfig(), description="跨群聊上下文共享配置"
     )
-    affinity_flow: AffinityFlowConfig = Field(
+    affinity_flow: AffinityFlowConfig = Field(default_factory=lambda: AffinityFlowConfig(), description="亲和流配置")
-        default_factory=lambda: AffinityFlowConfig(), description="亲和流配置"
-    )
 
 
 class APIAdapterConfig(ValidatedConfigBase):

src/config/official_configs.py

@@ -51,8 +51,12 @@ class PersonalityConfig(ValidatedConfigBase):
     personality_core: str = Field(..., description="核心人格")
     personality_side: str = Field(..., description="人格侧写")
     identity: str = Field(default="", description="身份特征")
-    background_story: str = Field(default="", description="世界观背景故事，这部分内容会作为背景知识，LLM被指导不应主动复述")
+    background_story: str = Field(
-    safety_guidelines: List[str] = Field(default_factory=list, description="安全与互动底线，Bot在任何情况下都必须遵守的原则")
+        default="", description="世界观背景故事，这部分内容会作为背景知识，LLM被指导不应主动复述"
+    )
+    safety_guidelines: List[str] = Field(
+        default_factory=list, description="安全与互动底线，Bot在任何情况下都必须遵守的原则"
+    )
     reply_style: str = Field(default="", description="表达风格")
     prompt_mode: Literal["s4u", "normal"] = Field(default="s4u", description="Prompt模式")
     compress_personality: bool = Field(default=True, description="是否压缩人格")
@@ -79,7 +83,8 @@ class ChatConfig(ValidatedConfigBase):
     talk_frequency_adjust: list[list[str]] = Field(default_factory=lambda: [], description="聊天频率调整")
     focus_value: float = Field(default=1.0, description="专注值")
     focus_mode_quiet_groups: List[str] = Field(
-        default_factory=list, description='专注模式下需要保持安静的群组列表, 格式: ["platform:group_id1", "platform:group_id2"]'
+        default_factory=list,
+        description='专注模式下需要保持安静的群组列表, 格式: ["platform:group_id1", "platform:group_id2"]',
     )
     force_reply_private: bool = Field(default=False, description="强制回复私聊")
     group_chat_mode: Literal["auto", "normal", "focus"] = Field(default="auto", description="群聊模式")
@@ -343,6 +348,7 @@ class ExpressionConfig(ValidatedConfigBase):
         # 如果都没有匹配，返回默认值
         return True, True, 1.0
 
+
 class ToolConfig(ValidatedConfigBase):
     """工具配置类"""
 
@@ -477,7 +483,6 @@ class ExperimentalConfig(ValidatedConfigBase):
     pfc_chatting: bool = Field(default=False, description="启用PFC聊天")
 
 
-
 class MaimMessageConfig(ValidatedConfigBase):
     """maim_message配置类"""
 
@@ -602,8 +607,12 @@ class SleepSystemConfig(ValidatedConfigBase):
     sleep_by_schedule: bool = Field(default=True, description="是否根据日程表进行睡觉")
     fixed_sleep_time: str = Field(default="23:00", description="固定的睡觉时间")
     fixed_wake_up_time: str = Field(default="07:00", description="固定的起床时间")
-    sleep_time_offset_minutes: int = Field(default=15, ge=0, le=60, description="睡觉时间随机偏移量范围（分钟），实际睡觉时间会在±该值范围内随机")
+    sleep_time_offset_minutes: int = Field(
-    wake_up_time_offset_minutes: int = Field(default=15, ge=0, le=60, description="起床时间随机偏移量范围（分钟），实际起床时间会在±该值范围内随机")
+        default=15, ge=0, le=60, description="睡觉时间随机偏移量范围（分钟），实际睡觉时间会在±该值范围内随机"
+    )
+    wake_up_time_offset_minutes: int = Field(
+        default=15, ge=0, le=60, description="起床时间随机偏移量范围（分钟），实际起床时间会在±该值范围内随机"
+    )
     wakeup_threshold: float = Field(default=15.0, ge=1.0, description="唤醒阈值，达到此值时会被唤醒")
     private_message_increment: float = Field(default=3.0, ge=0.1, description="私聊消息增加的唤醒度")
     group_mention_increment: float = Field(default=2.0, ge=0.1, description="群聊艾特增加的唤醒度")
@@ -618,10 +627,10 @@ class SleepSystemConfig(ValidatedConfigBase):
     # --- 失眠机制相关参数 ---
     enable_insomnia_system: bool = Field(default=True, description="是否启用失眠系统")
     insomnia_trigger_delay_minutes: List[int] = Field(
-        default_factory=lambda:[30, 60], description="入睡后触发失眠判定的延迟时间范围（分钟）"
+        default_factory=lambda: [30, 60], description="入睡后触发失眠判定的延迟时间范围（分钟）"
     )
     insomnia_duration_minutes: List[int] = Field(
-        default_factory=lambda:[15, 45], description="单次失眠状态的持续时间范围（分钟）"
+        default_factory=lambda: [15, 45], description="单次失眠状态的持续时间范围（分钟）"
     )
     sleep_pressure_threshold: float = Field(default=30.0, description="触发“压力不足型失眠”的睡眠压力阈值")
     deep_sleep_threshold: float = Field(default=80.0, description="进入“深度睡眠”的睡眠压力阈值")
@@ -657,6 +666,8 @@ class CrossContextConfig(ValidatedConfigBase):
 
     enable: bool = Field(default=False, description="是否启用跨群聊上下文共享功能")
     groups: List[ContextGroup] = Field(default_factory=list, description="上下文共享组列表")
+
+
 class CommandConfig(ValidatedConfigBase):
     """命令系统配置类"""
 

src/individuality/individuality.py

@@ -88,8 +88,7 @@ class Individuality:
 
         # 初始化智能兴趣系统
         await interest_scoring_system.initialize_smart_interests(
-            personality_description=full_personality,
+            personality_description=full_personality, personality_id=self.bot_person_id
-            personality_id=self.bot_person_id
         )
 
         logger.info("智能兴趣系统初始化完成")

src/main.py

@@ -130,7 +130,8 @@ class MainSystem:
             # 停止消息重组器
             from src.plugin_system.core.event_manager import event_manager
             from src.plugin_system import EventType
-            asyncio.run(event_manager.trigger_event(EventType.ON_STOP,permission_group="SYSTEM"))
+
+            asyncio.run(event_manager.trigger_event(EventType.ON_STOP, permission_group="SYSTEM"))
             from src.utils.message_chunker import reassembler
 
             loop = asyncio.get_event_loop()
@@ -250,6 +251,7 @@ MoFox_Bot(第三方修改版)
 
         # 初始化回复后关系追踪系统
         from src.chat.affinity_flow.relationship_integration import initialize_relationship_tracking
+
         relationship_tracker = initialize_relationship_tracking()
         if relationship_tracker:
             logger.info("回复后关系追踪系统初始化成功")
@@ -273,6 +275,7 @@ MoFox_Bot(第三方修改版)
 
         # 初始化LPMM知识库
         from src.chat.knowledge.knowledge_lib import initialize_lpmm_knowledge
+
         initialize_lpmm_knowledge()
         logger.info("LPMM知识库初始化成功")
 
@@ -298,6 +301,7 @@ MoFox_Bot(第三方修改版)
 
         # 启动消息管理器
         from src.chat.message_manager import message_manager
+
         await message_manager.start()
         logger.info("消息管理器已启动")
 

src/person_info/person_info.py

@@ -102,6 +102,7 @@ class PersonInfoManager:
             return hashlib.md5(key.encode()).hexdigest()
 
         qq_id = hashlib.md5(key.encode()).hexdigest()
+
         # 对于 qq 平台，先检查该 person_id 是否已存在；如果存在直接返回
         def _db_check_and_migrate_sync(p_id: str, raw_user_id: str):
             try:

src/person_info/relationship_fetcher.py

@@ -123,7 +123,9 @@ class RelationshipFetcher:
         all_points = current_points + forgotten_points
         if all_points:
             # 按权重和时效性综合排序
-            all_points.sort(key=lambda x: (float(x[1]) if len(x) > 1 else 0, float(x[2]) if len(x) > 2 else 0), reverse=True)
+            all_points.sort(
+                key=lambda x: (float(x[1]) if len(x) > 1 else 0, float(x[2]) if len(x) > 2 else 0), reverse=True
+            )
             selected_points = all_points[:points_num]
             points_text = "\n".join([f"- {point[0]}（{point[2]}）" for point in selected_points if len(point) > 2])
         else:
@@ -139,7 +141,8 @@ class RelationshipFetcher:
         # 2. 认识时间和频率
         if know_since:
             from datetime import datetime
-            know_time = datetime.fromtimestamp(know_since).strftime('%Y年%m月%d日')
+
+            know_time = datetime.fromtimestamp(know_since).strftime("%Y年%m月%d日")
             relation_parts.append(f"你从{know_time}开始认识{person_name}")
 
         if know_times > 0:
@@ -147,7 +150,8 @@ class RelationshipFetcher:
 
         if last_know:
             from datetime import datetime
-            last_time = datetime.fromtimestamp(last_know).strftime('%m月%d日')
+
+            last_time = datetime.fromtimestamp(last_know).strftime("%m月%d日")
             relation_parts.append(f"最近一次交流是在{last_time}")
 
         # 3. 态度和印象
@@ -173,7 +177,7 @@ class RelationshipFetcher:
             relationships = await db_query(
                 UserRelationships,
                 filters=[UserRelationships.user_id == str(person_info_manager.get_value_sync(person_id, "user_id"))],
-                limit=1
+                limit=1,
             )
 
             if relationships:
@@ -189,7 +193,9 @@ class RelationshipFetcher:
 
         # 构建最终的关系信息字符串
         if relation_parts:
-            relation_info = f"关于{person_name}，你知道以下信息：\n" + "\n".join([f"• {part}" for part in relation_parts])
+            relation_info = f"关于{person_name}，你知道以下信息：\n" + "\n".join(
+                [f"• {part}" for part in relation_parts]
+            )
         else:
             relation_info = f"你对{person_name}了解不多，这是比较初步的交流。"
 

src/plugin_system/base/base_action.py

@@ -93,7 +93,6 @@ class BaseAction(ABC):
         self.associated_types: list[str] = getattr(self.__class__, "associated_types", []).copy()
         self.chat_type_allow: ChatType = getattr(self.__class__, "chat_type_allow", ChatType.ALL)
 
-
         # =============================================================================
         # 便捷属性 - 直接在初始化时获取常用聊天信息（带类型注解）
         # =============================================================================
@@ -398,6 +397,7 @@ class BaseAction(ABC):
         try:
             # 1. 从注册中心获取Action类
             from src.plugin_system.core.component_registry import component_registry
+
             action_class = component_registry.get_component_class(action_name, ComponentType.ACTION)
             if not action_class:
                 logger.error(f"{log_prefix} 未找到Action: {action_name}")

src/plugin_system/base/base_events_handler.py

@@ -107,7 +107,7 @@ class BaseEventHandler(ABC):
         """
         self.plugin_name = plugin_name
 
-    def set_plugin_config(self,plugin_config) -> None:
+    def set_plugin_config(self, plugin_config) -> None:
         self.plugin_config = plugin_config
 
     def get_config(self, key: str, default=None):

src/plugin_system/base/component_types.py

@@ -69,7 +69,7 @@ class EventType(Enum):
     """
 
     ON_START = "on_start"  # 启动事件，用于调用按时任务
-    ON_STOP ="on_stop"
+    ON_STOP = "on_stop"
     ON_MESSAGE = "on_message"
     ON_PLAN = "on_plan"
     POST_LLM = "post_llm"

src/plugin_system/core/component_registry.py

@@ -270,7 +270,9 @@ class ComponentRegistry:
         # 使用EventManager进行事件处理器注册
         from src.plugin_system.core.event_manager import event_manager
 
-        return event_manager.register_event_handler(handler_class,self.get_plugin_config(handler_info.plugin_name) or {})
+        return event_manager.register_event_handler(
+            handler_class, self.get_plugin_config(handler_info.plugin_name) or {}
+        )
 
     # === 组件移除相关 ===
 
@@ -686,9 +688,10 @@ class ComponentRegistry:
         # 如果插件实例不存在，尝试从配置文件读取
         try:
             import toml
+
             config_path = Path("config") / "plugins" / plugin_name / "config.toml"
             if config_path.exists():
-                with open(config_path, 'r', encoding='utf-8') as f:
+                with open(config_path, "r", encoding="utf-8") as f:
                     config_data = toml.load(f)
                     logger.debug(f"从配置文件读取插件 {plugin_name} 的配置")
                     return config_data

src/plugin_system/core/event_manager.py

@@ -145,7 +145,9 @@ class EventManager:
         logger.info(f"事件 {event_name} 已禁用")
         return True
 
-    def register_event_handler(self, handler_class: Type[BaseEventHandler], plugin_config: Optional[dict] = None) -> bool:
+    def register_event_handler(
+        self, handler_class: Type[BaseEventHandler], plugin_config: Optional[dict] = None
+    ) -> bool:
         """注册事件处理器
 
         Args:
@@ -167,7 +169,7 @@ class EventManager:
         # 创建事件处理器实例，传递插件配置
         handler_instance = handler_class()
         handler_instance.plugin_config = plugin_config
-        if plugin_config is not None and hasattr(handler_instance, 'set_plugin_config'):
+        if plugin_config is not None and hasattr(handler_instance, "set_plugin_config"):
             handler_instance.set_plugin_config(plugin_config)
 
         self._event_handlers[handler_name] = handler_instance

src/plugin_system/core/plugin_manager.py

@@ -199,9 +199,7 @@ class PluginManager:
                 self._show_plugin_components(plugin_name)
 
                 # 检查并调用 on_plugin_loaded 钩子（如果存在）
-                if hasattr(plugin_instance, "on_plugin_loaded") and callable(
+                if hasattr(plugin_instance, "on_plugin_loaded") and callable(plugin_instance.on_plugin_loaded):
-                    plugin_instance.on_plugin_loaded
-                ):
                     logger.debug(f"为插件 '{plugin_name}' 调用 on_plugin_loaded 钩子")
                     try:
                         # 使用 asyncio.create_task 确保它不会阻塞加载流程

src/plugins/built_in/at_user_plugin/plugin.py

@@ -85,7 +85,7 @@ class AtAction(BaseAction):
                 reply_to=reply_to,
                 extra_info=extra_info,
                 enable_tool=False,  # 艾特回复通常不需要工具调用
-                from_plugin=False
+                from_plugin=False,
             )
 
             if success and llm_response:

src/plugins/built_in/core_actions/emoji.py

@@ -70,7 +70,9 @@ class EmojiAction(BaseAction):
 
             # 2. 获取所有有效的表情包对象
             emoji_manager = get_emoji_manager()
-            all_emojis_obj: list[MaiEmoji] = [e for e in emoji_manager.emoji_objects if not e.is_deleted and e.description]
+            all_emojis_obj: list[MaiEmoji] = [
+                e for e in emoji_manager.emoji_objects if not e.is_deleted and e.description
+            ]
             if not all_emojis_obj:
                 logger.warning(f"{self.log_prefix} 无法获取任何带有描述的有效表情包")
                 return False, "无法获取任何带有描述的有效表情包"
@@ -171,7 +173,9 @@ class EmojiAction(BaseAction):
 
                         if matched_key:
                             emoji_base64, emoji_description = random.choice(emotion_map[matched_key])
-                            logger.info(f"{self.log_prefix} 找到匹配情感 '{chosen_emotion}' (匹配到: '{matched_key}') 的表情包: {emoji_description}")
+                            logger.info(
+                                f"{self.log_prefix} 找到匹配情感 '{chosen_emotion}' (匹配到: '{matched_key}') 的表情包: {emoji_description}"
+                            )
                         else:
                             logger.warning(
                                 f"{self.log_prefix} LLM选择的情感 '{chosen_emotion}' 不在可用列表中, 将随机选择一个表情包"
@@ -226,15 +230,23 @@ class EmojiAction(BaseAction):
                     logger.info(f"{self.log_prefix} LLM选择的描述: {chosen_description}")
 
                     # 简单关键词匹配
-                    matched_emoji = next((item for item in all_emojis_data if chosen_description.lower() in item[1].lower() or item[1].lower() in chosen_description.lower()), None)
+                    matched_emoji = next(
+                        (
+                            item
+                            for item in all_emojis_data
+                            if chosen_description.lower() in item[1].lower()
+                            or item[1].lower() in chosen_description.lower()
+                        ),
+                        None,
+                    )
 
                     # 如果包含匹配失败，尝试关键词匹配
                     if not matched_emoji:
-                        keywords = ['惊讶', '困惑', '呆滞', '震惊', '懵', '无语', '萌', '可爱']
+                        keywords = ["惊讶", "困惑", "呆滞", "震惊", "懵", "无语", "萌", "可爱"]
                         for keyword in keywords:
                             if keyword in chosen_description:
                                 for item in all_emojis_data:
-                                    if any(k in item[1] for k in ['呆', '萌', '惊', '困惑', '无语']):
+                                    if any(k in item[1] for k in ["呆", "萌", "惊", "困惑", "无语"]):
                                         matched_emoji = item
                                         break
                                 if matched_emoji:
@@ -255,7 +267,9 @@ class EmojiAction(BaseAction):
 
             if not success:
                 logger.error(f"{self.log_prefix} 表情包发送失败")
-                await self.store_action_info(action_build_into_prompt = True,action_prompt_display =f"发送了一个表情包,但失败了",action_done= False)
+                await self.store_action_info(
+                    action_build_into_prompt=True, action_prompt_display=f"发送了一个表情包,但失败了", action_done=False
+                )
                 return False, "表情包发送失败"
 
             # 发送成功后，记录到历史
@@ -264,7 +278,9 @@ class EmojiAction(BaseAction):
             except Exception as e:
                 logger.error(f"{self.log_prefix} 添加表情到历史记录时出错: {e}")
 
-            await self.store_action_info(action_build_into_prompt = True,action_prompt_display =f"发送了一个表情包",action_done= True)
+            await self.store_action_info(
+                action_build_into_prompt=True, action_prompt_display=f"发送了一个表情包", action_done=True
+            )
 
             return True, f"发送表情包: {emoji_description}"
 

src/plugins/built_in/napcat_adapter_plugin/event_handlers.py

@@ -1,4 +1,3 @@
-
 from src.plugin_system import BaseEventHandler
 from src.plugin_system.base.base_event import HandlerResult
 
@@ -1748,6 +1747,7 @@ class SetGroupSignHandler(BaseEventHandler):
             logger.error("事件 napcat_set_group_sign 请求失败！")
             return HandlerResult(False, False, {"status": "error"})
 
+
 # ===PERSONAL===
 class SetInputStatusHandler(BaseEventHandler):
     handler_name: str = "napcat_set_input_status_handler"

src/plugins/built_in/napcat_adapter_plugin/plugin.py

@@ -285,7 +285,7 @@ class NapcatAdapterPlugin(BasePlugin):
     def enable_plugin(self) -> bool:
         """通过配置文件动态控制插件启用状态"""
         # 如果已经通过配置加载了状态，使用配置中的值
-        if hasattr(self, '_is_enabled'):
+        if hasattr(self, "_is_enabled"):
             return self._is_enabled
         # 否则使用默认值（禁用状态）
         return False
@@ -308,60 +308,107 @@ class NapcatAdapterPlugin(BasePlugin):
             "nickname": ConfigField(type=str, default="", description="昵称配置（目前未使用）"),
         },
         "napcat_server": {
-            "mode": ConfigField(type=str, default="reverse", description="连接模式：reverse=反向连接(作为服务器), forward=正向连接(作为客户端)", choices=["reverse", "forward"]),
+            "mode": ConfigField(
+                type=str,
+                default="reverse",
+                description="连接模式：reverse=反向连接(作为服务器), forward=正向连接(作为客户端)",
+                choices=["reverse", "forward"],
+            ),
             "host": ConfigField(type=str, default="localhost", description="主机地址"),
             "port": ConfigField(type=int, default=8095, description="端口号"),
-            "url": ConfigField(type=str, default="", description="正向连接时的完整WebSocket URL，如 ws://localhost:8080/ws (仅在forward模式下使用)"),
+            "url": ConfigField(
-            "access_token": ConfigField(type=str, default="", description="WebSocket 连接的访问令牌，用于身份验证（可选）"),
+                type=str,
+                default="",
+                description="正向连接时的完整WebSocket URL，如 ws://localhost:8080/ws (仅在forward模式下使用)",
+            ),
+            "access_token": ConfigField(
+                type=str, default="", description="WebSocket 连接的访问令牌，用于身份验证（可选）"
+            ),
             "heartbeat_interval": ConfigField(type=int, default=30, description="心跳间隔时间（按秒计）"),
         },
         "maibot_server": {
-            "host": ConfigField(type=str, default="localhost", description="麦麦在.env文件中设置的主机地址，即HOST字段"),
+            "host": ConfigField(
+                type=str, default="localhost", description="麦麦在.env文件中设置的主机地址，即HOST字段"
+            ),
             "port": ConfigField(type=int, default=8000, description="麦麦在.env文件中设置的端口，即PORT字段"),
             "platform_name": ConfigField(type=str, default="qq", description="平台名称，用于消息路由"),
         },
         "voice": {
-            "use_tts": ConfigField(type=bool, default=False, description="是否使用tts语音（请确保你配置了tts并有对应的adapter）"),
+            "use_tts": ConfigField(
+                type=bool, default=False, description="是否使用tts语音（请确保你配置了tts并有对应的adapter）"
+            ),
         },
         "slicing": {
-            "max_frame_size": ConfigField(type=int, default=64, description="WebSocket帧的最大大小，单位为字节，默认64KB"),
+            "max_frame_size": ConfigField(
+                type=int, default=64, description="WebSocket帧的最大大小，单位为字节，默认64KB"
+            ),
             "delay_ms": ConfigField(type=int, default=10, description="切片发送间隔时间，单位为毫秒"),
         },
         "debug": {
-            "level": ConfigField(type=str, default="INFO", description="日志等级（DEBUG, INFO, WARNING, ERROR, CRITICAL）", choices=["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]),
+            "level": ConfigField(
+                type=str,
+                default="INFO",
+                description="日志等级（DEBUG, INFO, WARNING, ERROR, CRITICAL）",
+                choices=["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"],
+            ),
         },
         "features": {
             # 权限设置
-            "group_list_type": ConfigField(type=str, default="blacklist", description="群聊列表类型：whitelist（白名单）或 blacklist（黑名单）", choices=["whitelist", "blacklist"]),
+            "group_list_type": ConfigField(
+                type=str,
+                default="blacklist",
+                description="群聊列表类型：whitelist（白名单）或 blacklist（黑名单）",
+                choices=["whitelist", "blacklist"],
+            ),
             "group_list": ConfigField(type=list, default=[], description="群聊ID列表"),
-            "private_list_type": ConfigField(type=str, default="blacklist", description="私聊列表类型：whitelist（白名单）或 blacklist（黑名单）", choices=["whitelist", "blacklist"]),
+            "private_list_type": ConfigField(
+                type=str,
+                default="blacklist",
+                description="私聊列表类型：whitelist（白名单）或 blacklist（黑名单）",
+                choices=["whitelist", "blacklist"],
+            ),
             "private_list": ConfigField(type=list, default=[], description="用户ID列表"),
-            "ban_user_id": ConfigField(type=list, default=[], description="全局禁止用户ID列表，这些用户无法在任何地方使用机器人"),
+            "ban_user_id": ConfigField(
+                type=list, default=[], description="全局禁止用户ID列表，这些用户无法在任何地方使用机器人"
+            ),
             "ban_qq_bot": ConfigField(type=bool, default=False, description="是否屏蔽QQ官方机器人消息"),
-            
             # 聊天功能设置
             "enable_poke": ConfigField(type=bool, default=True, description="是否启用戳一戳功能"),
             "ignore_non_self_poke": ConfigField(type=bool, default=False, description="是否无视不是针对自己的戳一戳"),
-            "poke_debounce_seconds": ConfigField(type=int, default=3, description="戳一戳防抖时间（秒），在指定时间内第二次针对机器人的戳一戳将被忽略"),
+            "poke_debounce_seconds": ConfigField(
+                type=int, default=3, description="戳一戳防抖时间（秒），在指定时间内第二次针对机器人的戳一戳将被忽略"
+            ),
             "enable_reply_at": ConfigField(type=bool, default=True, description="是否启用引用回复时艾特用户的功能"),
             "reply_at_rate": ConfigField(type=float, default=0.5, description="引用回复时艾特用户的几率 (0.0 ~ 1.0)"),
             "enable_emoji_like": ConfigField(type=bool, default=True, description="是否启用群聊表情回复功能"),
-            
             # 视频处理设置
             "enable_video_analysis": ConfigField(type=bool, default=True, description="是否启用视频识别功能"),
             "max_video_size_mb": ConfigField(type=int, default=100, description="视频文件最大大小限制（MB）"),
             "download_timeout": ConfigField(type=int, default=60, description="视频下载超时时间（秒）"),
-            "supported_formats": ConfigField(type=list, default=["mp4", "avi", "mov", "mkv", "flv", "wmv", "webm"], description="支持的视频格式"),
+            "supported_formats": ConfigField(
-            
+                type=list, default=["mp4", "avi", "mov", "mkv", "flv", "wmv", "webm"], description="支持的视频格式"
+            ),
             # 消息缓冲设置
             "enable_message_buffer": ConfigField(type=bool, default=True, description="是否启用消息缓冲合并功能"),
             "message_buffer_enable_group": ConfigField(type=bool, default=True, description="是否启用群聊消息缓冲合并"),
-            "message_buffer_enable_private": ConfigField(type=bool, default=True, description="是否启用私聊消息缓冲合并"),
+            "message_buffer_enable_private": ConfigField(
-            "message_buffer_interval": ConfigField(type=float, default=3.0, description="消息合并间隔时间（秒），在此时间内的连续消息将被合并"),
+                type=bool, default=True, description="是否启用私聊消息缓冲合并"
-            "message_buffer_initial_delay": ConfigField(type=float, default=0.5, description="消息缓冲初始延迟（秒），收到第一条消息后等待此时间开始合并"),
+            ),
-            "message_buffer_max_components": ConfigField(type=int, default=50, description="单个会话最大缓冲消息组件数量，超过此数量将强制合并"),
+            "message_buffer_interval": ConfigField(
-            "message_buffer_block_prefixes": ConfigField(type=list, default=["/", "!", "！", ".", "。", "#", "%"], description="消息缓冲屏蔽前缀，以这些前缀开头的消息不会被缓冲"),
+                type=float, default=3.0, description="消息合并间隔时间（秒），在此时间内的连续消息将被合并"
-        }
+            ),
+            "message_buffer_initial_delay": ConfigField(
+                type=float, default=0.5, description="消息缓冲初始延迟（秒），收到第一条消息后等待此时间开始合并"
+            ),
+            "message_buffer_max_components": ConfigField(
+                type=int, default=50, description="单个会话最大缓冲消息组件数量，超过此数量将强制合并"
+            ),
+            "message_buffer_block_prefixes": ConfigField(
+                type=list,
+                default=["/", "!", "！", ".", "。", "#", "%"],
+                description="消息缓冲屏蔽前缀，以这些前缀开头的消息不会被缓冲",
+            ),
+        },
     }
 
     # 配置节描述
@@ -374,7 +421,7 @@ class NapcatAdapterPlugin(BasePlugin):
         "voice": "发送语音设置",
         "slicing": "WebSocket消息切片设置",
         "debug": "调试设置",
-        "features": "功能设置（权限控制、聊天功能、视频处理、消息缓冲等）"
+        "features": "功能设置（权限控制、聊天功能、视频处理、消息缓冲等）",
     }
 
     def register_events(self):
@@ -409,6 +456,7 @@ class NapcatAdapterPlugin(BasePlugin):
         chunker.set_plugin_config(self.config)
         # 设置response_pool的插件配置
         from .src.response_pool import set_plugin_config as set_response_pool_config
+
         set_response_pool_config(self.config)
         # 设置send_handler的插件配置
         send_handler.set_plugin_config(self.config)

src/plugins/built_in/napcat_adapter_plugin/src/message_buffer.py

@@ -102,7 +102,9 @@ class SimpleMessageBuffer:
             return True
 
         # 检查屏蔽前缀
-        block_prefixes = tuple(config_api.get_plugin_config(self.plugin_config, "features.message_buffer_block_prefixes", []))
+        block_prefixes = tuple(
+            config_api.get_plugin_config(self.plugin_config, "features.message_buffer_block_prefixes", [])
+        )
 
         text = text.strip()
         if text.startswith(block_prefixes):
@@ -134,9 +136,13 @@ class SimpleMessageBuffer:
 
         # 检查是否启用对应类型的缓冲
         message_type = event_data.get("message_type", "")
-        if message_type == "group" and not config_api.get_plugin_config(self.plugin_config, "features.message_buffer_enable_group", False):
+        if message_type == "group" and not config_api.get_plugin_config(
+            self.plugin_config, "features.message_buffer_enable_group", False
+        ):
             return False
-        elif message_type == "private" and not config_api.get_plugin_config(self.plugin_config, "features.message_buffer_enable_private", False):
+        elif message_type == "private" and not config_api.get_plugin_config(
+            self.plugin_config, "features.message_buffer_enable_private", False
+        ):
             return False
 
         # 提取文本
@@ -158,7 +164,9 @@ class SimpleMessageBuffer:
             session = self.buffer_pool[session_id]
 
             # 检查是否超过最大组件数量
-            if len(session.messages) >= config_api.get_plugin_config(self.plugin_config, "features.message_buffer_max_components", 5):
+            if len(session.messages) >= config_api.get_plugin_config(
+                self.plugin_config, "features.message_buffer_max_components", 5
+            ):
                 logger.debug(f"会话 {session_id} 消息数量达到上限，强制合并")
                 asyncio.create_task(self._force_merge_session(session_id))
                 self.buffer_pool[session_id] = BufferedSession(session_id=session_id, original_event=original_event)

src/plugins/built_in/napcat_adapter_plugin/src/recv_handler/__init__.py

@@ -32,7 +32,7 @@ class NoticeType:  # 通知事件
     group_recall = "group_recall"  # 群聊消息撤回
     notify = "notify"
     group_ban = "group_ban"  # 群禁言
-    group_msg_emoji_like = "group_msg_emoji_like"   # 群聊表情回复
+    group_msg_emoji_like = "group_msg_emoji_like"  # 群聊表情回复
 
     class Notify:
         poke = "poke"  # 戳一戳

src/plugins/built_in/napcat_adapter_plugin/src/recv_handler/message_handler.py

@@ -111,7 +111,9 @@ class MessageHandler:
                     return False
         else:
             # 检查私聊黑白名单
-            private_list_type = config_api.get_plugin_config(self.plugin_config, "features.private_list_type", "blacklist")
+            private_list_type = config_api.get_plugin_config(
+                self.plugin_config, "features.private_list_type", "blacklist"
+            )
             private_list = config_api.get_plugin_config(self.plugin_config, "features.private_list", [])
 
             if private_list_type == "whitelist":
@@ -158,17 +160,19 @@ class MessageHandler:
         """
 
         # 添加原始消息调试日志，特别关注message字段
-        logger.debug(f"收到原始消息: message_type={raw_message.get('message_type')}, message_id={raw_message.get('message_id')}")
+        logger.debug(
+            f"收到原始消息: message_type={raw_message.get('message_type')}, message_id={raw_message.get('message_id')}"
+        )
         logger.debug(f"原始消息内容: {raw_message.get('message', [])}")
 
         # 检查是否包含@或video消息段
-        message_segments = raw_message.get('message', [])
+        message_segments = raw_message.get("message", [])
         if message_segments:
             for i, seg in enumerate(message_segments):
-                seg_type = seg.get('type')
+                seg_type = seg.get("type")
-                if seg_type in ['at', 'video']:
+                if seg_type in ["at", "video"]:
                     logger.info(f"检测到 {seg_type.upper()} 消息段 [{i}]: {seg}")
-                elif seg_type not in ['text', 'face', 'image']:
+                elif seg_type not in ["text", "face", "image"]:
                     logger.warning(f"检测到特殊消息段 [{i}]: type={seg_type}, data={seg.get('data', {})}")
 
         message_type: str = raw_message.get("message_type")
@@ -308,9 +312,13 @@ class MessageHandler:
             message_type = raw_message.get("message_type")
             should_use_buffer = False
 
-            if message_type == "group" and config_api.get_plugin_config(self.plugin_config, "features.message_buffer_enable_group", True):
+            if message_type == "group" and config_api.get_plugin_config(
+                self.plugin_config, "features.message_buffer_enable_group", True
+            ):
                 should_use_buffer = True
-            elif message_type == "private" and config_api.get_plugin_config(self.plugin_config, "features.message_buffer_enable_private", True):
+            elif message_type == "private" and config_api.get_plugin_config(
+                self.plugin_config, "features.message_buffer_enable_private", True
+            ):
                 should_use_buffer = True
 
             if should_use_buffer:

src/plugins/built_in/napcat_adapter_plugin/src/recv_handler/message_sending.py

@@ -33,6 +33,7 @@ class MessageSending:
             try:
                 # 重新导入router
                 from ..mmc_com_layer import router
+
                 self.maibot_router = router
                 if self.maibot_router is not None:
                     logger.info("MaiBot router重连成功")
@@ -75,7 +76,7 @@ class MessageSending:
                     platform = message_base.message_info.platform
 
                     # 再次检查router状态（防止运行时被重置）
-                    if self.maibot_router is None or not hasattr(self.maibot_router, 'clients'):
+                    if self.maibot_router is None or not hasattr(self.maibot_router, "clients"):
                         logger.warning("MaiBot router连接已断开，尝试重新连接")
                         if not await self._attempt_reconnect():
                             logger.error("MaiBot router重连失败，切片发送中止")

src/plugins/built_in/napcat_adapter_plugin/src/recv_handler/meta_event_handler.py

@@ -22,7 +22,9 @@ class MetaEventHandler:
         """设置插件配置"""
         self.plugin_config = plugin_config
         # 更新interval值
-        self.interval = config_api.get_plugin_config(self.plugin_config, "napcat_server.heartbeat_interval", 5000) / 1000
+        self.interval = (
+            config_api.get_plugin_config(self.plugin_config, "napcat_server.heartbeat_interval", 5000) / 1000
+        )
 
     async def handle_meta_event(self, message: dict) -> None:
         event_type = message.get("meta_event_type")

src/plugins/built_in/napcat_adapter_plugin/src/recv_handler/notice_handler.py

@@ -116,9 +116,9 @@ class NoticeHandler:
                 sub_type = raw_message.get("sub_type")
                 match sub_type:
                     case NoticeType.Notify.poke:
-                        if config_api.get_plugin_config(self.plugin_config, "features.enable_poke", True) and await message_handler.check_allow_to_chat(
+                        if config_api.get_plugin_config(
-                            user_id, group_id, False, False
+                            self.plugin_config, "features.enable_poke", True
-                        ):
+                        ) and await message_handler.check_allow_to_chat(user_id, group_id, False, False):
                             logger.debug("处理戳一戳消息")
                             handled_message, user_info = await self.handle_poke_notify(raw_message, group_id, user_id)
                         else:
@@ -127,14 +127,18 @@ class NoticeHandler:
                         from src.plugin_system.core.event_manager import event_manager
                         from ...event_types import NapcatEvent
 
-                        await event_manager.trigger_event(NapcatEvent.ON_RECEIVED.FRIEND_INPUT, permission_group=PLUGIN_NAME)
+                        await event_manager.trigger_event(
+                            NapcatEvent.ON_RECEIVED.FRIEND_INPUT, permission_group=PLUGIN_NAME
+                        )
                     case _:
                         logger.warning(f"不支持的notify类型: {notice_type}.{sub_type}")
             case NoticeType.group_msg_emoji_like:
                 # 该事件转移到 handle_group_emoji_like_notify函数内触发
                 if config_api.get_plugin_config(self.plugin_config, "features.enable_emoji_like", True):
                     logger.debug("处理群聊表情回复")
-                    handled_message, user_info = await self.handle_group_emoji_like_notify(raw_message,group_id,user_id)
+                    handled_message, user_info = await self.handle_group_emoji_like_notify(
+                        raw_message, group_id, user_id
+                    )
                 else:
                     logger.warning("群聊表情回复被禁用，取消群聊表情回复处理")
             case NoticeType.group_ban:
@@ -308,8 +312,10 @@ class NoticeHandler:
         from src.plugin_system.core.event_manager import event_manager
         from ...event_types import NapcatEvent
 
-        target_message = await event_manager.trigger_event(NapcatEvent.MESSAGE.GET_MSG,message_id=raw_message.get("message_id",""))
+        target_message = await event_manager.trigger_event(
-        target_message_text = target_message.get_message_result().get("data",{}).get("raw_message","")
+            NapcatEvent.MESSAGE.GET_MSG, message_id=raw_message.get("message_id", "")
+        )
+        target_message_text = target_message.get_message_result().get("data", {}).get("raw_message", "")
         if not target_message:
             logger.error("未找到对应消息")
             return None, None
@@ -325,14 +331,17 @@ class NoticeHandler:
 
         like_emoji_id = raw_message.get("likes")[0].get("emoji_id")
         await event_manager.trigger_event(
-                        NapcatEvent.ON_RECEIVED.EMOJI_LIEK, 
+            NapcatEvent.ON_RECEIVED.EMOJI_LIEK,
-                        permission_group=PLUGIN_NAME, 
+            permission_group=PLUGIN_NAME,
-                        group_id=group_id,
+            group_id=group_id,
-                        user_id=user_id,
+            user_id=user_id,
-                        message_id=raw_message.get("message_id",""),
+            message_id=raw_message.get("message_id", ""),
-                        emoji_id=like_emoji_id
+            emoji_id=like_emoji_id,
-                        )     
+        )
-        seg_data = Seg(type="text",data=f"{user_name}使用Emoji表情{QQ_FACE.get(like_emoji_id,"")}回复了你的消息[{target_message_text}]")
+        seg_data = Seg(
+            type="text",
+            data=f"{user_name}使用Emoji表情{QQ_FACE.get(like_emoji_id, '')}回复了你的消息[{target_message_text}]",
+        )
         return seg_data, user_info
 
     async def handle_ban_notify(self, raw_message: dict, group_id: int) -> Tuple[Seg, UserInfo] | Tuple[None, None]:

src/plugins/built_in/napcat_adapter_plugin/src/send_handler.py

@@ -297,9 +297,9 @@ class SendHandler:
 
         try:
             # 检查是否为缓冲消息ID（格式：buffered-{original_id}-{timestamp}）
-            if id.startswith('buffered-'):
+            if id.startswith("buffered-"):
                 # 从缓冲消息ID中提取原始消息ID
-                original_id = id.split('-')[1]
+                original_id = id.split("-")[1]
                 msg_info_response = await self.send_message_to_napcat("get_msg", {"message_id": int(original_id)})
             else:
                 msg_info_response = await self.send_message_to_napcat("get_msg", {"message_id": int(id)})

src/plugins/built_in/napcat_adapter_plugin/src/websocket_manager.py

@@ -18,7 +18,9 @@ class WebSocketManager:
         self.max_reconnect_attempts = 10  # 最大重连次数
         self.plugin_config = None
 
-    async def start_connection(self, message_handler: Callable[[Server.ServerConnection], Any], plugin_config: dict) -> None:
+    async def start_connection(
+        self, message_handler: Callable[[Server.ServerConnection], Any], plugin_config: dict
+    ) -> None:
         """根据配置启动 WebSocket 连接"""
         self.plugin_config = plugin_config
         mode = config_api.get_plugin_config(plugin_config, "napcat_server.mode")
@@ -72,9 +74,7 @@ class WebSocketManager:
                 # 如果配置了访问令牌，添加到请求头
                 access_token = config_api.get_plugin_config(self.plugin_config, "napcat_server.access_token")
                 if access_token:
-                    connect_kwargs["additional_headers"] = {
+                    connect_kwargs["additional_headers"] = {"Authorization": f"Bearer {access_token}"}
-                        "Authorization": f"Bearer {access_token}"
-                    }
                     logger.info("已添加访问令牌到连接请求头")
 
                 async with Server.connect(url, **connect_kwargs) as websocket:

src/plugins/built_in/web_search_tool/engines/base.py

@@ -1,6 +1,7 @@
 """
 Base search engine interface
 """
+
 from abc import ABC, abstractmethod
 from typing import Dict, List, Any
 

src/plugins/built_in/web_search_tool/engines/bing_engine.py

@@ -1,6 +1,7 @@
 """
 Bing search engine implementation
 """
+
 import asyncio
 import functools
 import random
@@ -202,12 +203,7 @@ class BingSearchEngine(BaseSearchEngine):
                     if ABSTRACT_MAX_LENGTH and len(abstract) > ABSTRACT_MAX_LENGTH:
                         abstract = abstract[:ABSTRACT_MAX_LENGTH] + "..."
 
-                    list_data.append({
+                    list_data.append({"title": title, "url": url, "snippet": abstract, "provider": "Bing"})
-                        "title": title,
-                        "url": url,
-                        "snippet": abstract,
-                        "provider": "Bing"
-                    })
 
                     if len(list_data) >= 10:  # 限制结果数量
                         break
@@ -222,16 +218,28 @@ class BingSearchEngine(BaseSearchEngine):
                     text = link.get_text().strip()
 
                     # 过滤有效的搜索结果链接
-                    if (href and text and len(text) > 10 
+                    if (
+                        href
+                        and text
+                        and len(text) > 10
                         and not href.startswith("javascript:")
                         and not href.startswith("#")
                         and "http" in href
-                        and not any(x in href for x in [
+                        and not any(
-                            "bing.com/search", "bing.com/images", "bing.com/videos",
+                            x in href
-                            "bing.com/maps", "bing.com/news", "login", "account",
+                            for x in [
-                            "microsoft", "javascript"
+                                "bing.com/search",
-                        ])):
+                                "bing.com/images",
-                        
+                                "bing.com/videos",
+                                "bing.com/maps",
+                                "bing.com/news",
+                                "login",
+                                "account",
+                                "microsoft",
+                                "javascript",
+                            ]
+                        )
+                    ):
                         # 尝试获取摘要
                         abstract = ""
                         parent = link.parent
@@ -244,12 +252,7 @@ class BingSearchEngine(BaseSearchEngine):
                         if ABSTRACT_MAX_LENGTH and len(abstract) > ABSTRACT_MAX_LENGTH:
                             abstract = abstract[:ABSTRACT_MAX_LENGTH] + "..."
 
-                        list_data.append({
+                        list_data.append({"title": text, "url": href, "snippet": abstract, "provider": "Bing"})
-                            "title": text,
-                            "url": href,
-                            "snippet": abstract,
-                            "provider": "Bing"
-                        })
 
                         if len(list_data) >= 10:
                             break

src/plugins/built_in/web_search_tool/engines/ddg_engine.py

@@ -1,6 +1,7 @@
 """
 DuckDuckGo search engine implementation
 """
+
 from typing import Dict, List, Any
 from asyncddgs import aDDGS
 
@@ -29,12 +30,7 @@ class DDGSearchEngine(BaseSearchEngine):
                 search_response = await ddgs.text(query, max_results=num_results)
 
             return [
-                {
+                {"title": r.get("title"), "url": r.get("href"), "snippet": r.get("body"), "provider": "DuckDuckGo"}
-                    "title": r.get("title"),
-                    "url": r.get("href"),
-                    "snippet": r.get("body"),
-                    "provider": "DuckDuckGo"
-                }
                 for r in search_response
             ]
         except Exception as e:

src/plugins/built_in/web_search_tool/engines/exa_engine.py

@@ -1,6 +1,7 @@
 """
 Exa search engine implementation
 """
+
 import asyncio
 import functools
 from datetime import datetime, timedelta
@@ -29,11 +30,7 @@ class ExaSearchEngine(BaseSearchEngine):
         exa_api_keys = config_api.get_global_config("web_search.exa_api_keys", None)
 
         # 创建API密钥管理器
-        self.api_manager = create_api_key_manager_from_config(
+        self.api_manager = create_api_key_manager_from_config(exa_api_keys, lambda key: Exa(api_key=key), "Exa")
-            exa_api_keys,
-            lambda key: Exa(api_key=key),
-            "Exa"
-        )
 
     def is_available(self) -> bool:
         """检查Exa搜索引擎是否可用"""
@@ -52,7 +49,7 @@ class ExaSearchEngine(BaseSearchEngine):
         if time_range != "any":
             today = datetime.now()
             start_date = today - timedelta(days=7 if time_range == "week" else 30)
-            exa_args["start_published_date"] = start_date.strftime('%Y-%m-%d')
+            exa_args["start_published_date"] = start_date.strftime("%Y-%m-%d")
 
         try:
             # 使用API密钥管理器获取下一个客户端
@@ -69,8 +66,8 @@ class ExaSearchEngine(BaseSearchEngine):
                 {
                     "title": res.title,
                     "url": res.url,
-                    "snippet": " ".join(getattr(res, 'highlights', [])) or (getattr(res, 'text', '')[:250] + '...'),
+                    "snippet": " ".join(getattr(res, "highlights", [])) or (getattr(res, "text", "")[:250] + "..."),
-                    "provider": "Exa"
+                    "provider": "Exa",
                 }
                 for res in search_response.results
             ]

src/plugins/built_in/web_search_tool/engines/tavily_engine.py

@@ -1,6 +1,7 @@
 """
 Tavily search engine implementation
 """
+
 import asyncio
 import functools
 from typing import Dict, List, Any
@@ -29,9 +30,7 @@ class TavilySearchEngine(BaseSearchEngine):
 
         # 创建API密钥管理器
         self.api_manager = create_api_key_manager_from_config(
-            tavily_api_keys,
+            tavily_api_keys, lambda key: TavilyClient(api_key=key), "Tavily"
-            lambda key: TavilyClient(api_key=key),
-            "Tavily"
         )
 
     def is_available(self) -> bool:
@@ -60,7 +59,7 @@ class TavilySearchEngine(BaseSearchEngine):
                 "max_results": num_results,
                 "search_depth": "basic",
                 "include_answer": False,
-                "include_raw_content": False
+                "include_raw_content": False,
             }
 
             # 根据时间范围调整搜索参数
@@ -76,12 +75,14 @@ class TavilySearchEngine(BaseSearchEngine):
             results = []
             if search_response and "results" in search_response:
                 for res in search_response["results"]:
-                    results.append({
+                    results.append(
-                        "title": res.get("title", "无标题"),
+                        {
-                        "url": res.get("url", ""),
+                            "title": res.get("title", "无标题"),
-                        "snippet": res.get("content", "")[:300] + "..." if res.get("content") else "无摘要",
+                            "url": res.get("url", ""),
-                        "provider": "Tavily"
+                            "snippet": res.get("content", "")[:300] + "..." if res.get("content") else "无摘要",
-                    })
+                            "provider": "Tavily",
+                        }
+                    )
 
             return results
 

src/plugins/built_in/web_search_tool/plugin.py

@@ -3,15 +3,10 @@ Web Search Tool Plugin
 
 一个功能强大的网络搜索和URL解析插件，支持多种搜索引擎和解析策略。
 """
+
 from typing import List, Tuple, Type
 
-from src.plugin_system import (
+from src.plugin_system import BasePlugin, register_plugin, ComponentInfo, ConfigField, PythonDependency
-    BasePlugin,
-    register_plugin,
-    ComponentInfo,
-    ConfigField,
-    PythonDependency
-)
 from src.plugin_system.apis import config_api
 from src.common.logger import get_logger
 
@@ -61,7 +56,7 @@ class WEBSEARCHPLUGIN(BasePlugin):
                 "Exa": exa_engine.is_available(),
                 "Tavily": tavily_engine.is_available(),
                 "DuckDuckGo": ddg_engine.is_available(),
-                "Bing": bing_engine.is_available()
+                "Bing": bing_engine.is_available(),
             }
 
             available_engines = [name for name, available in engines_status.items() if available]
@@ -77,37 +72,30 @@ class WEBSEARCHPLUGIN(BasePlugin):
 
     # Python包依赖列表
     python_dependencies: List[PythonDependency] = [
-        PythonDependency(
+        PythonDependency(package_name="asyncddgs", description="异步DuckDuckGo搜索库", optional=False),
-            package_name="asyncddgs",
-            description="异步DuckDuckGo搜索库",
-            optional=False
-        ),
         PythonDependency(
             package_name="exa_py",
             description="Exa搜索API客户端库",
-            optional=True  # 如果没有API密钥，这个是可选的
+            optional=True,  # 如果没有API密钥，这个是可选的
         ),
         PythonDependency(
             package_name="tavily",
             install_name="tavily-python",  # 安装时使用这个名称
             description="Tavily搜索API客户端库",
-            optional=True  # 如果没有API密钥，这个是可选的
+            optional=True,  # 如果没有API密钥，这个是可选的
         ),
         PythonDependency(
             package_name="httpx",
             version=">=0.20.0",
             install_name="httpx[socks]",  # 安装时使用这个名称（包含可选依赖）
             description="支持SOCKS代理的HTTP客户端库",
-            optional=False
+            optional=False,
-        )
+        ),
     ]
     config_file_name: str = "config.toml"  # 配置文件名
 
     # 配置节描述
-    config_section_descriptions = {
+    config_section_descriptions = {"plugin": "插件基本信息", "proxy": "链接本地解析代理配置"}
-        "plugin": "插件基本信息", 
-        "proxy": "链接本地解析代理配置"
-    }
 
     # 配置Schema定义
     # 注意：EXA配置和组件设置已迁移到主配置文件(bot_config.toml)的[exa]和[web_search]部分
@@ -119,25 +107,15 @@ class WEBSEARCHPLUGIN(BasePlugin):
         },
         "proxy": {
             "http_proxy": ConfigField(
-                type=str, 
+                type=str, default=None, description="HTTP代理地址，格式如: http://proxy.example.com:8080"
-                default=None, 
-                description="HTTP代理地址，格式如: http://proxy.example.com:8080"
             ),
             "https_proxy": ConfigField(
-                type=str, 
+                type=str, default=None, description="HTTPS代理地址，格式如: http://proxy.example.com:8080"
-                default=None, 
-                description="HTTPS代理地址，格式如: http://proxy.example.com:8080"
             ),
             "socks5_proxy": ConfigField(
-                type=str, 
+                type=str, default=None, description="SOCKS5代理地址，格式如: socks5://proxy.example.com:1080"
-                default=None, 
-                description="SOCKS5代理地址，格式如: socks5://proxy.example.com:1080"
             ),
-            "enable_proxy": ConfigField(
+            "enable_proxy": ConfigField(type=bool, default=False, description="是否启用代理"),
-                type=bool, 
-                default=False, 
-                description="是否启用代理"
-            )
         },
     }
 

src/plugins/built_in/web_search_tool/tools/url_parser.py

@@ -1,6 +1,7 @@
 """
 URL parser tool implementation
 """
+
 import asyncio
 import functools
 from typing import Any, Dict
@@ -24,6 +25,7 @@ class URLParserTool(BaseTool):
     """
     一个用于解析和总结一个或多个网页URL内容的工具。
     """
+
     name: str = "parse_url"
     description: str = "当需要理解一个或多个特定网页链接的内容时，使用此工具。例如：'这些网页讲了什么？[https://example.com, https://example2.com]' 或 '帮我总结一下这些文章'"
     available_for_llm: bool = True
@@ -45,9 +47,7 @@ class URLParserTool(BaseTool):
 
         # 创建API密钥管理器
         self.api_manager = create_api_key_manager_from_config(
-            exa_api_keys,
+            exa_api_keys, lambda key: Exa(api_key=key), "Exa URL Parser"
-            lambda key: Exa(api_key=key),
-            "Exa URL Parser"
         )
 
     async def _local_parse_and_summarize(self, url: str) -> Dict[str, Any]:
@@ -104,12 +104,12 @@ class URLParserTool(BaseTool):
                 return {"error": "未配置LLM模型"}
 
             success, summary, reasoning, model_name = await llm_api.generate_with_model(
-                    prompt=summary_prompt,
+                prompt=summary_prompt,
-                    model_config=model_config,
+                model_config=model_config,
-                    request_type="story.generate",
+                request_type="story.generate",
-                    temperature=0.3,
+                temperature=0.3,
-                    max_tokens=1000
+                max_tokens=1000,
-                )
+            )
 
             if not success:
                 logger.info(f"生成摘要失败: {summary}")
@@ -117,12 +117,7 @@ class URLParserTool(BaseTool):
 
             logger.info(f"成功生成摘要内容：'{summary}'")
 
-            return {
+            return {"title": title, "url": url, "snippet": summary, "source": "local"}
-                "title": title,
-                "url": url,
-                "snippet": summary,
-                "source": "local"
-            }
 
         except httpx.HTTPStatusError as e:
             logger.warning(f"本地解析URL '{url}' 失败 (HTTP {e.response.status_code})")
@@ -137,6 +132,7 @@ class URLParserTool(BaseTool):
         """
         # 获取当前文件路径用于缓存键
         import os
+
         current_file_path = os.path.abspath(__file__)
 
         # 检查缓存
@@ -182,34 +178,38 @@ class URLParserTool(BaseTool):
                     contents_response = await loop.run_in_executor(None, func)
             except Exception as e:
                 logger.error(f"执行 Exa URL解析时发生严重异常: {e}", exc_info=True)
-                contents_response = None # 确保异常后为None
+                contents_response = None  # 确保异常后为None
 
         # 步骤 2: 处理Exa的响应
-        if contents_response and hasattr(contents_response, 'statuses'):
+        if contents_response and hasattr(contents_response, "statuses"):
-            results_map = {res.url: res for res in contents_response.results} if hasattr(contents_response, 'results') else {}
+            results_map = (
+                {res.url: res for res in contents_response.results} if hasattr(contents_response, "results") else {}
+            )
             if contents_response.statuses:
                 for status in contents_response.statuses:
-                    if status.status == 'success':
+                    if status.status == "success":
                         res = results_map.get(status.id)
                         if res:
-                            summary = getattr(res, 'summary', '')
+                            summary = getattr(res, "summary", "")
-                            highlights = " ".join(getattr(res, 'highlights', []))
+                            highlights = " ".join(getattr(res, "highlights", []))
-                            text_snippet = (getattr(res, 'text', '')[:300] + '...') if getattr(res, 'text', '') else ''
+                            text_snippet = (getattr(res, "text", "")[:300] + "...") if getattr(res, "text", "") else ""
-                            snippet = summary or highlights or text_snippet or '无摘要'
+                            snippet = summary or highlights or text_snippet or "无摘要"
 
-                            successful_results.append({
+                            successful_results.append(
-                                "title": getattr(res, 'title', '无标题'),
+                                {
-                                "url": getattr(res, 'url', status.id),
+                                    "title": getattr(res, "title", "无标题"),
-                                "snippet": snippet,
+                                    "url": getattr(res, "url", status.id),
-                                "source": "exa"
+                                    "snippet": snippet,
-                            })
+                                    "source": "exa",
+                                }
+                            )
                     else:
-                        error_tag = getattr(status, 'error', '未知错误')
+                        error_tag = getattr(status, "error", "未知错误")
                         logger.warning(f"Exa解析URL '{status.id}' 失败: {error_tag}。准备本地重试。")
                         urls_to_retry_locally.append(status.id)
         else:
             # 如果Exa未配置、API调用失败或返回无效响应，则所有URL都进入本地重试
-            urls_to_retry_locally.extend(url for url in urls if url not in [res['url'] for res in successful_results])
+            urls_to_retry_locally.extend(url for url in urls if url not in [res["url"] for res in successful_results])
 
         # 步骤 3: 对失败的URL进行本地解析
         if urls_to_retry_locally:
@@ -229,11 +229,7 @@ class URLParserTool(BaseTool):
 
         formatted_content = format_url_parse_results(successful_results)
 
-        result = {
+        result = {"type": "url_parse_result", "content": formatted_content, "errors": error_messages}
-            "type": "url_parse_result",
-            "content": formatted_content,
-            "errors": error_messages
-        }
 
         # 保存到缓存
         if "error" not in result:

src/plugins/built_in/web_search_tool/tools/web_search.py

@@ -1,6 +1,7 @@
 """
 Web search tool implementation
 """
+
 import asyncio
 from typing import Any, Dict, List
 
@@ -22,14 +23,23 @@ class WebSurfingTool(BaseTool):
     """
     网络搜索工具
     """
+
     name: str = "web_search"
-    description: str = "用于执行网络搜索。当用户明确要求搜索，或者需要获取关于公司、产品、事件的最新信息、新闻或动态时，必须使用此工具"
+    description: str = (
+        "用于执行网络搜索。当用户明确要求搜索，或者需要获取关于公司、产品、事件的最新信息、新闻或动态时，必须使用此工具"
+    )
     available_for_llm: bool = True
     parameters = [
         ("query", ToolParamType.STRING, "要搜索的关键词或问题。", True, None),
         ("num_results", ToolParamType.INTEGER, "期望每个搜索引擎返回的搜索结果数量，默认为5。", False, None),
-        ("time_range", ToolParamType.STRING, "指定搜索的时间范围，可以是 'any', 'week', 'month'。默认为 'any'。", False, ["any", "week", "month"])
+        (
-    ] # type: ignore
+            "time_range",
+            ToolParamType.STRING,
+            "指定搜索的时间范围，可以是 'any', 'week', 'month'。默认为 'any'。",
+            False,
+            ["any", "week", "month"],
+        ),
+    ]  # type: ignore
 
     def __init__(self, plugin_config=None):
         super().__init__(plugin_config)
@@ -38,7 +48,7 @@ class WebSurfingTool(BaseTool):
             "exa": ExaSearchEngine(),
             "tavily": TavilySearchEngine(),
             "ddg": DDGSearchEngine(),
-            "bing": BingSearchEngine()
+            "bing": BingSearchEngine(),
         }
 
     async def execute(self, function_args: Dict[str, Any]) -> Dict[str, Any]:
@@ -48,6 +58,7 @@ class WebSurfingTool(BaseTool):
 
         # 获取当前文件路径用于缓存键
         import os
+
         current_file_path = os.path.abspath(__file__)
 
         # 检查缓存
@@ -76,7 +87,9 @@ class WebSurfingTool(BaseTool):
 
         return result
 
-    async def _execute_parallel_search(self, function_args: Dict[str, Any], enabled_engines: List[str]) -> Dict[str, Any]:
+    async def _execute_parallel_search(
+        self, function_args: Dict[str, Any], enabled_engines: List[str]
+    ) -> Dict[str, Any]:
         """并行搜索策略：同时使用所有启用的搜索引擎"""
         search_tasks = []
 
@@ -113,7 +126,9 @@ class WebSurfingTool(BaseTool):
             logger.error(f"执行并行网络搜索时发生异常: {e}", exc_info=True)
             return {"error": f"执行网络搜索时发生严重错误: {str(e)}"}
 
-    async def _execute_fallback_search(self, function_args: Dict[str, Any], enabled_engines: List[str]) -> Dict[str, Any]:
+    async def _execute_fallback_search(
+        self, function_args: Dict[str, Any], enabled_engines: List[str]
+    ) -> Dict[str, Any]:
         """回退搜索策略：按顺序尝试搜索引擎，失败则尝试下一个"""
         for engine_name in enabled_engines:
             engine = self.engines.get(engine_name)

src/plugins/built_in/web_search_tool/utils/api_key_manager.py

@@ -1,13 +1,14 @@
 """
 API密钥管理器，提供轮询机制
 """
+
 import itertools
 from typing import List, Optional, TypeVar, Generic, Callable
 from src.common.logger import get_logger
 
 logger = get_logger("api_key_manager")
 
-T = TypeVar('T')
+T = TypeVar("T")
 
 
 class APIKeyManager(Generic[T]):
@@ -65,9 +66,7 @@ class APIKeyManager(Generic[T]):
 
 
 def create_api_key_manager_from_config(
-    config_keys: Optional[List[str]], 
+    config_keys: Optional[List[str]], client_factory: Callable[[str], T], service_name: str
-    client_factory: Callable[[str], T], 
-    service_name: str
 ) -> APIKeyManager[T]:
     """
     从配置创建API密钥管理器的便捷函数

src/plugins/built_in/web_search_tool/utils/formatters.py

@@ -1,6 +1,7 @@
 """
 Formatters for web search results
 """
+
 from typing import List, Dict, Any
 
 
@@ -13,9 +14,9 @@ def format_search_results(results: List[Dict[str, Any]]) -> str:
 
     formatted_string = "根据网络搜索结果：\n\n"
     for i, res in enumerate(results, 1):
-        title = res.get("title", '无标题')
+        title = res.get("title", "无标题")
-        url = res.get("url", '#')
+        url = res.get("url", "#")
-        snippet = res.get("snippet", '无摘要')
+        snippet = res.get("snippet", "无摘要")
         provider = res.get("provider", "未知来源")
 
         formatted_string += f"{i}. **{title}** (来自: {provider})\n"
@@ -31,10 +32,10 @@ def format_url_parse_results(results: List[Dict[str, Any]]) -> str:
     """
     formatted_parts = []
     for res in results:
-        title = res.get('title', '无标题')
+        title = res.get("title", "无标题")
-        url = res.get('url', '#')
+        url = res.get("url", "#")
-        snippet = res.get('snippet', '无摘要')
+        snippet = res.get("snippet", "无摘要")
-        source = res.get('source', '未知')
+        source = res.get("source", "未知")
 
         formatted_string = f"**{title}**\n"
         formatted_string += f"**内容摘要**:\n{snippet}\n"

src/plugins/built_in/web_search_tool/utils/url_utils.py

@@ -1,6 +1,7 @@
 """
 URL processing utilities
 """
+
 import re
 from typing import List
 
@@ -12,11 +13,11 @@ def parse_urls_from_input(urls_input) -> List[str]:
     if isinstance(urls_input, str):
         # 如果是字符串，尝试解析为URL列表
         # 提取所有HTTP/HTTPS URL
-        url_pattern = r'https?://[^\s\],]+'
+        url_pattern = r"https?://[^\s\],]+"
         urls = re.findall(url_pattern, urls_input)
         if not urls:
             # 如果没有找到标准URL，将整个字符串作为单个URL
-            if urls_input.strip().startswith(('http://', 'https://')):
+            if urls_input.strip().startswith(("http://", "https://")):
                 urls = [urls_input.strip()]
             else:
                 return []
@@ -34,6 +35,6 @@ def validate_urls(urls: List[str]) -> List[str]:
     """
     valid_urls = []
     for url in urls:
-        if url.startswith(('http://', 'https://')):
+        if url.startswith(("http://", "https://")):
             valid_urls.append(url)
     return valid_urls

src/plugins/reminder_plugin/plugin.py

@@ -21,8 +21,18 @@ logger = get_logger(__name__)
 
 # ============================ AsyncTask ============================
 
+
 class ReminderTask(AsyncTask):
-    def __init__(self, delay: float, stream_id: str, is_group: bool, target_user_id: str, target_user_name: str, event_details: str, creator_name: str):
+    def __init__(
+        self,
+        delay: float,
+        stream_id: str,
+        is_group: bool,
+        target_user_id: str,
+        target_user_name: str,
+        event_details: str,
+        creator_name: str,
+    ):
         super().__init__(task_name=f"ReminderTask_{target_user_id}_{datetime.now().timestamp()}")
         self.delay = delay
         self.stream_id = stream_id
@@ -44,15 +54,15 @@ class ReminderTask(AsyncTask):
 
             if self.is_group:
                 # 在群聊中，构造 @ 消息段并发送
-                group_id = self.stream_id.split('_')[-1] if '_' in self.stream_id else self.stream_id
+                group_id = self.stream_id.split("_")[-1] if "_" in self.stream_id else self.stream_id
                 message_payload = [
                     {"type": "at", "data": {"qq": self.target_user_id}},
-                    {"type": "text", "data": {"text": f" {reminder_text}"}}
+                    {"type": "text", "data": {"text": f" {reminder_text}"}},
                 ]
                 await send_api.adapter_command_to_stream(
                     action="send_group_msg",
                     params={"group_id": group_id, "message": message_payload},
-                    stream_id=self.stream_id
+                    stream_id=self.stream_id,
                 )
             else:
                 # 在私聊中，直接发送文本
@@ -66,6 +76,7 @@ class ReminderTask(AsyncTask):
 
 # =============================== Actions ===============================
 
+
 class RemindAction(BaseAction):
     """一个能从对话中智能识别并设置定时提醒的动作。"""
 
@@ -95,12 +106,12 @@ class RemindAction(BaseAction):
     action_parameters = {
         "user_name": "需要被提醒的人的称呼或名字，如果没有明确指定给某人，则默认为'自己'",
         "remind_time": "描述提醒时间的自然语言字符串，例如'十分钟后'或'明天下午3点'",
-        "event_details": "需要提醒的具体事件内容"
+        "event_details": "需要提醒的具体事件内容",
     }
     action_require = [
         "当用户请求在未来的某个时间点提醒他/她或别人某件事时使用",
         "适用于包含明确时间信息和事件描述的对话",
-        "例如：'10分钟后提醒我收快递'、'明天早上九点喊一下李四参加晨会'"
+        "例如：'10分钟后提醒我收快递'、'明天早上九点喊一下李四参加晨会'",
     ]
 
     async def execute(self) -> Tuple[bool, str]:
@@ -110,7 +121,15 @@ class RemindAction(BaseAction):
         event_details = self.action_data.get("event_details")
 
         if not all([user_name, remind_time_str, event_details]):
-            missing_params = [p for p, v in {"user_name": user_name, "remind_time": remind_time_str, "event_details": event_details}.items() if not v]
+            missing_params = [
+                p
+                for p, v in {
+                    "user_name": user_name,
+                    "remind_time": remind_time_str,
+                    "event_details": event_details,
+                }.items()
+                if not v
+            ]
             error_msg = f"缺少必要的提醒参数: {', '.join(missing_params)}"
             logger.warning(f"[ReminderPlugin] LLM未能提取完整参数: {error_msg}")
             return False, error_msg
@@ -162,7 +181,7 @@ class RemindAction(BaseAction):
                 target_user_id=str(user_id_to_remind),
                 target_user_name=str(user_name_to_remind),
                 event_details=str(event_details),
-                creator_name=str(self.user_nickname)
+                creator_name=str(self.user_nickname),
             )
             await async_task_manager.add_task(reminder_task)
 
@@ -179,6 +198,7 @@ class RemindAction(BaseAction):
 
 # =============================== Plugin ===============================
 
+
 @register_plugin
 class ReminderPlugin(BasePlugin):
     """一个能从对话中智能识别并设置定时提醒的插件。"""
@@ -193,6 +213,4 @@ class ReminderPlugin(BasePlugin):
 
     def get_plugin_components(self) -> List[Tuple[ActionInfo, Type[BaseAction]]]:
         """注册插件的所有功能组件。"""
-        return [
+        return [(RemindAction.get_action_info(), RemindAction)]
-            (RemindAction.get_action_info(), RemindAction)
-        ]