Merge branch 'dev' of github.com:MaiM-with-u/MaiBot into dev

bot.py

@@ -65,6 +65,7 @@ async def graceful_shutdown():  # sourcery skip: use-named-expression
 
         from src.plugin_system.core.events_manager import events_manager
         from src.plugin_system.base.component_types import EventType
+
         # 触发 ON_STOP 事件
         await events_manager.handle_mai_events(event_type=EventType.ON_STOP)
 

scripts/expression_stats.py

@@ -5,12 +5,11 @@ from typing import Dict, List
 
 # Add project root to Python path
 from src.common.database.database_model import Expression, ChatStreams
+
 project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 sys.path.insert(0, project_root)
 
 
-
-
 def get_chat_name(chat_id: str) -> str:
     """Get chat name from chat_id by querying ChatStreams table directly"""
     try:
@@ -35,72 +34,61 @@ def calculate_time_distribution(expressions) -> Dict[str, int]:
     """Calculate distribution of last active time in days"""
     now = time.time()
     distribution = {
-        '0-1天': 0,
+        "0-1天": 0,
-        '1-3天': 0,
+        "1-3天": 0,
-        '3-7天': 0,
+        "3-7天": 0,
-        '7-14天': 0,
+        "7-14天": 0,
-        '14-30天': 0,
+        "14-30天": 0,
-        '30-60天': 0,
+        "30-60天": 0,
-        '60-90天': 0,
+        "60-90天": 0,
-        '90+天': 0
+        "90+天": 0,
     }
     for expr in expressions:
-        diff_days = (now - expr.last_active_time) / (24*3600)
+        diff_days = (now - expr.last_active_time) / (24 * 3600)
         if diff_days < 1:
-            distribution['0-1天'] += 1
+            distribution["0-1天"] += 1
         elif diff_days < 3:
-            distribution['1-3天'] += 1
+            distribution["1-3天"] += 1
         elif diff_days < 7:
-            distribution['3-7天'] += 1
+            distribution["3-7天"] += 1
         elif diff_days < 14:
-            distribution['7-14天'] += 1
+            distribution["7-14天"] += 1
         elif diff_days < 30:
-            distribution['14-30天'] += 1
+            distribution["14-30天"] += 1
         elif diff_days < 60:
-            distribution['30-60天'] += 1
+            distribution["30-60天"] += 1
         elif diff_days < 90:
-            distribution['60-90天'] += 1
+            distribution["60-90天"] += 1
         else:
-            distribution['90+天'] += 1
+            distribution["90+天"] += 1
     return distribution
 
 
 def calculate_count_distribution(expressions) -> Dict[str, int]:
     """Calculate distribution of count values"""
-    distribution = {
+    distribution = {"0-1": 0, "1-2": 0, "2-3": 0, "3-4": 0, "4-5": 0, "5-10": 0, "10+": 0}
-        '0-1': 0,
-        '1-2': 0,
-        '2-3': 0,
-        '3-4': 0,
-        '4-5': 0,
-        '5-10': 0,
-        '10+': 0
-    }
     for expr in expressions:
         cnt = expr.count
         if cnt < 1:
-            distribution['0-1'] += 1
+            distribution["0-1"] += 1
         elif cnt < 2:
-            distribution['1-2'] += 1
+            distribution["1-2"] += 1
         elif cnt < 3:
-            distribution['2-3'] += 1
+            distribution["2-3"] += 1
         elif cnt < 4:
-            distribution['3-4'] += 1
+            distribution["3-4"] += 1
         elif cnt < 5:
-            distribution['4-5'] += 1
+            distribution["4-5"] += 1
         elif cnt < 10:
-            distribution['5-10'] += 1
+            distribution["5-10"] += 1
         else:
-            distribution['10+'] += 1
+            distribution["10+"] += 1
     return distribution
 
 
 def get_top_expressions_by_chat(chat_id: str, top_n: int = 5) -> List[Expression]:
     """Get top N most used expressions for a specific chat_id"""
-    return (Expression.select()
+    return Expression.select().where(Expression.chat_id == chat_id).order_by(Expression.count.desc()).limit(top_n)
-                    .where(Expression.chat_id == chat_id)
-                    .order_by(Expression.count.desc())
-                    .limit(top_n))
 
 
 def show_overall_statistics(expressions, total: int) -> None:
@@ -113,11 +101,11 @@ def show_overall_statistics(expressions, total: int) -> None:
 
     print("\n上次激活时间分布:")
     for period, count in time_dist.items():
-        print(f"{period}: {count} ({count/total*100:.2f}%)")
+        print(f"{period}: {count} ({count / total * 100:.2f}%)")
 
     print("\ncount分布:")
     for range_, count in count_dist.items():
-        print(f"{range_}: {count} ({count/total*100:.2f}%)")
+        print(f"{range_}: {count} ({count / total * 100:.2f}%)")
 
 
 def show_chat_statistics(chat_id: str, chat_name: str) -> None:
@@ -137,14 +125,14 @@ def show_chat_statistics(chat_id: str, chat_name: str) -> None:
     print("\n上次激活时间分布:")
     for period, count in time_dist.items():
         if count > 0:
-            print(f"{period}: {count} ({count/chat_total*100:.2f}%)")
+            print(f"{period}: {count} ({count / chat_total * 100:.2f}%)")
 
     # Count distribution for this chat
     count_dist = calculate_count_distribution(chat_exprs)
     print("\ncount分布:")
     for range_, count in count_dist.items():
         if count > 0:
-            print(f"{range_}: {count} ({count/chat_total*100:.2f}%)")
+            print(f"{range_}: {count} ({count / chat_total * 100:.2f}%)")
 
     # Top expressions
     print("\nTop 10使用最多的表达式:")
@@ -172,9 +160,9 @@ def interactive_menu() -> None:
     chat_info.sort(key=lambda x: x[1])  # Sort by chat name
 
     while True:
-        print("\n" + "="*50)
+        print("\n" + "=" * 50)
         print("表达式统计分析")
-        print("="*50)
+        print("=" * 50)
         print("0. 显示总体统计")
 
         for i, (chat_id, chat_name) in enumerate(chat_info, 1):
@@ -185,7 +173,7 @@ def interactive_menu() -> None:
 
         choice = input("\n请选择要查看的统计 (输入序号): ").strip()
 
-        if choice.lower() == 'q':
+        if choice.lower() == "q":
             print("再见！")
             break
 

scripts/import_openie.py

@@ -23,6 +23,7 @@ OPENIE_DIR = os.path.join(ROOT_PATH, "data", "openie")
 
 logger = get_logger("OpenIE导入")
 
+
 def ensure_openie_dir():
     """确保OpenIE数据目录存在"""
     if not os.path.exists(OPENIE_DIR):

scripts/info_extraction.py

@@ -12,6 +12,7 @@ sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
 from rich.progress import Progress  # 替换为 rich 进度条
 
 from src.common.logger import get_logger
+
 # from src.chat.knowledge.lpmmconfig import global_config
 from src.chat.knowledge.ie_process import info_extract_from_str
 from src.chat.knowledge.open_ie import OpenIE
@@ -36,6 +37,7 @@ TEMP_DIR = os.path.join(ROOT_PATH, "temp")
 # IMPORTED_DATA_PATH = os.path.join(ROOT_PATH, "data", "imported_lpmm_data")
 OPENIE_OUTPUT_DIR = os.path.join(ROOT_PATH, "data", "openie")
 
+
 def ensure_dirs():
     """确保临时目录和输出目录存在"""
     if not os.path.exists(TEMP_DIR):
@@ -48,6 +50,7 @@ def ensure_dirs():
         os.makedirs(RAW_DATA_PATH)
         logger.info(f"已创建原始数据目录: {RAW_DATA_PATH}")
 
+
 # 创建一个线程安全的锁，用于保护文件操作和共享数据
 file_lock = Lock()
 open_ie_doc_lock = Lock()
@@ -56,13 +59,11 @@ open_ie_doc_lock = Lock()
 shutdown_event = Event()
 
 lpmm_entity_extract_llm = LLMRequest(
-    model_set=model_config.model_task_config.lpmm_entity_extract,
+    model_set=model_config.model_task_config.lpmm_entity_extract, request_type="lpmm.entity_extract"
-    request_type="lpmm.entity_extract"
-)
-lpmm_rdf_build_llm = LLMRequest(
-    model_set=model_config.model_task_config.lpmm_rdf_build,
-    request_type="lpmm.rdf_build"
 )
+lpmm_rdf_build_llm = LLMRequest(model_set=model_config.model_task_config.lpmm_rdf_build, request_type="lpmm.rdf_build")
+
+
 def process_single_text(pg_hash, raw_data):
     """处理单个文本的函数，用于线程池"""
     temp_file_path = f"{TEMP_DIR}/{pg_hash}.json"

scripts/interest_value_analysis.py

@@ -3,12 +3,11 @@ import sys
 import os
 from typing import Dict, List, Tuple, Optional
 from datetime import datetime
+
 # Add project root to Python path
 project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 sys.path.insert(0, project_root)
-from src.common.database.database_model import Messages, ChatStreams #noqa
+from src.common.database.database_model import Messages, ChatStreams  # noqa
-
-
 
 
 def get_chat_name(chat_id: str) -> str:
@@ -39,15 +38,15 @@ def format_timestamp(timestamp: float) -> str:
 def calculate_interest_value_distribution(messages) -> Dict[str, int]:
     """Calculate distribution of interest_value"""
     distribution = {
-        '0.000-0.010': 0,
+        "0.000-0.010": 0,
-        '0.010-0.050': 0,
+        "0.010-0.050": 0,
-        '0.050-0.100': 0,
+        "0.050-0.100": 0,
-        '0.100-0.500': 0,
+        "0.100-0.500": 0,
-        '0.500-1.000': 0,
+        "0.500-1.000": 0,
-        '1.000-2.000': 0,
+        "1.000-2.000": 0,
-        '2.000-5.000': 0,
+        "2.000-5.000": 0,
-        '5.000-10.000': 0,
+        "5.000-10.000": 0,
-        '10.000+': 0
+        "10.000+": 0,
     }
 
     for msg in messages:
@@ -56,49 +55,45 @@ def calculate_interest_value_distribution(messages) -> Dict[str, int]:
 
         value = float(msg.interest_value)
         if value < 0.010:
-            distribution['0.000-0.010'] += 1
+            distribution["0.000-0.010"] += 1
         elif value < 0.050:
-            distribution['0.010-0.050'] += 1
+            distribution["0.010-0.050"] += 1
         elif value < 0.100:
-            distribution['0.050-0.100'] += 1
+            distribution["0.050-0.100"] += 1
         elif value < 0.500:
-            distribution['0.100-0.500'] += 1
+            distribution["0.100-0.500"] += 1
         elif value < 1.000:
-            distribution['0.500-1.000'] += 1
+            distribution["0.500-1.000"] += 1
         elif value < 2.000:
-            distribution['1.000-2.000'] += 1
+            distribution["1.000-2.000"] += 1
         elif value < 5.000:
-            distribution['2.000-5.000'] += 1
+            distribution["2.000-5.000"] += 1
         elif value < 10.000:
-            distribution['5.000-10.000'] += 1
+            distribution["5.000-10.000"] += 1
         else:
-            distribution['10.000+'] += 1
+            distribution["10.000+"] += 1
 
     return distribution
 
 
 def get_interest_value_stats(messages) -> Dict[str, float]:
     """Calculate basic statistics for interest_value"""
-    values = [float(msg.interest_value) for msg in messages if msg.interest_value is not None and msg.interest_value != 0.0]
+    values = [
+        float(msg.interest_value) for msg in messages if msg.interest_value is not None and msg.interest_value != 0.0
+    ]
 
     if not values:
-        return {
+        return {"count": 0, "min": 0, "max": 0, "avg": 0, "median": 0}
-            'count': 0,
-            'min': 0,
-            'max': 0,
-            'avg': 0,
-            'median': 0
-        }
 
     values.sort()
     count = len(values)
 
     return {
-        'count': count,
+        "count": count,
-        'min': min(values),
+        "min": min(values),
-        'max': max(values),
+        "max": max(values),
-        'avg': sum(values) / count,
+        "avg": sum(values) / count,
-        'median': values[count // 2] if count % 2 == 1 else (values[count // 2 - 1] + values[count // 2]) / 2
+        "median": values[count // 2] if count % 2 == 1 else (values[count // 2 - 1] + values[count // 2]) / 2,
     }
 
 
@@ -109,11 +104,15 @@ def get_available_chats() -> List[Tuple[str, str, int]]:
         chat_counts = {}
         for msg in Messages.select(Messages.chat_id).distinct():
             chat_id = msg.chat_id
-            count = Messages.select().where(
+            count = (
-                (Messages.chat_id == chat_id) & 
+                Messages.select()
-                (Messages.interest_value.is_null(False)) &
+                .where(
-                (Messages.interest_value != 0.0)
+                    (Messages.chat_id == chat_id)
-            ).count()
+                    & (Messages.interest_value.is_null(False))
+                    & (Messages.interest_value != 0.0)
+                )
+                .count()
+            )
             if count > 0:
                 chat_counts[chat_id] = count
 
@@ -146,13 +145,13 @@ def get_time_range_input() -> Tuple[Optional[float], Optional[float]]:
     now = time.time()
 
     if choice == "1":
-        return now - 24*3600, now
+        return now - 24 * 3600, now
     elif choice == "2":
-        return now - 3*24*3600, now
+        return now - 3 * 24 * 3600, now
     elif choice == "3":
-        return now - 7*24*3600, now
+        return now - 7 * 24 * 3600, now
     elif choice == "4":
-        return now - 30*24*3600, now
+        return now - 30 * 24 * 3600, now
     elif choice == "5":
         print("请输入开始时间 (格式: YYYY-MM-DD HH:MM:SS):")
         start_str = input().strip()
@@ -170,14 +169,13 @@ def get_time_range_input() -> Tuple[Optional[float], Optional[float]]:
         return None, None
 
 
-def analyze_interest_values(chat_id: Optional[str] = None, start_time: Optional[float] = None, end_time: Optional[float] = None) -> None:
+def analyze_interest_values(
+    chat_id: Optional[str] = None, start_time: Optional[float] = None, end_time: Optional[float] = None
+) -> None:
     """Analyze interest values with optional filters"""
 
     # 构建查询条件
-    query = Messages.select().where(
+    query = Messages.select().where((Messages.interest_value.is_null(False)) & (Messages.interest_value != 0.0))
-        (Messages.interest_value.is_null(False)) &
-        (Messages.interest_value != 0.0)
-    )
 
     if chat_id:
         query = query.where(Messages.chat_id == chat_id)
@@ -222,7 +220,7 @@ def analyze_interest_values(chat_id: Optional[str] = None, start_time: Optional[
     print(f"中位数: {stats['median']:.3f}")
 
     print("\nInterest Value 分布:")
-    total = stats['count']
+    total = stats["count"]
     for range_name, count in distribution.items():
         if count > 0:
             percentage = count / total * 100
@@ -233,16 +231,16 @@ def interactive_menu() -> None:
     """Interactive menu for interest value analysis"""
 
     while True:
-        print("\n" + "="*50)
+        print("\n" + "=" * 50)
         print("Interest Value 分析工具")
-        print("="*50)
+        print("=" * 50)
         print("1. 分析全部聊天")
         print("2. 选择特定聊天分析")
         print("q. 退出")
 
         choice = input("\n请选择分析模式 (1-2, q): ").strip()
 
-        if choice.lower() == 'q':
+        if choice.lower() == "q":
             print("再见！")
             break
 

scripts/log_viewer_optimized.py

@@ -1191,6 +1191,7 @@ class LogViewer:
 
         # 如果发现了新模块，在主线程中更新模块集合
         if new_modules:
+
             def update_modules():
                 self.modules.update(new_modules)
                 self.update_module_list()
@@ -1424,4 +1425,3 @@ def main():
 
 if __name__ == "__main__":
     main()
-

scripts/raw_data_preprocessor.py

@@ -2,6 +2,7 @@ import os
 from pathlib import Path
 import sys  # 新增系统模块导入
 from src.chat.knowledge.utils.hash import get_sha256
+
 sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
 from src.common.logger import get_logger
 
@@ -10,6 +11,7 @@ ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
 RAW_DATA_PATH = os.path.join(ROOT_PATH, "data/lpmm_raw_data")
 # IMPORTED_DATA_PATH = os.path.join(ROOT_PATH, "data/imported_lpmm_data")
 
+
 def _process_text_file(file_path):
     """处理单个文本文件，返回段落列表"""
     with open(file_path, "r", encoding="utf-8") as f:
@@ -44,6 +46,7 @@ def _process_multi_files() -> list:
         all_paragraphs.extend(paragraphs)
     return all_paragraphs
 
+
 def load_raw_data() -> tuple[list[str], list[str]]:
     """加载原始数据文件
 

scripts/text_length_analysis.py

@@ -4,10 +4,11 @@ import os
 import re
 from typing import Dict, List, Tuple, Optional
 from datetime import datetime
+
 # Add project root to Python path
 project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 sys.path.insert(0, project_root)
-from src.common.database.database_model import Messages, ChatStreams #noqa
+from src.common.database.database_model import Messages, ChatStreams  # noqa
 
 
 def contains_emoji_or_image_tags(text: str) -> bool:
@@ -16,8 +17,8 @@ def contains_emoji_or_image_tags(text: str) -> bool:
         return False
 
     # 检查是否包含 [表情包] 或 [图片] 标记
-    emoji_pattern = r'\[表情包[^\]]*\]'
+    emoji_pattern = r"\[表情包[^\]]*\]"
-    image_pattern = r'\[图片[^\]]*\]'
+    image_pattern = r"\[图片[^\]]*\]"
 
     return bool(re.search(emoji_pattern, text) or re.search(image_pattern, text))
 
@@ -29,7 +30,7 @@ def clean_reply_text(text: str) -> str:
 
     # 匹配 [回复 xxxx...] 格式的内容
     # 使用非贪婪匹配，匹配到第一个 ] 就停止
-    cleaned_text = re.sub(r'\[回复[^\]]*\]', '', text)
+    cleaned_text = re.sub(r"\[回复[^\]]*\]", "", text)
 
     # 去除多余的空白字符
     cleaned_text = cleaned_text.strip()
@@ -65,20 +66,20 @@ def format_timestamp(timestamp: float) -> str:
 def calculate_text_length_distribution(messages) -> Dict[str, int]:
     """Calculate distribution of processed_plain_text length"""
     distribution = {
-        '0': 0,           # 空文本
+        "0": 0,  # 空文本
-        '1-5': 0,         # 极短文本
+        "1-5": 0,  # 极短文本
-        '6-10': 0,        # 很短文本
+        "6-10": 0,  # 很短文本
-        '11-20': 0,       # 短文本
+        "11-20": 0,  # 短文本
-        '21-30': 0,       # 较短文本
+        "21-30": 0,  # 较短文本
-        '31-50': 0,       # 中短文本
+        "31-50": 0,  # 中短文本
-        '51-70': 0,       # 中等文本
+        "51-70": 0,  # 中等文本
-        '71-100': 0,      # 较长文本
+        "71-100": 0,  # 较长文本
-        '101-150': 0,     # 长文本
+        "101-150": 0,  # 长文本
-        '151-200': 0,     # 很长文本
+        "151-200": 0,  # 很长文本
-        '201-300': 0,     # 超长文本
+        "201-300": 0,  # 超长文本
-        '301-500': 0,     # 极长文本
+        "301-500": 0,  # 极长文本
-        '501-1000': 0,    # 巨长文本
+        "501-1000": 0,  # 巨长文本
-        '1000+': 0        # 超巨长文本
+        "1000+": 0,  # 超巨长文本
     }
 
     for msg in messages:
@@ -94,33 +95,33 @@ def calculate_text_length_distribution(messages) -> Dict[str, int]:
         length = len(cleaned_text)
 
         if length == 0:
-            distribution['0'] += 1
+            distribution["0"] += 1
         elif length <= 5:
-            distribution['1-5'] += 1
+            distribution["1-5"] += 1
         elif length <= 10:
-            distribution['6-10'] += 1
+            distribution["6-10"] += 1
         elif length <= 20:
-            distribution['11-20'] += 1
+            distribution["11-20"] += 1
         elif length <= 30:
-            distribution['21-30'] += 1
+            distribution["21-30"] += 1
         elif length <= 50:
-            distribution['31-50'] += 1
+            distribution["31-50"] += 1
         elif length <= 70:
-            distribution['51-70'] += 1
+            distribution["51-70"] += 1
         elif length <= 100:
-            distribution['71-100'] += 1
+            distribution["71-100"] += 1
         elif length <= 150:
-            distribution['101-150'] += 1
+            distribution["101-150"] += 1
         elif length <= 200:
-            distribution['151-200'] += 1
+            distribution["151-200"] += 1
         elif length <= 300:
-            distribution['201-300'] += 1
+            distribution["201-300"] += 1
         elif length <= 500:
-            distribution['301-500'] += 1
+            distribution["301-500"] += 1
         elif length <= 1000:
-            distribution['501-1000'] += 1
+            distribution["501-1000"] += 1
         else:
-            distribution['1000+'] += 1
+            distribution["1000+"] += 1
 
     return distribution
 
@@ -144,26 +145,26 @@ def get_text_length_stats(messages) -> Dict[str, float]:
 
     if not lengths:
         return {
-            'count': 0,
+            "count": 0,
-            'null_count': null_count,
+            "null_count": null_count,
-            'excluded_count': excluded_count,
+            "excluded_count": excluded_count,
-            'min': 0,
+            "min": 0,
-            'max': 0,
+            "max": 0,
-            'avg': 0,
+            "avg": 0,
-            'median': 0
+            "median": 0,
         }
 
     lengths.sort()
     count = len(lengths)
 
     return {
-        'count': count,
+        "count": count,
-        'null_count': null_count,
+        "null_count": null_count,
-        'excluded_count': excluded_count,
+        "excluded_count": excluded_count,
-        'min': min(lengths),
+        "min": min(lengths),
-        'max': max(lengths),
+        "max": max(lengths),
-        'avg': sum(lengths) / count,
+        "avg": sum(lengths) / count,
-        'median': lengths[count // 2] if count % 2 == 1 else (lengths[count // 2 - 1] + lengths[count // 2]) / 2
+        "median": lengths[count // 2] if count % 2 == 1 else (lengths[count // 2 - 1] + lengths[count // 2]) / 2,
     }
 
 
@@ -174,12 +175,16 @@ def get_available_chats() -> List[Tuple[str, str, int]]:
         chat_counts = {}
         for msg in Messages.select(Messages.chat_id).distinct():
             chat_id = msg.chat_id
-            count = Messages.select().where(
+            count = (
-                (Messages.chat_id == chat_id) &
+                Messages.select()
-                (Messages.is_emoji != 1) &
+                .where(
-                (Messages.is_picid != 1) &
+                    (Messages.chat_id == chat_id)
-                (Messages.is_command != 1)
+                    & (Messages.is_emoji != 1)
-            ).count()
+                    & (Messages.is_picid != 1)
+                    & (Messages.is_command != 1)
+                )
+                .count()
+            )
             if count > 0:
                 chat_counts[chat_id] = count
 
@@ -212,13 +217,13 @@ def get_time_range_input() -> Tuple[Optional[float], Optional[float]]:
     now = time.time()
 
     if choice == "1":
-        return now - 24*3600, now
+        return now - 24 * 3600, now
     elif choice == "2":
-        return now - 3*24*3600, now
+        return now - 3 * 24 * 3600, now
     elif choice == "3":
-        return now - 7*24*3600, now
+        return now - 7 * 24 * 3600, now
     elif choice == "4":
-        return now - 30*24*3600, now
+        return now - 30 * 24 * 3600, now
     elif choice == "5":
         print("请输入开始时间 (格式: YYYY-MM-DD HH:MM:SS):")
         start_str = input().strip()
@@ -260,15 +265,13 @@ def get_top_longest_messages(messages, top_n: int = 10) -> List[Tuple[str, int,
     return message_lengths[:top_n]
 
 
-def analyze_text_lengths(chat_id: Optional[str] = None, start_time: Optional[float] = None, end_time: Optional[float] = None) -> None:
+def analyze_text_lengths(
+    chat_id: Optional[str] = None, start_time: Optional[float] = None, end_time: Optional[float] = None
+) -> None:
     """Analyze processed_plain_text lengths with optional filters"""
 
     # 构建查询条件，排除特殊类型的消息
-    query = Messages.select().where(
+    query = Messages.select().where((Messages.is_emoji != 1) & (Messages.is_picid != 1) & (Messages.is_command != 1))
-        (Messages.is_emoji != 1) &
-        (Messages.is_picid != 1) &
-        (Messages.is_command != 1)
-    )
 
     if chat_id:
         query = query.where(Messages.chat_id == chat_id)
@@ -312,14 +315,14 @@ def analyze_text_lengths(chat_id: Optional[str] = None, start_time: Optional[flo
     print(f"有文本消息数量: {stats['count']}")
     print(f"空文本消息数量: {stats['null_count']}")
     print(f"被排除的消息数量: {stats['excluded_count']}")
-    if stats['count'] > 0:
+    if stats["count"] > 0:
         print(f"最短长度: {stats['min']} 字符")
         print(f"最长长度: {stats['max']} 字符")
         print(f"平均长度: {stats['avg']:.2f} 字符")
         print(f"中位数长度: {stats['median']:.2f} 字符")
 
     print("\n文本长度分布:")
-    total = stats['count']
+    total = stats["count"]
     if total > 0:
         for range_name, count in distribution.items():
             if count > 0:
@@ -340,16 +343,16 @@ def interactive_menu() -> None:
     """Interactive menu for text length analysis"""
 
     while True:
-        print("\n" + "="*50)
+        print("\n" + "=" * 50)
         print("Processed Plain Text 长度分析工具")
-        print("="*50)
+        print("=" * 50)
         print("1. 分析全部聊天")
         print("2. 选择特定聊天分析")
         print("q. 退出")
 
         choice = input("\n请选择分析模式 (1-2, q): ").strip()
 
-        if choice.lower() == 'q':
+        if choice.lower() == "q":
             print("再见！")
             break
 

src/chat/emoji_system/emoji_manager.py

@@ -731,7 +731,7 @@ class EmojiManager:
                 emoji_record = Emoji.get_or_none(Emoji.emoji_hash == emoji_hash)
                 if emoji_record and emoji_record.emotion:
                     logger.info(f"[缓存命中] 从数据库获取表情包情感标签: {emoji_record.emotion[:50]}...")
-                    return emoji_record.emotion.split(',')
+                    return emoji_record.emotion.split(",")
             except Exception as e:
                 logger.error(f"从数据库查询表情包情感标签时出错: {e}")
 

src/chat/express/expression_selector.py

@@ -123,9 +123,7 @@ class ExpressionSelector:
                 return group_chat_ids
         return [chat_id]
 
-    def get_random_expressions(
+    def get_random_expressions(self, chat_id: str, total_num: int) -> List[Dict[str, Any]]:
-        self, chat_id: str, total_num: int
-    ) -> List[Dict[str, Any]]:
         # sourcery skip: extract-duplicate-method, move-assign
         # 支持多chat_id合并抽选
         related_chat_ids = self.get_related_chat_ids(chat_id)
@@ -248,7 +246,6 @@ class ExpressionSelector:
 
         # 4. 调用LLM
         try:
-            
             # start_time = time.time()
             content, (reasoning_content, model_name, _) = await self.llm_model.generate_response_async(prompt=prompt)
             # logger.info(f"LLM请求时间: {model_name}  {time.time() - start_time} \n{prompt}")
@@ -297,7 +294,6 @@ class ExpressionSelector:
             return [], []
 
 
-
 init_prompt()
 
 try:

src/chat/frequency_control/focus_value_control.py

@@ -119,4 +119,3 @@ def get_global_focus_value() -> Optional[float]:
             return get_time_based_focus_value(config_item[1:])
 
     return None
-

src/chat/frequency_control/talk_frequency_control.py

@@ -124,5 +124,3 @@ def get_global_frequency() -> Optional[float]:
             return get_time_based_frequency(config_item[1:])
 
     return None
-
-

src/chat/heart_flow/heartFC_chat.py

@@ -261,7 +261,11 @@ class HeartFChatting:
 
         return loop_info, reply_text, cycle_timers
 
-    async def _observe(self, interest_value: float = 0.0, recent_messages_list: List["DatabaseMessages"] = []) -> bool:
+    async def _observe(
+        self, interest_value: float = 0.0, recent_messages_list: Optional[List["DatabaseMessages"]] = None
+    ) -> bool:
+        if recent_messages_list is None:
+            recent_messages_list = []
         reply_text = ""  # 初始化reply_text变量，避免UnboundLocalError
 
         # 使用sigmoid函数将interest_value转换为概率

src/chat/heart_flow/heartflow.py

@@ -3,8 +3,10 @@ from typing import Any, Optional, Dict
 
 from src.common.logger import get_logger
 from src.chat.heart_flow.heartFC_chat import HeartFChatting
+
 logger = get_logger("heartflow")
 
+
 class Heartflow:
     """主心流协调器，负责初始化并协调聊天"""
 
@@ -18,7 +20,7 @@ class Heartflow:
                 if chat := self.heartflow_chat_list.get(chat_id):
                     return chat
             else:
-                new_chat = HeartFChatting(chat_id = chat_id)
+                new_chat = HeartFChatting(chat_id=chat_id)
                 await new_chat.start()
                 self.heartflow_chat_list[chat_id] = new_chat
                 return new_chat
@@ -27,4 +29,5 @@ class Heartflow:
             traceback.print_exc()
             return None
 
+
 heartflow = Heartflow()

src/chat/heart_flow/heartflow_message_processor.py

@@ -23,6 +23,7 @@ if TYPE_CHECKING:
 
 logger = get_logger("chat")
 
+
 async def _calculate_interest(message: MessageRecv) -> Tuple[float, list[str]]:
     """计算消息的兴趣度
 
@@ -35,13 +36,13 @@ async def _calculate_interest(message: MessageRecv) -> Tuple[float, list[str]]:
     if message.is_picid or message.is_emoji:
         return 0.0, []
 
-    is_mentioned,is_at,reply_probability_boost = is_mentioned_bot_in_message(message)
+    is_mentioned, is_at, reply_probability_boost = is_mentioned_bot_in_message(message)
     interested_rate = 0.0
 
     with Timer("记忆激活"):
-        interested_rate, keywords,keywords_lite = await hippocampus_manager.get_activate_from_text(
+        interested_rate, keywords, keywords_lite = await hippocampus_manager.get_activate_from_text(
             message.processed_plain_text,
-            max_depth= 4,
+            max_depth=4,
             fast_retrieval=global_config.chat.interest_rate_mode == "fast",
         )
         message.key_words = keywords
@@ -79,7 +80,6 @@ async def _calculate_interest(message: MessageRecv) -> Tuple[float, list[str]]:
     # 确保在范围内
     base_interest = min(max(base_interest, 0.01), 0.3)
 
-        
     message.interest_value = base_interest
     message.is_mentioned = is_mentioned
     message.is_at = is_at
@@ -116,7 +116,6 @@ class HeartFCMessageReceiver:
             # 2. 兴趣度计算与更新
             interested_rate, keywords = await _calculate_interest(message)
 
-
             await self.storage.store_message(message, chat)
 
             heartflow_chat: HeartFChatting = await heartflow.get_or_create_heartflow_chat(chat.stream_id)  # type: ignore
@@ -145,18 +144,20 @@ class HeartFCMessageReceiver:
                         # 如果没有找到图片描述，则移除[picid:xxxx]标记
                         processed_text = processed_text.replace(f"[picid:{picid}]", "[图片：网络不好，图片无法加载]")
 
-            
             # 应用用户引用格式替换，将回复<aaa:bbb>和@<aaa:bbb>格式转换为可读格式
             processed_plain_text = replace_user_references(
                 processed_text,
-                message.message_info.platform, # type: ignore
+                message.message_info.platform,  # type: ignore
-                replace_bot_name=True
+                replace_bot_name=True,
             )
 
-
             logger.info(f"[{mes_name}]{userinfo.user_nickname}:{processed_plain_text}[{interested_rate:.2f}]")  # type: ignore
 
-            _ = Person.register_person(platform=message.message_info.platform, user_id=message.message_info.user_info.user_id,nickname=userinfo.user_nickname) # type: ignore
+            _ = Person.register_person(
+                platform=message.message_info.platform,
+                user_id=message.message_info.user_info.user_id,
+                nickname=userinfo.user_nickname,
+            )  # type: ignore
 
         except Exception as e:
             logger.error(f"消息处理失败: {e}")

src/chat/heart_flow/hfc_utils.py

@@ -124,6 +124,7 @@ async def send_typing():
         message_type="state", content="typing", stream_id=chat.stream_id, storage_message=False
     )
 
+
 async def stop_typing():
     group_info = GroupInfo(platform="amaidesu_default", group_id="114514", group_name="内心")
 

src/chat/knowledge/__init__.py

@@ -30,6 +30,7 @@ DATA_PATH = os.path.join(ROOT_PATH, "data")
 qa_manager = None
 inspire_manager = None
 
+
 def lpmm_start_up():  # sourcery skip: extract-duplicate-method
     # 检查LPMM知识库是否启用
     if global_config.lpmm_knowledge.enable:

src/chat/knowledge/embedding_store.py

@@ -32,11 +32,11 @@ install(extra_lines=3)
 
 # 多线程embedding配置常量
 DEFAULT_MAX_WORKERS = 10  # 默认最大线程数
-DEFAULT_CHUNK_SIZE = 10   # 默认每个线程处理的数据块大小
+DEFAULT_CHUNK_SIZE = 10  # 默认每个线程处理的数据块大小
-MIN_CHUNK_SIZE = 1        # 最小分块大小
+MIN_CHUNK_SIZE = 1  # 最小分块大小
-MAX_CHUNK_SIZE = 50       # 最大分块大小
+MAX_CHUNK_SIZE = 50  # 最大分块大小
-MIN_WORKERS = 1           # 最小线程数
+MIN_WORKERS = 1  # 最小线程数
-MAX_WORKERS = 20          # 最大线程数
+MAX_WORKERS = 20  # 最大线程数
 
 ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
 EMBEDDING_DATA_DIR = os.path.join(ROOT_PATH, "data", "embedding")
@@ -93,7 +93,13 @@ class EmbeddingStoreItem:
 
 
 class EmbeddingStore:
-    def __init__(self, namespace: str, dir_path: str, max_workers: int = DEFAULT_MAX_WORKERS, chunk_size: int = DEFAULT_CHUNK_SIZE):
+    def __init__(
+        self,
+        namespace: str,
+        dir_path: str,
+        max_workers: int = DEFAULT_MAX_WORKERS,
+        chunk_size: int = DEFAULT_CHUNK_SIZE,
+    ):
         self.namespace = namespace
         self.dir = dir_path
         self.embedding_file_path = f"{dir_path}/{namespace}.parquet"
@@ -106,9 +112,13 @@ class EmbeddingStore:
 
         # 如果配置值被调整，记录日志
         if self.max_workers != max_workers:
-            logger.warning(f"max_workers 已从 {max_workers} 调整为 {self.max_workers} (范围: {MIN_WORKERS}-{MAX_WORKERS})")
+            logger.warning(
+                f"max_workers 已从 {max_workers} 调整为 {self.max_workers} (范围: {MIN_WORKERS}-{MAX_WORKERS})"
+            )
         if self.chunk_size != chunk_size:
-            logger.warning(f"chunk_size 已从 {chunk_size} 调整为 {self.chunk_size} (范围: {MIN_CHUNK_SIZE}-{MAX_CHUNK_SIZE})")
+            logger.warning(
+                f"chunk_size 已从 {chunk_size} 调整为 {self.chunk_size} (范围: {MIN_CHUNK_SIZE}-{MAX_CHUNK_SIZE})"
+            )
 
         self.store = {}
 
@@ -147,7 +157,9 @@ class EmbeddingStore:
             except Exception:
                 pass
 
-    def _get_embeddings_batch_threaded(self, strs: List[str], chunk_size: int = 10, max_workers: int = 10, progress_callback=None) -> List[Tuple[str, List[float]]]:
+    def _get_embeddings_batch_threaded(
+        self, strs: List[str], chunk_size: int = 10, max_workers: int = 10, progress_callback=None
+    ) -> List[Tuple[str, List[float]]]:
         """使用多线程批量获取嵌入向量
 
         Args:
@@ -165,7 +177,7 @@ class EmbeddingStore:
         # 分块
         chunks = []
         for i in range(0, len(strs), chunk_size):
-            chunk = strs[i:i + chunk_size]
+            chunk = strs[i : i + chunk_size]
             chunks.append((i, chunk))  # 保存起始索引以维持顺序
 
         # 结果存储，使用字典按索引存储以保证顺序
@@ -264,7 +276,7 @@ class EmbeddingStore:
         embedding_results = self._get_embeddings_batch_threaded(
             EMBEDDING_TEST_STRINGS,
             chunk_size=min(self.chunk_size, len(EMBEDDING_TEST_STRINGS)),
-            max_workers=min(self.max_workers, len(EMBEDDING_TEST_STRINGS))
+            max_workers=min(self.max_workers, len(EMBEDDING_TEST_STRINGS)),
         )
 
         # 构建测试向量字典
@@ -311,7 +323,7 @@ class EmbeddingStore:
         embedding_results = self._get_embeddings_batch_threaded(
             EMBEDDING_TEST_STRINGS,
             chunk_size=min(self.chunk_size, len(EMBEDDING_TEST_STRINGS)),
-            max_workers=min(self.max_workers, len(EMBEDDING_TEST_STRINGS))
+            max_workers=min(self.max_workers, len(EMBEDDING_TEST_STRINGS)),
         )
 
         # 检查一致性
@@ -370,8 +382,16 @@ class EmbeddingStore:
 
             if new_strs:
                 # 使用实例配置的参数，智能调整分块和线程数
-                optimal_chunk_size = max(MIN_CHUNK_SIZE, min(self.chunk_size, len(new_strs) // self.max_workers if self.max_workers > 0 else self.chunk_size))
+                optimal_chunk_size = max(
-                optimal_max_workers = min(self.max_workers, max(MIN_WORKERS, len(new_strs) // optimal_chunk_size if optimal_chunk_size > 0 else 1))
+                    MIN_CHUNK_SIZE,
+                    min(
+                        self.chunk_size, len(new_strs) // self.max_workers if self.max_workers > 0 else self.chunk_size
+                    ),
+                )
+                optimal_max_workers = min(
+                    self.max_workers,
+                    max(MIN_WORKERS, len(new_strs) // optimal_chunk_size if optimal_chunk_size > 0 else 1),
+                )
 
                 logger.debug(f"使用多线程处理: chunk_size={optimal_chunk_size}, max_workers={optimal_max_workers}")
 
@@ -384,7 +404,7 @@ class EmbeddingStore:
                     new_strs,
                     chunk_size=optimal_chunk_size,
                     max_workers=optimal_max_workers,
-                    progress_callback=update_progress
+                    progress_callback=update_progress,
                 )
 
                 # 存入结果（不再需要在这里更新进度，因为已经在回调中更新了）

src/chat/knowledge/kg_manager.py

@@ -426,9 +426,7 @@ class KGManager:
         # 获取最终结果
         # 从搜索结果中提取文段节点的结果
         passage_node_res = [
-            (node_key, score)
+            (node_key, score) for node_key, score in ppr_res.items() if node_key.startswith("paragraph")
-            for node_key, score in ppr_res.items()
-            if node_key.startswith("paragraph")
         ]
         del ppr_res
 

src/chat/knowledge/mem_active_manager.py

@@ -1,8 +1,8 @@
 raise DeprecationWarning("MemoryActiveManager is not used yet, please do not import it")
-from .lpmmconfig import global_config
+from .lpmmconfig import global_config  # noqa
-from .embedding_store import EmbeddingManager
+from .embedding_store import EmbeddingManager  # noqa
-from .llm_client import LLMClient
+from .llm_client import LLMClient  # noqa
-from .utils.dyn_topk import dyn_select_top_k
+from .utils.dyn_topk import dyn_select_top_k  # noqa
 
 
 class MemoryActiveManager:

src/chat/planner_actions/action_modifier.py

@@ -103,25 +103,23 @@ class ActionModifier:
             self.action_manager.remove_action_from_using(action_name)
             logger.debug(f"{self.log_prefix}阶段二移除动作: {action_name}，原因: {reason}")
 
-
-
         # === 第三阶段：激活类型判定 ===
         # if chat_content is not None:
-            # logger.debug(f"{self.log_prefix}开始激活类型判定阶段")
+        # logger.debug(f"{self.log_prefix}开始激活类型判定阶段")
 
-            # 获取当前使用的动作集（经过第一阶段处理）
+        # 获取当前使用的动作集（经过第一阶段处理）
-            # current_using_actions = self.action_manager.get_using_actions()
+        # current_using_actions = self.action_manager.get_using_actions()
 
-            # 获取因激活类型判定而需要移除的动作
+        # 获取因激活类型判定而需要移除的动作
-            # removals_s3 = await self._get_deactivated_actions_by_type(
+        # removals_s3 = await self._get_deactivated_actions_by_type(
-                # current_using_actions,
+        # current_using_actions,
-                # chat_content,
+        # chat_content,
-            # )
+        # )
 
-            # 应用第三阶段的移除
+        # 应用第三阶段的移除
-            # for action_name, reason in removals_s3:
+        # for action_name, reason in removals_s3:
-                # self.action_manager.remove_action_from_using(action_name)
+        # self.action_manager.remove_action_from_using(action_name)
-                # logger.debug(f"{self.log_prefix}阶段三移除动作: {action_name}，原因: {reason}")
+        # logger.debug(f"{self.log_prefix}阶段三移除动作: {action_name}，原因: {reason}")
 
         # === 统一日志记录 ===
         all_removals = removals_s1 + removals_s2
@@ -131,9 +129,7 @@ class ActionModifier:
 
         available_actions = list(self.action_manager.get_using_actions().keys())
         available_actions_text = "、".join(available_actions) if available_actions else "无"
-        logger.debug(
+        logger.debug(f"{self.log_prefix} 当前可用动作: {available_actions_text}||移除: {removals_summary}")
-            f"{self.log_prefix} 当前可用动作: {available_actions_text}||移除: {removals_summary}"
-        )
 
     def _check_action_associated_types(self, all_actions: Dict[str, ActionInfo], chat_context: ChatMessageContext):
         type_mismatched_actions: List[Tuple[str, str]] = []

src/chat/utils/statistic.py

@@ -396,7 +396,7 @@ class StatisticOutputTask(AsyncTask):
                         # 计算标准差
                         if len(time_costs) > 1:
                             variance = sum((x - avg_time_cost) ** 2 for x in time_costs) / len(time_costs)
-                            std_time_cost = variance ** 0.5
+                            std_time_cost = variance**0.5
                             stats[period_key][std_key][item_name] = round(std_time_cost, 3)
                         else:
                             stats[period_key][std_key][item_name] = 0.0
@@ -506,8 +506,6 @@ class StatisticOutputTask(AsyncTask):
                     break
         return stats
 
-    
-
     def _collect_all_statistics(self, now: datetime) -> Dict[str, Dict[str, Any]]:
         """
         收集各时间段的统计数据
@@ -639,7 +637,9 @@ class StatisticOutputTask(AsyncTask):
             cost = stats[COST_BY_MODEL][model_name]
             avg_time_cost = stats[AVG_TIME_COST_BY_MODEL][model_name]
             std_time_cost = stats[STD_TIME_COST_BY_MODEL][model_name]
-            output.append(data_fmt.format(name, count, in_tokens, out_tokens, tokens, cost, avg_time_cost, std_time_cost))
+            output.append(
+                data_fmt.format(name, count, in_tokens, out_tokens, tokens, cost, avg_time_cost, std_time_cost)
+            )
 
         output.append("")
         return "\n".join(output)
@@ -728,7 +728,9 @@ class StatisticOutputTask(AsyncTask):
                     f"<td>{stat_data[STD_TIME_COST_BY_MODEL][model_name]:.1f} 秒</td>"
                     f"</tr>"
                     for model_name, count in sorted(stat_data[REQ_CNT_BY_MODEL].items())
-                ] if stat_data[REQ_CNT_BY_MODEL] else ["<tr><td colspan='8' style='text-align: center; color: #999;'>暂无数据</td></tr>"]
+                ]
+                if stat_data[REQ_CNT_BY_MODEL]
+                else ["<tr><td colspan='8' style='text-align: center; color: #999;'>暂无数据</td></tr>"]
             )
             # 按请求类型分类统计
             type_rows = "\n".join(
@@ -744,7 +746,9 @@ class StatisticOutputTask(AsyncTask):
                     f"<td>{stat_data[STD_TIME_COST_BY_TYPE][req_type]:.1f} 秒</td>"
                     f"</tr>"
                     for req_type, count in sorted(stat_data[REQ_CNT_BY_TYPE].items())
-                ] if stat_data[REQ_CNT_BY_TYPE] else ["<tr><td colspan='8' style='text-align: center; color: #999;'>暂无数据</td></tr>"]
+                ]
+                if stat_data[REQ_CNT_BY_TYPE]
+                else ["<tr><td colspan='8' style='text-align: center; color: #999;'>暂无数据</td></tr>"]
             )
             # 按模块分类统计
             module_rows = "\n".join(
@@ -760,7 +764,9 @@ class StatisticOutputTask(AsyncTask):
                     f"<td>{stat_data[STD_TIME_COST_BY_MODULE][module_name]:.1f} 秒</td>"
                     f"</tr>"
                     for module_name, count in sorted(stat_data[REQ_CNT_BY_MODULE].items())
-                ] if stat_data[REQ_CNT_BY_MODULE] else ["<tr><td colspan='8' style='text-align: center; color: #999;'>暂无数据</td></tr>"]
+                ]
+                if stat_data[REQ_CNT_BY_MODULE]
+                else ["<tr><td colspan='8' style='text-align: center; color: #999;'>暂无数据</td></tr>"]
             )
 
             # 聊天消息统计
@@ -768,7 +774,9 @@ class StatisticOutputTask(AsyncTask):
                 [
                     f"<tr><td>{self.name_mapping[chat_id][0]}</td><td>{count}</td></tr>"
                     for chat_id, count in sorted(stat_data[MSG_CNT_BY_CHAT].items())
-                ] if stat_data[MSG_CNT_BY_CHAT] else ["<tr><td colspan='2' style='text-align: center; color: #999;'>暂无数据</td></tr>"]
+                ]
+                if stat_data[MSG_CNT_BY_CHAT]
+                else ["<tr><td colspan='2' style='text-align: center; color: #999;'>暂无数据</td></tr>"]
             )
             # 生成HTML
             return f"""

src/chat/utils/utils.py

@@ -51,7 +51,7 @@ def is_mentioned_bot_in_message(message: MessageRecv) -> tuple[bool, bool, float
     is_mentioned = False
 
     # 这部分怎么处理啊啊啊啊
-    #我觉得可以给消息加一个 reply_probability_boost字段
+    # 我觉得可以给消息加一个 reply_probability_boost字段
     if (
         message.message_info.additional_config is not None
         and message.message_info.additional_config.get("is_mentioned") is not None
@@ -826,20 +826,48 @@ def parse_keywords_string(keywords_input) -> list[str]:
     return [keywords_str] if keywords_str else []
 
 
-
-
 def cut_key_words(concept_name: str) -> list[str]:
     """对概念名称进行jieba分词，并过滤掉关键词列表中的关键词"""
     concept_name_tokens = list(jieba.cut(concept_name))
 
     # 定义常见连词、停用词与标点
-    conjunctions = {
+    conjunctions = {"和", "与", "及", "跟", "以及", "并且", "而且", "或", "或者", "并"}
-        "和", "与", "及", "跟", "以及", "并且", "而且", "或", "或者", "并"
-    }
     stop_words = {
-        "的", "了", "呢", "吗", "吧", "啊", "哦", "恩", "嗯", "呀", "嘛", "哇",
+        "的",
-        "在", "是", "很", "也", "又", "就", "都", "还", "更", "最", "被", "把",
+        "了",
-        "给", "对", "和", "与", "及", "跟", "并", "而且", "或者", "或", "以及"
+        "呢",
+        "吗",
+        "吧",
+        "啊",
+        "哦",
+        "恩",
+        "嗯",
+        "呀",
+        "嘛",
+        "哇",
+        "在",
+        "是",
+        "很",
+        "也",
+        "又",
+        "就",
+        "都",
+        "还",
+        "更",
+        "最",
+        "被",
+        "把",
+        "给",
+        "对",
+        "和",
+        "与",
+        "及",
+        "跟",
+        "并",
+        "而且",
+        "或者",
+        "或",
+        "以及",
     }
     chinese_punctuations = set("，。！？、；：（）【】《》“”‘’—…·-——,.!?;:()[]<>'\"/\\")
 
@@ -864,11 +892,16 @@ def cut_key_words(concept_name: str) -> list[str]:
             left = merged_tokens[-1]
             right = cleaned_tokens[i + 1]
             # 左右都需要是有效词
-            if left and right \
+            if (
-                and left not in conjunctions and right not in conjunctions \
+                left
-                and left not in stop_words and right not in stop_words \
+                and right
-                and not all(ch in chinese_punctuations for ch in left) \
+                and left not in conjunctions
-                and not all(ch in chinese_punctuations for ch in right):
+                and right not in conjunctions
+                and left not in stop_words
+                and right not in stop_words
+                and not all(ch in chinese_punctuations for ch in left)
+                and not all(ch in chinese_punctuations for ch in right)
+            ):
                 # 合并为一个新词，并替换掉左侧与跳过右侧
                 combined = f"{left}{tok}{right}"
                 merged_tokens[-1] = combined
@@ -889,7 +922,7 @@ def cut_key_words(concept_name: str) -> list[str]:
         if tok in stop_words:
             continue
         # if tok in ban_words:
-            # continue
+        # continue
         if all(ch in chinese_punctuations for ch in tok):
             continue
         if tok.strip() == "":

src/chat/utils/utils_image.py

@@ -94,6 +94,7 @@ class ImageManager:
 
     async def get_emoji_tag(self, image_base64: str) -> str:
         from src.chat.emoji_system.emoji_manager import get_emoji_manager
+
         emoji_manager = get_emoji_manager()
         if isinstance(image_base64, str):
             image_base64 = image_base64.encode("ascii", errors="ignore").decode("ascii")
@@ -120,6 +121,7 @@ class ImageManager:
             # 优先使用EmojiManager查询已注册表情包的描述
             try:
                 from src.chat.emoji_system.emoji_manager import get_emoji_manager
+
                 emoji_manager = get_emoji_manager()
                 tags = await emoji_manager.get_emoji_tag_by_hash(image_hash)
                 if tags:

src/common/data_models/database_data_model.py

@@ -205,6 +205,7 @@ 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/llm_data_model.py

@@ -2,10 +2,12 @@ from dataclasses import dataclass
 from typing import Optional, List, TYPE_CHECKING
 
 from . import BaseDataModel
+
 if TYPE_CHECKING:
     from src.common.data_models.message_data_model import ReplySetModel
     from src.llm_models.payload_content.tool_option import ToolCall
 
+
 @dataclass
 class LLMGenerationDataModel(BaseDataModel):
     content: Optional[str] = None

src/common/database/database_model.py

@@ -271,9 +271,6 @@ class PersonInfo(BaseModel):
     attitude_to_me = TextField(null=True)  # 对bot的态度
     attitude_to_me_confidence = FloatField(null=True)  # 对bot的态度置信度
 
-
-
-
     class Meta:
         # database = db # 继承自 BaseModel
         table_name = "person_info"
@@ -299,6 +296,7 @@ class GroupInfo(BaseModel):
         # database = db # 继承自 BaseModel
         table_name = "group_info"
 
+
 class Expression(BaseModel):
     """
     用于存储表达风格的模型。
@@ -315,6 +313,7 @@ class Expression(BaseModel):
     class Meta:
         table_name = "expression"
 
+
 class GraphNodes(BaseModel):
     """
     用于存储记忆图节点的模型
@@ -504,8 +503,9 @@ def sync_field_constraints():
 
                 # 获取当前表结构信息
                 cursor = db.execute_sql(f"PRAGMA table_info('{table_name}')")
-                current_schema = {row[1]: {'type': row[2], 'notnull': bool(row[3]), 'default': row[4]} 
+                current_schema = {
-                                for row in cursor.fetchall()}
+                    row[1]: {"type": row[2], "notnull": bool(row[3]), "default": row[4]} for row in cursor.fetchall()
+                }
 
                 # 检查每个模型字段的约束
                 constraints_to_fix = []
@@ -513,29 +513,33 @@ def sync_field_constraints():
                     if field_name not in current_schema:
                         continue  # 字段不存在，跳过
 
-                    current_notnull = current_schema[field_name]['notnull']
+                    current_notnull = current_schema[field_name]["notnull"]
                     model_allows_null = field_obj.null
 
                     # 如果模型允许 null 但数据库字段不允许 null，需要修复
                     if model_allows_null and current_notnull:
-                        constraints_to_fix.append({
+                        constraints_to_fix.append(
-                            'field_name': field_name,
+                            {
-                            'field_obj': field_obj,
+                                "field_name": field_name,
-                            'action': 'allow_null',
+                                "field_obj": field_obj,
-                            'current_constraint': 'NOT NULL',
+                                "action": "allow_null",
-                            'target_constraint': 'NULL'
+                                "current_constraint": "NOT NULL",
-                        })
+                                "target_constraint": "NULL",
+                            }
+                        )
                         logger.warning(f"字段 '{field_name}' 约束不一致: 模型允许NULL，但数据库为NOT NULL")
 
                     # 如果模型不允许 null 但数据库字段允许 null，也需要修复（但要小心）
                     elif not model_allows_null and not current_notnull:
-                        constraints_to_fix.append({
+                        constraints_to_fix.append(
-                            'field_name': field_name,
+                            {
-                            'field_obj': field_obj,
+                                "field_name": field_name,
-                            'action': 'disallow_null',
+                                "field_obj": field_obj,
-                            'current_constraint': 'NULL',
+                                "action": "disallow_null",
-                            'target_constraint': 'NOT NULL'
+                                "current_constraint": "NULL",
-                        })
+                                "target_constraint": "NOT NULL",
+                            }
+                        )
                         logger.warning(f"字段 '{field_name}' 约束不一致: 模型不允许NULL，但数据库允许NULL")
 
                 # 修复约束不一致的字段
@@ -575,7 +579,7 @@ def _fix_table_constraints(table_name, model, constraints_to_fix):
         # 4. 从备份表恢复数据
         # 获取字段列表
         fields = list(model._meta.fields.keys())
-        fields_str = ', '.join(fields)
+        fields_str = ", ".join(fields)
 
         # 对于需要从 NOT NULL 改为 NULL 的字段，直接复制数据
         # 对于需要从 NULL 改为 NOT NULL 的字段，需要处理 NULL 值
@@ -583,8 +587,7 @@ def _fix_table_constraints(table_name, model, constraints_to_fix):
 
         # 检查是否有字段需要从 NULL 改为 NOT NULL
         null_to_notnull_fields = [
-            constraint['field_name'] for constraint in constraints_to_fix 
+            constraint["field_name"] for constraint in constraints_to_fix if constraint["action"] == "disallow_null"
-            if constraint['action'] == 'disallow_null'
         ]
 
         if null_to_notnull_fields:
@@ -612,7 +615,7 @@ def _fix_table_constraints(table_name, model, constraints_to_fix):
                 else:
                     select_fields.append(field_name)
 
-            select_str = ', '.join(select_fields)
+            select_str = ", ".join(select_fields)
             insert_sql = f"INSERT INTO {table_name} ({fields_str}) SELECT {select_str} FROM {backup_table}"
 
         db.execute_sql(insert_sql)
@@ -633,8 +636,10 @@ def _fix_table_constraints(table_name, model, constraints_to_fix):
 
         # 记录修复的约束
         for constraint in constraints_to_fix:
-            logger.info(f"已修复字段 '{constraint['field_name']}': "
+            logger.info(
-                       f"{constraint['current_constraint']} -> {constraint['target_constraint']}")
+                f"已修复字段 '{constraint['field_name']}': "
+                f"{constraint['current_constraint']} -> {constraint['target_constraint']}"
+            )
 
     except Exception as e:
         logger.exception(f"修复表 '{table_name}' 约束时出错: {e}")
@@ -681,8 +686,9 @@ def check_field_constraints():
 
                 # 获取当前表结构信息
                 cursor = db.execute_sql(f"PRAGMA table_info('{table_name}')")
-                current_schema = {row[1]: {'type': row[2], 'notnull': bool(row[3]), 'default': row[4]} 
+                current_schema = {
-                                for row in cursor.fetchall()}
+                    row[1]: {"type": row[2], "notnull": bool(row[3]), "default": row[4]} for row in cursor.fetchall()
+                }
 
                 table_inconsistencies = []
 
@@ -691,25 +697,29 @@ def check_field_constraints():
                     if field_name not in current_schema:
                         continue
 
-                    current_notnull = current_schema[field_name]['notnull']
+                    current_notnull = current_schema[field_name]["notnull"]
                     model_allows_null = field_obj.null
 
                     if model_allows_null and current_notnull:
-                        table_inconsistencies.append({
+                        table_inconsistencies.append(
-                            'field_name': field_name,
+                            {
-                            'issue': 'model_allows_null_but_db_not_null',
+                                "field_name": field_name,
-                            'model_constraint': 'NULL',
+                                "issue": "model_allows_null_but_db_not_null",
-                            'db_constraint': 'NOT NULL',
+                                "model_constraint": "NULL",
-                            'recommended_action': 'allow_null'
+                                "db_constraint": "NOT NULL",
-                        })
+                                "recommended_action": "allow_null",
+                            }
+                        )
                     elif not model_allows_null and not current_notnull:
-                        table_inconsistencies.append({
+                        table_inconsistencies.append(
-                            'field_name': field_name,
+                            {
-                            'issue': 'model_not_null_but_db_allows_null',
+                                "field_name": field_name,
-                            'model_constraint': 'NOT NULL',
+                                "issue": "model_not_null_but_db_allows_null",
-                            'db_constraint': 'NULL',
+                                "model_constraint": "NOT NULL",
-                            'recommended_action': 'disallow_null'
+                                "db_constraint": "NULL",
-                        })
+                                "recommended_action": "disallow_null",
+                            }
+                        )
 
                 if table_inconsistencies:
                     inconsistencies[table_name] = table_inconsistencies
@@ -720,10 +730,5 @@ def check_field_constraints():
     return inconsistencies
 
 
-
 # 模块加载时调用初始化函数
 initialize_database(sync_constraints=True)
-
-
-
-

src/common/logger.py

@@ -339,24 +339,18 @@ MODULE_COLORS = {
     #   67         ：具体的颜色编号（0-255），这里是较暗的蓝色
     "sender": "\033[38;5;24m",  # 67号色，较暗的蓝色，适合不显眼的日志
     "send_api": "\033[38;5;24m",  # 208号色，橙色，适合突出显示
-    
     # 生成
     "replyer": "\033[38;5;208m",  # 橙色
     "llm_api": "\033[38;5;208m",  # 橙色
-    
     # 消息处理
     "chat": "\033[38;5;82m",  # 亮蓝色
     "chat_image": "\033[38;5;68m",  # 浅蓝色
-    
+    # emoji
-    #emoji
     "emoji": "\033[38;5;214m",  # 橙黄色，偏向橙色
     "emoji_api": "\033[38;5;214m",  # 橙黄色，偏向橙色
-    
     # 核心模块
     "main": "\033[1;97m",  # 亮白色+粗体 (主程序)
-
     "memory": "\033[38;5;34m",  # 天蓝色
-    
     "config": "\033[93m",  # 亮黄色
     "common": "\033[95m",  # 亮紫色
     "tools": "\033[96m",  # 亮青色
@@ -367,9 +361,6 @@ MODULE_COLORS = {
     "llm_models": "\033[36m",  # 青色
     "remote": "\033[38;5;242m",  # 深灰色，更不显眼
     "planner": "\033[36m",
-   
-
-
     "relation": "\033[38;5;139m",  # 柔和的紫色，不刺眼
     # 聊天相关模块
     "normal_chat": "\033[38;5;81m",  # 亮蓝绿色
@@ -379,11 +370,9 @@ MODULE_COLORS = {
     "background_tasks": "\033[38;5;240m",  # 灰色
     "chat_message": "\033[38;5;45m",  # 青色
     "chat_stream": "\033[38;5;51m",  # 亮青色
-
     "message_storage": "\033[38;5;33m",  # 深蓝色
     "expressor": "\033[38;5;166m",  # 橙色
     # 专注聊天模块
-    
     "memory_activator": "\033[38;5;117m",  # 天蓝色
     # 插件系统
     "plugins": "\033[31m",  # 红色
@@ -412,7 +401,6 @@ MODULE_COLORS = {
     # 工具和实用模块
     "prompt_build": "\033[38;5;105m",  # 紫色
     "chat_utils": "\033[38;5;111m",  # 蓝色
-    
     "maibot_statistic": "\033[38;5;129m",  # 紫色
     # 特殊功能插件
     "mute_plugin": "\033[38;5;240m",  # 灰色
@@ -447,10 +435,8 @@ MODULE_ALIASES = {
     "llm_api": "生成API",
     "emoji": "表情包",
     "emoji_api": "表情包API",
-    
     "chat": "所见",
     "chat_image": "识图",
-    
     "action_manager": "动作",
     "memory_activator": "记忆",
     "tool_use": "工具",
@@ -460,7 +446,6 @@ MODULE_ALIASES = {
     "memory": "记忆",
     "tool_executor": "工具",
     "hfc": "聊天节奏",
-    
     "plugin_manager": "插件",
     "relationship_builder": "关系",
     "llm_models": "模型",

src/config/official_configs.py

@@ -47,6 +47,7 @@ class PersonalityConfig(ConfigBase):
     interest: str = ""
     """兴趣"""
 
+
 @dataclass
 class RelationshipConfig(ConfigBase):
     """关系配置类"""
@@ -80,7 +81,6 @@ class ChatConfig(ConfigBase):
     # 合并后的时段频率配置
     talk_frequency_adjust: list[list[str]] = field(default_factory=lambda: [])
 
-
     focus_value: float = 0.5
     """麦麦的专注思考能力，越低越容易专注，消耗token也越多"""
 
@@ -112,7 +112,6 @@ class ChatConfig(ConfigBase):
     """
 
 
-
 @dataclass
 class MessageReceiveConfig(ConfigBase):
     """消息接收配置类"""
@@ -123,6 +122,7 @@ class MessageReceiveConfig(ConfigBase):
     ban_msgs_regex: set[str] = field(default_factory=lambda: set())
     """过滤正则表达式列表"""
 
+
 @dataclass
 class ExpressionConfig(ConfigBase):
     """表达配置类"""

src/llm_models/model_client/openai_client.py

@@ -531,7 +531,7 @@ class OpenaiClient(BaseClient):
             # 添加详细的错误信息以便调试
             logger.error(f"OpenAI API连接错误（嵌入模型）: {str(e)}")
             logger.error(f"错误类型: {type(e)}")
-            if hasattr(e, '__cause__') and e.__cause__:
+            if hasattr(e, "__cause__") and e.__cause__:
                 logger.error(f"底层错误: {str(e.__cause__)}")
             raise NetworkConnectionError() from e
         except APIStatusError as e:

src/llm_models/payload_content/resp_format.py

@@ -48,8 +48,7 @@ def _json_schema_type_check(instance) -> str | None:
     elif not isinstance(instance["name"], str) or instance["name"].strip() == "":
         return "schema的'name'字段必须是非空字符串"
     if "description" in instance and (
-        not isinstance(instance["description"], str)
+        not isinstance(instance["description"], str) or instance["description"].strip() == ""
-        or instance["description"].strip() == ""
     ):
         return "schema的'description'字段只能填入非空字符串"
     if "schema" not in instance:
@@ -101,9 +100,7 @@ def _link_definitions(schema: dict[str, Any]) -> dict[str, Any]:
             # 如果当前Schema是列表，则遍历每个元素
             for i in range(len(sub_schema)):
                 if isinstance(sub_schema[i], dict):
-                    sub_schema[i] = link_definitions_recursive(
+                    sub_schema[i] = link_definitions_recursive(f"{path}/{str(i)}", sub_schema[i], defs)
-                        f"{path}/{str(i)}", sub_schema[i], defs
-                    )
         else:
             # 否则为字典
             if "$defs" in sub_schema:
@@ -125,9 +122,7 @@ def _link_definitions(schema: dict[str, Any]) -> dict[str, Any]:
             for key, value in sub_schema.items():
                 if isinstance(value, (dict, list)):
                     # 如果当前值是字典或列表，则递归调用
-                    sub_schema[key] = link_definitions_recursive(
+                    sub_schema[key] = link_definitions_recursive(f"{path}/{key}", value, defs)
-                        f"{path}/{key}", value, defs
-                    )
 
         return sub_schema
 
@@ -163,9 +158,7 @@ class RespFormat:
     def _generate_schema_from_model(schema):
         json_schema = {
             "name": schema.__name__,
-            "schema": _remove_defs(
+            "schema": _remove_defs(_link_definitions(_remove_title(schema.model_json_schema()))),
-                _link_definitions(_remove_title(schema.model_json_schema()))
-            ),
             "strict": False,
         }
         if schema.__doc__:

src/llm_models/utils.py

@@ -155,7 +155,13 @@ class LLMUsageRecorder:
             logger.error(f"创建 LLMUsage 表失败: {str(e)}")
 
     def record_usage_to_database(
-        self, model_info: ModelInfo, model_usage: UsageRecord, user_id: str, request_type: str, endpoint: str, time_cost: float = 0.0
+        self,
+        model_info: ModelInfo,
+        model_usage: UsageRecord,
+        user_id: str,
+        request_type: str,
+        endpoint: str,
+        time_cost: float = 0.0,
     ):
         input_cost = (model_usage.prompt_tokens / 1000000) * model_info.price_in
         output_cost = (model_usage.completion_tokens / 1000000) * model_info.price_out
@@ -173,7 +179,7 @@ class LLMUsageRecorder:
                 completion_tokens=model_usage.completion_tokens or 0,
                 total_tokens=model_usage.total_tokens or 0,
                 cost=total_cost or 0.0,
-                time_cost = round(time_cost or 0.0, 3),
+                time_cost=round(time_cost or 0.0, 3),
                 status="success",
                 timestamp=datetime.now(),  # Peewee 会处理 DateTimeField
             )
@@ -186,4 +192,5 @@ class LLMUsageRecorder:
         except Exception as e:
             logger.error(f"记录token使用情况失败: {str(e)}")
 
+
 llm_usage_recorder = LLMUsageRecorder()

src/mais4u/mais4u_chat/context_web_manager.py

@@ -23,17 +23,17 @@ class ContextMessage:
         self.group_name = message.message_info.group_info.group_name if message.message_info.group_info else "私聊"
 
         # 识别消息类型
-        self.is_gift = getattr(message, 'is_gift', False)
+        self.is_gift = getattr(message, "is_gift", False)
-        self.is_superchat = getattr(message, 'is_superchat', False)
+        self.is_superchat = getattr(message, "is_superchat", False)
 
         # 添加礼物和SC相关信息
         if self.is_gift:
-            self.gift_name = getattr(message, 'gift_name', '')
+            self.gift_name = getattr(message, "gift_name", "")
-            self.gift_count = getattr(message, 'gift_count', '1')
+            self.gift_count = getattr(message, "gift_count", "1")
             self.content = f"送出了 {self.gift_name} x{self.gift_count}"
         elif self.is_superchat:
-            self.superchat_price = getattr(message, 'superchat_price', '0')
+            self.superchat_price = getattr(message, "superchat_price", "0")
-            self.superchat_message = getattr(message, 'superchat_message_text', '')
+            self.superchat_message = getattr(message, "superchat_message_text", "")
             if self.superchat_message:
                 self.content = f"[¥{self.superchat_price}] {self.superchat_message}"
             else:
@@ -47,7 +47,7 @@ class ContextMessage:
             "timestamp": self.timestamp.strftime("%m-%d %H:%M:%S"),
             "group_name": self.group_name,
             "is_gift": self.is_gift,
-            "is_superchat": self.is_superchat
+            "is_superchat": self.is_superchat,
         }
 
 
@@ -83,20 +83,20 @@ class ContextWebManager:
             self.app = web.Application()
 
             # 设置CORS
-            cors = aiohttp_cors.setup(self.app, defaults={
+            cors = aiohttp_cors.setup(
-                "*": aiohttp_cors.ResourceOptions(
+                self.app,
-                    allow_credentials=True,
+                defaults={
-                    expose_headers="*",
+                    "*": aiohttp_cors.ResourceOptions(
-                    allow_headers="*",
+                        allow_credentials=True, expose_headers="*", allow_headers="*", allow_methods="*"
-                    allow_methods="*"
+                    )
-                )
+                },
-            })
+            )
 
             # 添加路由
-            self.app.router.add_get('/', self.index_handler)
+            self.app.router.add_get("/", self.index_handler)
-            self.app.router.add_get('/ws', self.websocket_handler)
+            self.app.router.add_get("/ws", self.websocket_handler)
-            self.app.router.add_get('/api/contexts', self.get_contexts_handler)
+            self.app.router.add_get("/api/contexts", self.get_contexts_handler)
-            self.app.router.add_get('/debug', self.debug_handler)
+            self.app.router.add_get("/debug", self.debug_handler)
 
             # 为所有路由添加CORS
             for route in list(self.app.router.routes()):
@@ -105,7 +105,7 @@ class ContextWebManager:
             self.runner = web.AppRunner(self.app)
             await self.runner.setup()
 
-            self.site = web.TCPSite(self.runner, 'localhost', self.port)
+            self.site = web.TCPSite(self.runner, "localhost", self.port)
             await self.site.start()
 
             logger.info(f"🌐 上下文网页服务器启动成功在 http://localhost:{self.port}")
@@ -135,7 +135,8 @@ class ContextWebManager:
 
     async def index_handler(self, request):
         """主页处理器"""
-        html_content = '''
+        html_content = (
+            """
 <!DOCTYPE html>
 <html>
 <head>
@@ -286,7 +287,9 @@ class ContextWebManager:
         
                  function connectWebSocket() {
              console.log('正在连接WebSocket...');
-             ws = new WebSocket('ws://localhost:''' + str(self.port) + '''/ws');
+             ws = new WebSocket('ws://localhost:"""
+            + str(self.port)
+            + """/ws');
              
              ws.onopen = function() {
                  console.log('WebSocket连接已建立');
@@ -470,8 +473,9 @@ class ContextWebManager:
     </script>
 </body>
 </html>
-        '''
+        """
-        return web.Response(text=html_content, content_type='text/html')
+        )
+        return web.Response(text=html_content, content_type="text/html")
 
     async def websocket_handler(self, request):
         """WebSocket处理器"""
@@ -486,7 +490,7 @@ class ContextWebManager:
 
         async for msg in ws:
             if msg.type == WSMsgType.ERROR:
-                logger.error(f'WebSocket错误: {ws.exception()}')
+                logger.error(f"WebSocket错误: {ws.exception()}")
                 break
 
         # 清理断开的连接
@@ -506,7 +510,7 @@ class ContextWebManager:
         all_context_msgs.sort(key=lambda x: x.timestamp)
 
         # 转换为字典格式
-        contexts_data = [msg.to_dict() for msg in all_context_msgs[-self.max_messages:]]
+        contexts_data = [msg.to_dict() for msg in all_context_msgs[-self.max_messages :]]
 
         logger.debug(f"返回上下文数据，共 {len(contexts_data)} 条消息")
         return web.json_response({"contexts": contexts_data})
@@ -529,14 +533,14 @@ class ContextWebManager:
                 content = msg.content[:50] + "..." if len(msg.content) > 50 else msg.content
                 messages_html += f'<div class="message">[{timestamp}] {msg.user_name}: {content}</div>'
 
-            chats_html += f'''
+            chats_html += f"""
             <div class="chat">
                 <h3>聊天 {chat_id} ({len(contexts)} 条消息)</h3>
                 {messages_html}
             </div>
-            '''
+            """
 
-        html_content = f'''
+        html_content = f"""
 <!DOCTYPE html>
 <html>
 <head>
@@ -578,9 +582,9 @@ class ContextWebManager:
     </script>
 </body>
 </html>
-        '''
+        """
 
-        return web.Response(text=html_content, content_type='text/html')
+        return web.Response(text=html_content, content_type="text/html")
 
     async def add_message(self, chat_id: str, message: MessageRecv):
         """添加新消息到上下文"""
@@ -594,14 +598,18 @@ class ContextWebManager:
         # 统计当前总消息数
         total_messages = sum(len(contexts) for contexts in self.contexts.values())
 
-        logger.info(f"✅ 添加消息到上下文 [总数: {total_messages}]: [{context_msg.group_name}] {context_msg.user_name}: {context_msg.content}")
+        logger.info(
+            f"✅ 添加消息到上下文 [总数: {total_messages}]: [{context_msg.group_name}] {context_msg.user_name}: {context_msg.content}"
+        )
 
         # 调试：打印当前所有消息
         logger.info("📝 当前上下文中的所有消息：")
         for cid, contexts in self.contexts.items():
             logger.info(f"  聊天 {cid}: {len(contexts)} 条消息")
             for i, msg in enumerate(contexts):
-                logger.info(f"    {i+1}. [{msg.timestamp.strftime('%H:%M:%S')}] {msg.user_name}: {msg.content[:30]}...")
+                logger.info(
+                    f"    {i + 1}. [{msg.timestamp.strftime('%H:%M:%S')}] {msg.user_name}: {msg.content[:30]}..."
+                )
 
         # 广播更新给所有WebSocket连接
         await self.broadcast_contexts()
@@ -616,7 +624,7 @@ class ContextWebManager:
         all_context_msgs.sort(key=lambda x: x.timestamp)
 
         # 转换为字典格式
-        contexts_data = [msg.to_dict() for msg in all_context_msgs[-self.max_messages:]]
+        contexts_data = [msg.to_dict() for msg in all_context_msgs[-self.max_messages :]]
 
         data = {"contexts": contexts_data}
         await ws.send_str(json.dumps(data, ensure_ascii=False))
@@ -635,7 +643,7 @@ class ContextWebManager:
         all_context_msgs.sort(key=lambda x: x.timestamp)
 
         # 转换为字典格式
-        contexts_data = [msg.to_dict() for msg in all_context_msgs[-self.max_messages:]]
+        contexts_data = [msg.to_dict() for msg in all_context_msgs[-self.max_messages :]]
 
         data = {"contexts": contexts_data}
         message = json.dumps(data, ensure_ascii=False)
@@ -682,4 +690,3 @@ async def init_context_web_manager():
     manager = get_context_web_manager()
     await manager.start_server()
     return manager
-

src/mais4u/mais4u_chat/gift_manager.py

@@ -11,6 +11,7 @@ logger = get_logger("gift_manager")
 @dataclass
 class PendingGift:
     """等待中的礼物消息"""
+
     message: MessageRecvS4U
     total_count: int
     timer_task: asyncio.Task
@@ -25,7 +26,9 @@ class GiftManager:
         self.pending_gifts: Dict[Tuple[str, str], PendingGift] = {}
         self.debounce_timeout = 5.0  # 3秒防抖时间
 
-    async def handle_gift(self, message: MessageRecvS4U, callback: Optional[Callable[[MessageRecvS4U], None]] = None) -> bool:
+    async def handle_gift(
+        self, message: MessageRecvS4U, callback: Optional[Callable[[MessageRecvS4U], None]] = None
+    ) -> bool:
         """处理礼物消息，返回是否应该立即处理
 
         Args:
@@ -73,17 +76,12 @@ class GiftManager:
             # 如果无法解析数量，保持原有数量不变
 
         # 重新创建定时器
-        pending_gift.timer_task = asyncio.create_task(
+        pending_gift.timer_task = asyncio.create_task(self._gift_timeout(gift_key))
-            self._gift_timeout(gift_key)
-        )
 
         logger.debug(f"合并礼物: {gift_key}, 总数量: {pending_gift.total_count}")
 
     async def _create_pending_gift(
-        self, 
+        self, gift_key: Tuple[str, str], message: MessageRecvS4U, callback: Optional[Callable[[MessageRecvS4U], None]]
-        gift_key: Tuple[str, str], 
-        message: MessageRecvS4U, 
-        callback: Optional[Callable[[MessageRecvS4U], None]]
     ) -> None:
         """创建新的等待礼物"""
         try:
@@ -96,12 +94,7 @@ class GiftManager:
         timer_task = asyncio.create_task(self._gift_timeout(gift_key))
 
         # 创建等待礼物对象
-        pending_gift = PendingGift(
+        pending_gift = PendingGift(message=message, total_count=initial_count, timer_task=timer_task, callback=callback)
-            message=message,
-            total_count=initial_count,
-            timer_task=timer_task,
-            callback=callback
-        )
 
         self.pending_gifts[gift_key] = pending_gift
 
@@ -152,4 +145,3 @@ class GiftManager:
 
 # 创建全局礼物管理器实例
 gift_manager = GiftManager()
-    

src/mais4u/mais4u_chat/internal_manager.py

@@ -2,7 +2,7 @@ class InternalManager:
     def __init__(self):
         self.now_internal_state = str()
 
-    def set_internal_state(self,internal_state:str):
+    def set_internal_state(self, internal_state: str):
         self.now_internal_state = internal_state
 
     def get_internal_state(self):
@@ -11,4 +11,5 @@ class InternalManager:
     def get_internal_state_str(self):
         return f"你今天的直播内容是直播QQ水群，你正在一边回复弹幕，一边在QQ群聊天，你在QQ群聊天中产生的想法是：{self.now_internal_state}"
 
+
 internal_manager = InternalManager()

src/mais4u/mais4u_chat/s4u_chat.py

@@ -16,7 +16,6 @@ import json
 from .s4u_mood_manager import mood_manager
 from src.mais4u.s4u_config import s4u_config
 from src.person_info.person_info import get_person_id
-from .super_chat_manager import get_super_chat_manager
 from .yes_or_no import yes_or_no_head
 
 logger = get_logger("S4U_chat")
@@ -40,9 +39,6 @@ class MessageSenderContainer:
 
         self.voice_done = ""
 
-
-        
-
     async def add_message(self, chunk: str):
         """向队列中添加一个消息块。"""
         await self.queue.put(chunk)
@@ -199,7 +195,7 @@ class S4UChat:
         self.gpt.chat_stream = self.chat_stream
         self.interest_dict: Dict[str, float] = {}  # 用户兴趣分
 
-        self.internal_message :List[MessageRecvS4U] = []
+        self.internal_message: List[MessageRecvS4U] = []
 
         self.msg_id = ""
         self.voice_done = ""
@@ -252,14 +248,13 @@ class S4UChat:
             else:
                 self.interest_dict[person_id] = 0
 
-    async def add_message(self, message: MessageRecvS4U|MessageRecv) -> None:
+    async def add_message(self, message: MessageRecvS4U | MessageRecv) -> None:
-        
         self.decay_interest_score()
 
         """根据VIP状态和中断逻辑将消息放入相应队列。"""
         user_id = message.message_info.user_info.user_id
         platform = message.message_info.platform
-        person_id = get_person_id(platform, user_id)
+        _person_id = get_person_id(platform, user_id)
 
         # try:
         #     is_gift = message.is_gift
@@ -292,8 +287,11 @@ class S4UChat:
         new_priority_score = self._calculate_base_priority_score(message, priority_info)
 
         should_interrupt = False
-        if (s4u_config.enable_message_interruption and 
+        if (
-            self._current_generation_task and not self._current_generation_task.done()):
+            s4u_config.enable_message_interruption
+            and self._current_generation_task
+            and not self._current_generation_task.done()
+        ):
             if self._current_message_being_replied:
                 current_queue, current_priority, _, current_msg = self._current_message_being_replied
 
@@ -359,7 +357,9 @@ class S4UChat:
                 neg_priority, entry_count, timestamp, message = item
 
                 # 如果消息在最近N条消息范围内，保留它
-                logger.info(f"检查消息:{message.processed_plain_text},entry_count:{entry_count} cutoff_counter:{cutoff_counter}")
+                logger.info(
+                    f"检查消息:{message.processed_plain_text},entry_count:{entry_count} cutoff_counter:{cutoff_counter}"
+                )
 
                 if entry_count >= cutoff_counter:
                     temp_messages.append(item)
@@ -375,8 +375,12 @@ class S4UChat:
             self._normal_queue.put_nowait(item)
 
         if removed_count > 0:
-            logger.info(f"消息{message.processed_plain_text}超过{s4u_config.recent_message_keep_count}条，现在counter:{self._entry_counter}被移除")
+            logger.info(
-            logger.info(f"[{self.stream_name}] Cleaned up {removed_count} old normal messages outside recent {s4u_config.recent_message_keep_count} range.")
+                f"消息{message.processed_plain_text}超过{s4u_config.recent_message_keep_count}条，现在counter:{self._entry_counter}被移除"
+            )
+            logger.info(
+                f"[{self.stream_name}] Cleaned up {removed_count} old normal messages outside recent {s4u_config.recent_message_keep_count} range."
+            )
 
     async def _message_processor(self):
         """调度器：优先处理VIP队列，然后处理普通队列。"""
@@ -396,7 +400,6 @@ class S4UChat:
                     queue_name = "vip"
                 # 其次处理普通队列
                 elif not self._normal_queue.empty():
-
                     neg_priority, entry_count, timestamp, message = self._normal_queue.get_nowait()
                     priority = -neg_priority
                     # 检查普通消息是否超时
@@ -417,7 +420,9 @@ class S4UChat:
                         entry_count = 0
                         queue_name = "internal"
 
-                        logger.info(f"[{self.stream_name}] normal/vip 队列都空，触发 internal_message 回复: {getattr(message, 'processed_plain_text', str(message))[:20]}...")
+                        logger.info(
+                            f"[{self.stream_name}] normal/vip 队列都空，触发 internal_message 回复: {getattr(message, 'processed_plain_text', str(message))[:20]}..."
+                        )
                     else:
                         continue  # 没有消息了，回去等事件
 
@@ -458,12 +463,10 @@ class S4UChat:
                 logger.error(f"[{self.stream_name}] Message processor main loop error: {e}", exc_info=True)
                 await asyncio.sleep(1)
 
-        
     def get_processing_message_id(self):
         self.last_msg_id = self.msg_id
         self.msg_id = f"{time.time()}_{random.randint(1000, 9999)}"
 
-
     async def _generate_and_send(self, message: MessageRecv):
         """为单个消息生成文本回复。整个过程可以被中断。"""
         self._is_replying = True
@@ -516,7 +519,12 @@ class S4UChat:
                 total_chars_sent = len("麦麦不知道哦")
 
             mood = mood_manager.get_mood_by_chat_id(self.stream_id)
-            await yes_or_no_head(text = total_chars_sent,emotion = mood.mood_state,chat_history=message.processed_plain_text,chat_id=self.stream_id)
+            await yes_or_no_head(
+                text=total_chars_sent,
+                emotion=mood.mood_state,
+                chat_history=message.processed_plain_text,
+                chat_id=self.stream_id,
+            )
 
             # 等待所有文本消息发送完成
             await sender_container.close()
@@ -524,8 +532,6 @@ class S4UChat:
 
             await chat_watching.on_thinking_finished()
 
-            
-            
             start_time = time.time()
             logged = False
             while not self.go_processing():
@@ -576,4 +582,3 @@ class S4UChat:
             await self._processing_task
         except asyncio.CancelledError:
             logger.info(f"处理任务已成功取消: {self.stream_name}")
-        

src/mais4u/mais4u_chat/s4u_msg_processor.py

@@ -40,7 +40,7 @@ async def _calculate_interest(message: MessageRecv) -> Tuple[float, bool]:
 
     if global_config.memory.enable_memory:
         with Timer("记忆激活"):
-            interested_rate,_ ,_= await hippocampus_manager.get_activate_from_text(
+            interested_rate, _, _ = await hippocampus_manager.get_activate_from_text(
                 message.processed_plain_text,
                 fast_retrieval=True,
             )
@@ -133,20 +133,16 @@ class S4UMessageProcessor:
         if await self.handle_screen_message(message):
             return
 
-
         await self.storage.store_message(message, chat)
 
         s4u_chat = get_s4u_chat_manager().get_or_create_chat(chat)
 
-
         await s4u_chat.add_message(message)
 
         _interested_rate, _ = await _calculate_interest(message)
 
         await mood_manager.start()
 
-
-
         # 一系列llm驱动的前处理
         chat_mood = mood_manager.get_mood_by_chat_id(chat.stream_id)
         asyncio.create_task(chat_mood.update_mood_by_message(message))
@@ -167,30 +163,25 @@ class S4UMessageProcessor:
 
     async def handle_internal_message(self, message: MessageRecvS4U):
         if message.is_internal:
+            group_info = GroupInfo(platform="amaidesu_default", group_id=660154, group_name="内心")
 
-            group_info = GroupInfo(platform = "amaidesu_default",group_id = 660154,group_name = "内心")
+            chat = await get_chat_manager().get_or_create_stream(
-            
+                platform="amaidesu_default", user_info=message.message_info.user_info, group_info=group_info
-            chat =  await get_chat_manager().get_or_create_stream(
-                platform = "amaidesu_default",
-                user_info = message.message_info.user_info,
-                group_info = group_info
             )
             s4u_chat = get_s4u_chat_manager().get_or_create_chat(chat)
             message.message_info.group_info = s4u_chat.chat_stream.group_info
             message.message_info.platform = s4u_chat.chat_stream.platform
 
-            
             s4u_chat.internal_message.append(message)
             s4u_chat._new_message_event.set()
 
-            
+            logger.info(
-            logger.info(f"[{s4u_chat.stream_name}] 添加内部消息-------------------------------------------------------: {message.processed_plain_text}")
+                f"[{s4u_chat.stream_name}] 添加内部消息-------------------------------------------------------: {message.processed_plain_text}"
-            
+            )
 
             return True
         return False
 
-    
     async def handle_screen_message(self, message: MessageRecvS4U):
         if message.is_screen:
             screen_manager.set_screen(message.screen_info)
@@ -209,7 +200,7 @@ class S4UMessageProcessor:
         if message.is_gift:
             return False
 
-        gift_keywords = ["送出了礼物", "礼物", "送出了","投喂"]
+        gift_keywords = ["送出了礼物", "礼物", "送出了", "投喂"]
         if any(keyword in message.processed_plain_text for keyword in gift_keywords):
             message.is_fake_gift = True
             return True

src/mais4u/mais4u_chat/s4u_prompt.py

@@ -176,7 +176,7 @@ class PromptBuilder:
         message_list_before_now = get_raw_msg_before_timestamp_with_chat(
             chat_id=chat_stream.stream_id,
             timestamp=time.time(),
-        # sourcery skip: lift-duplicated-conditional, merge-duplicate-blocks, remove-redundant-if
+            # sourcery skip: lift-duplicated-conditional, merge-duplicate-blocks, remove-redundant-if
             limit=300,
         )
 
@@ -228,13 +228,17 @@ class PromptBuilder:
                 last_speaking_user_id = start_speaking_user_id
                 msg_seg_str = "对方的发言：\n"
 
-            msg_seg_str += f"{time.strftime('%H:%M:%S', time.localtime(first_msg.time))}: {first_msg.processed_plain_text}\n"
+            msg_seg_str += (
+                f"{time.strftime('%H:%M:%S', time.localtime(first_msg.time))}: {first_msg.processed_plain_text}\n"
+            )
 
             all_msg_seg_list = []
             for msg in core_dialogue_list[1:]:
                 speaker = msg.user_info.user_id
                 if speaker == last_speaking_user_id:
-                    msg_seg_str += f"{time.strftime('%H:%M:%S', time.localtime(msg.time))}: {msg.processed_plain_text}\n"
+                    msg_seg_str += (
+                        f"{time.strftime('%H:%M:%S', time.localtime(msg.time))}: {msg.processed_plain_text}\n"
+                    )
                 else:
                     msg_seg_str = f"{msg_seg_str}\n"
                     all_msg_seg_list.append(msg_seg_str)

src/mais4u/mais4u_chat/s4u_stream_generator.py

@@ -14,10 +14,7 @@ logger = get_logger("s4u_stream_generator")
 class S4UStreamGenerator:
     def __init__(self):
         # 使用LLMRequest替代AsyncOpenAIClient
-        self.llm_request = LLMRequest(
+        self.llm_request = LLMRequest(model_set=model_config.model_task_config.replyer, request_type="s4u_replyer")
-            model_set=model_config.model_task_config.replyer, 
-            request_type="s4u_replyer"
-        )
 
         self.current_model_name = "unknown model"
         self.partial_response = ""

src/mais4u/mais4u_chat/s4u_watching_manager.py

@@ -1,4 +1,3 @@
-
 from src.common.logger import get_logger
 from src.plugin_system.apis import send_api
 
@@ -47,6 +46,7 @@ HEAD_CODE = {
     "看向正前方": "(0,0,0)",
 }
 
+
 class ChatWatching:
     def __init__(self, chat_id: str):
         self.chat_id: str = chat_id
@@ -75,13 +75,13 @@ class ChatWatching:
             message_type="state", content="start_viewing", stream_id=self.chat_id, storage_message=False
         )
 
-    
     async def on_internal_message_start(self):
         """收到消息时调用"""
         await send_api.custom_to_stream(
             message_type="state", content="start_internal_thinking", stream_id=self.chat_id, storage_message=False
         )
 
+
 class WatchingManager:
     def __init__(self):
         self.watching_list: list[ChatWatching] = []
@@ -100,6 +100,7 @@ class WatchingManager:
 
         return new_watching
 
+
 # 全局视线管理器实例
 watching_manager = WatchingManager()
 """全局视线管理器"""

src/mais4u/mais4u_chat/screen_manager.py

@@ -2,7 +2,7 @@ class ScreenManager:
     def __init__(self):
         self.now_screen = str()
 
-    def set_screen(self,screen_str:str):
+    def set_screen(self, screen_str: str):
         self.now_screen = screen_str
 
     def get_screen(self):
@@ -11,4 +11,5 @@ class ScreenManager:
     def get_screen_str(self):
         return f"你可以看见面前的屏幕，目前屏幕的内容是:现在千石可乐在和你一起直播，这是他正在操作的屏幕内容：{self.now_screen}"
 
+
 screen_manager = ScreenManager()

src/mais4u/mais4u_chat/super_chat_manager.py

@@ -4,6 +4,7 @@ from dataclasses import dataclass
 from typing import Dict, List, Optional
 from src.common.logger import get_logger
 from src.chat.message_receive.message import MessageRecvS4U
+
 # 全局SuperChat管理器实例
 from src.mais4u.s4u_config import s4u_config
 
@@ -44,7 +45,7 @@ class SuperChatRecord:
             "timestamp": self.timestamp,
             "expire_time": self.expire_time,
             "group_name": self.group_name,
-            "remaining_time": self.remaining_time()
+            "remaining_time": self.remaining_time(),
         }
 
 
@@ -82,10 +83,7 @@ class SuperChatManager:
                 for chat_id in list(self.super_chats.keys()):
                     original_count = len(self.super_chats[chat_id])
                     # 移除过期的SuperChat
-                    self.super_chats[chat_id] = [
+                    self.super_chats[chat_id] = [sc for sc in self.super_chats[chat_id] if not sc.is_expired()]
-                        sc for sc in self.super_chats[chat_id] 
-                        if not sc.is_expired()
-                    ]
 
                     removed_count = original_count - len(self.super_chats[chat_id])
                     total_removed += removed_count
@@ -153,7 +151,7 @@ class SuperChatManager:
 
         user_info = message.message_info.user_info
         group_info = message.message_info.group_info
-        chat_id = getattr(message, 'chat_stream', None)
+        chat_id = getattr(message, "chat_stream", None)
         if chat_id:
             chat_id = chat_id.stream_id
         else:
@@ -173,7 +171,7 @@ class SuperChatManager:
             message_text=message.superchat_message_text or "",
             timestamp=message.message_info.time,
             expire_time=expire_time,
-            group_name=group_info.group_name if group_info else None
+            group_name=group_info.group_name if group_info else None,
         )
 
         # 添加到对应聊天的SuperChat列表
@@ -226,7 +224,9 @@ class SuperChatManager:
             remaining_minutes = int(sc.remaining_time() / 60)
             remaining_seconds = int(sc.remaining_time() % 60)
 
-            time_display = f"{remaining_minutes}分{remaining_seconds}秒" if remaining_minutes > 0 else f"{remaining_seconds}秒"
+            time_display = (
+                f"{remaining_minutes}分{remaining_seconds}秒" if remaining_minutes > 0 else f"{remaining_seconds}秒"
+            )
 
             line = f"{i}. 【{sc.price}元】{sc.user_nickname}: {sc.message_text}"
             if len(line) > 100:  # 限制单行长度
@@ -267,13 +267,7 @@ class SuperChatManager:
         superchats = self.get_superchats_by_chat(chat_id)
 
         if not superchats:
-            return {
+            return {"count": 0, "total_amount": 0, "average_amount": 0, "highest_amount": 0, "lowest_amount": 0}
-                "count": 0,
-                "total_amount": 0,
-                "average_amount": 0,
-                "highest_amount": 0,
-                "lowest_amount": 0
-            }
 
         amounts = [sc.price for sc in superchats]
 
@@ -282,7 +276,7 @@ class SuperChatManager:
             "total_amount": sum(amounts),
             "average_amount": sum(amounts) / len(amounts),
             "highest_amount": max(amounts),
-            "lowest_amount": min(amounts)
+            "lowest_amount": min(amounts),
         }
 
     async def shutdown(self):  # sourcery skip: use-contextlib-suppress
@@ -296,14 +290,13 @@ class SuperChatManager:
         logger.info("SuperChat管理器已关闭")
 
 
-
-
 # sourcery skip: assign-if-exp
 if s4u_config.enable_s4u:
     super_chat_manager = SuperChatManager()
 else:
     super_chat_manager = None
 
+
 def get_super_chat_manager() -> SuperChatManager:
     """获取全局SuperChat管理器实例"""
 

src/mais4u/s4u_config.py

@@ -10,10 +10,12 @@ from src.common.logger import get_logger
 
 logger = get_logger("s4u_config")
 
+
 # 新增：兼容dict和tomlkit Table
 def is_dict_like(obj):
     return isinstance(obj, (dict, Table))
 
+
 # 新增：递归将Table转为dict
 def table_to_dict(obj):
     if isinstance(obj, Table):
@@ -25,6 +27,7 @@ def table_to_dict(obj):
     else:
         return obj
 
+
 # 获取mais4u模块目录
 MAIS4U_ROOT = os.path.dirname(__file__)
 CONFIG_DIR = os.path.join(MAIS4U_ROOT, "config")
@@ -243,7 +246,6 @@ class S4UConfig(S4UConfigBase):
     # 兼容性字段，保持向后兼容
 
 
-
 @dataclass
 class S4UGlobalConfig(S4UConfigBase):
     """S4U总配置类"""
@@ -354,9 +356,9 @@ def load_s4u_config(config_path: str) -> S4UGlobalConfig:
         logger.critical("S4U配置文件解析失败")
         raise e
 
-
-
     # 初始化S4U配置
+
+
 logger.info(f"S4U当前版本: {S4U_VERSION}")
 update_s4u_config()
 

src/migrate_helper/migrate.py

@@ -21,7 +21,7 @@ async def migrate_memory_items_to_string():
         "empty_nodes": 0,
         "error_nodes": 0,
         "weight_updated_nodes": 0,
-        "truncated_nodes": 0
+        "truncated_nodes": 0,
     }
 
     try:
@@ -35,7 +35,7 @@ async def migrate_memory_items_to_string():
             try:
                 concept = node.concept
                 memory_items_raw = node.memory_items.strip() if node.memory_items else ""
-                original_weight = node.weight if hasattr(node, 'weight') and node.weight is not None else 1.0
+                original_weight = node.weight if hasattr(node, "weight") and node.weight is not None else 1.0
 
                 # 如果为空，跳过
                 if not memory_items_raw:
@@ -71,7 +71,9 @@ async def migrate_memory_items_to_string():
                             migration_stats["weight_updated_nodes"] += 1
 
                             length_info = f" (截断: {original_length}→100)" if original_length > 100 else ""
-                            logger.info(f"转换节点 '{concept}': {len(parsed_data)} 项 -> 字符串{length_info}, weight: {original_weight} -> {new_weight}")
+                            logger.info(
+                                f"转换节点 '{concept}': {len(parsed_data)} 项 -> 字符串{length_info}, weight: {original_weight} -> {new_weight}"
+                            )
                         else:
                             # 空list，设置为空字符串
                             node.memory_items = ""
@@ -99,7 +101,9 @@ async def migrate_memory_items_to_string():
                         update_needed = False
                         if original_weight == 1.0:
                             # 如果weight还是默认值，可以根据内容复杂度估算
-                            content_parts = current_content.split(" | ") if " | " in current_content else [current_content]
+                            content_parts = (
+                                current_content.split(" | ") if " | " in current_content else [current_content]
+                            )
                             estimated_weight = max(1.0, float(len(content_parts)))
 
                             if estimated_weight != original_weight:
@@ -195,14 +199,18 @@ async def migrate_memory_items_to_string():
     logger.info(f"权重更新节点: {migration_stats['weight_updated_nodes']}")
     logger.info(f"内容截断节点: {migration_stats['truncated_nodes']}")
 
-    success_rate = (migration_stats['converted_nodes'] + migration_stats['already_string_nodes']) / migration_stats['total_nodes'] * 100 if migration_stats['total_nodes'] > 0 else 0
+    success_rate = (
+        (migration_stats["converted_nodes"] + migration_stats["already_string_nodes"])
+        / migration_stats["total_nodes"]
+        * 100
+        if migration_stats["total_nodes"] > 0
+        else 0
+    )
     logger.info(f"迁移成功率: {success_rate:.1f}%")
 
     return migration_stats
 
 
-
-
 async def set_all_person_known():
     """
     将person_info库中所有记录的is_known字段设置为True
@@ -226,10 +234,10 @@ async def set_all_person_known():
         # 删除user_id或platform为空的记录
         deleted_count = 0
         invalid_records = PersonInfo.select().where(
-            (PersonInfo.user_id.is_null()) | 
+            (PersonInfo.user_id.is_null())
-            (PersonInfo.user_id == '') |
+            | (PersonInfo.user_id == "")
-            (PersonInfo.platform.is_null()) |
+            | (PersonInfo.platform.is_null())
-            (PersonInfo.platform == '')
+            | (PersonInfo.platform == "")
         )
 
         # 记录要删除的记录信息
@@ -237,15 +245,21 @@ async def set_all_person_known():
             user_id_info = f"'{record.user_id}'" if record.user_id else "NULL"
             platform_info = f"'{record.platform}'" if record.platform else "NULL"
             person_name_info = f"'{record.person_name}'" if record.person_name else "无名称"
-            logger.debug(f"删除无效记录: person_id={record.person_id}, user_id={user_id_info}, platform={platform_info}, person_name={person_name_info}")
+            logger.debug(
+                f"删除无效记录: person_id={record.person_id}, user_id={user_id_info}, platform={platform_info}, person_name={person_name_info}"
+            )
 
         # 执行删除操作
-        deleted_count = PersonInfo.delete().where(
+        deleted_count = (
-            (PersonInfo.user_id.is_null()) | 
+            PersonInfo.delete()
-            (PersonInfo.user_id == '') |
+            .where(
-            (PersonInfo.platform.is_null()) |
+                (PersonInfo.user_id.is_null())
-            (PersonInfo.platform == '')
+                | (PersonInfo.user_id == "")
-        ).execute()
+                | (PersonInfo.platform.is_null())
+                | (PersonInfo.platform == "")
+            )
+            .execute()
+        )
 
         if deleted_count > 0:
             logger.info(f"删除了 {deleted_count} 个user_id或platform为空的记录")
@@ -268,12 +282,7 @@ async def set_all_person_known():
         # 验证更新结果
         known_count = PersonInfo.select().where(PersonInfo.is_known).count()
 
-        result = {
+        result = {"total": total_count, "deleted": deleted_count, "updated": updated_count, "known_count": known_count}
-            "total": total_count,
-            "deleted": deleted_count,
-            "updated": updated_count,
-            "known_count": known_count
-        }
 
         logger.info("=== person_info更新完成 ===")
         logger.info(f"原始记录数: {result['total']}")
@@ -288,7 +297,6 @@ async def set_all_person_known():
         raise
 
 
-
 async def check_and_run_migrations():
     # 获取根目录
     project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", ".."))
@@ -309,4 +317,3 @@ async def check_and_run_migrations():
         # 创建done.mem文件
         with open(done_file, "w", encoding="utf-8") as f:
             f.write("done")
-        

src/person_info/person_info.py

@@ -282,7 +282,7 @@ class Person:
 
             memory_category = parts[0].strip()
             memory_text = parts[1].strip()
-            memory_weight = parts[2].strip()
+            _memory_weight = parts[2].strip()
 
             # 检查分类是否匹配
             if memory_category != category:

src/person_info/relationship_manager.py

@@ -1,11 +1,5 @@
-import json
-from json_repair import repair_json
-from datetime import datetime
 from src.common.logger import get_logger
-from src.llm_models.utils_model import LLMRequest
+from src.chat.utils.prompt_builder import Prompt
-from src.config.config import global_config, model_config
-from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
-from .person_info import Person
 
 
 logger = get_logger("relation")
@@ -43,4 +37,3 @@ def init_prompt():
 """,
         "attitude_to_me_prompt",
     )
-

src/plugin_system/__init__.py

@@ -121,5 +121,5 @@ __all__ = [
     "DatabaseChatInfo",
     "TargetPersonInfo",
     "ActionPlannerInfo",
-    "LLMGenerationDataModel"
+    "LLMGenerationDataModel",
 ]

src/plugin_system/apis/frequency_api.py

@@ -7,22 +7,24 @@ logger = get_logger("frequency_api")
 def get_current_focus_value(chat_id: str) -> float:
     return frequency_control_manager.get_or_create_frequency_control(chat_id).get_final_focus_value()
 
+
 def get_current_talk_frequency(chat_id: str) -> float:
     return frequency_control_manager.get_or_create_frequency_control(chat_id).get_final_talk_frequency()
 
+
 def set_focus_value_adjust(chat_id: str, focus_value_adjust: float) -> None:
     frequency_control_manager.get_or_create_frequency_control(chat_id).focus_value_external_adjust = focus_value_adjust
 
+
 def set_talk_frequency_adjust(chat_id: str, talk_frequency_adjust: float) -> None:
-    frequency_control_manager.get_or_create_frequency_control(chat_id).talk_frequency_external_adjust = talk_frequency_adjust
+    frequency_control_manager.get_or_create_frequency_control(
+        chat_id
+    ).talk_frequency_external_adjust = talk_frequency_adjust
+
 
 def get_focus_value_adjust(chat_id: str) -> float:
     return frequency_control_manager.get_or_create_frequency_control(chat_id).focus_value_external_adjust
 
+
 def get_talk_frequency_adjust(chat_id: str) -> float:
     return frequency_control_manager.get_or_create_frequency_control(chat_id).talk_frequency_external_adjust
-
-
-
-
-

src/plugin_system/apis/llm_api.py

@@ -72,7 +72,9 @@ async def generate_with_model(
 
         llm_request = LLMRequest(model_set=model_config, request_type=request_type)
 
-        response, (reasoning_content, model_name, _) = await llm_request.generate_response_async(prompt, temperature=temperature, max_tokens=max_tokens)
+        response, (reasoning_content, model_name, _) = await llm_request.generate_response_async(
+            prompt, temperature=temperature, max_tokens=max_tokens
+        )
         return True, response, reasoning_content, model_name
 
     except Exception as e:
@@ -80,6 +82,7 @@ async def generate_with_model(
         logger.error(f"[LLMAPI] {error_msg}")
         return False, error_msg, "", ""
 
+
 async def generate_with_model_with_tools(
     prompt: str,
     model_config: TaskConfig,
@@ -109,10 +112,7 @@ async def generate_with_model_with_tools(
         llm_request = LLMRequest(model_set=model_config, request_type=request_type)
 
         response, (reasoning_content, model_name, tool_call) = await llm_request.generate_response_async(
-            prompt,
+            prompt, tools=tool_options, temperature=temperature, max_tokens=max_tokens
-            tools=tool_options,
-            temperature=temperature,
-            max_tokens=max_tokens
         )
         return True, response, reasoning_content, model_name, tool_call
 

src/plugin_system/apis/message_api.py

@@ -435,9 +435,7 @@ def build_readable_messages_to_str(
     Returns:
         格式化后的可读字符串
     """
-    return build_readable_messages(
+    return build_readable_messages(messages, replace_bot_name, timestamp_mode, read_mark, truncate, show_actions)
-        messages, replace_bot_name, timestamp_mode, read_mark, truncate, show_actions
-    )
 
 
 async def build_readable_messages_with_details(
@@ -491,8 +489,6 @@ def filter_mai_messages(messages: List[DatabaseMessages]) -> List[DatabaseMessag
     return [msg for msg in messages if msg.user_info.user_id != str(global_config.bot.qq_account)]
 
 
-
-
 def translate_pid_to_description(pid: str) -> str:
     image = Images.get_or_none(Images.image_id == pid)
     description = ""

src/plugin_system/apis/plugin_register_api.py

@@ -2,7 +2,7 @@ from pathlib import Path
 
 from src.common.logger import get_logger
 
-logger = get_logger("plugin_manager") # 复用plugin_manager名称
+logger = get_logger("plugin_manager")  # 复用plugin_manager名称
 
 
 def register_plugin(cls):

src/plugin_system/core/plugin_manager.py

@@ -401,9 +401,7 @@ class PluginManager:
                         command_components = [
                             c for c in plugin_info.components if c.component_type == ComponentType.COMMAND
                         ]
-                        tool_components = [
+                        tool_components = [c for c in plugin_info.components if c.component_type == ComponentType.TOOL]
-                            c for c in plugin_info.components if c.component_type == ComponentType.TOOL
-                        ]
                         event_handler_components = [
                             c for c in plugin_info.components if c.component_type == ComponentType.EVENT_HANDLER
                         ]

src/plugin_system/core/tool_use.py

@@ -195,7 +195,9 @@ class ToolExecutor:
 
         return tool_results, used_tools
 
-    async def execute_tool_call(self, tool_call: ToolCall, tool_instance: Optional[BaseTool] = None) -> Optional[Dict[str, Any]]:
+    async def execute_tool_call(
+        self, tool_call: ToolCall, tool_instance: Optional[BaseTool] = None
+    ) -> Optional[Dict[str, Any]]:
         # sourcery skip: use-assigned-variable
         """执行单个工具调用
 

src/plugins/built_in/emoji_plugin/plugin.py

@@ -63,5 +63,4 @@ class CoreActionsPlugin(BasePlugin):
         if self.get_config("components.enable_emoji", True):
             components.append((EmojiAction.get_action_info(), EmojiAction))
 
-
         return components

src/plugins/built_in/memory/build_memory.py

@@ -74,7 +74,9 @@ class BuildMemoryAction(BaseAction):
 
     # 动作基本信息
     action_name = "build_memory"
-    action_description = "了解对于某个概念或者某件事的记忆，并存储下来，在之后的聊天中，你可以根据这条记忆来获取相关信息"
+    action_description = (
+        "了解对于某个概念或者某件事的记忆，并存储下来，在之后的聊天中，你可以根据这条记忆来获取相关信息"
+    )
 
     # 动作参数定义
     action_parameters = {
@@ -103,24 +105,28 @@ class BuildMemoryAction(BaseAction):
             concept_name = self.action_data.get("concept_name", "")
             # 2. 获取目标用户信息
 
-
-
             # 对 concept_name 进行jieba分词
             concept_name_tokens = cut_key_words(concept_name)
             # logger.info(f"{self.log_prefix} 对 concept_name 进行分词结果: {concept_name_tokens}")
 
             filtered_concept_name_tokens = [
-                token for token in concept_name_tokens if all(keyword not in token for keyword in global_config.memory.memory_ban_words)
+                token
+                for token in concept_name_tokens
+                if all(keyword not in token for keyword in global_config.memory.memory_ban_words)
             ]
 
             if not filtered_concept_name_tokens:
                 logger.warning(f"{self.log_prefix} 过滤后的概念名称列表为空，跳过添加记忆")
                 return False, "过滤后的概念名称列表为空，跳过添加记忆"
 
-            similar_topics_dict = hippocampus_manager.get_hippocampus().parahippocampal_gyrus.get_similar_topics_from_keywords(filtered_concept_name_tokens)
+            similar_topics_dict = (
-            await hippocampus_manager.get_hippocampus().parahippocampal_gyrus.add_memory_with_similar(concept_description, similar_topics_dict)
+                hippocampus_manager.get_hippocampus().parahippocampal_gyrus.get_similar_topics_from_keywords(
-            
+                    filtered_concept_name_tokens
-            
+                )
+            )
+            await hippocampus_manager.get_hippocampus().parahippocampal_gyrus.add_memory_with_similar(
+                concept_description, similar_topics_dict
+            )
 
             return True, f"成功添加记忆: {concept_name}"
 
@@ -129,6 +135,5 @@ class BuildMemoryAction(BaseAction):
             return False, f"构建记忆时出错: {e}"
 
 
-
 # 还缺一个关系的太多遗忘和对应的提取
 init_prompt()

src/plugins/built_in/relation/relation.py

@@ -178,7 +178,9 @@ class BuildRelationAction(BaseAction):
 
             chat_model_config = models.get("utils")
             success, update_memory, _, _ = await llm_api.generate_with_model(
-                prompt, model_config=chat_model_config, request_type="relation.category.update" # type: ignore
+                prompt,
+                model_config=chat_model_config,
+                request_type="relation.category.update",  # type: ignore
             )
 
             update_memory_data = json.loads(repair_json(update_memory))
@@ -207,7 +209,9 @@ class BuildRelationAction(BaseAction):
                     person.memory_points.append(f"{category}:{integrate_memory}:{memory_weight + 1.0}")
                     person.sync_to_database()
 
-                    logger.info(f"{self.log_prefix} 更新{person.person_name}的记忆点: {memory_content} -> {integrate_memory}")
+                    logger.info(
+                        f"{self.log_prefix} 更新{person.person_name}的记忆点: {memory_content} -> {integrate_memory}"
+                    )
 
                     return True, f"更新{person.person_name}的记忆点: {memory_content} -> {integrate_memory}"
 
@@ -215,7 +219,6 @@ class BuildRelationAction(BaseAction):
                     logger.warning(f"{self.log_prefix} 删除记忆点失败: {memory_content}")
                     return False, f"删除{person.person_name}的记忆点失败: {memory_content}"
 
-
             return True, "关系动作执行成功"
 
         except Exception as e: