🤖 自动格式化代码 [skip ci]

bot.py

@@ -2,6 +2,7 @@ import asyncio
 import hashlib
 import os
 from dotenv import load_dotenv
+
 if os.path.exists(".env"):
     load_dotenv(".env", override=True)
     print("成功加载环境变量配置")
@@ -13,9 +14,11 @@ import platform
 import traceback
 from pathlib import Path
 from rich.traceback import install
+
 # maim_message imports for console input
 from maim_message import Seg, UserInfo, BaseMessageInfo, MessageBase
 from src.chat.message_receive.bot import chat_bot
+
 # 最早期初始化日志系统，确保所有后续模块都使用正确的日志格式
 from src.common.logger import initialize_logging, get_logger, shutdown_logging
 from src.main import MainSystem
@@ -26,7 +29,6 @@ initialize_logging()
 logger = get_logger("main")
 
 
-
 install(extra_lines=3)
 
 # 设置工作目录为脚本所在目录

src/chat/express/expression_selector.py

@@ -12,6 +12,7 @@ from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
 
 logger = get_logger("expression_selector")
 
+
 def init_prompt():
     expression_evaluation_prompt = """
 你的名字是{bot_name}
@@ -42,6 +43,7 @@ def init_prompt():
 """
     Prompt(expression_evaluation_prompt, "expression_evaluation_prompt")
 
+
 def weighted_sample(population: List[Dict], weights: List[float], k: int) -> List[Dict]:
     """按权重随机抽样"""
     if not population or not weights or k <= 0:
@@ -66,6 +68,7 @@ def weighted_sample(population: List[Dict], weights: List[float], k: int) -> Lis
 
     return selected
 
+
 class ExpressionSelector:
     def __init__(self):
         self.expression_learner = get_expression_learner()
@@ -75,7 +78,9 @@ class ExpressionSelector:
             request_type="expression.selector",
         )
 
-    def get_random_expressions(self, chat_id: str, style_num: int, grammar_num: int, personality_num: int) -> Tuple[List[Dict[str, str]], List[Dict[str, str]]]:
+    def get_random_expressions(
+        self, chat_id: str, style_num: int, grammar_num: int, personality_num: int
+    ) -> Tuple[List[Dict[str, str]], List[Dict[str, str]]]:
         (
             learnt_style_expressions,
             learnt_grammar_expressions,
@@ -127,8 +132,9 @@ class ExpressionSelector:
 
             # 找到匹配的表达方式并更新count
             for expr in expressions:
-                if (expr.get("situation") == expression.get("situation") and 
+                if expr.get("situation") == expression.get("situation") and expr.get("style") == expression.get(
-                    expr.get("style") == expression.get("style")):
+                    "style"
+                ):
                     expr["count"] = expr.get("count", 1) * multiplier
                     expr["last_active_time"] = time.time()
                     break
@@ -234,10 +240,3 @@ try:
     expression_selector = ExpressionSelector()
 except Exception as e:
     print(f"ExpressionSelector初始化失败: {e}")
-
-
-
-
-
-
-

src/chat/focus_chat/info_processors/expression_selector_processor.py

@@ -24,7 +24,6 @@ class ExpressionSelectorProcessor(BaseProcessor):
         self.selection_interval = 10  # 40秒间隔
         self.cached_expressions = []  # 缓存上一次选择的表达方式
 
-
         name = get_chat_manager().get_stream_name(self.subheartflow_id)
         self.log_prefix = f"[{name}] 表达选择器"
 
@@ -72,7 +71,9 @@ class ExpressionSelectorProcessor(BaseProcessor):
 
         try:
             # LLM模式：调用LLM选择5-10个，然后随机选5个
-            selected_expressions = await expression_selector.select_suitable_expressions_llm(self.subheartflow_id, chat_info)
+            selected_expressions = await expression_selector.select_suitable_expressions_llm(
+                self.subheartflow_id, chat_info
+            )
             cache_size = len(selected_expressions) if selected_expressions else 0
             mode_desc = f"LLM模式（已缓存{cache_size}个）"
 
@@ -93,4 +94,3 @@ class ExpressionSelectorProcessor(BaseProcessor):
         except Exception as e:
             logger.error(f"{self.log_prefix} 处理表达方式选择时出错: {e}")
             return []
-

src/chat/normal_chat/normal_prompt.py

@@ -163,7 +163,9 @@ class PromptBuilder:
             show_actions=True,
         )
 
-        expressions = expression_selector.select_suitable_expressions_llm(chat_stream.stream_id, chat_talking_prompt_half)
+        expressions = expression_selector.select_suitable_expressions_llm(
+            chat_stream.stream_id, chat_talking_prompt_half
+        )
         style_habbits = []
         grammar_habbits = []
         if expressions:

src/individuality/individuality.py

@@ -99,9 +99,7 @@ class Individuality:
             logger.info("已将完整人设更新到bot的impression中")
 
         # 创建压缩版本的short_impression
-        asyncio.create_task(self._create_compressed_impression(
+        asyncio.create_task(self._create_compressed_impression(personality_core, personality_sides, identity_detail))
-            personality_core, personality_sides, identity_detail
-        ))
 
         asyncio.create_task(self.express_style.extract_and_store_personality_expressions())
 
@@ -430,9 +428,7 @@ class Individuality:
         # 更新short_impression字段
         if result:
             person_info_manager = get_person_info_manager()
-            await person_info_manager.update_one_field(
+            await person_info_manager.update_one_field(self.bot_person_id, "short_impression", result)
-                self.bot_person_id, "short_impression", result
-            )
             logger.info("已将压缩人设更新到bot的short_impression中")