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

src/chat/focus_chat/heartFC_chat.py

@@ -466,7 +466,9 @@ class HeartFChatting:
                         formatted_ptime = f"{ptime * 1000:.2f}毫秒" if ptime < 1 else f"{ptime:.2f}秒"
                         post_processor_time_strings.append(f"{pname}: {formatted_ptime}")
                     post_processor_time_log = (
-                        ("\n后处理器耗时: " + "; ".join(post_processor_time_strings)) if post_processor_time_strings else ""
+                        ("\n后处理器耗时: " + "; ".join(post_processor_time_strings))
+                        if post_processor_time_strings
+                        else ""
                     )
 
                     logger.info(
@@ -769,7 +771,9 @@ class HeartFChatting:
 
         return updated_action_data
 
-    async def _process_post_planning_processors_with_timing(self, observations: List[Observation], action_data: dict) -> tuple[dict, dict]:
+    async def _process_post_planning_processors_with_timing(
+        self, observations: List[Observation], action_data: dict
+    ) -> tuple[dict, dict]:
         """
         处理后期处理器（规划后执行的处理器）并收集详细时间统计
         包括：关系处理器、表达选择器、记忆激活器
@@ -883,7 +887,9 @@ class HeartFChatting:
                         )
                     elif task_type == "memory":
                         post_processor_time_costs["MemoryActivator"] = elapsed_time
-                        logger.warning(f"{self.log_prefix} 记忆激活器超时（>{MEMORY_ACTIVATION_TIMEOUT}s），已跳过，耗时: {elapsed_time:.3f}秒")
+                        logger.warning(
+                            f"{self.log_prefix} 记忆激活器超时（>{MEMORY_ACTIVATION_TIMEOUT}s），已跳过，耗时: {elapsed_time:.3f}秒"
+                        )
                         running_memorys = []
                 except Exception as e:
                     # 对于异常任务，记录已用时间
@@ -896,7 +902,10 @@ class HeartFChatting:
                         )
                     elif task_type == "memory":
                         post_processor_time_costs["MemoryActivator"] = elapsed_time
-                        logger.error(f"{self.log_prefix} 记忆激活器执行失败，耗时: {elapsed_time:.3f}秒. 错误: {e}", exc_info=True)
+                        logger.error(
+                            f"{self.log_prefix} 记忆激活器执行失败，耗时: {elapsed_time:.3f}秒. 错误: {e}",
+                            exc_info=True,
+                        )
                         running_memorys = []
 
         # 将后期处理器的结果整合到 action_data 中
@@ -938,7 +947,9 @@ class HeartFChatting:
 
         # 输出详细统计信息
         if post_processor_time_costs:
-            stats_str = ", ".join([f"{name}: {time_cost:.3f}s" for name, time_cost in post_processor_time_costs.items()])
+            stats_str = ", ".join(
+                [f"{name}: {time_cost:.3f}s" for name, time_cost in post_processor_time_costs.items()]
+            )
             logger.info(f"{self.log_prefix} 后期处理器详细耗时统计: {stats_str}")
 
         return updated_action_data, post_processor_time_costs
@@ -1048,7 +1059,9 @@ class HeartFChatting:
                     logger.debug(f"{self.log_prefix} 执行后期处理器（动作类型: {action_type}）")
                     # 记录详细的后处理器时间
                     post_start_time = time.time()
-                    action_data, post_processor_time_costs = await self._process_post_planning_processors_with_timing(self.observations, action_data)
+                    action_data, post_processor_time_costs = await self._process_post_planning_processors_with_timing(
+                        self.observations, action_data
+                    )
                     post_end_time = time.time()
                     logger.info(f"{self.log_prefix} 后期处理器总耗时: {post_end_time - post_start_time:.3f}秒")
             else:

src/chat/focus_chat/hfc_performance_logger.py

@@ -57,15 +57,14 @@ class HFCPerformanceLogger:
             log_parts = [
                 f"cycle_id={record['cycle_id']}",
                 f"action={record['action_type']}",
-                f"time={record['total_time']:.2f}s"
+                f"time={record['total_time']:.2f}s",
             ]
-            
+
             # 添加后处理器时间信息到日志
-            if record['post_processor_time_costs']:
+            if record["post_processor_time_costs"]:
-                post_processor_stats = ", ".join([
+                post_processor_stats = ", ".join(
-                    f"{name}: {time_cost:.3f}s" 
+                    [f"{name}: {time_cost:.3f}s" for name, time_cost in record["post_processor_time_costs"].items()]
-                    for name, time_cost in record['post_processor_time_costs'].items()
+                )
-                ])
                 log_parts.append(f"post_processors=({post_processor_stats})")
 
             logger.debug(f"记录HFC循环数据: {', '.join(log_parts)}")

src/chat/utils/statistic.py

@@ -60,7 +60,7 @@ FOCUS_AVG_TIMES_BY_VERSION = "focus_avg_times_by_version"
 
 # 新增: 后处理器统计数据的键
 FOCUS_POST_PROCESSOR_TIMES = "focus_post_processor_times"
-FOCUS_POST_PROCESSOR_COUNT = "focus_post_processor_count" 
+FOCUS_POST_PROCESSOR_COUNT = "focus_post_processor_count"
 FOCUS_POST_PROCESSOR_SUCCESS_RATE = "focus_post_processor_success_rate"
 FOCUS_PROCESSOR_TIMES = "focus_processor_times"  # 前处理器统计
 
@@ -566,7 +566,7 @@ class StatisticOutputTask(AsyncTask):
                 total_time = cycle_data.get("total_time", 0.0)
                 step_times = cycle_data.get("step_times", {})
                 version = cycle_data.get("version", "unknown")
-                
+
                 # 新增：获取前处理器和后处理器时间
                 processor_time_costs = cycle_data.get("processor_time_costs", {})
                 post_processor_time_costs = cycle_data.get("post_processor_time_costs", {})
@@ -930,7 +930,7 @@ class StatisticOutputTask(AsyncTask):
             # format总在线时间
 
             # 按模型分类统计
-            model_rows = "\n".join(
+            "\n".join(
                 [
                     f"<tr>"
                     f"<td>{model_name}</td>"
@@ -944,7 +944,7 @@ class StatisticOutputTask(AsyncTask):
                 ]
             )
             # 按请求类型分类统计
-            type_rows = "\n".join(
+            "\n".join(
                 [
                     f"<tr>"
                     f"<td>{req_type}</td>"
@@ -958,7 +958,7 @@ class StatisticOutputTask(AsyncTask):
                 ]
             )
             # 按模块分类统计
-            module_rows = "\n".join(
+            "\n".join(
                 [
                     f"<tr>"
                     f"<td>{module_name}</td>"
@@ -973,7 +973,7 @@ class StatisticOutputTask(AsyncTask):
             )
 
             # 聊天消息统计
-            chat_rows = "\n".join(
+            "\n".join(
                 [
                     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())
@@ -1028,7 +1028,7 @@ class StatisticOutputTask(AsyncTask):
                 basic_stages = ["观察", "并行调整动作、处理", "规划器", "后期处理器", "动作执行"]
                 existing_basic_stages = []
                 for stage in basic_stages:
-                                            # 检查是否有任何聊天流在这个阶段有数据
+                    # 检查是否有任何聊天流在这个阶段有数据
                     stage_exists = False
                     for _chat_id, stage_times in stat_data[FOCUS_AVG_TIMES_BY_CHAT_ACTION].items():
                         if stage in stage_times:
@@ -1275,7 +1275,9 @@ class StatisticOutputTask(AsyncTask):
                 for processor_name in sorted(stat_data[FOCUS_POST_PROCESSOR_TIMES].keys()):
                     avg_time = stat_data[FOCUS_POST_PROCESSOR_TIMES][processor_name]
                     count = stat_data[FOCUS_POST_PROCESSOR_COUNT].get(processor_name, 0)
-                    post_processor_rows.append(f"<tr><td>{processor_name}</td><td>{avg_time:.3f}秒</td><td>{count}</td></tr>")
+                    post_processor_rows.append(
+                        f"<tr><td>{processor_name}</td><td>{avg_time:.3f}秒</td><td>{count}</td></tr>"
+                    )
                 focus_post_processor_rows = "\n".join(post_processor_rows)
 
             # 计算时间范围

src/plugins/built_in/core_actions/plugin.py

@@ -248,10 +248,10 @@ class NoReplyAction(BaseAction):
                 # 判定条件：累计3条消息或等待超过5秒且有新消息
                 time_since_last_judge = current_time - last_judge_time
                 should_judge = (
-                    new_message_count >= 3 or  # 累计3条消息
+                    new_message_count >= 3  # 累计3条消息
-                    (new_message_count > 0 and time_since_last_judge >= 5.0)  # 等待超过5秒且有新消息
+                    or (new_message_count > 0 and time_since_last_judge >= 5.0)  # 等待超过5秒且有新消息
                 )
-                
+
                 if should_judge and time_since_last_judge >= min_judge_interval:
                     # 判断触发原因
                     trigger_reason = ""
@@ -259,7 +259,7 @@ class NoReplyAction(BaseAction):
                         trigger_reason = f"累计{new_message_count}条消息"
                     elif time_since_last_judge >= 5.0:
                         trigger_reason = f"等待{time_since_last_judge:.1f}秒且有{new_message_count}条新消息"
-                    
+
                     logger.info(f"{self.log_prefix} 触发判定({trigger_reason})，进行智能判断...")
 
                     # 获取最近的消息内容用于判断
@@ -342,7 +342,7 @@ class NoReplyAction(BaseAction):
                                 if self._skip_judge_when_tired and random.random() < skip_probability:
                                     should_skip_llm_judge = True
                                     logger.info(
-                                        f"{self.log_prefix} 发言过多(超过{over_count}条)，随机决定跳过此次LLM判断(概率{skip_probability*100:.0f}%)"
+                                        f"{self.log_prefix} 发言过多(超过{over_count}条)，随机决定跳过此次LLM判断(概率{skip_probability * 100:.0f}%)"
                                     )
 
                                 logger.info(