diff --git a/changelogs/changelog.md b/changelogs/changelog.md
index 461bd7bb..a0b39a62 100644
--- a/changelogs/changelog.md
+++ b/changelogs/changelog.md
@@ -1,12 +1,10 @@
 # Changelog
 
 ## [0.7.0] -2025-6-1
-- 重构数据库，弃用MongoDB，采用轻量sqlite,无需额外安装
-- 重构HFC，可扩展的聊天模式，支持独立的表达模式
-- HFC，丰富HFC的决策信息，更好的把握聊天内容
-- HFC初步支持插件v0.1（测试版）
-- 重构表情包模块
-- 移除日程系统
+- 你可以选择normal,focus和auto多种不同的聊天方式。normal提供更少的消耗，更快的回复速度。focus提供更好的聊天理解，更多工具使用和插件能力
+- 现在，你可以自定义麦麦的表达方式，并且麦麦也可以学习群友的聊天风格（需要在配置文件中打开）
+- 不再需要繁琐的安装MongoDB！弃用MongoDB，采用轻量sqlite,无需额外安装（提供数据迁移脚本）
+- focus模式初步支持了插件，我们提供了两个示例插件（需要手动启用），可以让麦麦实现更丰富的操作。禁言插件和豆包绘图插件是示例用插件。
 
 **重构专注聊天(HFC - focus_chat)**
 - 模块化设计，可以自定义不同的部件
@@ -30,10 +28,14 @@
 - 为专注模式添加关系线索
 - 在专注模式下，麦麦可以决定自行发送语音消息（需要搭配tts适配器）
 - 优化reply，减少复读
+- 可自定义连续回复次数
+- 可自定义处理器超时时间
 
 **优化普通聊天(normal_chat)**
+- 添加可学习的表达方式
 - 增加了talk_frequency参数来有效控制回复频率
 - 优化了进入和离开normal_chat的方式
+- 添加时间信息
 
 **新增表达方式学习**
 - 麦麦配置单独表达方式
@@ -48,7 +50,6 @@
 - 移除聊天限额数量
 
 **插件系统**
-- 添加示例插件
 - 示例插件：禁言插件
 - 示例插件：豆包绘图插件
 
@@ -65,6 +66,9 @@
 - 移除日程系统，减少幻觉（将会在未来版本回归）
 - 移除主心流思考和LLM进入聊天判定
 - 支持qwen3模型，支持自定义是否思考和思考长度
+- 优化提及和at的判定
+- 添加配置项
+- 添加临时配置文件读取器
 
 
 ## [0.6.3-fix-4] - 2025-5-18
diff --git a/scripts/070configexe.py b/scripts/070configexe.py
index eeba7d63..be1f56e4 100644
--- a/scripts/070configexe.py
+++ b/scripts/070configexe.py
@@ -403,15 +403,15 @@ class ConfigEditor:
                     # 创建模型名称标签（大字体）
                     model_name = var.get() if var.get() else providers[0]
                     section_translations = {
-                        "model.utils": "工具模型",
-                        "model.utils_small": "小型工具模型",
+                        "model.utils": "麦麦组件模型",
+                        "model.utils_small": "小型麦麦组件模型",
                         "model.memory_summary": "记忆概括模型",
                         "model.vlm": "图像识别模型",
                         "model.embedding": "嵌入模型",
                         "model.normal_chat_1": "普通聊天：主要聊天模型",
                         "model.normal_chat_2": "普通聊天：次要聊天模型",
                         "model.focus_working_memory": "专注模式：工作记忆模型",
-                        "model.focus_chat_mind": "专注模式：聊天规划模型",
+                        "model.focus_chat_mind": "专注模式：聊天思考模型",
                         "model.focus_tool_use": "专注模式：工具调用模型",
                         "model.focus_planner": "专注模式：决策模型",
                         "model.focus_expressor": "专注模式：表达器模型",
diff --git a/scripts/configexe.toml b/scripts/configexe.toml
index 603393f7..a322025f 100644
--- a/scripts/configexe.toml
+++ b/scripts/configexe.toml
@@ -302,6 +302,15 @@ description = "思考的时间间隔（秒），可以有效减少消耗"
 name = "连续回复能力"
 description = "连续回复能力，值越高，麦麦连续回复的概率越高"
 
+[translations.items.parallel_processing]
+name = "并行处理"
+description = "是否并行处理回忆和处理器阶段，可以节省时间"
+
+[translations.items.processor_max_time]
+name = "处理器最大时间"
+description = "处理器最大时间，单位秒，如果超过这个时间，处理器会自动停止"
+
+
 [translations.items.observation_context_size]
 name = "观察上下文大小"
 description = "观察到的最长上下文大小，建议15，太短太长都会导致脑袋尖尖"
diff --git a/src/chat/focus_chat/expressors/default_expressor.py b/src/chat/focus_chat/expressors/default_expressor.py
index d8cc1064..2d8cf123 100644
--- a/src/chat/focus_chat/expressors/default_expressor.py
+++ b/src/chat/focus_chat/expressors/default_expressor.py
@@ -41,8 +41,8 @@ def init_prompt():
 你需要使用合适的语法和句法，参考聊天内容，组织一条日常且口语化的回复。
 请你根据情景使用以下句法：
 {grammar_habbits}
-回复尽量简短一些。可以参考贴吧，知乎和微博的回复风格，你可以完全重组回复，保留最基本的表达含义就好，但注意回复要简短，但重组后保持语意通顺。
-回复不要浮夸，不要用夸张修辞，平淡一些。不要输出多余内容(包括前后缀，冒号和引号，括号，表情包，at或 @等 )，只输出一条回复就好。
+{config_expression_style}，你可以完全重组回复，保留最基本的表达含义就好，但重组后保持语意通顺。
+不要浮夸，不要夸张修辞，平淡且不要输出多余内容(包括前后缀，冒号和引号，括号，表情包，at或 @等 )，只输出一条回复就好。
 现在，你说：
 """,
         "default_expressor_prompt",
@@ -63,8 +63,8 @@ def init_prompt():
 你需要使用合适的语法和句法，参考聊天内容，组织一条日常且口语化的回复。
 请你根据情景使用以下句法：
 {grammar_habbits}
-回复尽量简短一些。可以参考贴吧，知乎和微博的回复风格，你可以完全重组回复，保留最基本的表达含义就好，但注意回复要简短，但重组后保持语意通顺。
-回复不要浮夸，不要用夸张修辞，平淡一些。不要输出多余内容(包括前后缀，冒号和引号，括号，表情包，at或 @等 )，只输出一条回复就好。
+{config_expression_style}，你可以完全重组回复，保留最基本的表达含义就好，但重组后保持语意通顺。
+不要浮夸，不要夸张修辞，平淡且不要输出多余内容(包括前后缀，冒号和引号，括号，表情包，at或 @等 )，只输出一条回复就好。
 现在，你说：
 """,
         "default_expressor_private_prompt",  # New template for private FOCUSED chat
@@ -128,7 +128,7 @@ class DefaultExpressor:
         # 创建思考消息
         await self._create_thinking_message(anchor_message, thinking_id)
 
-        reply = None  # 初始化 reply，防止未定义
+        reply = []  # 初始化 reply，防止未定义
         try:
             has_sent_something = False
 
@@ -216,6 +216,7 @@ class DefaultExpressor:
                     reason=reason,
                     sender_name=sender_name_for_prompt,  # Pass determined name
                     target_message=target_message,
+                    config_expression_style=global_config.expression.expression_style,
                 )
 
             # 4. 调用 LLM 生成回复
@@ -230,7 +231,7 @@ class DefaultExpressor:
                 with Timer("LLM生成", {}):  # 内部计时器，可选保留
                     # TODO: API-Adapter修改标记
                     # logger.info(f"{self.log_prefix}[Replier-{thinking_id}]\nPrompt:\n{prompt}\n")
-                    content, reasoning_content, model_name = await self.express_model.generate_response(prompt)
+                    content, (reasoning_content, model_name) = await self.express_model.generate_response_async(prompt)
 
                     # logger.info(f"{self.log_prefix}\nPrompt:\n{prompt}\n---------------------------\n")
 
@@ -275,6 +276,7 @@ class DefaultExpressor:
         sender_name,
         in_mind_reply,
         target_message,
+        config_expression_style,
     ) -> str:
         is_group_chat = bool(chat_stream.group_info)
 
@@ -343,6 +345,7 @@ class DefaultExpressor:
                 reason=reason,
                 in_mind_reply=in_mind_reply,
                 target_message=target_message,
+                config_expression_style=config_expression_style,
             )
         else:  # Private chat
             template_name = "default_expressor_private_prompt"
@@ -358,6 +361,7 @@ class DefaultExpressor:
                 reason=reason,
                 in_mind_reply=in_mind_reply,
                 target_message=target_message,
+                config_expression_style=config_expression_style,
             )
 
         return prompt
diff --git a/src/chat/focus_chat/expressors/exprssion_learner.py b/src/chat/focus_chat/expressors/exprssion_learner.py
index 817a188f..afee74af 100644
--- a/src/chat/focus_chat/expressors/exprssion_learner.py
+++ b/src/chat/focus_chat/expressors/exprssion_learner.py
@@ -19,11 +19,13 @@ def init_prompt() -> None:
     learn_style_prompt = """
 {chat_str}
 
-请从上面这段群聊中概括除了人名为"SELF"之外的人的语言风格，只考虑文字，不要考虑表情包和图片
-不要涉及具体的人名，只考虑语言风格
-语言风格包含特殊内容和情感
-思考有没有特殊的梗，一并总结成语言风格
-总结成如下格式的规律，总结的内容要详细，但具有概括性：
+请从上面这段群聊中概括除了人名为"SELF"之外的人的语言风格
+1. 只考虑文字，不要考虑表情包和图片
+2. 不要涉及具体的人名，只考虑语言风格
+3. 语言风格包含特殊内容和情感
+4. 思考有没有特殊的梗，一并总结成语言风格
+5. 例子仅供参考，请严格根据群聊内容总结!!!
+注意：总结成如下格式的规律，总结的内容要详细，但具有概括性：
 当"xxx"时，可以"xxx", xxx不超过10个字
 
 例如：
@@ -31,7 +33,7 @@ def init_prompt() -> None:
 当"表示讽刺的赞同，不想讲道理"时，使用"对对对"
 当"想说明某个观点，但懒得明说"，使用"懂的都懂"
 
-注意不要总结你自己的发言
+注意不要总结你自己（SELF）的发言
 现在请你概括
 """
     Prompt(learn_style_prompt, "learn_style_prompt")
@@ -40,9 +42,10 @@ def init_prompt() -> None:
 {chat_str}
 
 请从上面这段群聊中概括除了人名为"SELF"之外的人的语法和句法特点，只考虑纯文字，不要考虑表情包和图片
-不要总结【图片】，【动画表情】，[图片]，[动画表情]，不总结 表情符号 at @ 回复 和[回复]
-不要涉及具体的人名，只考虑语法和句法特点,
-语法和句法特点要包括，句子长短（具体字数），有何种语病，如何拆分句子。
+1.不要总结【图片】，【动画表情】，[图片]，[动画表情]，不总结 表情符号 at @ 回复 和[回复]
+2.不要涉及具体的人名，只考虑语法和句法特点,
+3.语法和句法特点要包括，句子长短（具体字数），有何种语病，如何拆分句子。
+4. 例子仅供参考，请严格根据群聊内容总结!!!
 总结成如下格式的规律，总结的内容要简洁，不浮夸：
 当"xxx"时，可以"xxx"
 
@@ -51,7 +54,7 @@ def init_prompt() -> None:
 当"不用详细说明的一般表达"时，使用"非常简洁的句子"的句法
 当"需要单纯简单的确认"时，使用"单字或几个字的肯定(1-2个字)"的句法
 
-注意不要总结你自己的发言
+注意不要总结你自己（SELF）的发言
 现在请你概括
 """
     Prompt(learn_grammar_prompt, "learn_grammar_prompt")
diff --git a/src/chat/focus_chat/heartFC_Cycleinfo.py b/src/chat/focus_chat/heartFC_Cycleinfo.py
index f1accecd..5a9a52fd 100644
--- a/src/chat/focus_chat/heartFC_Cycleinfo.py
+++ b/src/chat/focus_chat/heartFC_Cycleinfo.py
@@ -2,12 +2,14 @@ import time
 import os
 from typing import List, Optional, Dict, Any
 
+log_dir = "log/log_cycle_debug/"
 
 class CycleDetail:
     """循环信息记录类"""
 
     def __init__(self, cycle_id: int):
         self.cycle_id = cycle_id
+        self.prefix = ""
         self.thinking_id = ""
         self.start_time = time.time()
         self.end_time: Optional[float] = None
@@ -21,21 +23,80 @@ class CycleDetail:
 
     def to_dict(self) -> Dict[str, Any]:
         """将循环信息转换为字典格式"""
+        def convert_to_serializable(obj, depth=0, seen=None):
+            if seen is None:
+                seen = set()
+            
+            # 防止递归过深
+            if depth > 5:  # 降低递归深度限制
+                return str(obj)
+            
+            # 防止循环引用
+            obj_id = id(obj)
+            if obj_id in seen:
+                return str(obj)
+            seen.add(obj_id)
+            
+            try:
+                if hasattr(obj, 'to_dict'):
+                    # 对于有to_dict方法的对象，直接调用其to_dict方法
+                    return obj.to_dict()
+                elif isinstance(obj, dict):
+                    # 对于字典，只保留基本类型和可序列化的值
+                    return {k: convert_to_serializable(v, depth + 1, seen) 
+                        for k, v in obj.items() 
+                        if isinstance(k, (str, int, float, bool))}
+                elif isinstance(obj, (list, tuple)):
+                    # 对于列表和元组，只保留可序列化的元素
+                    return [convert_to_serializable(item, depth + 1, seen) 
+                        for item in obj 
+                        if not isinstance(item, (dict, list, tuple)) or 
+                        isinstance(item, (str, int, float, bool, type(None)))]
+                elif isinstance(obj, (str, int, float, bool, type(None))):
+                    return obj
+                else:
+                    return str(obj)
+            finally:
+                seen.remove(obj_id)
+
         return {
             "cycle_id": self.cycle_id,
             "start_time": self.start_time,
             "end_time": self.end_time,
             "timers": self.timers,
             "thinking_id": self.thinking_id,
-            "loop_observation_info": self.loop_observation_info,
-            "loop_process_info": self.loop_process_info,
-            "loop_plan_info": self.loop_plan_info,
-            "loop_action_info": self.loop_action_info,
+            "loop_observation_info": convert_to_serializable(self.loop_observation_info),
+            "loop_process_info": convert_to_serializable(self.loop_process_info),
+            "loop_plan_info": convert_to_serializable(self.loop_plan_info),
+            "loop_action_info": convert_to_serializable(self.loop_action_info),
         }
 
     def complete_cycle(self):
         """完成循环，记录结束时间"""
         self.end_time = time.time()
+        
+        # 处理 prefix，只保留中英文字符
+        if not self.prefix:
+            self.prefix = "group"
+        else:
+            # 只保留中文和英文字符
+            self.prefix = ''.join(char for char in self.prefix if '\u4e00' <= char <= '\u9fff' or char.isascii())
+            if not self.prefix:
+                self.prefix = "group"
+        
+        current_time_minute = time.strftime("%Y%m%d_%H%M", time.localtime())
+        self.log_cycle_to_file(log_dir + self.prefix + f"/{current_time_minute}_cycle_" + str(self.cycle_id) + ".json")
+        
+    def log_cycle_to_file(self, file_path: str):
+        """将循环信息写入文件"""
+        # 如果目录不存在，则创建目录
+        dir_name = os.path.dirname(file_path)
+        if dir_name and not os.path.exists(dir_name):
+            os.makedirs(dir_name, exist_ok=True)
+        # 写入文件
+        import json
+        with open(file_path, "a", encoding="utf-8") as f:
+            f.write(json.dumps(self.to_dict(), ensure_ascii=False) + "\n")
 
     def set_thinking_id(self, thinking_id: str):
         """设置思考消息ID"""
@@ -47,30 +108,3 @@ class CycleDetail:
         self.loop_processor_info = loop_info["loop_processor_info"]
         self.loop_plan_info = loop_info["loop_plan_info"]
         self.loop_action_info = loop_info["loop_action_info"]
-
-    @staticmethod
-    def list_cycles(stream_id: str, base_dir: str = "log_debug") -> List[str]:
-        """
-        列出指定stream_id的所有循环文件
-
-        参数:
-            stream_id: 聊天流ID
-            base_dir: 基础目录，默认为log_debug
-
-        返回:
-            List[str]: 文件路径列表
-        """
-        try:
-            stream_dir = os.path.join(base_dir, stream_id)
-            if not os.path.exists(stream_dir):
-                return []
-
-            files = [
-                os.path.join(stream_dir, f)
-                for f in os.listdir(stream_dir)
-                if f.startswith("cycle_") and f.endswith(".txt")
-            ]
-            return sorted(files)
-        except Exception as e:
-            print(f"列出循环文件时出错: {e}")
-            return []
diff --git a/src/chat/focus_chat/heartFC_chat.py b/src/chat/focus_chat/heartFC_chat.py
index 3835b2da..c69dea6b 100644
--- a/src/chat/focus_chat/heartFC_chat.py
+++ b/src/chat/focus_chat/heartFC_chat.py
@@ -44,21 +44,10 @@ PROCESSOR_CLASSES = {
     "ToolProcessor": (ToolProcessor, "tool_use_processor"),
     "WorkingMemoryProcessor": (WorkingMemoryProcessor, "working_memory_processor"),
     "SelfProcessor": (SelfProcessor, "self_identify_processor"),
-    # "ActionProcessor": (ActionProcessor, "action_processor"),  # 这个处理器不需要配置键名，默认启用
 }
 
-
-WAITING_TIME_THRESHOLD = 300  # 等待新消息时间阈值，单位秒
-
-EMOJI_SEND_PRO = 0.3  # 设置一个概率，比如 30% 才真的发
-
-CONSECUTIVE_NO_REPLY_THRESHOLD = 3  # 连续不回复的阈值
-
 logger = get_logger("hfc")  # Logger Name Changed
 
-# 设定处理器超时时间（秒）
-PROCESSOR_TIMEOUT = 30
-
 
 async def _handle_cycle_delay(action_taken_this_cycle: bool, cycle_start_time: float, log_prefix: str):
     """处理循环延迟"""
@@ -150,7 +139,7 @@ class HeartFChatting:
         # 添加循环信息管理相关的属性
         self._cycle_counter = 0
         self._cycle_history: Deque[CycleDetail] = deque(maxlen=10)  # 保留最近10个循环的信息
-        self._current_cycle: Optional[CycleDetail] = None
+        self._current_cycle_detail: Optional[CycleDetail] = None
         self._shutting_down: bool = False  # 关闭标志位
 
         # 存储回调函数
@@ -262,12 +251,12 @@ class HeartFChatting:
         try:
             exception = task.exception()
             if exception:
-                logger.error(f"{self.log_prefix} HeartFChatting: 麦麦脱离了聊天(异常): {exception}")
+                logger.error(f"{self.log_prefix} HeartFChatting: 脱离了聊天(异常): {exception}")
                 logger.error(traceback.format_exc())  # Log full traceback for exceptions
             else:
-                logger.info(f"{self.log_prefix} HeartFChatting: 麦麦脱离了聊天 (外部停止)")
+                logger.info(f"{self.log_prefix} HeartFChatting: 脱离了聊天 (外部停止)")
         except asyncio.CancelledError:
-            logger.info(f"{self.log_prefix} HeartFChatting: 麦麦脱离了聊天(任务取消)")
+            logger.info(f"{self.log_prefix} HeartFChatting: 脱离了聊天(任务取消)")
         finally:
             self._loop_active = False
             self._loop_task = None
@@ -286,7 +275,8 @@ class HeartFChatting:
 
                 # 创建新的循环信息
                 self._cycle_counter += 1
-                self._current_cycle = CycleDetail(self._cycle_counter)
+                self._current_cycle_detail = CycleDetail(self._cycle_counter)
+                self._current_cycle_detail.prefix = self.log_prefix
 
                 # 初始化周期状态
                 cycle_timers = {}
@@ -295,13 +285,12 @@ class HeartFChatting:
                 # 执行规划和处理阶段
                 async with self._get_cycle_context():
                     thinking_id = "tid" + str(round(time.time(), 2))
-                    self._current_cycle.set_thinking_id(thinking_id)
+                    self._current_cycle_detail.set_thinking_id(thinking_id)
                     # 主循环：思考->决策->执行
                     async with global_prompt_manager.async_message_scope(self.chat_stream.context.get_template_name()):
                         logger.debug(f"模板 {self.chat_stream.context.get_template_name()}")
                         loop_info = await self._observe_process_plan_action_loop(cycle_timers, thinking_id)
 
-                        print(loop_info["loop_action_info"]["command"])
                         if loop_info["loop_action_info"]["command"] == "stop_focus_chat":
                             logger.info(f"{self.log_prefix} 麦麦决定停止专注聊天")
                             # 如果设置了回调函数，则调用它
@@ -314,10 +303,10 @@ class HeartFChatting:
                                     logger.error(traceback.format_exc())
                             break
 
-                    self._current_cycle.set_loop_info(loop_info)
+                    self._current_cycle_detail.set_loop_info(loop_info)
 
-                    self.hfcloop_observation.add_loop_info(self._current_cycle)
-                    self._current_cycle.timers = cycle_timers
+                    self.hfcloop_observation.add_loop_info(self._current_cycle_detail)
+                    self._current_cycle_detail.timers = cycle_timers
 
                     # 防止循环过快消耗资源
                     await _handle_cycle_delay(
@@ -325,8 +314,8 @@ class HeartFChatting:
                     )
 
                 # 完成当前循环并保存历史
-                self._current_cycle.complete_cycle()
-                self._cycle_history.append(self._current_cycle)
+                self._current_cycle_detail.complete_cycle()
+                self._cycle_history.append(self._current_cycle_detail)
 
                 # 记录循环信息和计时器结果
                 timer_strings = []
@@ -335,7 +324,7 @@ class HeartFChatting:
                     timer_strings.append(f"{name}: {formatted_time}")
 
                 # 新增：输出每个处理器的耗时
-                processor_time_costs = self._current_cycle.loop_processor_info.get("processor_time_costs", {})
+                processor_time_costs = self._current_cycle_detail.loop_processor_info.get("processor_time_costs", {})
                 processor_time_strings = []
                 for pname, ptime in processor_time_costs.items():
                     formatted_ptime = f"{ptime * 1000:.2f}毫秒" if ptime < 1 else f"{ptime:.2f}秒"
@@ -345,9 +334,9 @@ class HeartFChatting:
                 )
 
                 logger.info(
-                    f"{self.log_prefix} 第{self._current_cycle.cycle_id}次思考,"
-                    f"耗时: {self._current_cycle.end_time - self._current_cycle.start_time:.1f}秒, "
-                    f"动作: {self._current_cycle.loop_plan_info['action_result']['action_type']}"
+                    f"{self.log_prefix} 第{self._current_cycle_detail.cycle_id}次思考,"
+                    f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒, "
+                    f"动作: {self._current_cycle_detail.loop_plan_info['action_result']['action_type']}"
                     + (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "")
                     + processor_time_log
                 )
@@ -384,7 +373,7 @@ class HeartFChatting:
                 self._processing_lock.release()
 
     async def _process_processors(
-        self, observations: List[Observation], running_memorys: List[Dict[str, Any]], cycle_timers: dict
+        self, observations: List[Observation], running_memorys: List[Dict[str, Any]]
     ) -> tuple[List[InfoBase], Dict[str, float]]:
         # 记录并行任务开始时间
         parallel_start_time = time.time()
@@ -400,7 +389,7 @@ class HeartFChatting:
             async def run_with_timeout(proc=processor):
                 return await asyncio.wait_for(
                     proc.process_info(observations=observations, running_memorys=running_memorys),
-                    timeout=PROCESSOR_TIMEOUT,
+                    timeout=global_config.focus_chat.processor_max_time,
                 )
 
             task = asyncio.create_task(run_with_timeout())
@@ -429,8 +418,8 @@ class HeartFChatting:
                     # 记录耗时
                     processor_time_costs[processor_name] = duration_since_parallel_start
                 except asyncio.TimeoutError:
-                    logger.info(f"{self.log_prefix} 处理器 {processor_name} 超时（>{PROCESSOR_TIMEOUT}s），已跳过")
-                    processor_time_costs[processor_name] = PROCESSOR_TIMEOUT
+                    logger.info(f"{self.log_prefix} 处理器 {processor_name} 超时（>{global_config.focus_chat.processor_max_time}s），已跳过")
+                    processor_time_costs[processor_name] = global_config.focus_chat.processor_max_time
                 except Exception as e:
                     logger.error(
                         f"{self.log_prefix} 处理器 {processor_name} 执行失败，耗时 (自并行开始): {duration_since_parallel_start:.2f}秒. 错误: {e}",
@@ -473,28 +462,42 @@ class HeartFChatting:
                 }
 
                 self.all_observations = observations
-
-            with Timer("回忆", cycle_timers):
-                running_memorys = await self.memory_activator.activate_memory(observations)
-
+                
             with Timer("调整动作", cycle_timers):
                 # 处理特殊的观察
-                await self.action_modifier.modify_actions(observations=observations, running_memorys=running_memorys)
+                await self.action_modifier.modify_actions(observations=observations)
                 await self.action_observation.observe()
                 observations.append(self.action_observation)
 
-            with Timer("执行 信息处理器", cycle_timers):
-                all_plan_info, processor_time_costs = await self._process_processors(
-                    observations, running_memorys, cycle_timers
-                )
+            # 根据配置决定是否并行执行回忆和处理器阶段
+            # print(global_config.focus_chat.parallel_processing)
+            if global_config.focus_chat.parallel_processing:
+                # 并行执行回忆和处理器阶段
+                with Timer("并行回忆和处理", cycle_timers):
+                    memory_task = asyncio.create_task(self.memory_activator.activate_memory(observations))
+                    processor_task = asyncio.create_task(self._process_processors(observations, []))
+                    
+                    # 等待两个任务完成
+                    running_memorys, (all_plan_info, processor_time_costs) = await asyncio.gather(memory_task, processor_task)
+            else:
+                # 串行执行
+                with Timer("回忆", cycle_timers):
+                    running_memorys = await self.memory_activator.activate_memory(observations)
+
+                with Timer("执行 信息处理器", cycle_timers):
+                    all_plan_info, processor_time_costs = await self._process_processors(
+                        observations, running_memorys
+                    )
+
+            loop_processor_info = {
+                "all_plan_info": all_plan_info,
+                "processor_time_costs": processor_time_costs,
+            }
+
 
-                loop_processor_info = {
-                    "all_plan_info": all_plan_info,
-                    "processor_time_costs": processor_time_costs,
-                }
 
             with Timer("规划器", cycle_timers):
-                plan_result = await self.action_planner.plan(all_plan_info, cycle_timers)
+                plan_result = await self.action_planner.plan(all_plan_info, running_memorys)
 
                 loop_plan_info = {
                     "action_result": plan_result.get("action_result", {}),
@@ -526,6 +529,7 @@ class HeartFChatting:
                     "action_taken": success,
                     "reply_text": reply_text,
                     "command": command,
+                    "taken_time": time.time(),
                 }
 
             loop_info = {
diff --git a/src/chat/focus_chat/info_processors/chattinginfo_processor.py b/src/chat/focus_chat/info_processors/chattinginfo_processor.py
index ca084d2a..3812a6fd 100644
--- a/src/chat/focus_chat/info_processors/chattinginfo_processor.py
+++ b/src/chat/focus_chat/info_processors/chattinginfo_processor.py
@@ -104,7 +104,7 @@ class ChattingInfoProcessor(BaseProcessor):
         if obs.compressor_prompt:
             summary = ""
             try:
-                summary_result, _, _ = await self.model_summary.generate_response(obs.compressor_prompt)
+                summary_result, _ = await self.model_summary.generate_response_async(obs.compressor_prompt)
                 summary = "没有主题的闲聊"
                 if summary_result:
                     summary = summary_result
diff --git a/src/chat/focus_chat/info_processors/mind_processor.py b/src/chat/focus_chat/info_processors/mind_processor.py
index 12671169..910b5c75 100644
--- a/src/chat/focus_chat/info_processors/mind_processor.py
+++ b/src/chat/focus_chat/info_processors/mind_processor.py
@@ -24,9 +24,7 @@ logger = get_logger("processor")
 def init_prompt():
     group_prompt = """
 你的名字是{bot_name}
-{memory_str}
-{extra_info}
-{relation_prompt}
+{memory_str}{extra_info}{relation_prompt}
 {cycle_info_block}
 现在是{time_now}，你正在上网，和qq群里的网友们聊天，以下是正在进行的聊天内容：
 {chat_observe_info}
@@ -46,15 +44,11 @@ def init_prompt():
 
     private_prompt = """
 你的名字是{bot_name}
-{memory_str}
-{extra_info}
-{relation_prompt}
+{memory_str}{extra_info}{relation_prompt}
 {cycle_info_block}
 现在是{time_now}，你正在上网，和qq群里的网友们聊天，以下是正在进行的聊天内容：
 {chat_observe_info}
-
 {action_observe_info}
-
 以下是你之前对聊天的观察和规划，你的名字是{bot_name}：
 {last_mind}
 
@@ -77,7 +71,7 @@ class MindProcessor(BaseProcessor):
 
         self.llm_model = LLMRequest(
             model=global_config.model.focus_chat_mind,
-            temperature=global_config.model.focus_chat_mind["temp"],
+            # temperature=global_config.model.focus_chat_mind["temp"],
             max_tokens=800,
             request_type="focus.processor.chat_mind",
         )
@@ -155,14 +149,14 @@ class MindProcessor(BaseProcessor):
 
         # ---------- 0. 更新和清理 structured_info ----------
         if self.structured_info:
-            updated_info = []
-            for item in self.structured_info:
-                item["ttl"] -= 1
-                if item["ttl"] > 0:
-                    updated_info.append(item)
-                else:
-                    logger.debug(f"{self.log_prefix} 移除过期的 structured_info 项: {item['id']}")
-            self.structured_info = updated_info
+            # updated_info = []
+            # for item in self.structured_info:
+            #     item["ttl"] -= 1
+            #     if item["ttl"] > 0:
+            #         updated_info.append(item)
+            #     else:
+            #         logger.debug(f"{self.log_prefix} 移除过期的 structured_info 项: {item['id']}")
+            # self.structured_info = updated_info
             self._update_structured_info_str()
         logger.debug(
             f"{self.log_prefix} 当前完整的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}"
@@ -231,7 +225,7 @@ class MindProcessor(BaseProcessor):
             # 处理总体异常
             logger.error(f"{self.log_prefix} 执行LLM请求或处理响应时出错: {e}")
             logger.error(traceback.format_exc())
-            content = "思考过程中出现错误"
+            content = "注意：思考过程中出现错误，应该是LLM大模型有问题！！你需要告诉别人，检查大模型配置"
 
         # 记录初步思考结果
         logger.debug(f"{self.log_prefix} 思考prompt: \n{prompt}\n")
diff --git a/src/chat/focus_chat/info_processors/self_processor.py b/src/chat/focus_chat/info_processors/self_processor.py
index d489efa2..72562ad5 100644
--- a/src/chat/focus_chat/info_processors/self_processor.py
+++ b/src/chat/focus_chat/info_processors/self_processor.py
@@ -25,9 +25,7 @@ def init_prompt():
 你是一个AI，但是你伪装成了一个人类，你的人格是，{prompt_personality}
 {indentify_block}
 
-{relation_prompt}
-{memory_str}
-
+{relation_prompt}{memory_str}
 现在是{time_now}，你正在上网，和qq群里的网友们聊天，以下是正在进行的聊天内容：
 {chat_observe_info}
 
diff --git a/src/chat/focus_chat/info_processors/tool_processor.py b/src/chat/focus_chat/info_processors/tool_processor.py
index 3c0dc116..46c2657d 100644
--- a/src/chat/focus_chat/info_processors/tool_processor.py
+++ b/src/chat/focus_chat/info_processors/tool_processor.py
@@ -23,10 +23,7 @@ def init_prompt():
     # 添加工具执行器提示词
     tool_executor_prompt = """
 你是一个专门执行工具的助手。你的名字是{bot_name}。现在是{time_now}。
-
-你当前的额外信息：
 {memory_str}
-
 群里正在进行的聊天内容：
 {chat_observe_info}
 
@@ -165,8 +162,9 @@ class ToolProcessor(BaseProcessor):
         logger.debug(f"开始执行工具调用{prompt}")
         response, _, tool_calls = await self.llm_model.generate_response_tool_async(prompt=prompt, tools=tools)
 
-        logger.debug(f"获取到工具原始输出:\n{tool_calls}")
-        # 处理工具调用和结果收集，类似于SubMind中的逻辑
+        if tool_calls:
+            logger.debug(f"获取到工具原始输出:\n{tool_calls}")
+            # 处理工具调用和结果收集，类似于SubMind中的逻辑
         new_structured_items = []
         used_tools = []  # 记录使用了哪些工具
 
diff --git a/src/chat/focus_chat/planners/actions/no_reply_action.py b/src/chat/focus_chat/planners/actions/no_reply_action.py
index 1b21a8ce..120ebe98 100644
--- a/src/chat/focus_chat/planners/actions/no_reply_action.py
+++ b/src/chat/focus_chat/planners/actions/no_reply_action.py
@@ -26,8 +26,8 @@ class NoReplyAction(BaseAction):
     action_parameters = {}
     action_require = [
         "话题无关/无聊/不感兴趣/不懂",
-        "最后一条消息是你自己发的且无人回应你",
-        "你发送了太多消息，且无人回复",
+        "聊天记录中最新一条消息是你自己发的且无人回应你",
+        "你连续发送了太多消息，且无人回复",
     ]
     default = True
 
diff --git a/src/chat/focus_chat/planners/modify_actions.py b/src/chat/focus_chat/planners/modify_actions.py
index 1648e6cf..731fe5f9 100644
--- a/src/chat/focus_chat/planners/modify_actions.py
+++ b/src/chat/focus_chat/planners/modify_actions.py
@@ -28,11 +28,8 @@ class ActionModifier:
     async def modify_actions(
         self,
         observations: Optional[List[Observation]] = None,
-        running_memorys: Optional[List[Dict]] = None,
         **kwargs: Any,
     ):
-        # print(f"observations: {observations}")
-        # processed_infos = []
 
         # 处理Observation对象
         if observations:
diff --git a/src/chat/focus_chat/planners/planner.py b/src/chat/focus_chat/planners/planner.py
index 528f7a7f..a0b0ccf9 100644
--- a/src/chat/focus_chat/planners/planner.py
+++ b/src/chat/focus_chat/planners/planner.py
@@ -15,6 +15,7 @@ from src.common.logger_manager import get_logger
 from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
 from src.individuality.individuality import individuality
 from src.chat.focus_chat.planners.action_manager import ActionManager
+from json_repair import repair_json
 
 logger = get_logger("planner")
 
@@ -26,9 +27,8 @@ def init_prompt():
         """
 你的自我认知是：
 {self_info_block}
-
 {extra_info_block}
-
+{memory_str}
 你需要基于以下信息决定如何参与对话
 这些信息可能会有冲突，请你整合这些信息，并选择一个最合适的action：
 {chat_content_block}
@@ -49,7 +49,7 @@ def init_prompt():
 请你以下面格式输出你选择的action：
 {{
     "action": "action_name",
-    "reasoning": "你的决策理由",
+    "reasoning": "说明你做出该action的原因",
     "参数1": "参数1的值",
     "参数2": "参数2的值",
     "参数3": "参数3的值",
@@ -84,13 +84,13 @@ class ActionPlanner:
 
         self.action_manager = action_manager
 
-    async def plan(self, all_plan_info: List[InfoBase], cycle_timers: dict) -> Dict[str, Any]:
+    async def plan(self, all_plan_info: List[InfoBase], running_memorys: List[Dict[str, Any]]) -> Dict[str, Any]:
         """
         规划器 (Planner): 使用LLM根据上下文决定做出什么动作。
 
         参数:
             all_plan_info: 所有计划信息
-            cycle_timers: 计时器字典
+            running_memorys: 回忆信息
         """
 
         action = "no_reply"  # 默认动作
@@ -169,12 +169,15 @@ class ActionPlanner:
                 current_available_actions=current_available_actions,  # <-- Pass determined actions
                 cycle_info=cycle_info,  # <-- Pass cycle info
                 extra_info=extra_info,
+                running_memorys=running_memorys,
             )
 
             # --- 调用 LLM (普通文本生成) ---
             llm_content = None
             try:
-                llm_content, reasoning_content, _ = await self.planner_llm.generate_response(prompt=prompt)
+                prompt = f"{prompt}"
+                print(len(prompt))
+                llm_content, (reasoning_content, _) = await self.planner_llm.generate_response_async(prompt=prompt)
                 logger.debug(f"{self.log_prefix}[Planner] LLM 原始 JSON 响应 (预期): {llm_content}")
                 logger.debug(f"{self.log_prefix}[Planner] LLM 原始理由 响应 (预期): {reasoning_content}")
             except Exception as req_e:
@@ -184,13 +187,16 @@ class ActionPlanner:
 
             if llm_content:
                 try:
-                    # 尝试去除可能的 markdown 代码块标记
-                    cleaned_content = (
-                        llm_content.strip().removeprefix("```json").removeprefix("```").removesuffix("```").strip()
-                    )
-                    if not cleaned_content:
-                        raise json.JSONDecodeError("Cleaned content is empty", cleaned_content, 0)
-                    parsed_json = json.loads(cleaned_content)
+                    fixed_json_string = repair_json(llm_content)
+                    if isinstance(fixed_json_string, str):
+                        try:
+                            parsed_json = json.loads(fixed_json_string)
+                        except json.JSONDecodeError as decode_error:
+                            logger.error(f"JSON解析错误: {str(decode_error)}")
+                            parsed_json = {}
+                    else:
+                        # 如果repair_json直接返回了字典对象，直接使用
+                        parsed_json = fixed_json_string
 
                     # 提取决策，提供默认值
                     extracted_action = parsed_json.get("action", "no_reply")
@@ -244,6 +250,7 @@ class ActionPlanner:
             "action_result": action_result,
             "current_mind": current_mind,
             "observed_messages": observed_messages,
+            "action_prompt": prompt,
         }
 
         return plan_result
@@ -259,10 +266,22 @@ class ActionPlanner:
         current_available_actions: Dict[str, ActionInfo],
         cycle_info: Optional[str],
         extra_info: list[str],
+        running_memorys: List[Dict[str, Any]],
     ) -> str:
         """构建 Planner LLM 的提示词 (获取模板并填充数据)"""
         try:
-            # --- Determine chat context ---
+            
+            memory_str = ""
+            if global_config.focus_chat.parallel_processing:
+                memory_str = ""
+                if running_memorys:
+                    memory_str = "以下是当前在聊天中，你回忆起的记忆：\n"
+                    for running_memory in running_memorys:
+                        memory_str += f"{running_memory['topic']}: {running_memory['content']}\n"
+            
+            
+            
+            
             chat_context_description = "你现在正在一个群聊中"
             chat_target_name = None  # Only relevant for private
             if not is_group_chat and chat_target_info:
@@ -324,6 +343,7 @@ class ActionPlanner:
             planner_prompt_template = await global_prompt_manager.get_prompt_async("planner_prompt")
             prompt = planner_prompt_template.format(
                 self_info_block=self_info_block,
+                memory_str=memory_str,
                 # bot_name=global_config.bot.nickname,
                 prompt_personality=personality_block,
                 chat_context_description=chat_context_description,
diff --git a/src/chat/heart_flow/observation/actions_observation.py b/src/chat/heart_flow/observation/actions_observation.py
index 8310a17b..6f0cd81c 100644
--- a/src/chat/heart_flow/observation/actions_observation.py
+++ b/src/chat/heart_flow/observation/actions_observation.py
@@ -34,3 +34,13 @@ class ActionObservation:
         action_info_block += "\n注意，除了上面动作选项之外，你在群聊里不能做其他任何事情，这是你能力的边界\n"
 
         self.observe_info = action_info_block
+
+    def to_dict(self) -> dict:
+        """将观察对象转换为可序列化的字典"""
+        return {
+            "observe_info": self.observe_info,
+            "observe_id": self.observe_id,
+            "last_observe_time": self.last_observe_time,
+            "all_actions": self.all_actions,
+            "all_using_actions": self.all_using_actions
+        }
diff --git a/src/chat/heart_flow/observation/chatting_observation.py b/src/chat/heart_flow/observation/chatting_observation.py
index e5c5069e..7e9e562d 100644
--- a/src/chat/heart_flow/observation/chatting_observation.py
+++ b/src/chat/heart_flow/observation/chatting_observation.py
@@ -66,6 +66,24 @@ class ChattingObservation(Observation):
         self.oldest_messages_str = ""
         self.compressor_prompt = ""
 
+    def to_dict(self) -> dict:
+        """将观察对象转换为可序列化的字典"""
+        return {
+            "chat_id": self.chat_id,
+            "platform": self.platform,
+            "is_group_chat": self.is_group_chat,
+            "chat_target_info": self.chat_target_info,
+            "talking_message_str": self.talking_message_str,
+            "talking_message_str_truncate": self.talking_message_str_truncate,
+            "name": self.name,
+            "nick_name": self.nick_name,
+            "mid_memory_info": self.mid_memory_info,
+            "person_list": self.person_list,
+            "oldest_messages_str": self.oldest_messages_str,
+            "compressor_prompt": self.compressor_prompt,
+            "last_observe_time": self.last_observe_time
+        }
+
     async def initialize(self):
         self.is_group_chat, self.chat_target_info = await get_chat_type_and_target_info(self.chat_id)
         logger.debug(f"初始化observation: self.is_group_chat: {self.is_group_chat}")
diff --git a/src/chat/heart_flow/observation/hfcloop_observation.py b/src/chat/heart_flow/observation/hfcloop_observation.py
index 7c782bfd..48bf33ed 100644
--- a/src/chat/heart_flow/observation/hfcloop_observation.py
+++ b/src/chat/heart_flow/observation/hfcloop_observation.py
@@ -27,40 +27,70 @@ class HFCloopObservation:
         recent_active_cycles: List[CycleDetail] = []
         for cycle in reversed(self.history_loop):
             # 只关心实际执行了动作的循环
-            action_taken = cycle.loop_action_info["action_taken"]
-            if action_taken:
-                recent_active_cycles.append(cycle)
-                if len(recent_active_cycles) == 5:
-                    break
+            # action_taken = cycle.loop_action_info["action_taken"]
+            # if action_taken:
+            recent_active_cycles.append(cycle)
+            if len(recent_active_cycles) == 5:
+                break
 
         cycle_info_block = ""
+        action_detailed_str = ""
         consecutive_text_replies = 0
         responses_for_prompt = []
 
+        cycle_last_reason = ""
+        
         # 检查这最近的活动循环中有多少是连续的文本回复 (从最近的开始看)
         for cycle in recent_active_cycles:
             action_type = cycle.loop_plan_info["action_result"]["action_type"]
+            action_reasoning = cycle.loop_plan_info["action_result"]["reasoning"]
+            is_taken = cycle.loop_action_info["action_taken"]
+            action_taken_time = cycle.loop_action_info["taken_time"]
+            action_taken_time_str = datetime.fromtimestamp(action_taken_time).strftime("%H:%M:%S")
+            # print(action_type)
+            # print(action_reasoning)
+            # print(is_taken)
+            # print(action_taken_time_str)
+            # print("--------------------------------")
+            if action_reasoning != cycle_last_reason:
+                cycle_last_reason = action_reasoning
+                action_reasoning_str = f"你选择这个action的原因是:{action_reasoning}"
+            else:
+                action_reasoning_str = ""
+            
             if action_type == "reply":
                 consecutive_text_replies += 1
                 response_text = cycle.loop_plan_info["action_result"]["action_data"].get("text", "[空回复]")
                 responses_for_prompt.append(response_text)
+                
+                if is_taken:
+                    action_detailed_str += f"{action_taken_time_str}时，你选择回复(action:{action_type},内容是:'{response_text}')。{action_reasoning_str}\n"
+                else:
+                    action_detailed_str += f"{action_taken_time_str}时，你选择回复(action:{action_type},内容是:'{response_text}')，但是动作失败了。{action_reasoning_str}\n"
+            elif action_type == "no_reply":
+                action_detailed_str += f"{action_taken_time_str}时，你选择不回复(action:{action_type})，{action_reasoning_str}\n"
             else:
-                break
-
+                if is_taken:
+                    action_detailed_str += f"{action_taken_time_str}时，你选择执行了(action:{action_type})，{action_reasoning_str}\n"
+                else:
+                    action_detailed_str += f"{action_taken_time_str}时，你选择执行了(action:{action_type})，但是动作失败了。{action_reasoning_str}\n"
+                
+        if action_detailed_str:
+            cycle_info_block = f"\n你最近做的事：\n{action_detailed_str}\n"
+        else:
+            cycle_info_block = "\n"
+        
         # 根据连续文本回复的数量构建提示信息
-        # 注意: responses_for_prompt 列表是从最近到最远排序的
         if consecutive_text_replies >= 3:  # 如果最近的三个活动都是文本回复
             cycle_info_block = f'你已经连续回复了三条消息（最近: "{responses_for_prompt[0]}"，第二近: "{responses_for_prompt[1]}"，第三近: "{responses_for_prompt[2]}"）。你回复的有点多了，请注意'
         elif consecutive_text_replies == 2:  # 如果最近的两个活动是文本回复
             cycle_info_block = f'你已经连续回复了两条消息（最近: "{responses_for_prompt[0]}"，第二近: "{responses_for_prompt[1]}"），请注意'
-        elif consecutive_text_replies == 1:  # 如果最近的一个活动是文本回复
-            cycle_info_block = f'你刚刚已经回复一条消息（内容: "{responses_for_prompt[0]}"）'
 
         # 包装提示块，增加可读性，即使没有连续回复也给个标记
-        if cycle_info_block:
-            cycle_info_block = f"\n你最近的回复\n{cycle_info_block}\n"
-        else:
-            cycle_info_block = "\n"
+        # if cycle_info_block:
+        #     cycle_info_block = f"\n你最近的回复\n{cycle_info_block}\n"
+        # else:
+        #     cycle_info_block = "\n"
 
         # 获取history_loop中最新添加的
         if self.history_loop:
@@ -70,10 +100,21 @@ class HFCloopObservation:
             if start_time is not None and end_time is not None:
                 time_diff = int(end_time - start_time)
                 if time_diff > 60:
-                    cycle_info_block += f"\n距离你上一次阅读消息已经过去了{time_diff / 60}分钟\n"
+                    cycle_info_block += f"距离你上一次阅读消息并思考和规划，已经过去了{int(time_diff / 60)}分钟\n"
                 else:
-                    cycle_info_block += f"\n距离你上一次阅读消息已经过去了{time_diff}秒\n"
+                    cycle_info_block += f"距离你上一次阅读消息并思考和规划，已经过去了{time_diff}秒\n"
             else:
-                cycle_info_block += "\n你还没看过消息\n"
+                cycle_info_block += "你还没看过消息\n"
 
         self.observe_info = cycle_info_block
+
+    def to_dict(self) -> dict:
+        """将观察对象转换为可序列化的字典"""
+        # 只序列化基本信息，避免循环引用
+        return {
+            "observe_info": self.observe_info,
+            "observe_id": self.observe_id,
+            "last_observe_time": self.last_observe_time,
+            # 不序列化history_loop，避免循环引用
+            "history_loop_count": len(self.history_loop)
+        }
diff --git a/src/chat/heart_flow/observation/observation.py b/src/chat/heart_flow/observation/observation.py
index 97e254fc..5c8b5fda 100644
--- a/src/chat/heart_flow/observation/observation.py
+++ b/src/chat/heart_flow/observation/observation.py
@@ -13,5 +13,13 @@ class Observation:
         self.observe_id = observe_id
         self.last_observe_time = datetime.now().timestamp()  # 初始化为当前时间
 
+    def to_dict(self) -> dict:
+        """将观察对象转换为可序列化的字典"""
+        return {
+            "observe_info": self.observe_info,
+            "observe_id": self.observe_id,
+            "last_observe_time": self.last_observe_time
+        }
+
     async def observe(self):
         pass
diff --git a/src/chat/heart_flow/observation/structure_observation.py b/src/chat/heart_flow/observation/structure_observation.py
index 73b5bf75..6e670f5e 100644
--- a/src/chat/heart_flow/observation/structure_observation.py
+++ b/src/chat/heart_flow/observation/structure_observation.py
@@ -15,6 +15,16 @@ class StructureObservation:
         self.history_loop = []
         self.structured_info = []
 
+    def to_dict(self) -> dict:
+        """将观察对象转换为可序列化的字典"""
+        return {
+            "observe_info": self.observe_info,
+            "observe_id": self.observe_id,
+            "last_observe_time": self.last_observe_time,
+            "history_loop": self.history_loop,
+            "structured_info": self.structured_info
+        }
+
     def get_observe_info(self):
         return self.structured_info
 
diff --git a/src/chat/heart_flow/observation/working_observation.py b/src/chat/heart_flow/observation/working_observation.py
index 7013c3a2..3cab4a37 100644
--- a/src/chat/heart_flow/observation/working_observation.py
+++ b/src/chat/heart_flow/observation/working_observation.py
@@ -32,3 +32,13 @@ class WorkingMemoryObservation:
 
     async def observe(self):
         pass
+
+    def to_dict(self) -> dict:
+        """将观察对象转换为可序列化的字典"""
+        return {
+            "observe_info": self.observe_info,
+            "observe_id": self.observe_id,
+            "last_observe_time": self.last_observe_time,
+            "working_memory": self.working_memory.to_dict() if hasattr(self.working_memory, 'to_dict') else str(self.working_memory),
+            "retrieved_working_memory": [item.to_dict() if hasattr(item, 'to_dict') else str(item) for item in self.retrieved_working_memory]
+        }
diff --git a/src/chat/heart_flow/sub_heartflow.py b/src/chat/heart_flow/sub_heartflow.py
index 435a7b61..984b3638 100644
--- a/src/chat/heart_flow/sub_heartflow.py
+++ b/src/chat/heart_flow/sub_heartflow.py
@@ -278,10 +278,6 @@ class SubHeartflow:
             self.update_last_chat_state_time()
             self.history_chat_state.append((current_state, self.chat_state_last_time))
 
-            # logger.info(
-            # f"{log_prefix} 麦麦的聊天状态从 {current_state.value} （持续了 {int(self.chat_state_last_time)} 秒） 变更为 {new_state.value}"
-            # )
-
             self.chat_state.chat_status = new_state
             self.chat_state_last_time = 0
             self.chat_state_changed_time = time.time()
diff --git a/src/chat/normal_chat/normal_prompt.py b/src/chat/normal_chat/normal_prompt.py
index 5b82b8b8..e4d69a0f 100644
--- a/src/chat/normal_chat/normal_prompt.py
+++ b/src/chat/normal_chat/normal_prompt.py
@@ -185,20 +185,23 @@ class PromptBuilder:
 
         # 关键词检测与反应
         keywords_reaction_prompt = ""
-        for rule in global_config.keyword_reaction.rules:
-            if rule.enable:
-                if any(keyword in message_txt for keyword in rule.keywords):
-                    logger.info(f"检测到以下关键词之一：{rule.keywords}，触发反应：{rule.reaction}")
-                    keywords_reaction_prompt += f"{rule.reaction}，"
-                else:
-                    for pattern in rule.regex:
-                        if result := pattern.search(message_txt):
-                            reaction = rule.reaction
-                            for name, content in result.groupdict().items():
-                                reaction = reaction.replace(f"[{name}]", content)
-                            logger.info(f"匹配到以下正则表达式：{pattern}，触发反应：{reaction}")
-                            keywords_reaction_prompt += reaction + "，"
-                            break
+        try:
+            for rule in global_config.keyword_reaction.rules:
+                if rule.enable:
+                    if any(keyword in message_txt for keyword in rule.keywords):
+                        logger.info(f"检测到以下关键词之一：{rule.keywords}，触发反应：{rule.reaction}")
+                        keywords_reaction_prompt += f"{rule.reaction}，"
+                    else:
+                        for pattern in rule.regex:
+                            if result := pattern.search(message_txt):
+                                reaction = rule.reaction
+                                for name, content in result.groupdict().items():
+                                    reaction = reaction.replace(f"[{name}]", content)
+                                logger.info(f"匹配到以下正则表达式：{pattern}，触发反应：{reaction}")
+                                keywords_reaction_prompt += reaction + "，"
+                                break
+        except Exception as e:
+            logger.warning(f"关键词检测与反应时发生异常，可能是配置文件有误，跳过关键词匹配: {str(e)}")
 
         # 中文高手(新加的好玩功能)
         prompt_ger = ""
diff --git a/src/config/official_configs.py b/src/config/official_configs.py
index af729db3..1a1469fe 100644
--- a/src/config/official_configs.py
+++ b/src/config/official_configs.py
@@ -143,9 +143,15 @@ class FocusChatConfig(ConfigBase):
 
     think_interval: float = 1
     """思考间隔（秒）"""
-    
+
     consecutive_replies: float = 1
     """连续回复能力，值越高，麦麦连续回复的概率越高"""
+    
+    parallel_processing: bool = False
+    """是否允许处理器阶段和回忆阶段并行执行"""
+    
+    processor_max_time: int = 25
+    """处理器最大时间，单位秒，如果超过这个时间，处理器会自动停止"""
 
 
 @dataclass
@@ -160,6 +166,11 @@ class FocusChatProcessorConfig(ConfigBase):
 
     working_memory_processor: bool = True
     """是否启用工作记忆处理器"""
+    
+    lite_chat_mind_processor: bool = False
+    """是否启用轻量级聊天思维处理器，可以节省token消耗和时间"""
+
+
 
 
 @dataclass
diff --git a/src/individuality/expression_style.py b/src/individuality/expression_style.py
index f4eed60b..cb3778da 100644
--- a/src/individuality/expression_style.py
+++ b/src/individuality/expression_style.py
@@ -14,13 +14,13 @@ def init_prompt() -> None:
     personality_expression_prompt = """
 {personality}
 
-请从以上人设中总结出这个角色可能的语言风格
+请从以上人设中总结出这个角色可能的语言风格，你必须严格根据人设引申，不要输出例子
 思考回复的特殊内容和情感
 思考有没有特殊的梗，一并总结成语言风格
 总结成如下格式的规律，总结的内容要详细，但具有概括性：
 当"xxx"时，可以"xxx", xxx不超过10个字
 
-例如：
+例如（不要输出例子）：
 当"表示十分惊叹"时，使用"我嘞个xxxx"
 当"表示讽刺的赞同，不想讲道理"时，使用"对对对"
 当"想说明某个观点，但懒得明说"，使用"懂的都懂"
@@ -34,13 +34,12 @@ class PersonalityExpression:
     def __init__(self):
         self.express_learn_model: LLMRequest = LLMRequest(
             model=global_config.model.focus_expressor,
-            temperature=0.1,
-            max_tokens=256,
+            max_tokens=512,
             request_type="expressor.learner",
         )
         self.meta_file_path = os.path.join("data", "expression", "personality", "expression_style_meta.json")
         self.expressions_file_path = os.path.join("data", "expression", "personality", "expressions.json")
-        self.max_calculations = 5
+        self.max_calculations = 10
 
     def _read_meta_data(self):
         if os.path.exists(self.meta_file_path):
diff --git a/src/llm_models/utils_model.py b/src/llm_models/utils_model.py
index 712d51d8..3df45460 100644
--- a/src/llm_models/utils_model.py
+++ b/src/llm_models/utils_model.py
@@ -753,8 +753,13 @@ class LLMRequest:
 
         response = await self._execute_request(endpoint="/chat/completions", payload=data, prompt=prompt)
         # 原样返回响应，不做处理
-
-        return response
+        
+        if len(response) == 3:
+            content, reasoning_content, tool_calls = response
+            return content, (reasoning_content, self.model_name, tool_calls)
+        else:
+            content, reasoning_content = response
+            return content, (reasoning_content, self.model_name)
 
     async def generate_response_tool_async(self, prompt: str, tools: list, **kwargs) -> tuple[str, str, list]:
         """异步方式根据输入的提示生成模型的响应"""
diff --git a/src/plugins.md b/src/plugins.md
deleted file mode 100644
index 71ca741a..00000000
--- a/src/plugins.md
+++ /dev/null
@@ -1,101 +0,0 @@
-# 如何编写MaiBot插件
-
-## 基本步骤
-
-1. 在`src/plugins/你的插件名/actions/`目录下创建插件文件
-2. 继承`PluginAction`基类
-3. 实现`process`方法
-
-## 插件结构示例
-
-```python
-from src.common.logger_manager import get_logger
-from src.chat.focus_chat.planners.actions.plugin_action import PluginAction, register_action
-from typing import Tuple
-
-logger = get_logger("your_action_name")
-
-@register_action
-class YourAction(PluginAction):
-    """你的动作描述"""
-
-    action_name = "your_action_name"  # 动作名称，必须唯一
-    action_description = "这个动作的详细描述，会展示给用户"
-    action_parameters = {
-        "param1": "参数1的说明（可选）",
-        "param2": "参数2的说明（可选）"
-    }
-    action_require = [
-        "使用场景1",
-        "使用场景2"
-    ]
-    default = False  # 是否默认启用
-
-    async def process(self) -> Tuple[bool, str]:
-        """插件核心逻辑"""
-        # 你的代码逻辑...
-        return True, "执行结果"
-```
-
-## 可用的API方法
-
-插件可以使用`PluginAction`基类提供的以下API：
-
-### 1. 发送消息
-
-```python
-await self.send_message("要发送的文本", target="可选的回复目标")
-```
-
-### 2. 获取聊天类型
-
-```python
-chat_type = self.get_chat_type()  # 返回 "group" 或 "private" 或 "unknown"
-```
-
-### 3. 获取最近消息
-
-```python
-messages = self.get_recent_messages(count=5)  # 获取最近5条消息
-# 返回格式: [{"sender": "发送者", "content": "内容", "timestamp": 时间戳}, ...]
-```
-
-### 4. 获取动作参数
-
-```python
-param_value = self.action_data.get("param_name", "默认值")
-```
-
-### 5. 日志记录
-
-```python
-logger.info(f"{self.log_prefix} 你的日志信息")
-logger.warning("警告信息")
-logger.error("错误信息")
-```
-
-## 返回值说明
-
-`process`方法必须返回一个元组，包含两个元素：
-- 第一个元素(bool): 表示动作是否执行成功
-- 第二个元素(str): 执行结果的文本描述
-
-```python
-return True, "执行成功的消息"
-# 或
-return False, "执行失败的原因"
-```
-
-## 最佳实践
-
-1. 使用`action_parameters`清晰定义你的动作需要的参数
-2. 使用`action_require`描述何时应该使用你的动作
-3. 使用`action_description`准确描述你的动作功能
-4. 使用`logger`记录重要信息，方便调试
-5. 避免操作底层系统，尽量使用`PluginAction`提供的API
-
-## 注册与加载
-
-插件会在系统启动时自动加载，只要放在正确的目录并添加了`@register_action`装饰器。
-
-若设置`default = True`，插件会自动添加到默认动作集；否则需要在系统中手动启用。
diff --git a/src/plugins/test_plugin/actions/mute_action.py b/src/plugins/test_plugin/actions/mute_action.py
index 21a8e057..5bae71e0 100644
--- a/src/plugins/test_plugin/actions/mute_action.py
+++ b/src/plugins/test_plugin/actions/mute_action.py
@@ -23,7 +23,7 @@ class MuteAction(PluginAction):
         "当有人戳你两次以上时，防止刷屏，禁言他，必须牢记",
         "当你想回避某个话题时使用",
     ]
-    default = True  # 默认动作，是否手动添加到使用集
+    default = False  # 默认动作，是否手动添加到使用集
     associated_types = ["command", "text"]
     # associated_types = ["text"]
 
diff --git a/template/bot_config_template.toml b/template/bot_config_template.toml
index 95d329cd..439a6e12 100644
--- a/template/bot_config_template.toml
+++ b/template/bot_config_template.toml
@@ -41,7 +41,7 @@ identity_detail = [
 [expression]
 # 表达方式
 expression_style = "描述麦麦说话的表达风格，表达习惯，例如：(回复尽量简短一些。可以参考贴吧，知乎和微博的回复风格，回复不要浮夸，不要用夸张修辞，平淡一些。不要有额外的符号，尽量简单简短)"
-enable_expression_learning = true # 是否启用表达学习，麦麦会学习人类说话风格
+enable_expression_learning = false # 是否启用表达学习，麦麦会学习人类说话风格
 learning_interval = 600 # 学习间隔 单位秒
 
 [relationship]
@@ -94,8 +94,11 @@ talk_frequency_down_groups = []  #降低回复频率的群号码
 think_interval = 3 # 思考间隔 单位秒，可以有效减少消耗
 consecutive_replies = 1 # 连续回复能力，值越高，麦麦连续回复的概率越高
 
+parallel_processing = true # 是否并行处理回忆和处理器阶段，可以节省时间
 
-observation_context_size = 16 # 观察到的最长上下文大小,建议15，太短太长都会导致脑袋尖尖
+processor_max_time = 25 # 处理器最大时间，单位秒，如果超过这个时间，处理器会自动停止
+
+observation_context_size = 16 # 观察到的最长上下文大小
 compressed_length = 8 # 不能大于observation_context_size,心流上下文压缩的最短压缩长度，超过心流观察到的上下文长度，会压缩，最短压缩长度为5
 compress_length_limit = 4 #最多压缩份数，超过该数值的压缩上下文会被删除