diff --git a/src/config/config.py b/src/config/config.py
index ebfc444c1..28de20538 100644
--- a/src/config/config.py
+++ b/src/config/config.py
@@ -234,7 +234,7 @@ class BotConfig:
     forget_memory_interval: int = 600  # 记忆遗忘间隔（秒）
     memory_forget_time: int = 24  # 记忆遗忘时间（小时）
     memory_forget_percentage: float = 0.01  # 记忆遗忘比例
-    
+
     consolidate_memory_interval: int = 1000  # 记忆整合间隔（秒）
     consolidation_similarity_threshold: float = 0.7  # 相似度阈值
     consolidate_memory_percentage: float = 0.01  # 检查节点比例
diff --git a/src/main.py b/src/main.py
index 047e075f4..c0e743d66 100644
--- a/src/main.py
+++ b/src/main.py
@@ -146,7 +146,7 @@ class MainSystem:
             print("\033[1;32m[记忆遗忘]\033[0m 开始遗忘记忆...")
             await HippocampusManager.get_instance().forget_memory(percentage=global_config.memory_forget_percentage)
             print("\033[1;32m[记忆遗忘]\033[0m 记忆遗忘完成")
-            
+
     @staticmethod
     async def consolidate_memory_task():
         """记忆整合任务"""
diff --git a/src/plugins/PFC/action_planner.py b/src/plugins/PFC/action_planner.py
index 3765a7d6c..8d2c7ea90 100644
--- a/src/plugins/PFC/action_planner.py
+++ b/src/plugins/PFC/action_planner.py
@@ -93,8 +93,7 @@ class ActionPlanner:
             max_tokens=1500,
             request_type="action_planning",
         )
-        self.personality_info = Individuality.get_instance().get_prompt(type="personality", x_person=2, level=3)
-        self.identity_detail_info = Individuality.get_instance().get_prompt(type="identity", x_person=2, level=2)
+        self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
         self.name = global_config.BOT_NICKNAME
         self.private_name = private_name
         self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
@@ -244,21 +243,7 @@ class ActionPlanner:
             chat_history_text = "处理聊天记录时出错。\n"
 
         # 构建 Persona 文本 (persona_text)
-        # (这部分逻辑不变)
-        identity_details_only = self.identity_detail_info
-        identity_addon = ""
-        if isinstance(identity_details_only, str):
-            pronouns = ["你", "我", "他"]
-            for p in pronouns:
-                if identity_details_only.startswith(p):
-                    identity_details_only = identity_details_only[len(p) :]
-                    break
-            if identity_details_only.endswith("。"):
-                identity_details_only = identity_details_only[:-1]
-            cleaned_details = identity_details_only.strip(",， ")
-            if cleaned_details:
-                identity_addon = f"并且{cleaned_details}"
-        persona_text = f"你的名字是{self.name}，{self.personality_info}{identity_addon}。"
+        persona_text = f"你的名字是{self.name}，{self.personality_info}。"
 
         # 构建行动历史和上一次行动结果 (action_history_summary, last_action_context)
         # (这部分逻辑不变)
diff --git a/src/plugins/PFC/conversation.py b/src/plugins/PFC/conversation.py
index 37966a76e..6a8636e18 100644
--- a/src/plugins/PFC/conversation.py
+++ b/src/plugins/PFC/conversation.py
@@ -368,6 +368,15 @@ class Conversation:
                 self.conversation_info.last_successful_reply_action = "send_new_message"
                 action_successful = True  # 标记动作成功
 
+            elif need_replan:
+                # 打回动作决策
+                logger.warning(
+                    f"[私聊][{self.private_name}]经过 {reply_attempt_count} 次尝试，追问回复决定打回动作决策。打回原因: {check_reason}"
+                )
+                conversation_info.done_action[action_index].update(
+                    {"status": "recall", "final_reason": f"追问尝试{reply_attempt_count}次后打回: {check_reason}"}
+                )
+
             else:
                 # 追问失败
                 logger.warning(
@@ -463,6 +472,15 @@ class Conversation:
                 self.conversation_info.last_successful_reply_action = "direct_reply"
                 action_successful = True  # 标记动作成功
 
+            elif need_replan:
+                # 打回动作决策
+                logger.warning(
+                    f"[私聊][{self.private_name}]经过 {reply_attempt_count} 次尝试，首次回复决定打回动作决策。打回原因: {check_reason}"
+                )
+                conversation_info.done_action[action_index].update(
+                    {"status": "recall", "final_reason": f"首次回复尝试{reply_attempt_count}次后打回: {check_reason}"}
+                )
+
             else:
                 # 首次回复失败
                 logger.warning(
diff --git a/src/plugins/PFC/pfc.py b/src/plugins/PFC/pfc.py
index 32755c29b..d6f4c5192 100644
--- a/src/plugins/PFC/pfc.py
+++ b/src/plugins/PFC/pfc.py
@@ -23,8 +23,7 @@ class GoalAnalyzer:
             model=global_config.llm_normal, temperature=0.7, max_tokens=1000, request_type="conversation_goal"
         )
 
-        self.personality_info = Individuality.get_instance().get_prompt(type="personality", x_person=2, level=3)
-        self.identity_detail_info = Individuality.get_instance().get_prompt(type="identity", x_person=2, level=2)
+        self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
         self.name = global_config.BOT_NICKNAME
         self.nick_name = global_config.BOT_ALIAS_NAMES
         self.private_name = private_name
@@ -79,21 +78,7 @@ class GoalAnalyzer:
 
             # await observation_info.clear_unprocessed_messages()
 
-        identity_details_only = self.identity_detail_info
-        identity_addon = ""
-        if isinstance(identity_details_only, str):
-            pronouns = ["你", "我", "他"]
-            for p in pronouns:
-                if identity_details_only.startswith(p):
-                    identity_details_only = identity_details_only[len(p) :]
-                    break
-            if identity_details_only.endswith("。"):
-                identity_details_only = identity_details_only[:-1]
-            cleaned_details = identity_details_only.strip(",， ")
-            if cleaned_details:
-                identity_addon = f"并且{cleaned_details}"
-
-        persona_text = f"你的名字是{self.name}，{self.personality_info}{identity_addon}。"
+        persona_text = f"你的名字是{self.name}，{self.personality_info}。"
         # 构建action历史文本
         action_history_list = conversation_info.done_action
         action_history_text = "你之前做的事情是："
@@ -241,21 +226,8 @@ class GoalAnalyzer:
             timestamp_mode="relative",
             read_mark=0.0,
         )
-        identity_details_only = self.identity_detail_info
-        identity_addon = ""
-        if isinstance(identity_details_only, str):
-            pronouns = ["你", "我", "他"]
-            for p in pronouns:
-                if identity_details_only.startswith(p):
-                    identity_details_only = identity_details_only[len(p) :]
-                    break
-            if identity_details_only.endswith("。"):
-                identity_details_only = identity_details_only[:-1]
-            cleaned_details = identity_details_only.strip(",， ")
-            if cleaned_details:
-                identity_addon = f"并且{cleaned_details}"
 
-        persona_text = f"你的名字是{self.name}，{self.personality_info}{identity_addon}。"
+        persona_text = f"你的名字是{self.name}，{self.personality_info}。"
         # ===> Persona 文本构建结束 <===
 
         # --- 修改 Prompt 字符串，使用 persona_text ---
diff --git a/src/plugins/PFC/reply_checker.py b/src/plugins/PFC/reply_checker.py
index 178503259..180888956 100644
--- a/src/plugins/PFC/reply_checker.py
+++ b/src/plugins/PFC/reply_checker.py
@@ -55,9 +55,9 @@ class ReplyChecker:
                     )
                     return (
                         False,
-                        "回复内容与你上一条发言完全相同，请修改，可以选择深入话题或寻找其它话题或等待",
-                        False,
-                    )  # 不合适，无需重新规划
+                        "被逻辑检查拒绝：回复内容与你上一条发言完全相同，可以选择深入话题或寻找其它话题或等待",
+                        True,
+                    )  # 不合适，需要返回至决策层
                 # 2. 相似度检查 (如果精确匹配未通过)
                 import difflib  # 导入 difflib 库
 
@@ -73,8 +73,8 @@ class ReplyChecker:
                     )
                     return (
                         False,
-                        f"拒绝发送：回复内容与你上一条发言高度相似 (相似度 {similarity_ratio:.2f})，请修改，可以选择深入话题或寻找其它话题或等待。",
-                        False,
+                        f"被逻辑检查拒绝：回复内容与你上一条发言高度相似 (相似度 {similarity_ratio:.2f})，可以选择深入话题或寻找其它话题或等待。",
+                        True,
                     )
 
         except Exception as e:
@@ -83,37 +83,37 @@ class ReplyChecker:
             logger.error(f"[私聊][{self.private_name}]检查回复时出错: 类型={type(e)}, 值={e}")
             logger.error(f"[私聊][{self.private_name}]{traceback.format_exc()}")  # 打印详细的回溯信息
 
-        prompt = f"""请检查以下回复或消息是否合适：
+        prompt = f"""你是一个聊天逻辑检查器，请检查以下回复或消息是否合适：
 
 当前对话目标：{goal}
 最新的对话记录：
 {chat_history_text}
 
-待检查的回复：
+待检查的消息：
 {reply}
 
 请结合聊天记录检查以下几点：
-1. 回复是否依然符合当前对话目标和实现方式
-2. 回复是否与最新的对话记录保持一致性
-3. 回复是否重复发言，或重复表达同质内容（尤其是只是换一种方式表达了相同的含义）
-4. 回复是否包含违规内容（例如血腥暴力，政治敏感等）
-5. 回复是否以你的角度发言,不要把"你"说的话当做对方说的话，这是你自己说的话（不要自己回复自己的消息）
-6. 回复是否通俗易懂
-7. 回复是否有些多余，例如在对方没有回复的情况下，依然连续多次“消息轰炸”（尤其是已经连续发送3条信息的情况，这很可能不合理，需要着重判断）
-8. 回复是否使用了完全没必要的修辞
-9. 回复是否逻辑通顺
-10. 回复是否太过冗长了（通常私聊的每条消息长度在20字以内，除非特殊情况）
-11. 在连续多次发送消息的情况下，当前回复是否衔接自然，会不会显得奇怪（例如连续两条消息中部分内容重叠）
+1. 这条消息是否依然符合当前对话目标和实现方式
+2. 这条消息是否与最新的对话记录保持一致性
+3. 是否存在重复发言，或重复表达同质内容（尤其是只是换一种方式表达了相同的含义）
+4. 这条消息是否包含违规内容（例如血腥暴力，政治敏感等）
+5. 这条消息是否以发送者的角度发言（不要让发送者自己回复自己的消息）
+6. 这条消息是否通俗易懂
+7. 这条消息是否有些多余，例如在对方没有回复的情况下，依然连续多次“消息轰炸”（尤其是已经连续发送3条信息的情况，这很可能不合理，需要着重判断）
+8. 这条消息是否使用了完全没必要的修辞
+9. 这条消息是否逻辑通顺
+10. 这条消息是否太过冗长了（通常私聊的每条消息长度在20字以内，除非特殊情况）
+11. 在连续多次发送消息的情况下，这条消息是否衔接自然，会不会显得奇怪（例如连续两条消息中部分内容重叠）
 
 请以JSON格式输出，包含以下字段：
 1. suitable: 是否合适 (true/false)
 2. reason: 原因说明
-3. need_replan: 是否需要重新规划对话目标 (true/false)，当发现当前对话目标不再适合时设为true
+3. need_replan: 是否需要重新决策 (true/false)，当你认为此时已经不适合发消息，需要规划其它行动时，设为true
 
 输出格式示例：
 {{
     "suitable": true,
-    "reason": "回复符合要求，内容得体",
+    "reason": "回复符合要求，虽然有可能略微偏离目标，但是整体内容流畅得体",
     "need_replan": false
 }}
 
diff --git a/src/plugins/PFC/reply_generator.py b/src/plugins/PFC/reply_generator.py
index dea42b045..0c257a938 100644
--- a/src/plugins/PFC/reply_generator.py
+++ b/src/plugins/PFC/reply_generator.py
@@ -68,8 +68,7 @@ class ReplyGenerator:
             max_tokens=300,
             request_type="reply_generation",
         )
-        self.personality_info = Individuality.get_instance().get_prompt(type="personality", x_person=2, level=3)
-        self.identity_detail_info = Individuality.get_instance().get_prompt(type="identity", x_person=2, level=2)
+        self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
         self.name = global_config.BOT_NICKNAME
         self.private_name = private_name
         self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
@@ -130,20 +129,7 @@ class ReplyGenerator:
             chat_history_text = "还没有聊天记录。"
 
         # 构建 Persona 文本 (persona_text)
-        identity_details_only = self.identity_detail_info
-        identity_addon = ""
-        if isinstance(identity_details_only, str):
-            pronouns = ["你", "我", "他"]
-            for p in pronouns:
-                if identity_details_only.startswith(p):
-                    identity_details_only = identity_details_only[len(p) :]
-                    break
-            if identity_details_only.endswith("。"):
-                identity_details_only = identity_details_only[:-1]
-            cleaned_details = identity_details_only.strip(",， ")
-            if cleaned_details:
-                identity_addon = f"并且{cleaned_details}"
-        persona_text = f"你的名字是{self.name}，{self.personality_info}{identity_addon}。"
+        persona_text = f"你的名字是{self.name}，{self.personality_info}。"
 
         # --- 选择 Prompt ---
         if action_type == "send_new_message":
diff --git a/src/plugins/emoji_system/emoji_manager.py b/src/plugins/emoji_system/emoji_manager.py
index 2055c5ef2..5baddb771 100644
--- a/src/plugins/emoji_system/emoji_manager.py
+++ b/src/plugins/emoji_system/emoji_manager.py
@@ -360,6 +360,7 @@ class EmojiManager:
                 return
 
             total_count = len(self.emoji_objects)
+            self.emoji_num = total_count
             removed_count = 0
             # 使用列表复制进行遍历，因为我们会在遍历过程中修改列表
             for emoji in self.emoji_objects[:]:
@@ -376,10 +377,22 @@ class EmojiManager:
                         removed_count += 1
                         continue
 
+                    if emoji.description == None:
+                        logger.warning(f"[检查] 表情包文件已被删除: {emoji.path}")
+                        # 执行表情包对象的删除方法
+                        await emoji.delete()
+                        # 从列表中移除该对象
+                        self.emoji_objects.remove(emoji)
+                        # 更新计数
+                        self.emoji_num -= 1
+                        removed_count += 1
+                        continue
+
                 except Exception as item_error:
                     logger.error(f"[错误] 处理表情包记录时出错: {str(item_error)}")
                     continue
 
+            await self.clean_unused_emojis(EMOJI_REGISTED_DIR, self.emoji_objects)
             # 输出清理结果
             if removed_count > 0:
                 logger.success(f"[清理] 已清理 {removed_count} 个失效的表情包记录")
@@ -749,7 +762,7 @@ class EmojiManager:
             await new_emoji.initialize_hash_format()
             emoji_base64 = image_path_to_base64(os.path.join(EMOJI_DIR, filename))
             description, emotions = await self.build_emoji_description(emoji_base64)
-            if description == "":
+            if description == "" or description == None:
                 return False
             new_emoji.description = description
             new_emoji.emotion = emotions
@@ -817,6 +830,26 @@ class EmojiManager:
 
         logger.success("[清理] 临时文件清理完成")
 
+    async def clean_unused_emojis(self, emoji_dir, emoji_objects):
+        """清理未使用的表情包文件
+        遍历指定文件夹中的所有文件，删除未在emoji_objects列表中的文件
+        """
+        # 获取所有表情包路径
+        emoji_paths = {emoji.path for emoji in emoji_objects}
+
+        # 遍历文件夹中的所有文件
+        for file_name in os.listdir(emoji_dir):
+            file_path = os.path.join(emoji_dir, file_name)
+
+            # 检查文件是否在表情包路径列表中
+            if file_path not in emoji_paths:
+                try:
+                    # 删除未在表情包列表中的文件
+                    os.remove(file_path)
+                    logger.info(f"[清理] 删除未使用的表情包文件: {file_path}")
+                except Exception as e:
+                    logger.error(f"[错误] 删除文件时出错: {str(e)}")
+
 
 # 创建全局单例
 emoji_manager = EmojiManager()
diff --git a/src/plugins/heartFC_chat/heartflow_prompt_builder.py b/src/plugins/heartFC_chat/heartflow_prompt_builder.py
index afc29f246..1c4458846 100644
--- a/src/plugins/heartFC_chat/heartflow_prompt_builder.py
+++ b/src/plugins/heartFC_chat/heartflow_prompt_builder.py
@@ -5,7 +5,7 @@ from ...individuality.individuality import Individuality
 from src.plugins.utils.prompt_builder import Prompt, global_prompt_manager
 from src.plugins.utils.chat_message_builder import build_readable_messages, get_raw_msg_before_timestamp_with_chat
 from src.plugins.person_info.relationship_manager import relationship_manager
-from src.plugins.chat.utils import get_embedding, parse_text_timestamps
+from src.plugins.chat.utils import get_embedding
 import time
 from typing import Union, Optional
 from ...common.database import db
diff --git a/src/plugins/memory_system/Hippocampus.py b/src/plugins/memory_system/Hippocampus.py
index 5cca0d074..e5aa096fa 100644
--- a/src/plugins/memory_system/Hippocampus.py
+++ b/src/plugins/memory_system/Hippocampus.py
@@ -1353,11 +1353,11 @@ class ParahippocampalGyrus:
             if not memory_items:
                 try:
                     self.memory_graph.G.remove_node(node)
-                    node_changes["removed"].append(f"{node}(空节点)") # 标记为空节点移除
+                    node_changes["removed"].append(f"{node}(空节点)")  # 标记为空节点移除
                     logger.debug(f"[遗忘] 移除了空的节点: {node}")
                 except nx.NetworkXError as e:
                     logger.warning(f"[遗忘] 移除空节点 {node} 时发生错误（可能已被移除）: {e}")
-                continue # 处理下一个节点
+                continue  # 处理下一个节点
 
             # --- 如果节点不为空，则执行原来的不活跃检查和随机移除逻辑 ---
             last_modified = node_data.get("last_modified", current_time)
@@ -1373,15 +1373,15 @@ class ParahippocampalGyrus:
                             memory_items.remove(removed_item)
 
                             # 条件3：检查移除后 memory_items 是否变空
-                            if memory_items: # 如果移除后列表不为空
+                            if memory_items:  # 如果移除后列表不为空
                                 # self.memory_graph.G.nodes[node]["memory_items"] = memory_items # 直接修改列表即可
-                                self.memory_graph.G.nodes[node]["last_modified"] = current_time # 更新修改时间
+                                self.memory_graph.G.nodes[node]["last_modified"] = current_time  # 更新修改时间
                                 node_changes["reduced"].append(f"{node} (数量: {current_count} -> {len(memory_items)})")
-                            else: # 如果移除后列表为空
+                            else:  # 如果移除后列表为空
                                 # 尝试移除节点，处理可能的错误
                                 try:
                                     self.memory_graph.G.remove_node(node)
-                                    node_changes["removed"].append(f"{node}(遗忘清空)") # 标记为遗忘清空
+                                    node_changes["removed"].append(f"{node}(遗忘清空)")  # 标记为遗忘清空
                                     logger.debug(f"[遗忘] 节点 {node} 因移除最后一项而被清空。")
                                 except nx.NetworkXError as e:
                                     logger.warning(f"[遗忘] 尝试移除节点 {node} 时发生错误（可能已被移除）：{e}")
@@ -1464,9 +1464,9 @@ class ParahippocampalGyrus:
             node_data = self.memory_graph.G.nodes[node]
             memory_items = node_data.get("memory_items", [])
             if not isinstance(memory_items, list) or len(memory_items) < 2:
-                continue # 双重检查，理论上不会进入
+                continue  # 双重检查，理论上不会进入
 
-            items_copy = list(memory_items) # 创建副本以安全迭代和修改
+            items_copy = list(memory_items)  # 创建副本以安全迭代和修改
 
             # 遍历所有记忆项组合
             for item1, item2 in combinations(items_copy, 2):
@@ -1495,21 +1495,24 @@ class ParahippocampalGyrus:
                     # 从原始列表中移除信息量较低的项
                     try:
                         memory_items.remove(item_to_remove)
-                        logger.info(f"[整合] 已合并节点 '{node}' 中的记忆，保留: '{item_to_keep[:60]}...', 移除: '{item_to_remove[:60]}...'" )
+                        logger.info(
+                            f"[整合] 已合并节点 '{node}' 中的记忆，保留: '{item_to_keep[:60]}...', 移除: '{item_to_remove[:60]}...'"
+                        )
                         merged_count += 1
                         nodes_modified.add(node)
-                        node_data['last_modified'] = current_timestamp # 更新修改时间
+                        node_data["last_modified"] = current_timestamp  # 更新修改时间
                         _merged_in_this_node = True
-                        break # 每个节点每次检查只合并一对
+                        break  # 每个节点每次检查只合并一对
                     except ValueError:
                         # 如果项已经被移除（例如，在之前的迭代中作为 item_to_keep），则跳过
-                        logger.warning(f"[整合] 尝试移除节点 '{node}' 中不存在的项 '{item_to_remove[:30]}...'，可能已被合并。")
+                        logger.warning(
+                            f"[整合] 尝试移除节点 '{node}' 中不存在的项 '{item_to_remove[:30]}...'，可能已被合并。"
+                        )
                         continue
-            # # 如果节点内发生了合并，更新节点数据 (这种方式不安全，会丢失其他属性)        
+            # # 如果节点内发生了合并，更新节点数据 (这种方式不安全，会丢失其他属性)
             # if merged_in_this_node:
             #      self.memory_graph.G.nodes[node]["memory_items"] = memory_items
 
-
         if merged_count > 0:
             logger.info(f"[整合] 共合并了 {merged_count} 对相似记忆项，分布在 {len(nodes_modified)} 个节点中。")
             sync_start = time.time()
@@ -1594,7 +1597,7 @@ class HippocampusManager:
         if not self._initialized:
             raise RuntimeError("HippocampusManager 尚未初始化，请先调用 initialize 方法")
         return await self._hippocampus.parahippocampal_gyrus.operation_forget_topic(percentage)
-    
+
     async def consolidate_memory(self):
         """整合记忆的公共接口"""
         if not self._initialized:
diff --git a/src/plugins/memory_system/memory_config.py b/src/plugins/memory_system/memory_config.py
index 8f7e1ffe7..b2fb72801 100644
--- a/src/plugins/memory_system/memory_config.py
+++ b/src/plugins/memory_system/memory_config.py
@@ -19,9 +19,9 @@ class MemoryConfig:
     memory_ban_words: List[str]  # 记忆过滤词列表
 
     # 新增：记忆整合相关配置
-    consolidation_similarity_threshold: float # 相似度阈值
-    consolidate_memory_percentage: float # 检查节点比例
-    consolidate_memory_interval: int # 记忆整合间隔
+    consolidation_similarity_threshold: float  # 相似度阈值
+    consolidate_memory_percentage: float  # 检查节点比例
+    consolidate_memory_interval: int  # 记忆整合间隔
 
     llm_topic_judge: str  # 话题判断模型
     llm_summary_by_topic: str  # 话题总结模型
@@ -31,7 +31,9 @@ class MemoryConfig:
         """从全局配置创建记忆系统配置"""
         # 使用 getattr 提供默认值，防止全局配置缺少这些项
         return cls(
-            memory_build_distribution=getattr(global_config, "memory_build_distribution", (24, 12, 0.5, 168, 72, 0.5)), # 添加默认值
+            memory_build_distribution=getattr(
+                global_config, "memory_build_distribution", (24, 12, 0.5, 168, 72, 0.5)
+            ),  # 添加默认值
             build_memory_sample_num=getattr(global_config, "build_memory_sample_num", 5),
             build_memory_sample_length=getattr(global_config, "build_memory_sample_length", 30),
             memory_compress_rate=getattr(global_config, "memory_compress_rate", 0.1),
@@ -41,6 +43,8 @@ class MemoryConfig:
             consolidation_similarity_threshold=getattr(global_config, "consolidation_similarity_threshold", 0.7),
             consolidate_memory_percentage=getattr(global_config, "consolidate_memory_percentage", 0.01),
             consolidate_memory_interval=getattr(global_config, "consolidate_memory_interval", 1000),
-            llm_topic_judge=getattr(global_config, "llm_topic_judge", "default_judge_model"), # 添加默认模型名
-            llm_summary_by_topic=getattr(global_config, "llm_summary_by_topic", "default_summary_model"), # 添加默认模型名
+            llm_topic_judge=getattr(global_config, "llm_topic_judge", "default_judge_model"),  # 添加默认模型名
+            llm_summary_by_topic=getattr(
+                global_config, "llm_summary_by_topic", "default_summary_model"
+            ),  # 添加默认模型名
         )
diff --git a/src/plugins/person_info/relationship_manager.py b/src/plugins/person_info/relationship_manager.py
index 7f3f51177..5110e2e6d 100644
--- a/src/plugins/person_info/relationship_manager.py
+++ b/src/plugins/person_info/relationship_manager.py
@@ -4,8 +4,8 @@ import math
 from bson.decimal128 import Decimal128
 from .person_info import person_info_manager
 import time
-import re
-import traceback
+# import re
+# import traceback
 
 
 logger = get_logger("relation")