diff --git a/api/app/core/memory/agent/langgraph_graph/write_graph.py b/api/app/core/memory/agent/langgraph_graph/write_graph.py
index 5101fa29..d0e8a45d 100644
--- a/api/app/core/memory/agent/langgraph_graph/write_graph.py
+++ b/api/app/core/memory/agent/langgraph_graph/write_graph.py
@@ -39,7 +39,6 @@ async def make_write_graph():
     graph = workflow.compile()
 
     yield graph
-
 async def long_term_storage(long_term_type:str="chunk",langchain_messages:list=[],memory_config:str='',end_user_id:str='',scope:int=6):
     from app.core.memory.agent.langgraph_graph.routing.write_router import memory_long_term_storage, window_dialogue,aggregate_judgment
     from app.core.memory.agent.langgraph_graph.tools.write_tool import chat_data_format
@@ -49,7 +48,7 @@ async def long_term_storage(long_term_type:str="chunk",langchain_messages:list=[
     db_session = next(get_db())
     config_service = MemoryConfigService(db_session)
     memory_config = config_service.load_memory_config(
-        config_id="08ed205c-0f05-49c3-8e0c-a580d28f5fd4",  # 改为整数
+        config_id=memory_config,  # 改为整数
         service_name="MemoryAgentService"
     )
     if long_term_type=='chunk':
@@ -63,7 +62,7 @@ async def long_term_storage(long_term_type:str="chunk",langchain_messages:list=[
         """方案三：聚合判断"""
         await aggregate_judgment(end_user_id, langchain_messages, memory_config)
 
-#
+
 # async def main():
 #     """主函数 - 运行工作流"""
 #     langchain_messages = [
@@ -80,14 +79,7 @@ async def long_term_storage(long_term_type:str="chunk",langchain_messages:list=[
 #     end_user_id = '837fee1b-04a2-48ee-94d7-211488908940'  # 组ID
 #     memory_config="08ed205c-0f05-49c3-8e0c-a580d28f5fd4"
 #     # await long_term_storage(long_term_type="chunk",langchain_messages=langchain_messages,memory_config=memory_config,end_user_id=end_user_id,scope=2)
-#     from app.core.memory.agent.utils.redis_tool import write_store
-#     result=write_store.get_session_by_userid(end_user_id)
-#     data=await format_parsing(result,"dict")
-#     chunk_data=data[:6]
-#
-#     long_time_data = write_store.find_user_recent_sessions(end_user_id, 240)
-#     long_=await messages_parse(long_time_data)
-#     print(long_)
+#     result=await long_term_storage(long_term_type="chunk",langchain_messages=langchain_messages,memory_config=memory_config,end_user_id=end_user_id,scope=2)
 #
 #
 # if __name__ == "__main__":
diff --git a/api/app/services/memory_reflection_service.py b/api/app/services/memory_reflection_service.py
index 3287366e..e025c1b3 100644
--- a/api/app/services/memory_reflection_service.py
+++ b/api/app/services/memory_reflection_service.py
@@ -286,7 +286,7 @@ class MemoryReflectionService:
                 # 检查是否需要执行反思
                 should_execute = False
                 hours_diff = 0
-                
+
                 if current_reflection_time is None:
                     # 首次执行反思
                     should_execute = True
@@ -298,11 +298,11 @@ class MemoryReflectionService:
                             reflection_time = datetime.fromisoformat(current_reflection_time)
                         else:
                             reflection_time = current_reflection_time
-                        
+
                         current_time = datetime.now()
                         time_diff = current_time - reflection_time
                         hours_diff = int(time_diff.total_seconds() / 3600)
-                        
+
                         # 检查是否达到反思周期
                         if hours_diff >= iteration_period:
                             should_execute = True
@@ -312,7 +312,7 @@ class MemoryReflectionService:
                     except (ValueError, TypeError) as e:
                         api_logger.warning(f"解析反思时间失败: {e}，将执行反思")
                         should_execute = True
-                
+
                 if should_execute:
                     api_logger.info(f"与上次的反思时间间隔为: {hours_diff} 小时")
                     # 3. 执行反思引擎
@@ -345,7 +345,7 @@ class MemoryReflectionService:
                         "next_reflection_in_hours": iteration_period - hours_diff
                     }
 
-            
+
         except Exception as e:
             config_id = config_data.get("config_id", "unknown")
             api_logger.error(f"启动反思失败，config_id: {config_id}, end_user_id: {end_user_id}, 错误: {str(e)}")
@@ -356,7 +356,7 @@ class MemoryReflectionService:
                 "end_user_id": end_user_id,
                 "config_data": config_data
             }
-    
+
     def _create_reflection_config_from_data(self, config_data: Dict[str, Any]) -> ReflectionConfig:
         """Create reflective configuration objects from configuration data"""
 
@@ -364,12 +364,12 @@ class MemoryReflectionService:
         if reflexion_range_value is None or reflexion_range_value == "":
             reflexion_range_value = "partial"
         reflexion_range = ReflectionRange(reflexion_range_value)
-        
+
         baseline_value = config_data.get("baseline")
         if baseline_value is None or baseline_value == "":
             baseline_value = "TIME"
         baseline = ReflectionBaseline(baseline_value)
-        
+
         # iteration_period =
         iteration_period = config_data.get("iteration_period", 24)
         if isinstance(iteration_period, str):
@@ -377,7 +377,6 @@ class MemoryReflectionService:
                 iteration_period = int(iteration_period)
             except (ValueError, TypeError):
                 iteration_period = 24  # 默认24小时
-        
         return ReflectionConfig(
             enabled=config_data.get("enable_self_reflexion", False),
             iteration_period=str(iteration_period),  # ReflectionConfig期望字符串