fix: update long term memory extraction to use apply_async with countdown

--bug=1069038@tapd-62980211 --user=刘瑞斌 【长期记忆】开启后默认是10次生成记忆，对话2次后，生成记忆轮次调整为5次，但对话到第10次才生成记忆 https://www.tapd.cn/62980211/s/1916875

Author: liuruibin

apps/application/chat_pipeline/step/chat_step/impl/base_chat_step.py

@@ -214,8 +214,13 @@ def execute(self, message_list: List[BaseMessage],
 
     def get_details(self, manage, **kwargs):
         # 提取长期记忆
-        extract_long_term_memory.delay(
-            manage.context.get('workspace_id'), manage.context.get('application_id'), manage.context.get('chat_user_id')
+        extract_long_term_memory.apply_async(
+            args=(
+                manage.context.get('workspace_id'),
+                manage.context.get('application_id'),
+                manage.context.get('chat_user_id'),
+            ),
+            countdown=1,
         )
         return {
             'status': self.status,

apps/application/flow/i_step_node.py

@@ -103,8 +103,13 @@ def handler(self, workflow):
                 application_public_access_client.save()
         self.chat_info = None
 
-        extract_long_term_memory.delay(
-            workflow_body.get('workspace_id'), workflow_body.get('application_id'), workflow_body.get('chat_user_id')
+        extract_long_term_memory.apply_async(
+            args=(
+                workflow_body.context.get('workspace_id'),
+                workflow_body.context.get('application_id'),
+                workflow_body.context.get('chat_user_id'),
+            ),
+            countdown=1,
         )
 
 

apps/application/long_term_memory/__init__.py

@@ -525,6 +525,7 @@ def extract_long_term_memory(workspace_id, application_id, chat_user_id):
         chat__application_id=application_id,
         chat__chat_user_id=chat_user_id,
     ).count()
+    maxkb_logger.info(f'extract_long_term_memory: current_rounds={current_rounds}, rounds={rounds}')
     if current_rounds % rounds != 0:
         return