[feature] update the prompt and utils

config/demo_config_cn.yaml

@@ -143,6 +143,7 @@ worker:
   get_reflection_subject:
     class: memory.worker.summary.get_reflection_subject_worker
     generation_model: dashscope_generation
+    reflect_obs_cnt_threshold: 10
     generation_model_kwargs:
       top_k: 1
   update_insight:

config/demo_config_en.yaml

@@ -143,6 +143,7 @@ worker:
   get_reflection_subject:
     class: memory.worker.summary.get_reflection_subject_worker
     generation_model: dashscope_generation
+    reflect_obs_cnt_threshold: 10
     generation_model_kwargs:
       top_k: 1
   update_insight:

memory_scope/memory/worker/frontend/extract_time_worker.py

@@ -41,7 +41,7 @@ class ExtractTimeWorker(MemoryBaseWorker):
         # Prepare the prompt with necessary contextual details
         query_time_str = DatetimeHandler(dt=query_timestamp).string_format(self.prompt_handler.time_string_format)
         system_prompt = self.prompt_handler.extract_time_system
-        few_shot = self.prompt_handler.extract_time_few_shot.format(user_name=self.target_name)
+        few_shot = self.prompt_handler.extract_time_few_shot
         user_query = self.prompt_handler.extract_time_user_query.format(query=query, query_time_str=query_time_str)
         extract_time_message = prompt_to_msg(system_prompt=system_prompt, few_shot=few_shot, user_query=user_query)
         self.logger.info(f"extract_time_message={extract_time_message}")

memory_scope/memory/worker/frontend/print_memory_worker.py

@@ -7,6 +7,18 @@ from memory_scope.memory.worker.memory_base_worker import MemoryBaseWorker
 from memory_scope.scheme.memory_node import MemoryNode
 from memory_scope.utils.datetime_handler import DatetimeHandler
 
+PRINT_TEMPLATE = """
+The memories of {user_name} about {target_name}.
+
+{obs_content}
+
+
+{insight_content}
+
+
+{expired_content}
+"""
+
 
 class PrintMemoryWorker(MemoryBaseWorker):
 
@@ -44,15 +56,11 @@ class PrintMemoryWorker(MemoryBaseWorker):
         obs_content = "\n".join(obs_content_list)
         insight_content = "\n".join(insight_content_list)
         expired_content = "\n".join(expired_content_list)
-        result: str = f"""
-The memories of {self.user_name} about {self.target_name}.
-
-{obs_content}
-
-
-{insight_content}
-
-
-{expired_content}
-        """.strip()
+        result: str = PRINT_TEMPLATE.format(
+            user_name=self.user_name,
+            target_name=self.target_name,
+            obs_content=obs_content,
+            insight_content=insight_content,
+            expired_content=expired_content,
+        ).strip()
         self.set_context(RESULT, result)

memory_scope/memory/worker/summary/long_contra_repeat_worker.yaml

@@ -39,9 +39,9 @@ long_contra_repeat_few_shot:
     思考：第5句中陈伟业是{user_name}的领导的信息被前面序号中第3句的信息包含，但新增了陈伟业是银行分行行长的信息，故不是被完全包含。
     判断：<5> <无> <>
     思考：第6句中表达了{user_name}的水果偏好，喜欢吃西瓜，信息没有在前面序号句子中出现。
-    判断：<6> <无>
+    判断：<6> <无> <>
     思考：第7句也表达了{user_name}的水果偏好，喜欢吃桃子，和前面序号中的第6句不冲突，喜好可以同时存在。
-    判断：<7> <无>
+    判断：<7> <无> <>
     
     示例2
     句子：
@@ -87,9 +87,9 @@ long_contra_repeat_few_shot:
     Thought: The information that Charles is {user_name}'s supervisor in the fifth sentence is contained within the information of the third sentence, but the new information that Charles is the branch manager of a bank is not, so it is not contained.
     Judgment: <5> <None> <>
     Thought: Sentence 6 expresses {user_name}'s fruit preference, liking to eat watermelon, which is information not present in any preceding sentences.
-    Judgment: <6> <None>
+    Judgment: <6> <None> <>
     Thought: Sentence 7 also expresses {user_name}'s fruit preference, liking to eat apples; it does not conflict with sentence 6, and both preferences can coexist.
-    Judgment: <7> <None>
+    Judgment: <7> <None> <>
     
     Example 2
     Sentences:

memory_scope/memory/worker/summary/update_insight_worker.py

@@ -166,14 +166,14 @@ class UpdateInsightWorker(MemoryBaseWorker):
 
         # Process active insight nodes with corresponding not updated nodes
         for node in insight_nodes:
-            if node.action_status == ActionStatusEnum.NONE.value:
-                self.submit_thread_task(fn=self.filter_obs_nodes,
-                                        insight_node=node,
-                                        obs_nodes=not_updated_nodes)
-            else:
+            if node.action_status == ActionStatusEnum.NEW.value:
                 self.submit_thread_task(fn=self.filter_obs_nodes,
                                         insight_node=node,
                                         obs_nodes=not_reflected_nodes)
+            else:
+                self.submit_thread_task(fn=self.filter_obs_nodes,
+                                        insight_node=node,
+                                        obs_nodes=not_updated_nodes)
 
         # select top n
         result_list = []

memory_scope/memory/worker/write/contra_repeat_worker.py

@@ -63,8 +63,7 @@ class ContraRepeatWorker(MemoryBaseWorker):
         system_prompt = self.prompt_handler.contra_repeat_system.format(num_obs=len(user_query_list),
                                                                         user_name=self.target_name)
         few_shot = self.prompt_handler.contra_repeat_few_shot.format(user_name=self.target_name)
-        user_query = self.prompt_handler.contra_repeat_user_query.format(user_query="\n".join(user_query_list),
-                                                                         user_name=self.target_name)
+        user_query = self.prompt_handler.contra_repeat_user_query.format(user_query="\n".join(user_query_list))
         contra_repeat_message = prompt_to_msg(system_prompt=system_prompt, few_shot=few_shot, user_query=user_query)
         self.logger.info(f"contra_repeat_message={contra_repeat_message}")
 

memory_scope/memory/worker/write/info_filter_worker.py

@@ -63,8 +63,7 @@ class InfoFilterWorker(MemoryBaseWorker):
         system_prompt = self.prompt_handler.info_filter_system.format(batch_size=len(info_messages),
                                                                       user_name=self.target_name)
         few_shot = self.prompt_handler.info_filter_few_shot.format(user_name=self.target_name)
-        user_query = self.prompt_handler.info_filter_user_query.format(user_query="\n".join(user_query_list),
-                                                                       user_name=self.target_name)
+        user_query = self.prompt_handler.info_filter_user_query.format(user_query="\n".join(user_query_list))
         info_filter_message = prompt_to_msg(system_prompt=system_prompt, few_shot=few_shot, user_query=user_query)
         self.logger.info(f"info_filter_message={info_filter_message}")
 

memory_scope/utils/tool_functions.py

@@ -87,7 +87,7 @@ def init_instance_by_config(config: dict,
     return getattr(module, cls_name)(**config_copy)
 
 
-def prompt_to_msg(system_prompt: str, few_shot: str, user_query: str) -> List[Message]:
+def prompt_to_msg(system_prompt: str, few_shot: str, user_query: str, concat_system_prompt: bool = True) -> List[Message]:
     """
     Converts input strings into a structured list of message objects suitable for AI interactions.
 
@@ -95,14 +95,28 @@ def prompt_to_msg(system_prompt: str, few_shot: str, user_query: str) -> List[Me
         system_prompt (str): The system-level instruction or context.
         few_shot (str): An example or demonstration input, often used for illustrating expected behavior.
         user_query (str): The actual user query or prompt to be processed.
+        concat_system_prompt(bool): Concat system prompt again or not in the user message.
+            A simple method to improve the effectiveness for some LLMs.
 
     Returns:
         List[Message]: A list of Message objects, each representing a part of the conversation setup.
     """
+    if concat_system_prompt:
+        user_message = Message(
+            role=MessageRoleEnum.USER.value,
+            content="\n".join(
+                [x.strip() for x in [few_shot, system_prompt, user_query]]
+            ),
+        )
+    else:
+        user_message = Message(
+            role=MessageRoleEnum.USER.value,
+            content="\n".join([x.strip() for x in [few_shot, user_query]]),
+        )
+
     return [
         Message(role=MessageRoleEnum.SYSTEM.value, content=system_prompt.strip()),  # System message
-        Message(role=MessageRoleEnum.USER.value,
-                content="\n".join([x.strip() for x in [few_shot, system_prompt, user_query]]))
+        user_message
         # User message combining few shot, system prompt, and user query
     ]