diff --git a/doc/agent memory.md b/doc/agent memory.md
new file mode 100644
index 0000000..407187f
--- /dev/null
+++ b/doc/agent memory.md	
@@ -0,0 +1,34 @@
+# agent memory
+
+## memory的基本形式
+memory的基本形式上是 topic+内容 
+topic用一个有意义的路径表示 /xxx/xxx/xxx （有点类似脑图的逻辑，可以通过逐级展开遍历浏览所有的memory）
+同一个memory可以被多个路径指向
+内容则是一个json文件
+
+
+## Agent 使用memory的
+1. 根据当前会话的主题，尝试在known_info中加载必要的memory
+2. 提供memory的 list/查询 函数， 允许agent在必要的时候 list / 查询memory
+该使用逻辑的本质和kb查询逻辑很像
+
+## Agent 更新/创建memory
+1. 在任何llm process的过程中，agent都可以用写文件的形式创建memory
+2. 更新memory通常是一个专门的 self-think过程，agent此时会用某种模式整理自己所有的logs和memory,并对memory进行更新、创建、删除
+该更新逻辑与Agent 与KB的Self-learning逻辑很像。但根据log->summary的过程基本上是 self-think独有的
+
+## 实现逻辑
+基本思路：
+1. 核心API是一组通用的文件操作API（有些场景可以是只读的） + 一组特化的对象查询API
+    路径->Object，Object中包含ObjectId等信息
+    ObjectId->Object
+    Object一定是一个json,里面包含可以打开原始文件的路径(fileId)
+2. 通过一组文件系统描述来引导Agent操作特定文件
+3. 通过一组搜索API来引导Agent操作特定文件
+
+对象查询API，基本思路是
+
+ObjectId->Object
+
+
+
diff --git a/doc/package_manager.md b/doc/package_manager.md
index 33d9ce7..f7d1273 100644
--- a/doc/package_manager.md
+++ b/doc/package_manager.md
@@ -18,6 +18,7 @@ Let's start by introducing the two important processes.
 Note that the dependency check during installation allows for the missing packages to be installed into the current environment.
 
 # Some Basic Concepts
+
 - ***env***:A target environment consisting of a series of configuration files, where packages can be loaded/installed.
 - ***pkg***:A Package(pkg) is either a folder or a file that serves the same purpose as a folder (such as zip, iso, etc.).
 - ***pkg_name***:A unique string used to label a package. It's usually a readable package name, but can also include the version number or even the ContentId.
diff --git a/doc/promps/readme.md b/doc/promps/readme.md
new file mode 100644
index 0000000..e0cc8d0
--- /dev/null
+++ b/doc/promps/readme.md
@@ -0,0 +1,15 @@
+# prompts
+
+四个循环
+1. 立刻处理消息+深度思考整理循环
+Process <-> Self Thinking
+
+2. 任务迭代完整循环致力于完成所有的待完成任务（不一定是成功完成）
+Task -> Todo -> Check
+
+3. 知识库整理
+New Knowledge -> Self-Learning 
+使用知识库的时机？是否有quick process和deep thing的区别？
+
+4. Self-Improve
+根据四元组：输入，提示词，输出，上级意见 （可选），对提示词进行改进
\ No newline at end of file
diff --git a/rootfs/agents/Jarvis/agent.toml b/rootfs/agents/Jarvis/agent.toml
index 419eea7..132eaab 100644
--- a/rootfs/agents/Jarvis/agent.toml
+++ b/rootfs/agents/Jarvis/agent.toml
@@ -12,6 +12,28 @@ Your name is Jarvis, the super personal assistant to the Principal. Help the Pri
 Only clearly specifying the task you completed can be completed independently.
 """
 
+kb_query_desc = """
+$ introduce (have default config)
+$ dir descriptions
+$     dir1
+$     dir2
+$     dir3
+$ support actions(if enable)
+$ support funcitons(if enable)
+
+现有信息以知识图谱的形式保存在存储系统中。
+1. 介绍知识图谱的结构 
+2. 不同部分的规则说明（可选）创建知识图谱的指导思路（目前不允许AI自创结构）
+
+
+# read (function)
+access_knowledge_graph($op_name,$params) 
+
+# write (action)
+update_knowledge_graph($op_name,$params) 
+
+"""
+
 [behavior.on_message]
 type="AgentMessageProcess"
 mutil_model="gpt-4-vision-preview"
@@ -45,8 +67,8 @@ known_info_tips = """
 
 tools_tips = """
 """
-llm_context.actions.enable = ["agent.workspace.create_task","agent.workspace.cancel_task"]
-llm_context.functions.enable = ["agent.workspace.list_task"]
+llm_context.actions.enable = ["agent.workspace.create_task","agent.workspace.cancel_task","knowledge_base.knowledge_graph_update"]
+llm_context.functions.enable = ["agent.workspace.list_task","knowledge_base.knowledge_graph_read"]
 
 
 [behavior.triage_tasks]
diff --git a/src/aios/__init__.py b/src/aios/__init__.py
index 3d37b64..18f7823 100644
--- a/src/aios/__init__.py
+++ b/src/aios/__init__.py
@@ -29,6 +29,7 @@ from .ai_functions.image_2_text_function import Image2TextFunction
 from .environment.workspace_env import WorkspaceEnvironment
 
 from .storage.storage import ResourceLocation,AIStorage,UserConfig,UserConfigItem
+from .storage.objfs import ObjFS
 
 from .net import *
 from .knowledge import *
@@ -36,4 +37,4 @@ from .package_manager import *
 from .utils import *
 
 
-AIOS_Version = "0.5.2, build 2023-12-15"
+AIOS_Version = "0.5.2, build 2024-3-31"
diff --git a/src/aios/agent/agent_memory.py b/src/aios/agent/agent_memory.py
index c660a76..a3307e2 100644
--- a/src/aios/agent/agent_memory.py
+++ b/src/aios/agent/agent_memory.py
@@ -9,10 +9,11 @@ import sqlite3
 import aiofiles
 
 from ..storage.storage import AIStorage
+from ..knowledge.knowledge_base import BaseKnowledgeGraph,ObjFSKnowledgeGrpah
 from ..frame.compute_kernel import ComputeKernel
 from ..frame.contact_manager import ContactManager
 from ..frame.contact import Contact
-from ..proto.ai_function import ParameterDefine, SimpleAIAction, SimpleAIFunction
+from ..proto.ai_function import ParameterDefine, SimpleAIFunction
 from ..proto.agent_msg import AgentMsg, AgentMsgType
 from ..proto.agent_task import AgentWorkLog
 
@@ -35,20 +36,34 @@ logger = logging.getLogger(__name__)
 
 
 class AgentMemory:
-    def __init__(self,agent_id:str,base_dir:str) -> None:
+    def __init__(self,agent_id:str,base_dir:str,enable_knowledge_graph = True) -> None:
         self.agent_memory_base_dir = base_dir
         self.agent_id:str= agent_id
 
         AIStorage.get_instance().ensure_directory_exists(self.agent_memory_base_dir)
-        AIStorage.get_instance().ensure_directory_exists(f"{self.agent_memory_base_dir}/experience")
-        AIStorage.get_instance().ensure_directory_exists(f"{self.agent_memory_base_dir}/contacts")
-        AIStorage.get_instance().ensure_directory_exists(f"{self.agent_memory_base_dir}/relations")
-        AIStorage.get_instance().ensure_directory_exists(f"{self.agent_memory_base_dir}/summary")
+        #AIStorage.get_instance().ensure_directory_exists(f"{self.agent_memory_base_dir}/experience")
+        #AIStorage.get_instance().ensure_directory_exists(f"{self.agent_memory_base_dir}/contacts")
+        #AIStorage.get_instance().ensure_directory_exists(f"{self.agent_memory_base_dir}/relations")
+        #AIStorage.get_instance().ensure_directory_exists(f"{self.agent_memory_base_dir}/summary")
 
         self.memory_db:str = f"{self.agent_memory_base_dir}/memory.db"
-        self.model_name:str = "gp4-1106-preview"
+        
         self.threshold_hours = 72
         self.last_think_time : float = 0.0
+        self.enable_knowledge_graph : bool = enable_knowledge_graph
+        if self.enable_knowledge_graph:
+            kb_desc = """The Knowledgegraph is used to store important information obtained by Agent in the conversation.Use the following ways to store information:
+            /contacts/$name:Related information of the contact
+            /relations/$obj1/$obj2:The relationship between obj2 and obj1
+            /summary/$topic:Based on topic summary
+            """
+
+            self.knowledge_graph = ObjFSKnowledgeGrpah(f"{self.agent_id}.memory",self.memory_db,kb_desc)
+            BaseKnowledgeGraph.add_kb(self.knowledge_graph)
+            self.simple_memory_sentences = None
+        else:
+            self.knowledge_graph = None
+            self.simple_memory_sentences : List[str] = []
 
         self.load_memory_meta()
 
@@ -84,7 +99,7 @@ class AgentMemory:
         return chatsession
     
     # return last record time
-    async def load_records(self,starttime,tokenlimit=8000)->float:
+    async def load_records(self,starttime,tokenlimit=8000,model_name=None)->float:
         # 专用思路：做聊天记录/工作经验的整理
         # 通用思路：没有具体的目的，让Agent根据提示词自己工作（可能效果很差也可能很好）
         # 先实现通用思路
@@ -92,7 +107,7 @@ class AgentMemory:
         work_records = self.load_worklogs(self.agent_id,token_limit=tokenlimit)
         pass
 
-    async def load_chatlogs(self,msg:AgentMsg,token_limit=800):
+    async def load_chatlogs(self,msg:AgentMsg,token_limit=800,model_name=""):
         chatsession = self.get_session_from_msg(msg)
         # Must load n (n> = 2), and hope to load the M
         # The information in the # M is gradually added, knowing that it is less than 72 hours from the current time, and consumes enough tokens
@@ -105,7 +120,7 @@ class AgentMemory:
             dt = datetime.fromtimestamp(float(msg.create_time))
             formatted_time = dt.strftime('%y-%m-%d %H:%M:%S')
             record_str = f"{msg.sender},[{formatted_time}]\n{msg.body}\n"
-            token_limit -= ComputeKernel.llm_num_tokens_from_text(record_str,self.model_name)
+            token_limit -= ComputeKernel.llm_num_tokens_from_text(record_str)
             if token_limit <= 32:
                 is_all = False
                 break
@@ -156,7 +171,7 @@ class AgentMemory:
         rows = c.fetchall()
 
 
-        return [self.from_db_row(row) for row in rows]
+        return [self.worklog_from_db_row(row) for row in rows]
 
     def _create_table(self,conn):
         c = conn.cursor()
@@ -176,7 +191,7 @@ class AgentMemory:
         #conn.close()
 
     @classmethod
-    def from_db_row(self,row):
+    def worklog_from_db_row(self,row):
         log = AgentWorkLog()
         # 这里高度依赖表结构的顺序
         log.logid, log.owner_id, log.work_type, log.timestamp, log.content, log.result, meta_str, log.operator = row
@@ -202,6 +217,7 @@ class AgentMemory:
     
     def load_meta(self,Dict):
         self.last_think_time = Dict.get("last_think_time",0.0)
+        self.simple_memory_sentences = Dict.get("simple_memory_sentences",[])
     
     def load_memory_meta(self):
         meta_file_path = f"{self.agent_memory_base_dir}/meta.json"
@@ -230,7 +246,12 @@ class AgentMemory:
         self.last_think_time = last_time    
         self.save_memory_meta()
 
+    
     async def get_contact_summary(self,contact_id:str) -> str:
+        # There is two part of contact summary
+        # Part 1. user defined summary (set by owner or by contac) , global , imutable
+        # Part 2. auto generated summary, local in agent memory , mutable
+
         if contact_id is None:
             return "Contact id is None"
         
@@ -241,107 +262,107 @@ class AgentMemory:
             result["relation"] = contact_info.relationship
             result["notes"]  = contact_info.notes
 
-        summary_path = f"{self.agent_memory_base_dir}/contacts/{contact_id}.summary"
-        try:
-            async with aiofiles.open(summary_path, mode='r') as file:
-                result["summary"] =  await file.read()
+        # summary_path = f"{self.agent_memory_base_dir}/contacts/{contact_id}.summary"
+        # try:
+        #     async with aiofiles.open(summary_path, mode='r') as file:
+        #         result["summary"] =  await file.read()
                 
-        except Exception as e:
-            logger.error(f"read contact summary failed: {e}")
+        # except Exception as e:
+        #     logger.error(f"read contact summary failed: {e}")
             
         return json.dumps(result,ensure_ascii=False)
     
-    async def update_contact_summary(self,contact_id:str,summary:str):
-        summary_path = f"{self.agent_memory_base_dir}/contacts/{contact_id}.summary"
-        try:
-            async with aiofiles.open(summary_path, mode='w') as file:
-                await file.write(summary)
-                return "OK"
-        except Exception as e:
-            logger.error(f"write contact summary failed: {e}")
-            return "write contact summary failed: {e}"
+    # async def update_contact_summary(self,contact_id:str,summary:str):
+    #     summary_path = f"{self.agent_memory_base_dir}/contacts/{contact_id}.summary"
+    #     try:
+    #         async with aiofiles.open(summary_path, mode='w') as file:
+    #             await file.write(summary)
+    #             return "OK"
+    #     except Exception as e:
+    #         logger.error(f"write contact summary failed: {e}")
+    #         return "write contact summary failed: {e}"
     
-    async def get_summary(self,object_name:str) -> str:
-        summary_path = f"{self.agent_memory_base_dir}/{object_name}.summary"
-        try:
-            async with aiofiles.open(summary_path, mode='r') as file:
-                return await file.read()
-        except Exception as e:
-            logger.error(f"read summary failed: {e}")
-            return f"read summary failed: {e}"
+    # async def get_summary(self,object_name:str) -> str:
+    #     summary_path = f"{self.agent_memory_base_dir}/{object_name}.summary"
+    #     try:
+    #         async with aiofiles.open(summary_path, mode='r') as file:
+    #             return await file.read()
+    #     except Exception as e:
+    #         logger.error(f"read summary failed: {e}")
+    #         return f"read summary failed: {e}"
         
-    async def update_summary(self,object_name:str,summary:str) -> str:
-        summary_path = f"{self.agent_memory_base_dir}/{object_name}.summary"
-        try:
-            async with aiofiles.open(summary_path, mode='w') as file:
-                await file.write(summary)
-                return "OK" 
-        except Exception as e:
-            logger.error(f"write summary failed: {e}")
-            return f"write summary failed: {e}"
+    # async def update_summary(self,object_name:str,summary:str) -> str:
+    #     summary_path = f"{self.agent_memory_base_dir}/{object_name}.summary"
+    #     try:
+    #         async with aiofiles.open(summary_path, mode='w') as file:
+    #             await file.write(summary)
+    #             return "OK" 
+    #     except Exception as e:
+    #         logger.error(f"write summary failed: {e}")
+    #         return f"write summary failed: {e}"
     
-    async def list_summary_object_names(self) -> List[str]:
-        # list dir
-        try:
-            contents = os.listdir(self.agent_memory_base_dir)
-            return [x for x in contents if x.endswith(".summary")]
-        except Exception as e:
-            logger.error(f"list summary object names failed: {e}")
-            return []
+    # async def list_summary_object_names(self) -> List[str]:
+    #     # list dir
+    #     try:
+    #         contents = os.listdir(self.agent_memory_base_dir)
+    #         return [x for x in contents if x.endswith(".summary")]
+    #     except Exception as e:
+    #         logger.error(f"list summary object names failed: {e}")
+    #         return []
         
     # means object1 feel object2 is ... 
-    async def get_relation_summary(self,object_name1:str,object_name2:str) -> str:
-        summary_path = f"{self.agent_memory_base_dir}/relations/{object_name1}.relation.{object_name2}.summary"
-        try:
-            async with aiofiles.open(summary_path, mode='r') as file:
-                await file.read()
-        except FileNotFoundError:
-            return "no summary"
-        except Exception as e:
-            logger.error(f"read relation summary failed: {e}")
-            return f"read relation summary failed: {e}"
+    # async def get_relation_summary(self,object_name1:str,object_name2:str) -> str:
+    #     summary_path = f"{self.agent_memory_base_dir}/relations/{object_name1}.relation.{object_name2}.summary"
+    #     try:
+    #         async with aiofiles.open(summary_path, mode='r') as file:
+    #             await file.read()
+    #     except FileNotFoundError:
+    #         return "no summary"
+    #     except Exception as e:
+    #         logger.error(f"read relation summary failed: {e}")
+    #         return f"read relation summary failed: {e}"
         
     
-    async def update_relation_summary(self,object_name1:str,object_name2:str,summary:Dict):
-        summary_path = f"{self.agent_memory_base_dir}/relations/{object_name1}.relation.{object_name2}.summary"
-        try:
-            async with aiofiles.open(summary_path, mode='w') as file:
-                await file.write(json.dumps(summary))
-                return "OK"
-        except Exception as e:
-            logger.error(f"write relation summary failed: {e}")
-            return "write relation summary failed: {e}"
+    # async def update_relation_summary(self,object_name1:str,object_name2:str,summary:Dict):
+    #     summary_path = f"{self.agent_memory_base_dir}/relations/{object_name1}.relation.{object_name2}.summary"
+    #     try:
+    #         async with aiofiles.open(summary_path, mode='w') as file:
+    #             await file.write(json.dumps(summary))
+    #             return "OK"
+    #     except Exception as e:
+    #         logger.error(f"write relation summary failed: {e}")
+    #         return "write relation summary failed: {e}"
     
-    async def get_experience(self,topic_name:str) -> str:
-        experience_path = f"{self.agent_memory_base_dir}/experience/{topic_name}.experience"
-        try:
-            async with aiofiles.open(experience_path, mode='r') as file:
-                await file.read()
-        except FileNotFoundError:
-            return "no experience"
-        except Exception as e:
-            logger.error(f"read experience failed: {e}")
-            return f"read experience failed: {e}"
+    # async def get_experience(self,topic_name:str) -> str:
+    #     experience_path = f"{self.agent_memory_base_dir}/experience/{topic_name}.experience"
+    #     try:
+    #         async with aiofiles.open(experience_path, mode='r') as file:
+    #             await file.read()
+    #     except FileNotFoundError:
+    #         return "no experience"
+    #     except Exception as e:
+    #         logger.error(f"read experience failed: {e}")
+    #         return f"read experience failed: {e}"
 
     
-    async def set_experience(self,topic_name:str,summary:str) -> str:
-        experience_path = f"{self.agent_memory_base_dir}/experience/{topic_name}.experience"
-        try:
-            async with aiofiles.open(experience_path, mode='w') as file:
-                await file.write(summary)
-                return "OK"
-        except Exception as e:
-            logger.error(f"write experience failed: {e}")
-            return "write experience failed: {e}"
+    # async def set_experience(self,topic_name:str,summary:str) -> str:
+    #     experience_path = f"{self.agent_memory_base_dir}/experience/{topic_name}.experience"
+    #     try:
+    #         async with aiofiles.open(experience_path, mode='w') as file:
+    #             await file.write(summary)
+    #             return "OK"
+    #     except Exception as e:
+    #         logger.error(f"write experience failed: {e}")
+    #         return "write experience failed: {e}"
     
-    async def list_experience(self) -> List[str]:
-        dir_path = f"{self.agent_memory_base_dir}/experience"
-        try:
-            contents = os.listdir(dir_path)
-            return [x for x in contents if x.endswith(".experience")]
-        except Exception as e:
-            logger.error(f"list experience failed: {e}")
-            return []
+    # async def list_experience(self) -> List[str]:
+    #     dir_path = f"{self.agent_memory_base_dir}/experience"
+    #     try:
+    #         contents = os.listdir(dir_path)
+    #         return [x for x in contents if x.endswith(".experience")]
+    #     except Exception as e:
+    #         logger.error(f"list experience failed: {e}")
+    #         return []
 
     @staticmethod
     def register_ai_functions():
diff --git a/src/aios/agent/llm_process.py b/src/aios/agent/llm_process.py
index df8b816..d686147 100644
--- a/src/aios/agent/llm_process.py
+++ b/src/aios/agent/llm_process.py
@@ -14,6 +14,7 @@ from .workspace import AgentWorkspace
 from .llm_context import LLMProcessContext,GlobaToolsLibrary, SimpleLLMContext
 
 from ..frame.compute_kernel import ComputeKernel
+from ..knowledge.knowledge_base import BaseKnowledgeGraph
 
 from abc import ABC,abstractmethod
 import copy
@@ -229,8 +230,7 @@ class LLMAgentBaseProcess(BaseLLMProcess):
 
         self.workspace : AgentWorkspace = None # If Workspace is not none , enable Agent Tasklist
         self.memory : AgentMemory = None
-        self.enable_kb : bool = False
-        self.kb = None
+        self.enable_kb_list : List[str] = None
 
     async def initial(self,params:Dict = None) -> bool:
         self.memory = params.get("memory")
@@ -265,26 +265,49 @@ class LLMAgentBaseProcess(BaseLLMProcess):
         if config.get("context"):
             self.context = config.get("context")
 
+        if config.get("knowledge_grpah_introduce"):
+            self.knowledge_grpah_introduce = config.get("knowledge_grpah_introduce")
+
         self.llm_context = SimpleLLMContext()
         if config.get("llm_context"):
             self.llm_context.load_from_config(config.get("llm_context"))
 
-        if config.get("enable_kb"):
-            self.enable_kb = config.get("enable_kb") == "true"
+    def prepare_knowledge_grpah_prompt(self) -> Dict:
+        result = {}
+ 
+        result["introduce"] = BaseKnowledgeGraph.get_kb_default_desc_str()
+        result["knowledge_graph_list"] = {}
+        have_kb = False
 
+        if self.memory.enable_knowledge_graph:
+            result["knowledge_graph_list"][self.memory.knowledge_graph.kb_id] = self.memory.knowledge_graph.get_description()
+            have_kb = True
+        
+        if self.enable_kb_list:
+            for kb_id in self.enable_kb_list:
+                kb = BaseKnowledgeGraph.get_kb(kb_id) 
+                if kb:
+                    have_kb = True
+                    result["knowledge_graph_list"][kb_id] = kb.get_description()
+                else:
+                    logger.error(f"knowledge base {kb_id} not found")
+        
+        if have_kb is False:
+            return None
+        
+        return result
+    
+   
     def prepare_role_system_prompt(self,context_info:Dict) -> Dict:
         system_prompt_dict = {}
-        # System Prompt
-        ## LLM的身份说明
-        system_prompt_dict["role_description"] = self.role_description
-        #prompt.append_system_message(self.role_description)
 
-        ## 处理信息的流程说明
+        system_prompt_dict["role_description"] = self.role_description
         system_prompt_dict["process_rule"] = self.process_description
-        #prompt.append_system_message(self.process_description)
-        ### 回复的格式
         system_prompt_dict["reply_format"] = self.reply_format
-        #prompt.append_system_message(self.reply_format)
+
+        kb_prompt = self.prepare_knowledge_grpah_prompt()
+        if kb_prompt:
+            system_prompt_dict["knowledge_graph"] = kb_prompt
 
         ## Context
         if self.context:
@@ -301,9 +324,13 @@ class LLMAgentBaseProcess(BaseLLMProcess):
 
     def get_action_desc(self) -> Dict:
         result = {}
-        actions_list = self.llm_context.get_all_ai_action()
+        actions_list = []
+
+        actions_list.extend(self.llm_context.get_all_ai_action())
+    
         for action in actions_list:
             result[action.get_name()] = action.get_description()
+ 
         return result
 
     async def get_inner_function_for_exec(self,func_name:str) -> AIFunction:
@@ -483,10 +510,6 @@ class AgentMessageProcess(LLMAgentBaseProcess):
             #TODO eanble workspace functions?
             logger.info(f"workspace is not none,enable workspace functions")
 
-        ## 给予查询KB的权限
-        if self.enable_kb:
-            logger.info(f"enable kb")
-
 
         ### 根据Token Limit加载聊天记录
         remain_token = self.get_remain_prompt_length(prompt,json.dumps(system_prompt_dict,ensure_ascii=False))
@@ -575,7 +598,7 @@ class AgentSelfThinking(LLMAgentBaseProcess):
 
                     history_str = history_str + record_str
 
-                if read_history_msg >= 2:
+                if ComputeKernel.llm_num_tokens_from_text(history_str,self.model_name) > self.chat_summary_token_len:
                     session_history["history"] = history_str
                     chat_history[session_id] = session_history
                     chatsession.summarize_pos = cur_pos
diff --git a/src/aios/frame/compute_kernel.py b/src/aios/frame/compute_kernel.py
index 9458e18..1ab785d 100644
--- a/src/aios/frame/compute_kernel.py
+++ b/src/aios/frame/compute_kernel.py
@@ -105,7 +105,7 @@ class ComputeKernel:
         return True
 
     @staticmethod
-    def llm_num_tokens_from_text(text:str,model:str) -> int:
+    def llm_num_tokens_from_text(text:str,model:str = None) -> int:
         if model is None:
             model = "gpt-4-turbo-preview"
 
diff --git a/src/aios/knowledge/__init__.py b/src/aios/knowledge/__init__.py
index 361a67d..e0d5dfd 100644
--- a/src/aios/knowledge/__init__.py
+++ b/src/aios/knowledge/__init__.py
@@ -3,4 +3,5 @@ from .vector import *
 from .data import *
 from .store import KnowledgeStore
 from .core_object import *
-from .pipeline import *
\ No newline at end of file
+from .pipeline import *
+from .knowledge_base import *
\ No newline at end of file
diff --git a/src/aios/knowledge/knowledge_base.py b/src/aios/knowledge/knowledge_base.py
new file mode 100644
index 0000000..8a7993c
--- /dev/null
+++ b/src/aios/knowledge/knowledge_base.py
@@ -0,0 +1,371 @@
+from abc import ABC, abstractmethod
+import json
+import os
+import uuid
+from typing import List
+
+from ..proto.ai_function import ParameterDefine, SimpleAIAction, SimpleAIFunction
+from ..agent.llm_context import GlobaToolsLibrary
+from ..storage.objfs import ObjFS
+
+import logging
+
+logger = logging.getLogger(__name__)
+
+class BaseKnowledgeGraph(ABC):
+    _all_knowledge_bases = {}
+    _default_kb = None
+    @classmethod
+    def get_kb(cls, kb_id:str):
+        if kb_id is None:
+            return cls._default_kb
+        
+        return cls._all_knowledge_bases.get(kb_id)
+
+    @classmethod
+    def add_kb(cls,kb:'BaseKnowledgeGraph',is_default=False):
+        cls._all_knowledge_bases[kb.kb_id] = kb
+        if is_default:
+            cls._default_kb = kb
+
+    @classmethod
+    def remove_kb(cls,kb_id:str):
+        if cls._default_kb is not None and cls._default_kb.kb_id == kb_id:
+            cls._default_kb = None
+
+        if cls._all_knowledge_bases.get(kb_id) is not None:
+            del cls._all_knowledge_bases[kb_id]
+
+    def __init__(self, kb_id: str,kb_desc:str=None):
+        self.kb_id = kb_id
+        if kb_desc is None:
+            self.kb_desc = """
+            """
+        else:
+            self.kb_desc = kb_desc
+
+    def get_description(self)->str:
+        return self.kb_desc
+
+    # 读接口： 查询，浏览
+    @abstractmethod
+    async def serach(self,  query: str,query_type:str):
+        pass
+
+    @abstractmethod
+    async def get_obj_by_path(self,path)->str:
+        pass
+
+    @abstractmethod
+    async def get_obj_by_id(self,obj_id)->str:
+        pass
+
+    @abstractmethod
+    async def list_by_path(self,base_path)->List[str]:
+        pass
+    
+    @abstractmethod
+    def list_source(self) -> List[str]:
+        pass
+
+
+    @abstractmethod
+    async def add_obj(self,obj_id,obj_name,obj_content,paths) -> bool:
+        pass
+
+    @abstractmethod
+    async def remove(self,remove_path) -> bool:
+        pass
+
+    @abstractmethod
+    async def remove_obj(self,objid):
+        pass
+
+    @abstractmethod
+    async def link(self,obj_id,paths) -> bool:
+        pass
+
+    @abstractmethod
+    async def unlink(self,paths) -> bool:
+        pass
+
+    @abstractmethod
+    async def update_obj(self,obj_id,new_content) -> bool:
+        pass
+
+    @staticmethod  
+    def get_kb_default_desc_str():
+        return """The basic design of the Knowledge Graph is
+1. Each object can be described in JSON, and have a unique obj_id.
+2. The object can be accessed through the PATH, and multiple paths can point to the same object.
+3. Carefully understand the semantics of the path, and follow the description of the knowledge graph.You can list all the sub-paths of a path through the LIST operation
+All Knowledge Graph APIs return are json format string."""
+
+
+    # 写接口：通常由KnowledgePipeline调用
+    @staticmethod
+    def register_ai_functions():
+
+        async def knowledge_graph_access(parameters):
+            kb_id = parameters['kb_id']
+            op_name = parameters['op']
+            param = parameters['param']
+            
+            
+            if op_name is None:
+                logger.error("Operation type is not specified")
+                return "Operation type is not specified"
+            if param is None:
+                logger.error("Operation parameters is not specified")
+                return "Error! Operation parameters is not specified"
+            param = json.loads(param)
+            
+            kb = BaseKnowledgeGraph.get_kb(kb_id)
+            if kb is None:
+                logger.error(f"Knowledge base is not found id:{kb_id}")
+                return "Error! Knowledge base is not found"
+
+            if op_name == "list":
+                root_path = param.get("path")
+                if root_path is None:
+                    logger.error("Path is not specified")
+                    return "Error! Path is not specified"
+                
+                return json.dumps(await kb.list_by_path(root_path), ensure_ascii=False)
+            
+            if op_name == "tree":
+                root_path = param.get("path")
+                if root_path is None:
+                    logger.error("Path is not specified")
+                    return "Error! Path is not specified"
+                
+                depth = param.get("depth")
+                if depth is None:
+                    depth = 3
+                return json.dumps(await kb.tree(root_path,depth), ensure_ascii=False)
+            
+            if op_name == "read":
+                obj_path = param.get("path")
+                if obj_path is None:
+                    logger.error("Path is not specified")
+                    return "Error! Path is not specified"
+                return json.dumps(await kb.get_obj_by_path(obj_path), ensure_ascii=False)
+            
+            if op_name == "get_obj":
+                obj_id = param.get("obj_id")
+                if obj_id is None:
+                    logger.error("Object ID is not specified")
+                    return "Error! Object ID is not specified"
+                return json.dumps(await kb.get_obj_by_id(obj_id), ensure_ascii=False)
+            
+               
+            return "Error! Operation type is not supported"
+        
+        # search is not supported currently
+        func_desc = "Read knowledge graph, op_param format is as follows: list:{'path':$path}, read:{'path':$path}, get_obj:{'obj_id':$obj_id}, tree:{'path':$path,'depth':$depth}"
+        parameters = ParameterDefine.create_parameters({
+            "kb_id": "Knowledge Base ID",
+            "op": "Operation Type,could be [list, read, get_obj]",
+            "op_param": "Operation Param, must be a json string"
+        })
+
+        knowledge_graph_access_func = SimpleAIFunction("knowledge_base.knowledge_graph_read",
+                                                        func_desc,
+                                                        knowledge_graph_access,
+                                                        parameters)
+        GlobaToolsLibrary.get_instance().register_tool_function(knowledge_graph_access_func)
+
+        async def knwoledge_graph_update(parameters):
+            kb_id = parameters['kb_id']
+            op_name = parameters['op']
+            param = parameters['param']
+            result = {}
+            if op_name is None:
+                logger.error("Operation type is not specified")
+                result["result"] = "Error! Operation type is not specified"
+                return json.dumps(result, ensure_ascii=False)
+            if param is None:
+                logger.error("Operation parameters is not specified")
+                result["result"] = "Error! Operation parameters is not specified"
+                return json.dumps(result, ensure_ascii=False)
+            param = json.loads(param)
+            
+            kb = BaseKnowledgeGraph.get_kb(kb_id)
+            if kb is None:
+                logger.error(f"Knowledge base is not found id:{kb_id}")
+                result["result"] = "Error! Knowledge base is not found"
+                return json.dumps(result, ensure_ascii=False)
+            
+            if op_name == "write":
+                write_path = param.get("path")
+                if write_path is None:
+                    logger.error("Path is not specified")
+                    result["result"] = "Error! Path is not specified"
+                    return json.dumps(result, ensure_ascii=False)
+                obj_content = param.get("obj_json")
+                if obj_content is None:
+                    logger.error("Object content is not specified")
+                    result["result"] = "Error! Object content is not specified"
+                    return json.dumps(result, ensure_ascii=False)
+                
+                objid = uuid.uuid4()
+                objname = os.path.basename(write_path)
+                paths = []
+                paths.append(write_path)
+                if await kb.add_obj(objid,objname,obj_content['content'],paths):
+                    result["result"] = "OK"
+                    result['obj_id'] = objid
+                else:
+                    result["result"] = "Error! Add object failed"
+                
+            if op_name == "remove":
+                remove_path = param.get("path")
+                if remove_path is None:
+                    logger.error("Path is not specified")
+                    result["result"] = "Error! Path is not specified"
+                    return json.dumps(result, ensure_ascii=False)
+                
+                if await kb.remove(remove_path):
+                    result["result"] = "OK"
+                else:
+                    result["result"] = "Error! Remove path failed"
+
+            if op_name == "remove_obj":
+                obj_id = param.get("obj_id")
+                if obj_id is None:
+                    logger.error("Object ID is not specified")
+                    result["result"] =  "Error! Object ID is not specified"
+                    return result
+                
+                obj = await kb.get_obj_by_id(obj_id)
+                if obj is None:
+                    logger.error(f"Object is not found id:{obj_id}")
+                    result["result"] = "Error! Object is not found"
+                    return result
+                
+                await kb.remove_obj(obj_id)
+                result["result"] = "OK" 
+
+            if op_name == "set_obj":
+                obj_id = param.get("obj_id")
+                if obj_id is None:
+                    logger.error("Object ID is not specified")
+                    result["result"] = "Error! Object ID is not specified"
+                    return json.dumps(result, ensure_ascii=False)
+                
+                obj = await kb.get_obj_by_id(obj_id)
+                if obj is None:
+                    logger.error(f"Object is not found id:{obj_id}")
+                    result["result"] = "Error! Object is not found"
+                    return result
+                
+                obj_content = param.get("obj_json")
+                if obj_content is None:
+                    logger.error("new object is not specified")
+                    result["result"] = "Error! new object is not specified"
+                    return json.dumps(result, ensure_ascii=False)
+                
+                await kb.update_obj(obj_id,obj_content)
+                result["result"] = "OK"
+
+            if op_name == "link":
+                path_from = param.get("path")
+                path_to = param.get("target") 
+                if path_from is None or path_to is None:
+                    logger.error("Path is not specified")
+                    result["result"] = "Error! Path is not specified"
+                    return json.dumps(result, ensure_ascii=False)
+
+                objid = await kb.get_obj_by_path(path_to)
+                if objid is None:
+                    logger.error(f"Object is not found path:{path_to}")
+                    result["result"] = "Error!Target Object is not found"
+                    return json.dumps(result, ensure_ascii=False)
+                
+                await kb.link(objid,[path_from])
+                result["result"] = "OK"
+                
+            if op_name == "unlink":
+                path_will_remove = param.get("path")
+                if path_will_remove is None:
+                    logger.error("Path is not specified")
+                    result["result"] = "Error! Path is not specified"
+                    return json.dumps(result, ensure_ascii=False)
+
+                await kb.unlink([path_will_remove])
+                result["result"] = "OK"
+
+            return json.dumps(result, ensure_ascii=False)
+        
+
+        OperationParames = """Parameters is a json string, the format is as follows:
+        write:{'path':$path,'obj_json':$obj_json},
+        remove:{'path':$path},
+        remove_obj:{'obj_id':$obj_id},
+        set_obj:{'obj_id':$obj_id,'obj_json':$new_obj_json},
+        link:{'path':$path,'target':$target_obj_path},
+        unlink:{'path':$path}
+"""
+        parameters = ParameterDefine.create_parameters({
+            "kb_id": "Knowledge Base ID",
+            "op": "Operation Type,could be [write, remove, remove_obj, set_obj, link, unlink",
+            "param": OperationParames
+        })
+
+        knowledge_graph_update_func = SimpleAIFunction("knowledge_base.knowledge_graph_update",
+                                                        "Update Knowledge Graph APIs",
+                                                        knwoledge_graph_update,
+                                                        parameters)
+        GlobaToolsLibrary.get_instance().register_tool_function(knowledge_graph_update_func)
+
+
+class ObjFSKnowledgeGrpah(BaseKnowledgeGraph):
+    def __init__(self, kb_id:str,db_path:str,kb_desc:str=None):
+        super().__init__(kb_id,kb_desc)
+        self.db_path = db_path
+        self.obj_storage : ObjFS = ObjFS(db_path)
+    
+    async def serach(self,  query: str,query_type:str):
+        pass
+
+    def list_source(self):
+        pass
+
+    async def get_obj_by_path(self,path)->str:
+        return self.obj_storage.get_obj_by_path(path)
+    
+    async def get_obj_by_id(self,obj_id)->str:
+        return self.obj_storage.get_obj_by_id(obj_id)
+    
+    async def list_by_path(self,base_path)->List[str]:
+        return self.obj_storage.list_paths(base_path)
+    
+    async def tree(self,base_path,depth:int)->str:
+        return self.obj_storage.tree(base_path,depth)
+    
+    async def add_obj(self,obj_id,obj_name,obj_content,paths)->bool:
+        self.obj_storage.add_obj(obj_id,obj_name,obj_content,paths)
+
+    #todo 更新默认是做dict的merge
+    async def update_obj(self, obj_id, new_content)->bool:
+        return self.obj_storage.update_obj(obj_id,new_content)
+    
+    async def remove(self,remove_path)->bool:
+        self.obj_storage.remove_path(remove_path)
+
+    async def remove_obj(self,objid)->bool:
+        self.obj_storage.remove_obj(objid)
+
+    async def link(self,from_path,target_path)->bool:
+        objid = self.obj_storage.get_obj_by_path(target_path)
+        if objid is None:
+            return False
+        self.obj_storage.add_path(objid,from_path)
+        return True
+
+    async def unlink(self,paths)->bool:
+        self.obj_storage.remove_path(paths)
+
+    
+
+
diff --git a/src/aios/storage/obj_storage.py b/src/aios/storage/obj_storage.py
new file mode 100644
index 0000000..267a1a5
--- /dev/null
+++ b/src/aios/storage/obj_storage.py
@@ -0,0 +1,18 @@
+from typing import List
+
+class NamedObjectStorage:
+    def __init__(self, storage, name: str):
+        self.storage = storage
+        self.name = name
+
+    async def get(self, key: str) -> bytes:
+        return await self.storage.get(self.name, key)
+
+    async def put(self, key: str, data: bytes):
+        await self.storage.put(self.name, key, data)
+
+    async def delete(self, key: str):
+        await self.storage.delete(self.name, key)
+
+    async def list(self) -> List[str]:
+        return await self.storage.list(self.name)
\ No newline at end of file
diff --git a/src/aios/storage/objfs.py b/src/aios/storage/objfs.py
new file mode 100644
index 0000000..286631f
--- /dev/null
+++ b/src/aios/storage/objfs.py
@@ -0,0 +1,217 @@
+from abc import ABC, abstractmethod
+import sqlite3
+from sqlite3 import Error
+from typing import List
+
+import threading
+import time
+import uuid
+import logging
+
+logger = logging.getLogger(__name__)
+
+class ObjFSReader(ABC):
+    @abstractmethod
+    def get_obj_by_path(self,path):
+        pass
+
+    @abstractmethod
+    def get_obj_by_id(self,obj_id):
+        pass
+
+    @abstractmethod
+    def list_paths(self,base_path):
+        pass
+
+
+#ObjFS provides structured data storage similar to brain-like, as an object storage layer of Agent Friendly
+class ObjFS(ObjFSReader):
+    def __init__(self, db_file):
+        """ initialize db connection """
+        self.db_file = db_file
+        self._get_conn()
+
+    def _get_conn(self):
+        """ get db connection """
+        local = threading.local()
+        if not hasattr(local, 'conn'):
+            local.conn = self._create_connection(self.db_file)
+        return local.conn
+
+    def _create_connection(self, db_file):
+        """ create a database connection to a SQLite database """
+        conn = None
+        try:
+            conn = sqlite3.connect(db_file)
+
+        except Error as e:
+            logger.error("Error occurred while connecting to database: %s", e)
+            return None
+
+        if conn:
+            self._create_table(conn)
+
+        return conn
+    
+    def _create_table(self, conn):
+        try:
+            conn.execute('''CREATE TABLE IF NOT EXISTS objects
+                        (id TEXT PRIMARY KEY, name TEXT, content TEXT, created_at REAL, modified_at REAL, size INTEGER)''')
+
+            conn.execute('''CREATE TABLE IF NOT EXISTS paths
+                        (id INTEGER PRIMARY KEY AUTOINCREMENT, path TEXT UNIQUE, obj_id TEXT, FOREIGN KEY(obj_id) REFERENCES objects(id))''')
+
+        except Error as e:
+            logger.error("Error occurred while creating tables: %s", e)
+
+    def close(self):
+        local = threading.local()
+        if not hasattr(local, 'conn'):
+            return
+        local.conn.close()
+        
+    def add_obj(self,obj_uuid, name, content, paths) -> bool:
+        conn = self._get_conn()
+        c = conn.cursor()
+        #obj id是guid,由外部生成
+
+        # 获取当前时间戳
+        current_time = time.time()
+
+        # 计算内容大小
+        content_size = len(content.encode('utf-8'))
+        try:
+            # 插入对象
+            c.execute("INSERT INTO objects (id, name, content, created_at, modified_at, size) VALUES (?, ?, ?, ?, ?, ?)", (obj_uuid, name, content, current_time, current_time, content_size))
+
+            # 插入路径
+            for path in paths:
+                c.execute("INSERT OR IGNORE INTO paths (path, obj_id) VALUES (?, ?)", (path, obj_uuid))
+
+            conn.commit()
+        except Error as e:
+            logger.warning("Error occurred while adding object: %s", e)
+            return False
+        
+        return True
+
+    def update_obj(self,obj_id, new_content) -> bool:
+        #UPDATE orders
+        #SET data = json_set(
+        #    data,
+        #    '$.items[1].price',
+        #    0.35
+        #)
+        #WHERE id = 1;
+        
+        try:
+            conn = self._get_conn()
+            c = conn.cursor()
+            # 获取当前时间戳
+            current_time = time.time()
+
+            # 计算新内容大小
+
+            new_content_size = len(new_content.encode('utf-8'))
+
+            c.execute("UPDATE objects SET content = ?, modified_at = ?, size = ? WHERE id = ?", (new_content, current_time, new_content_size, obj_id))
+            conn.commit()
+            return True
+        except Error as e:
+            logger.warning("Error occurred while updating object: %s", e)
+            return False
+
+    def add_path(self,obj_id, new_path) -> bool:
+        try:
+            conn = self._get_conn()
+            c = conn.cursor()        
+            c.execute("INSERT OR IGNORE INTO paths (path, obj_id) VALUES (?, ?)", (new_path, obj_id))
+            conn.commit()
+            return True
+        except Error as e:
+            logger.warning("Error occurred while adding path: %s", e)
+            return False
+
+    def remove_path(self,path) -> bool:
+        try:
+            conn = self._get_conn()
+            c = conn.cursor()    
+            #TODO     
+            c.execute("DELETE FROM paths WHERE path = ?", (path,))
+            conn.commit()
+            return True
+        except Error as e:
+            logger.warning("Error occurred while removing path: %s", e)
+            return False
+
+    def remove_obj(self,obj_id) -> bool:
+        try:
+            conn = self._get_conn()
+            c = conn.cursor()
+            c.execute("DELETE FROM objects WHERE id = ?", (obj_id,))
+
+            # 删除所有与该对象相关的路径
+            c.execute("DELETE FROM paths WHERE obj_id = ?", (obj_id,))
+            conn.commit()
+            return True
+        except Error as e:
+            logger.warning("Error occurred while removing object: %s", e)
+            return False
+
+    def get_obj_by_path(self,path) -> str:
+        try:
+            conn = self._get_conn()
+            c = conn.cursor()        
+            c.execute("SELECT objects.id, objects.name, objects.content FROM objects JOIN paths ON objects.id = paths.obj_id WHERE paths.path = ?", (path,))
+            obj_row = c.fetchone()
+            if obj_row:
+                return obj_row[2]
+            return None
+        except Error as e:
+            logger.warning("Error occurred while getting object by path: %s", e)
+            return None
+
+
+    def get_obj_by_id(self,obj_id) -> str:
+        try:
+            conn = self._get_conn()
+            c = conn.cursor()        
+            c.execute("SELECT id, name, content FROM objects WHERE id = ?", (obj_id,))
+            obj_row =  c.fetchone()
+            if obj_row:
+                return obj_row[2]
+            return None
+        except Error as e:
+            logger.warning("Error occurred while getting object by id: %s", e)
+            return None
+
+    def list_paths(self,base_path)->List[str]:
+        try:
+            conn = self._get_conn()
+            c = conn.cursor()        
+            c.execute("SELECT path FROM paths WHERE path LIKE ? ESCAPE '/'", (base_path + "/%",))
+            return [row[0] for row in c.fetchall()]
+        except Error as e:
+            logger.warning("Error occurred while listing paths: %s", e)
+            return None
+        
+    def tree(self, base_path,max_depth=3):
+        try:
+            conn = self._get_conn()
+            c = conn.cursor()        
+            c.execute("SELECT path FROM paths WHERE path LIKE ? ESCAPE '/'", (base_path + "/%",))
+            paths = [row[0] for row in c.fetchall()]
+            tree = {}
+            for path in paths:
+                parts = path.split("/")
+                node = tree
+                for part in parts:
+                    if part not in node:
+                        node[part] = {}
+                    node = node[part]
+            return tree
+        except Error as e:
+            logger.warning("Error occurred while listing paths: %s", e)
+            return None
+
+
diff --git a/src/component/openai_node/open_ai_node.py b/src/component/openai_node/open_ai_node.py
index 345c6c4..52cb83b 100644
--- a/src/component/openai_node/open_ai_node.py
+++ b/src/component/openai_node/open_ai_node.py
@@ -27,7 +27,7 @@ class OpenAI_ComputeNode(ComputeNode):
 
     @classmethod
     def declare_user_config(cls):
-        if os.getenv("OPENAI_API_KEY_") is None:
+        if os.getenv("OPENAI_API_KEY") is None:
             user_config = AIStorage.get_instance().get_user_config()
             user_config.add_user_config("openai_api_key","openai api key",False,None)
 
diff --git a/src/service/aios_shell/aios_shell.py b/src/service/aios_shell/aios_shell.py
index 2c26929..79a77cc 100644
--- a/src/service/aios_shell/aios_shell.py
+++ b/src/service/aios_shell/aios_shell.py
@@ -153,6 +153,7 @@ class AIOS_Shell:
         #AgentManager.get_instance().register_environment("knowledge", LocalKnowledgeBase)
         AgentWorkspace.register_ai_functions()
         AgentMemory.register_ai_functions()
+        BaseKnowledgeGraph.register_ai_functions()
         ShellEnvironment.register_ai_functions()