learn knowledge design document
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tsukasa
@@ -133,19 +133,6 @@ class AIAgent(BaseAIAgent):
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self.owenr_bus = None
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self.enable_function_list = None
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# @classmethod
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# def create_from_templete(cls,templete:AIAgentTemplete, fullname:str):
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# # Agent just inherit from templete on craete,if template changed,agent will not change
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# result_agent = AIAgent()
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# result_agent.llm_model_name = templete.llm_model_name
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# result_agent.max_token_size = templete.max_token_size
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# result_agent.template_id = templete.template_id
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# result_agent.agent_id = "agent#" + uuid.uuid4().hex
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# result_agent.fullname = fullname
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# result_agent.powerby = templete.author
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# result_agent.agent_prompt = templete.prompt
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# return result_agent
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def load_from_config(self,config:dict) -> bool:
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if config.get("instance_id") is None:
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logger.error("agent instance_id is None!")
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@@ -281,82 +268,6 @@ class AIAgent(BaseAIAgent):
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if event.type == "AgentThink":
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return await self.do_self_think()
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# async def _process_group_chat_msg(self,msg:AgentMsg) -> AgentMsg:
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# session_topic = msg.target + "#" + msg.topic
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# chatsession = AIChatSession.get_session(self.agent_id,session_topic,self.chat_db)
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# workspace = self.get_current_workspace()
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# need_process = False
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# if msg.mentions is not None:
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# if self.agent_id in msg.mentions:
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# need_process = True
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# logger.info(f"agent {self.agent_id} recv a group chat message from {msg.sender},but is not mentioned,ignore!")
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# if need_process is not True:
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# chatsession.append(msg)
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# resp_msg = msg.create_group_resp_msg(self.agent_id,"")
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# return resp_msg
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# else:
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# msg_prompt = AgentPrompt()
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# msg_prompt.messages = [{"role":"user","content":f"{msg.sender}:{msg.body}"}]
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# prompt = AgentPrompt()
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# prompt.append(self.get_agent_prompt())
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# if workspace:
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# prompt.append(workspace.get_prompt())
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# prompt.append(workspace.get_role_prompt(self.agent_id))
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# if self.need_session_summmary(msg,chatsession):
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# # get relate session(todos) summary
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# summary = self.llm_select_session_summary(msg,chatsession)
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# prompt.append(AgentPrompt(summary))
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# self._format_msg_by_env_value(prompt)
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# inner_functions,function_token_len = self._get_inner_functions()
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# system_prompt_len = self.token_len(prompt=prompt)
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# input_len = len(msg.body)
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# history_prmpt,history_token_len = await self._get_prompt_from_session_for_groupchat(chatsession,system_prompt_len + function_token_len,input_len)
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# prompt.append(history_prmpt) # chat context
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# prompt.append(msg_prompt)
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# logger.debug(f"Agent {self.agent_id} do llm token static system:{system_prompt_len},function:{function_token_len},history:{history_token_len},input:{input_len}, totoal prompt:{system_prompt_len + function_token_len + history_token_len} ")
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# task_result = await self._do_llm_complection(prompt,inner_functions,msg)
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# if task_result.result_code != ComputeTaskResultCode.OK:
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# error_resp = msg.create_error_resp(task_result.error_str)
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# return error_resp
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# final_result = task_result.result_str
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# llm_result : LLMResult = LLMResult.from_str(final_result)
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# is_ignore = False
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# result_prompt_str = ""
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# match llm_result.state:
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# case "ignore":
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# is_ignore = True
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# case "waiting":
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# for sendmsg in llm_result.send_msgs:
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# target = sendmsg.target
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# sendmsg.sender = self.agent_id
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# sendmsg.topic = msg.topic
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# sendmsg.prev_msg_id = msg.get_msg_id()
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# send_resp = await AIBus.get_default_bus().send_message(sendmsg)
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# if send_resp is not None:
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# result_prompt_str += f"\n{target} response is :{send_resp.body}"
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# agent_sesion = AIChatSession.get_session(self.agent_id,f"{sendmsg.target}#{sendmsg.topic}",self.chat_db)
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# agent_sesion.append(sendmsg)
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# agent_sesion.append(send_resp)
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# final_result = llm_result.resp + result_prompt_str
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# if is_ignore is not True:
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# resp_msg = msg.create_group_resp_msg(self.agent_id,final_result)
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# chatsession.append(msg)
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# chatsession.append(resp_msg)
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# return resp_msg
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# return None
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def get_workspace_by_msg(self,msg:AgentMsg) -> WorkspaceEnvironment:
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return self.agent_workspace
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@@ -884,10 +795,6 @@ class AIAgent(BaseAIAgent):
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# if learn_power <= 0:
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# break
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def parser_learn_llm_result(self,llm_result:LLMResult):
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pass
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async def do_self_think(self):
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session_id_list = AIChatSession.list_session(self.agent_id,self.chat_db)
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for session_id in session_id_list:
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@@ -980,17 +887,6 @@ class AIAgent(BaseAIAgent):
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return None,0
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def need_work(self) -> bool:
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if self.do_prompt is not None:
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return True
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if self.check_prompt is not None:
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return True
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if self.agent_energy > 2:
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return True
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return False
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def need_self_think(self) -> bool:
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return False
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