Agent can create todo by op_list
This commit is contained in:
Liu Zhicong
+48
-26
@@ -129,6 +129,7 @@ class AIAgent:
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self.owner_env : Environment = None
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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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@@ -148,6 +149,7 @@ class AIAgent:
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logger.error("agent instance_id is None!")
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return False
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self.agent_id = config["instance_id"]
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self.agent_workspace = WorkspaceEnvironment(self.agent_id)
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if config.get("fullname") is None:
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logger.error(f"agent {self.agent_id} fullname is None!")
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@@ -412,7 +414,7 @@ class AIAgent:
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# return None
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def get_workspace_by_msg(self,msg:AgentMsg) -> WorkspaceEnvironment:
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return None
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return self.agent_workspace
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def need_session_summmary(self,msg:AgentMsg,session:AIChatSession) -> bool:
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return False
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@@ -455,14 +457,26 @@ class AIAgent:
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summary = self.llm_select_session_summary(msg,chatsession)
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prompt.append(AgentPrompt(summary))
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known_info_str = "# 已知信息\n"
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have_known_info = False
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todos_str,todo_count = await workspace.get_todo_tree()
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if todo_count > 0:
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have_known_info = True
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known_info_str += f"## 已有todo\n{todos_str}\n"
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inner_functions,function_token_len = self._get_inner_functions()
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system_prompt_len = prompt.get_prompt_token_len()
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input_len = len(msg.body)
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if msg.msg_type == AgentMsgType.TYPE_GROUPMSG:
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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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history_str,history_token_len = await self._get_prompt_from_session_for_groupchat(chatsession,system_prompt_len + function_token_len,input_len)
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else:
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history_prmpt,history_token_len = await self.get_prompt_from_session(chatsession,system_prompt_len + function_token_len,input_len)
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prompt.append(history_prmpt) # chat context
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history_str,history_token_len = await self.get_prompt_from_session(chatsession,system_prompt_len + function_token_len,input_len)
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if history_str:
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have_known_info = True
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known_info_str += history_str
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if have_known_info:
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known_info_prompt = AgentPrompt(known_info_str)
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prompt.append(known_info_prompt) # chat context
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prompt.append(msg_prompt)
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@@ -475,12 +489,18 @@ class AIAgent:
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return error_resp
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final_result = task_result.result_str
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if final_result is not None:
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if final_result[0] == "{":
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llm_result = LLMResult.from_json_str(final_result)
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else:
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llm_result : LLMResult = LLMResult.from_str(final_result)
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else:
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llm_result = LLMResult()
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llm_result.state = "ignore"
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llm_result : LLMResult = LLMResult.from_str(final_result)
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# extra_info include the operation about workspace
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if llm_result.extra_info is not None:
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await workspace.update_state_by_msg(msg,llm_result.extra_info)
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final_result = llm_result.resp
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await workspace.exec_op_list(llm_result.op_list)
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is_ignore = False
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result_prompt_str = ""
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@@ -899,38 +919,37 @@ class AIAgent:
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history_len = (self.max_token_size * 0.7) - system_token_len - input_token_len
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messages = chatsession.read_history(self.history_len) # read
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result_token_len = 0
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result_prompt = AgentPrompt()
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read_history_msg = 0
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have_known_info = False
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known_info = ""
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if chatsession.summary is not None:
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if len(chatsession.summary) > 1:
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result_prompt.messages.append({"role":"user","content":chatsession.summary})
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known_info += f"## 最近交流的总结 \n {chatsession.summary}\n"
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result_token_len -= len(chatsession.summary)
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have_known_info = True
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histroy_str = ""
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for msg in reversed(messages):
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read_history_msg += 1
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dt = datetime.datetime.fromtimestamp(float(msg.create_time))
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formatted_time = dt.strftime('%y-%m-%d %H:%M:%S')
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if msg.sender == self.agent_id:
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if self.enable_timestamp:
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result_prompt.messages.append({"role":"assistant","content":f"(create on {formatted_time}) {msg.body} "})
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else:
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result_prompt.messages.append({"role":"assistant","content":msg.body})
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else:
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if self.enable_timestamp:
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result_prompt.messages.append({"role":"user","content":f"(create on {formatted_time}) {msg.body} "})
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else:
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result_prompt.messages.append({"role":"user","content":msg.body})
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record_str = f"{msg.sender},[{formatted_time}]\n{msg.body}\n"
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have_known_info = True
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histroy_str = histroy_str + record_str
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history_len -= len(msg.body)
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result_token_len += len(msg.body)
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if history_len < 0:
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logger.warning(f"_get_prompt_from_session reach limit of token,just read {read_history_msg} history message.")
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break
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return result_prompt,result_token_len
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known_info += f"## 最近的沟通记录 \n {histroy_str}\n"
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if have_known_info:
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return known_info,result_token_len
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return None,0
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async def _do_llm_complection(self,prompt:AgentPrompt,inner_functions:dict=None,org_msg:AgentMsg=None) -> ComputeTaskResult:
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from .compute_kernel import ComputeKernel
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@@ -952,6 +971,9 @@ class AIAgent:
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return task_result
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async def execute_op_list(self,oplist:list,workspace:WorkspaceEnvironment):
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pass
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def need_work(self) -> bool:
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return True
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