framework code has been completed basicly. Through the use of aios_shell, we are now able to get agents run able (at openai compute node)

This commit is contained in:
Liu Zhicong
2023-08-27 18:07:33 -07:00
parent 1a6cf1ad7a
commit ccbef2104b
25 changed files with 1011 additions and 198 deletions
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# workflow实例场景
# 能展示sub workflow
# 能展示env的整合
# 能展示filter的使用
# 能展示function的调用
# 能展示基于工作目标/KPI的sub workflow迭代流程
# 多人场景安排
# 例子:举办一个团队活动
# 方案讨论(通过交互引导的方式收集主人的需求)与确定
# 活动前:
# 通讯员,对接管理参加活动的人的情况 (email spider)
# 酒店预订 简单:搜索(酒店评价) 处理异常
# 行程(票务)预订 :搜索,处理异常
# 餐饮预订:给出方案,确定细节,预订
# 活动中:
# 进行统计和分析,调整设备
# 安保,空调,音乐,拍照,录像
# 响应紧急情况
# 活动结束后:
# 整理照片,视频,进行必要的二次创作,发送给相关人员
# 对活动进行总结,提出改件意见(指导下一次活动)
# 1. 人员
# 主管,负责和客户沟通,并对每个环境的结果进行总结
# 嘉宾对接
# 酒店组
# 行程组
# 财务组
# 多媒体组
[filter]
"*" = "manager"
[roles.manager]
name = "经理"
prompt = "你是一个活动策划公司的经理,与客户对接并向团队下达指令。你的团队分为下面几个小组:嘉宾对接组,酒店预定组,行程预订组,财务组,活动摄像组。活动策划分为四个阶段:方案讨论,活动前,活动中,活动后。你会根据客户的需求,对团队进行分工,分别完成各个阶段的工作。你的基本工作模式是:
1. 收到客户的明确的指令后,基于客户的已有信息和客户商量活动方案,和活动策划公司无关的业务你会回答‘与我无关’。当和客户完成活动方案的确认后,你会将拆解后的任务分配给各个小组
2. 根据目前已经确认的活动方案,你要根据时间适时的检查不同小组的工作情况。当收到小组的工作情况反馈后,你会站在全局的角度判断是否需要调整活动方案,如果需要调整,你会和客户商量重新确定方案,然后再将调整后的方案分配给各个小组。
3. 有时工作小组会主动与你沟通,反馈一些问题。你会站在全局的角度给与指导,适当的调整工作小组的工作目标。如果反馈的问题需要你和客户沟通,你会和客户沟通后重新确定方案。再将调整后的方案分配给受到影响各个小组。
4. 当你决定要和工作小组通信时,请使用`send_message({小组名称},{内容}`)的形式。
"
agent="agent.manager"
[sub_workflows]
[sub_workflows."嘉宾对接组"]
# 展现读取email和发送email与嘉宾沟通的能力
[sub_workflows."嘉宾对接组".environments.email]
new_mail = "收到来自{event.data.from},标题为{event.data.subject}的邮件,内容为{event.data.content}的电子邮件" # 这里将new_mail事件转换为了一个来自环境的message
[sub_workflows."嘉宾对接组".roles.leader]
name = "嘉宾对接组组长"
prompt = "你是一家活动策划公司的嘉宾对接组的组长,你的工作是基于已知信息,当前活动信息、公司经理的指令与嘉宾沟通,收集嘉宾的信息,然后将信息反馈给经理。在你看来,参加活动的多少有成员都是嘉宾,你可以通过你知道的信息给不同的成员进行分级。你的基本工作模式是:
1. 处理收到的邮件,如果邮件来自嘉宾,你会尝试从邮件的表态和内容中分享嘉宾的需要,并结合你对当前活动方案的理解判断是否需要和经理沟通,如果需要和经理沟通,你会将嘉宾的需求总结和告诉经理。不需要沟通的事项可以直接回复嘉宾。
2. 你总是通过`call_function(get_env,'parent.topic'`的形式查询当前的活动方案。等待函数返回后,你会根据函数的返回结果继续处理上一个对话。
3. 当你决定要和经理通信时,请使用`send_message(manager,{内容}`)的形式,内容的长度不超过200字。
4. 当你决定要回复嘉宾时,请使用`call_function(sendmail,{嘉宾邮件地址},{标题},{内容})的形式,内容的长度不超过500字。
"
# 这里是孤立工作模式,组长只和经理沟通,也可以赋予其和其它组沟通的能力
agent="agent.email.leader"
[sub_workflows."酒店预定组"]
# 展现使用搜索引擎,并调用预订酒店的能力
[sub_workflows."酒店预定组".environments.email]
[sub_workflows."酒店预定组".roles.leader]
name="酒店预定组组长"
[sub_workflows."酒店预定组".roles.research]
name="酒店搜索专家"
[sub_workflows."行程预订组"]
# 展现处理冲突并反推
nam3="3"
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@@ -15,7 +15,7 @@ Let's start by introducing the two important processes.
## Install Package
[![](./install_package.png)](pkg_procedure.drawio)
注意安装的依赖检测流程,按照流程允许将确实的package安装到当前env
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.
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@@ -1,6 +1,6 @@
<mxfile host="65bd71144e" pages="3">
<diagram id="C5RBs43oDa-KdzZeNtuy" name="Page-1">
<mxGraphModel dx="951" dy="944" grid="1" gridSize="10" guides="1" tooltips="1" connect="1" arrows="1" fold="1" page="1" pageScale="1" pageWidth="827" pageHeight="1169" math="0" shadow="0">
<mxGraphModel dx="1800" dy="674" grid="1" gridSize="10" guides="1" tooltips="1" connect="1" arrows="1" fold="1" page="1" pageScale="1" pageWidth="827" pageHeight="1169" math="0" shadow="0">
<root>
<mxCell id="WIyWlLk6GJQsqaUBKTNV-0"/>
<mxCell id="WIyWlLk6GJQsqaUBKTNV-1" parent="WIyWlLk6GJQsqaUBKTNV-0"/>
@@ -220,7 +220,7 @@
</mxGraphModel>
</diagram>
<diagram id="7NYJTgo0U9cdVshLy85U" name="Page-3">
<mxGraphModel dx="951" dy="944" grid="1" gridSize="10" guides="1" tooltips="1" connect="1" arrows="1" fold="1" page="1" pageScale="1" pageWidth="850" pageHeight="1100" math="0" shadow="0">
<mxGraphModel dx="1800" dy="674" grid="1" gridSize="10" guides="1" tooltips="1" connect="1" arrows="1" fold="1" page="1" pageScale="1" pageWidth="850" pageHeight="1100" math="0" shadow="0">
<root>
<mxCell id="0"/>
<mxCell id="1" parent="0"/>
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instance_id = "agent:xxxxxxabcde"
fullname = "tracy wang"
[[prompt]]
role = "system"
content = "你是我的私人英文老师,和我用地道的美式英语进行交流。你会在和我交流的同时,调整我的输入成为更地道的美式句子,并根据你对我英文水平的预测,对可能发错英的单词标上音标。如果我给你发中文,说明我不知道这句话用美式英语怎么说,你依旧按上述规则回应我。"
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main = "./"
cache = "./.agents"
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main = "./"
cache = "./.templetes"
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@@ -1,5 +1,5 @@
from .environment import Environment,EnvironmentEvent
from .agent import AgentMsg,AIAgent,AIAgentTemplete
from .agent import AgentMsg,AIAgent,AIAgentTemplete,AgentMsgState,AgentPrompt,AgentMsgState
from .compute_kernel import ComputeKernel,ComputeTask
from .compute_node import ComputeNode,LocalComputeNode
from .open_ai_node import OpenAI_ComputeNode
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@@ -1,14 +1,37 @@
from typing import Optional
from enum import Enum
from asyncio import Queue
import asyncio
import logging
import uuid
import time
logger = logging.getLogger(__name__)
class AgentMsgState(Enum):
RESPONSED = 0
INIT = 1
SENDING = 2
PROCESSING = 3
ERROR = 4
class AgentMsg:
def __init__(self) -> None:
self.sender = None
self.target = None
self.body = None
self.create_time = 0
self.sender:str = None
self.target:str = None
self.body:str = None
self.state = AgentMsgState.INIT
self.resp_msg = None
def set(self,sender:str,target:str,body:str) -> None:
self.sender = sender
self.target = target
self.body = body
self.create_time = time.time()
def get_msg_id(self) -> str:
pass
@@ -25,22 +48,35 @@ class AgentMsg:
class AgentPrompt:
def __init__(self) -> None:
pass
self.messages = []
def as_str(self)->str:
pass
result_str = ""
if self.messages:
for msg in self.messages:
result_str += msg.get("role") + ":" + msg.get("content") + "\n"
def append(self,prompt) -> None:
pass
return result_str
def append(self,prompt):
self.messages.extend(prompt.messages)
def load_from_config(self,config:list) -> bool:
if isinstance(config,list) is not True:
logger.error("prompt is not list!")
return False
self.messages = config
return True
# chat session store the chat history between owner and agent
# chat session might be large, so can read / write at stream mode.
class AIChatSession:
def __init__(self) -> None:
pass
def __init__(self,owner_id) -> None:
self.owner_id = owner_id
def get_owner_id(self) -> str:
pass
return self.owner_id
def append_post(self,msg:AgentMsg) -> None:
"""append msg to session, msg is post from session (owner => msg.target)"""
@@ -58,27 +94,204 @@ class AIChatSession:
class AIAgentTemplete:
def __init__(self) -> None:
pass
self.llm_model_name:str = "gpt-4-0613"
self.max_token_size:int = 0
self.template_id:str = None
self.introduce:str = None
self.author:str = None
self.prompt:AgentPrompt = None
def load_from_config(self,config:dict) -> bool:
if config.get("llm_model_name") is not None:
self.llm_model_name = config["llm_model_name"]
if config.get("max_token_size") is not None:
self.max_token_size = config["max_token_size"]
if config.get("template_id") is not None:
self.template_id = config["template_id"]
if config.get("prompt") is not None:
self.prompt = AgentPrompt()
if self.prompt.load_from_config(config["prompt"]) is False:
logger.error("load prompt from config failed!")
return False
return True
class AIAgent:
def __init__(self) -> None:
self.chat_sessions = None
self.llm_model_name = None
self.max_token_size = 0
self.instance_id = None
self.template_id = None
self.prompt:AgentPrompt = None
self.llm_model_name:str = None
self.max_token_size:int = 0
self.instance_id:str = None
self.template_id:str = None
self.fullname:str = None
self.powerby = None
self.enable = True
self.chat_sessions = {}
self.unread_msg = Queue() # msg from other agent
@classmethod
def create_from_templete(cls,templete:AIAgentTemplete, fullname:str):
# Agent just inherit from templete on craete,if template changed,agent will not change
result_agent = AIAgent()
result_agent.llm_model_name = templete.llm_model_name
result_agent.max_token_size = templete.max_token_size
result_agent.template_id = templete.template_id
result_agent.instance_id = "agent#" + uuid.uuid4().hex
result_agent.fullname = fullname
result_agent.powerby = templete.author
result_agent.prompt = templete.prompt
return result_agent
def load_from_config(self,config:dict) -> bool:
if config.get("instance_id") is None:
logger.error("agent instance_id is None!")
return False
self.instance_id = config["instance_id"]
if config.get("fullname") is None:
logger.error(f"agent {self.instance_id} fullname is None!")
return False
self.fullname = config["fullname"]
if config.get("prompt") is not None:
self.prompt = AgentPrompt()
self.prompt.load_from_config(config["prompt"])
if config.get("powerby") is not None:
self.powerby = config["powerby"]
if config.get("template_id") is not None:
self.template_id = config["template_id"]
if config.get("llm_model_name") is not None:
self.llm_model_name = config["llm_model_name"]
if config.get("max_token_size") is not None:
self.max_token_size = config["max_token_size"]
return True
def post_msg(self,msg:AgentMsg) -> None:
# TODO: drop same msg already processed
msg.state = AgentMsgState.SENDING
self.unread_msg.put_nowait(msg)
def start(self) -> None:
async def _process_msg_loop():
while True:
msg = await self.unread_msg.get()
if msg is None:
continue
msg.state = AgentMsgState.PROCESSING
resp_msg = await self._process_msg(msg)
if resp_msg is None:
msg.state = AgentMsgState.ERROR
continue
else:
msg.state = AgentMsgState.RESPONSED
msg.resp_msg = resp_msg
asyncio.create_task(_process_msg_loop())
def _get_llm_result_type(self,result:str) -> str:
if result == "ignore":
return "ignore"
return "text"
async def _process_msg(self,msg:AgentMsg) -> AgentMsg:
from .compute_kernel import ComputeKernel
prompt = AgentPrompt()
prompt.append(self.prompt)
msg_prompt = AgentPrompt()
msg_prompt.messages = [{"role":msg.sender,"content":msg.body}]
prompt.append(msg_prompt)
# prompt.append(self._get_function_prompt(the_role.get_name()))
# prompt.append(self._get_knowlege_prompt(the_role.get_name()))
# prompt.append(await self._get_prompt_from_session(chatsession,the_role.get_name())) # chat context
result = await ComputeKernel().do_llm_completion(prompt,self.llm_model_name,self.max_token_size)
final_result = result
result_type : str = self._get_llm_result_type(result)
is_ignore = False
match result_type:
# case "function":
# callchain:CallChain = self._parse_function_call_chain(result)
# resp = await callchain.exec()
# if callchain.have_result():
# # generator proc resp prompt with WAITING state
# proc_resp_prompt:AgentPrompt = self._get_resp_prompt(resp,msg,the_role,prompt,chatsession)
# final_result = await ComputeKernel().do_llm_completion(proc_resp_prompt,the_role.agent.get_llm_model_name(),the_role.agent.get_max_token_size())
# return final_result
# case "send_message":
# # send message to other / sub workflow
# next_msg:AgentMsg = self._parse_to_msg(result)
# if next_msg is not None:
# # TODO: Next Target can be another role in workflow
# next_workflow:Workflow = self.get_workflow(next_msg.get_target())
# inner_chat_session = the_role.agent.get_chat_session(next_msg.get_target(),next_msg.get_session_id())
# inner_chat_session.append_post(next_msg)
# resp = await next_workflow.send_msg(next_msg)
# inner_chat_session.append_recv(resp)
# # generator proc resp prompt with WAITING state
# proc_resp_prompt:AgentPrompt = self._get_resp_prompt(resp,msg,the_role,prompt,chatsession)
# final_result = await ComputeKernel().do_llm_completion(proc_resp_prompt,the_role.agent.get_llm_model_name(),the_role.agent.get_max_token_size())
# return final_result
#case "post_message":
# # post message to other / sub workflow
# next_msg:AgentMsg = self._parse_to_msg(result)
# if next_msg is not None:
# next_workflow:Workflow = self.get_workflow(next_msg.get_target())
# inner_chat_session = the_role.agent.get_chat_session(next_msg.get_target(),next_msg.get_session_id())
# inner_chat_session.append_post(next_msg)
# next_workflow.post_msg(next_msg)
case "ignore":
is_ignore = True
if is_ignore is not True:
# TODO : how to get inner chat session?
chatsession = self.get_chat_session(msg.sender)
resp_msg = AgentMsg()
resp_msg.set(self.instance_id,msg.sender,final_result)
if chatsession is not None:
chatsession.append_recv(msg)
chatsession.append_post(final_result)
return resp_msg
return None
def get_id(self) -> str:
return self.instance_id
def get_fullname(self) -> str:
return self.fullname
def get_template_id(self) -> str:
return self.template_id
def get_chat_session_for_msg(self,msg:AgentMsg) -> AIChatSession:
pass
def get_chat_session(self,sender:str,session_id:str) -> AIChatSession:
pass
def get_chat_session(self,remote:str,topic_name:str=None) -> AIChatSession:
if topic_name is None:
topic_name = "_"
result_session = self.chat_sessions.get(topic_name + "@" + remote)
if result_session is not None:
return result_session
result_session = AIChatSession(self)
self.chat_sessions[topic_name + "@" + remote] = result_session
return result_session
def get_llm_model_name(self) -> str:
return self.llm_model_name
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@@ -1,14 +0,0 @@
# aiso shell like bash of linux
from .workflow import Workflow
class AIOS_Shell:
def __init__(self,username:str) -> None:
pass
async def send_msg(self,msg:str,target_workflow:str) -> str:
pass
async def install_workflow(self,workflow_id:Workflow) -> None:
pass
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@@ -2,32 +2,39 @@ from abc import ABC, abstractmethod
from typing import Optional
import logging
import asyncio
from asyncio import Queue
from .agent import AgentPrompt
from .compute_node import ComputeNode
from .compute_task import ComputeTask,ComputeTaskState,ComputeTaskResult
logger = logging.getLogger(__name__)
# How to dispatch different computing tasks (some tasks may contain a large amount of state for correct execution)
# to suitable computing nodes, achieving a balance of speed, cost, and power consumption,
# is the CORE GOAL of the entire computing task schedule system (aios_kernel).
class ComputeTask(ABC):
@abstractmethod
def display(self) -> str:
pass
class ComputeKernel:
_instance = None
def __new__(cls):
if cls._instance is None:
cls._instance = super(ComputeKernel, cls).__new__(cls)
cls._instance = super().__new__(cls)
cls._instance.is_start = False
else:
print("ComputeKernel is already created!")
return cls._instance
def __init__(self) -> None:
self.task_queue = []
if self.is_start is True:
print("ComputeKernel is already start!")
return
print("init ComputeKernel!!!")
self.is_start = True
self.task_queue = Queue()
self.is_start = False
pass
self.compute_nodes = {}
self.start()
def run(self,task:ComputeTask) -> None:
# check there is compute node can support this task
@@ -35,7 +42,7 @@ class ComputeKernel:
logger.error(f"task {task.display()} is not support by any compute node")
return
# add task to working_queue
self.task_queue.append(task)
self.task_queue.put_nowait(task)
def start(self):
@@ -46,32 +53,72 @@ class ComputeKernel:
self.is_start = True
async def _run_task_loop():
while True:
task = self.task_queue.pop(0)
c_node:ComputeNode= await self._schedule(task)
c_node.push_task(task)
logger.info("compute_kernel is waiting for task...")
task = await self.task_queue.get()
logger.info(f"compute_kernel get task: {task.display()}")
c_node:ComputeNode = self._schedule(task)
await c_node.push_task(task)
logger.warn("compute_kernel is stoped!")
asyncio.create_task(_run_task_loop())
async def _schedule(self,task) -> ComputeNode:
pass
def _schedule(self,task) -> ComputeNode:
for node in self.compute_nodes.values():
if node.is_support(task) is True:
return node
logger.warning(f"task {task.display()} is not support by any compute node")
return None
def add_compute_node(self,node:ComputeNode):
pass
if self.compute_nodes.get(node.node_id) is not None:
logger.warn(f"compute_node {node.display()} already in compute_kernel")
return
self.compute_nodes[node.node_id] = node
logger.info(f"add compute_node {node.display()} to compute_kernel")
def disable_compute_node(self,):
pass
def disable_compute_node(self,node_id:str):
node = self.compute_nodes.get(node_id)
if node is None:
logger.warn(f"compute_node {node_id} not in compute_kernel")
return
node.enable = False
def is_task_support(self,task:ComputeTask) -> bool:
pass
return True
# friendly interface for use:
def llm_completion(self,prompt:AgentPrompt,mode_name:Optional[str] = None,max_token:int = 0) -> ComputeTask:
def llm_completion(self,prompt:AgentPrompt,mode_name:Optional[str] = None,max_token:int = 0):
# craete a llm_work_task ,push on queue's end
# then task_schedule would run this task.(might schedule some work_task to another host)
pass
task_req = ComputeTask()
task_req.set_llm_params(prompt,mode_name,max_token)
self.run(task_req)
return task_req
async def do_llm_completion(self,prompt:AgentPrompt,mode_name:Optional[str] = None,max_token:int = 0) -> str:
pass
task_req = self.llm_completion(prompt,mode_name,max_token)
async def check_timer():
check_times = 0
while True:
if task_req.state == ComputeTaskState.DONE:
break
if task_req.state == ComputeTaskState.ERROR:
break
if check_times >= 20:
task_req.state = ComputeTaskState.ERROR
break
await asyncio.sleep(0.5)
check_times += 1
await asyncio.create_task(check_timer())
if task_req.state == ComputeTaskState.DONE:
return task_req.result.result_str
return "error!"
+7 -2
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@@ -1,11 +1,17 @@
from abc import ABC, abstractmethod
from .compute_kernel import ComputeTask
from .compute_task import ComputeTask
class ComputeNode(ABC):
def __init__(self) -> None:
self.node_id = "default"
self.enable = True
@abstractmethod
async def push_task(self,task:ComputeTask,proiority:int = 0):
pass
@abstractmethod
async def remove_task(self,task_id:str):
pass
@@ -29,7 +35,6 @@ class ComputeNode(ABC):
def is_local(self) -> bool:
pass
@abstractmethod
def is_trusted(self) -> bool:
return True
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@@ -0,0 +1,60 @@
from enum import Enum
import uuid
import time
class ComputeTaskState(Enum):
DONE = 0
INIT = 1
RUNNING = 2
ERROR = 3
PENDING = 4
class ComputeTask:
def __init__(self) -> None:
self.task_type = "llm_completion"
self.create_time = None
self.task_id:str = None
self.callchain_id:str = None
self.params:dict = {}
self.refers:dict = None
self.pading_data:bytearray = None
self.state = ComputeTaskState.INIT
self.result = None
self.error_str = None
def set_llm_params(self,prompts,model_name,max_token_size,callchain_id = None):
self.task_type = "llm_completion"
self.create_time = time.time()
self.task_id = uuid.uuid4().hex
self.callchain_id = callchain_id
self.params["prompts"] = prompts.messages
if model_name is not None:
self.params["model_name"] = model_name
else:
self.params["model_name"] = "gpt-4-0613"
self.params["max_token_size"] = max_token_size
def display(self) -> str:
return f"ComputeTask: {self.task_id} {self.task_type} {self.state}"
class ComputeTaskResult:
def __init__(self) -> None:
self.create_time = None
self.task_id:str = None
self.callchain_id:str = None
self.worker_id:str = None
self.result_code:int = 0
self.result_str:str = None
self.result:dict = {}
self.result_refers:dict = None
self.pading_data:bytearray = None
def set_from_task(self,task:ComputeTask):
self.task_id = task.task_id
self.callchain_id = task.callchain_id
-2
View File
@@ -4,8 +4,6 @@
from abc import ABC, abstractmethod
from typing import Callable
from .agent import AgentMsg
class EnvironmentEvent(ABC):
@abstractmethod
def display(self) -> str:
+103 -1
View File
@@ -1,8 +1,110 @@
import openai
import os
import asyncio
from asyncio import Queue
import logging
from .compute_task import ComputeTask,ComputeTaskResult,ComputeTaskState
from .compute_node import ComputeNode
logger = logging.getLogger(__name__)
class OpenAI_ComputeNode(ComputeNode):
_instance = None
def __new__(cls):
if cls._instance is None:
cls._instance = super(OpenAI_ComputeNode, cls).__new__(cls)
cls._instance.is_start = False
return cls._instance
def __init__(self) -> None:
super().__init__()
if self.is_start is True:
logger.warn("OpenAI_ComputeNode is already start")
return
self.is_start = True
#openai.organization = "org-AoKrOtF2myemvfiFfnsSU8rF" #buckycloud
self.openai_api_key = ""
self.node_id = "openai_node"
self.task_queue = Queue()
if os.getenv("OPENAI_API_KEY") is not None:
openai.api_key = os.getenv("OPENAI_API_KEY")
else:
openai.api_key = self.openai_api_key
self.start()
async def push_task(self,task:ComputeTask,proiority:int = 0):
logger.info(f"openai_node push task: {task.display()}")
self.task_queue.put_nowait(task)
async def remove_task(self,task_id:str):
pass
def _run_task(self,task:ComputeTask):
task.state = ComputeTaskState.RUNNING
mode_name = task.params["model_name"]
# max_token_size = task.params["max_token_size"]
prompts = task.params["prompts"]
logger.info(f"call openai {mode_name} prompts: {prompts}")
resp = openai.ChatCompletion.create(model=mode_name,
messages=prompts,
max_tokens=2000,
temperature=1.2)
logger.info(f"openai response: {resp}")
status_code = resp["choices"][0]["finish_reason"]
if status_code != "stop":
task.state = ComputeTaskState.ERROR
task.error_str =f"The status code was {status_code}."
return None
result = ComputeTaskResult()
result.set_from_task(task)
result.worker_id = self.node_id
result.result_str = resp["choices"][0]["message"]["content"]
result.result = resp["choices"][0]["message"]
return result
def start(self):
async def _run_task_loop():
while True:
logger.info("openai_node is waiting for task...")
task = await self.task_queue.get()
logger.info(f"openai_node get task: {task.display()}")
result = self._run_task(task)
if result is not None:
task.state = ComputeTaskState.DONE
task.result = result
asyncio.create_task(_run_task_loop())
def display(self) -> str:
return super().display()
return f"OpenAI_ComputeNode: {self.node_id}"
def get_task_state(self,task_id:str):
pass
def get_capacity(self):
pass
def is_support(self,task_type:str) -> bool:
return True
def is_local(self) -> bool:
return False
+6 -3
View File
@@ -1,7 +1,9 @@
import logging
import asyncio
from asyncio import Queue
from typing import Optional,Tuple
from abc import ABC, abstractmethod
from .environment import Environment,EnvironmentEvent
from .agent import AgentPrompt,AgentMsg,AIChatSession
@@ -17,13 +19,14 @@ class MessageFilter:
def select(self,msg:AgentMsg) -> AIRole:
pass
class Workflow:
def __init__(self) -> None:
self.rule_prompt : AgentPrompt = None
self.workflow_config = None
self.role_group = None
self.input_filter : MessageFilter= None
self.msg_queue = []
self.msg_queue = Queue()
self.connected_environment = {}
def load_from_disk(self,config_path:str,context_dir_path) -> int:
@@ -34,7 +37,7 @@ class Workflow:
# chatsession is synchronous, it has to wait for the previous message to finish processing before it can process the next message.
# Therefore, post a message needs to specify the session_id explicitly, if not specified it will be automatically created by workflow.
def post_msg(self,msg:AgentMsg) -> None:
self.msg_queue.append(msg)
self.msg_queue.put_nowait(msg)
return
async def send_msg(self,msg:AgentMsg) -> str:
@@ -180,7 +183,7 @@ class Workflow:
def _parse_to_msg(self,llm_resp_str) -> AgentMsg:
pass
def get_workflow(self,workflow_name:str) -> Workflow:
def get_workflow(self,workflow_name:str):
"""get workflow from known workflow list or sub workflow list"""
pass
+1 -3
View File
@@ -1,3 +1 @@
from .agent_manager import AgentManager,AgentManagerClient
from .agent import ai_agent
from .templete import ai_agent_templete
from .agent_manager import AgentManager
+31 -9
View File
@@ -22,13 +22,13 @@ class AgentManager:
def initial(self,root_dir:str) -> None:
self.agent_templete_env : PackageEnv = PackageEnvManager().get_env(f"{root_dir}templetes/agent_templetes.cfg")
self.agent_templete_env : PackageEnv = PackageEnvManager().get_env(f"{root_dir}templetes/templetes.cfg")
self.agent_env : PackageEnv = PackageEnvManager().get_env(f"{root_dir}agents/agents.cfg")
if self.agent_templete_env is None:
raise Exception("agent_manager initial failed")
def get(self,agent_id:str) -> AIAgent:
async def get(self,agent_id:str) -> AIAgent:
the_agent = self.loaded_agent_instance.get(agent_id)
if the_agent:
return the_agent
@@ -38,17 +38,17 @@ class AgentManager:
if agent_media_info is None:
return None
the_agent : AIAgent = self._load_agent_from_media(agent_media_info)
the_agent : AIAgent = await self._load_agent_from_media(agent_media_info)
if the_agent is None:
logger.warn(f"load agent {agent_id} from media failed!")
else:
the_agent.start()
return the_agent
def remove(self,agent_id:str)->int:
pass
def get_templete(self,templete_id) -> AIAgentTemplete:
async def get_templete(self,templete_id) -> AIAgentTemplete:
template_media_info = self.agent_templete_env.get(templete_id)
if template_media_info is None:
return None
@@ -61,11 +61,33 @@ class AgentManager:
def uninstall(self,templete_id) -> int:
pass
def _load_templete_from_media(self,templete_media:PackageMediaInfo) -> AIAgentTemplete:
async def _load_templete_from_media(self,templete_media:PackageMediaInfo) -> AIAgentTemplete:
pass
def _load_agent_from_media(self,agent_media:PackageMediaInfo) -> AIAgent:
pass
async def _load_agent_from_media(self,agent_media:PackageMediaInfo) -> AIAgent:
reader = self.agent_env._create_media_loader(agent_media)
if reader is None:
logger.error(f"create media loader for {agent_media} failed!")
return None
try:
config_file = await reader.read("agent.toml","r")
if config_file is None:
logger.error(f"read agent config from {agent_media} failed!")
return None
config_data = await config_file.read()
config = toml.loads(config_data)
result_agent = AIAgent()
if result_agent.load_from_config(config) is False:
logger.error(f"load agent from {agent_media} failed!")
return None
return result_agent
except Exception as e:
logger.error(f"read agent.toml cfg from {agent_media} failed! unexpected error occurred: {str(e)}")
return None
def create(self,template,agent_name,agent_last_name,agent_introduce) -> AIAgent:
pass
+3
View File
@@ -4,6 +4,9 @@ class ContentId:
def __init__(self) -> None:
pass
def as_str(self) -> str:
pass
@staticmethod
def create_from_str(cid_str:str):
pass
+107 -3
View File
@@ -1,13 +1,117 @@
import asyncio,aiofiles,aiohttp
import logging
from typing import Optional
from .cid import ContentId
logger = logging.getLogger(__name__)
NDN_GET_TASK_STATE_INIT = 0
NDN_GET_TAKS_CONNECTING = 1
NDN_GET_TASK_STATE_DOWNLOADING = 2
NDN_GET_TASK_STATE_VERIFYING = 3
NDN_GET_TASK_STATE_DONE = 4
NDN_GET_TASK_STATE_ERROR = 5
class NDN_GetTask:
def __init__(self) -> None:
self.cid:str = None
self.target_path:str = None
self.urls:[str] = None
self.options:Optional[dict] = None
self.working_task = None
self.state = NDN_GET_TASK_STATE_INIT
self.total_size = 0
self.recv_bytes = 0
self.write_bytes = 0
self.error_str = None
self.chunk_queue = None
self.retry_count = 0
self.used_urls = []
self.hash_update = None
def select_url(self,index:int)->str:
return self.urls[0]
def get_chunk_for_download(self)->bytes:
pass
class NDN_Client:
def __init__(self):
pass
self.cache_dir = ""
self.default_ndn_http_gateway = ""
self.all_task = {}
self.memory_chunk_size = 1024*1024*2
self.chunk_queue_size = 16
def load_config(self,config:dict):
if config.get("cache_dir"):
self.cache_dir = config.get("cache_dir")
if config.get("dndn_gateway"):
self.default_ndn_http_gateway = config.get("ndn_gateway")
def get_file(self,cid:ContentId,target_path:str,urls:{}=None,options:{}=None)->NDN_GetTask:
get_task = self.all_task.get(cid.as_str())
if get_task:
return get_task
else:
get_task = NDN_GetTask()
self.all_task[cid.as_str()] = get_task
get_task.cid = cid
get_task.target_path = target_path
get_task.urls = urls
get_task.options = options
if get_task.urls is None:
get_task.urls = [f"{self.default_ndn_http_gateway}/{cid.as_str()}"]
logger.info(f"get_file {cid.as_str()} urls is None, use {get_task.urls[0]} as default")
async def get_file_async():
target_file = aiofiles.open(target, 'wb')
# if file exist, check hash first
http_session = aiohttp.ClientSession()
resp = http_session.get(get_task.select_url(0))
if resp.status != 200:
get_task.error_str = f"get_file {cid.as_str()} failed,http status:{resp.status}"
return
get_task.total_size = resp.content_length
async def write_file_async():
while True:
chunk = await get_task.chunk_queue.pop()
chunk_size = len(chunk)
if not chunk or chunk_size == 0:
break
get_task.hash_update.update(chunk)
await target_file.write(chunk)
get_task.write_bytes += chunk_size
#verify
get_task.state = NDN_GET_TASK_STATE_VERIFYING
await target_file.close()
return
write_task = asyncio.create_task(write_file_async())
while True:
await get_task.chunk_queue.pop()
chunk = resp.content.read(self.memory_chunk_size)
chunk_size = len(chunk)
if not chunk or chunk_size == 0:
break
get_task.recv_bytes += len(chunk)
get_task.chunk_queue.push(chunk)
get_task.state = NDN_GET_TASK_STATE_DONE
await write_task
get_task.working_task = asyncio.create_task(get_file_async())
return get_task
def get_file(self,cid:ContentId,target_path:str,urls:{}=None,options:{}=None):
pass
+127 -105
View File
@@ -1,13 +1,137 @@
import logging
import toml
import os
from .pkg import PackageInfo,PackageMediaInfo,
from .env import PackageEnv
from .installer import PackageInstaller,PackageInstallTask
from .pkg import PackageInfo,PackageMediaInfo
from .media_reader import MediaReader
logger = logging.getLogger(__name__)
class PackageEnv:
def __init__(self,cfg_path:str) -> None:
self.pkg_dir : str = "./pkgs/"
self.pkg_obj_dir : str = "./.pkgs/"
self.locked_index : str = "./pkg.lock"
self.is_strict : bool = True
self.parent_envs : list[PackageEnv] = None
self.index_dbs = None
self.env_dir = None
self.cfg_path = cfg_path
self._load_pkg_cfg(cfg_path)
pass
def load_from_config(self,config:dict) -> bool:
if config.get("main") is not None:
self.pkg_dir = os.path.abspath(self.env_dir + "/" + config["main"])
if config.get("cache") is not None:
self.pkg_obj_dir = os.path.abspath(self.env_dir + "/ " + config["cache"])
def load(self,pkg_name:str,search_parent=True) -> PackageMediaInfo:
pkg_path = None
pkg_id,verion_str,cid = PackageInfo.parse_pkg_name(pkg_name)
if cid is None:
if verion_str is None:
pkg_path = f"{self.pkg_dir}/{pkg_id}"
else:
#TODO fix bug about channel here
channel:str = self.get_pkg_channel_from_version(verion_str)
the_version:str = self.get_exact_version_from_installed(verion_str)
if the_version is None:
logger.warn(f"load {pkg_name} failed: no match version from {verion_str}")
return None
if channel is None:
pkg_path = f"{self.pkg_dir}/{pkg_id}#{the_version}"
else:
pkg_path = f"{self.pkg_dir}/{pkg_id}#{channel}#{the_version}"
else:
pkg_path = f"{self.pkg_obj_dir}/.{pkg_id}/{cid}"
media_info:PackageMediaInfo = self.try_load_pkg_media_info(pkg_path)
if media_info is None:
if search_parent is True and self.parent_envs is not None:
for parent_env in self.parent_envs:
media_info = parent_env.load(pkg_id,cid,False)
if media_info is not None:
return media_info
if media_info is None:
logger.warn(f"pkg_load {pkg_id}, cid:{cid} error,not found ,search_parent={search_parent}")
return media_info
def get_exact_version_from_installed(self,verion_str:str) -> str:
pass
def get_pkg_channel_from_version(self,pkg_version:str) -> str:
args = pkg_version.split("~")
if len(args) == 1:
return None
else:
return args[0]
def get_pkg_media_info(self,pkg_name:str)->PackageMediaInfo:
pass
def try_load_pkg_media_info(self,pkg_full_path:str) -> PackageMediaInfo:
the_result : PackageMediaInfo = None
logger.debug(f"try load pkng from:{pkg_full_path}")
if os.path.isdir(pkg_full_path):
the_result = PackageMediaInfo(pkg_full_path,"dir")
return the_result
def _create_media_loader(self,media_info:PackageMediaInfo) -> MediaReader:
match media_info.media_type:
case "dir":
from .media_reader import FolderMediaReader
return FolderMediaReader(media_info.full_path)
logger.error(f"create media loader for {media_info} failed!")
return None
def get_installed_pkg_info(self,pkg_name:str) -> PackageInfo:
pass
def lookup(self,pkg_id:str,version_str:str) -> PackageInfo:
# to make sure pkg.cid is correct, we MUST verfiy eveything here
pass
@classmethod
def is_valied_media(pkg_full_path:str) -> bool:
pass
def do_pkg_media_trans(self,pkg_info:PackageInfo,source_path:str,target_path:str) -> bool:
pass
def _load_pkg_cfg(self,cfg_path:str):
if cfg_path is None:
return
cfg = None
if len(cfg_path) < 1:
return
try:
cfg = toml.load(cfg_path)
self.env_dir = os.path.abspath(os.path.dirname(cfg_path))
self.cfg_path = os.path.abspath(cfg_path)
except Exception as e:
logger.error(f"read pkg cfg from {cfg_path} failed! unexpected error occurred: {str(e)}")
return
return self.load_from_config(cfg)
def _preprocess_prefixs(self,prefixs):
pass
class PackageEnvManager:
_instance = None
def __new__(cls):
@@ -33,105 +157,3 @@ class PackageEnvManager:
def get_system_env(self) -> PackageEnv:
pass
class PackageEnv:
def __init__(self,cfg_path:str) -> None:
self.pkg_dir : str = ""
self.pkg_obj_dir : str = ""
self.is_strict : bool = True
self.parent_envs : list[PackageEnv] = None
self.index_dbs = None
self.cfg_path = cfg_path
self._load_pkg_cfg(cfg_path)
pass
def load(self,pkg_name:str,search_parent=True) -> PackageMediaInfo:
pkg_path = None
pkg_id,verion_str,cid = PackageInfo.parse_pkg_name(pkg_name)
if cid is None:
if verion_str is None:
channel:str = self.get_pkg_channel_from_version(verion_str)
if channel is None:
pkg_path = f"{self.pkg_dir}{pkg_id}"
else:
pkg_path = f"{self.pkg_dir}{pkg_id}#{channel}"
else:
channel:str = self.get_pkg_channel_from_version(verion_str)
the_version:str = self.get_exact_version_from_installed(verion_str)
if the_version is None:
logger.warn(f"load {pkg_name} failed: no match version from {verion_str}")
return None
if channel is None:
pkg_path = f"{self.pkg_dir}{pkg_id}#{the_version}"
else:
pkg_path = f"{self.pkg_dir}{pkg_id}#{channel}#{the_version}"
else:
pkg_path = f"{self.pkg_obj_dir}.{pkg_id}/{cid}"
media_info:PackageMediaInfo = self.try_load_pkg_media_info(pkg_path)
if media_info is None:
if search_parent:
for parent_env in self.parent_envs:
media_info = parent_env.load(pkg_id,cid,False)
if media_info is not None:
return media_info
logger.warn(f"load {pkg_id}#{cid} error,not found ,search_parent={search_parent}")
return None
def get_exact_version_from_installed(self,verion_str:str) -> str:
pass
def get_pkg_channel_from_version(self,pkg_version:str) -> str:
pass
def get_pkg_media_info(self,pkg_name:str)->PackageMediaInfo:
pass
def try_load_pkg_media_info(self,pkg_full_path:str) -> PackageMediaInfo:
pass
def get_installed_pkg_info(self,pkg_name:str) -> PackageInfo:
pass
def lookup(self,pkg_id:str,version_str:str) -> PackageInfo:
# to make sure pkg.cid is correct, we MUST verfiy eveything here
pass
def get_installer(self) -> PackageInstaller:
pass
@classmethod
def is_valied_media(pkg_full_path:str) -> bool:
pass
def do_pkg_media_trans(self,pkg_info:PackageInfo,source_path:str,target_path:str) -> bool:
pass
def _load_pkg_cfg(self,cfg_path:str):
if cfg_path is None:
return
cfg = None
if len(cfg_path) < 1:
return
try:
cfg = toml.load(cfg_path)
except Exception as e:
logger.error(f"read pkg cfg from {cfg_path} failed! unexpected error occurred: {str(e)}")
return
if cfg:
if cfg.env:
if cfg.env.is_strict is not None:
self.is_strict = cfg.env.is_strict
if cfg.env.prefixs is not None:
self.prefixs = self._preprocess_prefixs(cfg.env.prefixs)
def _preprocess_prefixs(self,prefixs):
pass
+14 -5
View File
@@ -1,9 +1,18 @@
class MediaReader:
def __init__(self):
from abc import ABC, abstractmethod
import aiofiles
class MediaReader(ABC):
@abstractmethod
async def read(self, inner_path:str,mode:str):
pass
def load_from_media(self,media_info:str) -> int:
class FolderMediaReader(MediaReader):
def __init__(self, root_dir:str) -> None:
self.root_dir = root_dir
pass
def read(self, inner_path:str):
raise NotImplementedError
async def read(self, inner_path:str,mode:str):
full_path = self.root_dir + "/" + inner_path
result_file = await aiofiles.open(full_path, mode,encoding='utf-8')
return result_file
+17 -6
View File
@@ -11,10 +11,20 @@ class PackageInfo:
self.target_media_type = "dir"
self.source_media_type = "7z"
@classmethod
def parse_pkg_name(cls,pkg_name:str) -> Tuple[str, str, str]:
"""parse pkg name like test-pkg#nightly#>0.2.31#sha1:323423423 to test-pkg,nightly#>0.2.31,sha1:323423423"""
pass
@staticmethod
def parse_pkg_name(pkg_name:str) -> Tuple[str, str, str]:
"""parse pkg name like test-pkg#nightly~>0.2.31#sha1:323423423 to test-pkg,nightly#>0.2.31,sha1:323423423"""
args = pkg_name.split("#")
if len(args) == 1:
return args[0],None,None
elif len(args) == 2:
return args[0],None,arg[2]
elif len(args) == 3:
return args[0],args[1],args[2]
else:
logger.error(f"parse pkg name {pkg_name} failed!")
return None,None,None
@@ -23,8 +33,9 @@ class PackageInfo:
return self.cid
class PackageMediaInfo:
def __init__(self) -> None:
pass
def __init__(self,full_path,media_type) -> None:
self.media_type = media_type
self.full_path = full_path
@@ -0,0 +1 @@
from .workflow_manager import WorkflowManager
@@ -0,0 +1,11 @@
from aios_kernel import Workflow
class WorkflowManager:
def __init__(self) -> None:
pass
def initial(self,root_dir:str) -> None:
pass
def get_workflow(self,workflow_id:str) -> Workflow:
pass
+128
View File
@@ -0,0 +1,128 @@
# aiso shell like bash for linux
import asyncio
import sys
import os
import logging
from typing import Any, Optional, TypeVar, Tuple, Sequence
import argparse
from prompt_toolkit.formatted_text.base import AnyFormattedText
from prompt_toolkit import Application, PromptSession, prompt
from prompt_toolkit.selection import SelectionState
from prompt_toolkit.history import FileHistory
from prompt_toolkit.auto_suggest import AutoSuggestFromHistory
from prompt_toolkit.completion import WordCompleter
directory = os.path.dirname(__file__)
sys.path.append(directory + '/../../')
from aios_kernel import Workflow,AIAgent,AgentMsg,AgentMsgState,ComputeKernel,OpenAI_ComputeNode
sys.path.append(directory + '/../../component/')
from agent_manager import AgentManager
from workflow_manager import WorkflowManager
class AIOS_Shell:
def __init__(self,username:str) -> None:
self.username = username
self.user_chatsession = {}
async def initial(self) -> bool:
AgentManager().initial(directory + "/../../../rootfs/")
WorkflowManager().initial(directory + "/../../../../rootfs/workflows/workflows.cfg")
open_ai_node = OpenAI_ComputeNode()
open_ai_node.start()
ComputeKernel().add_compute_node(open_ai_node)
return True
def get_version(self) -> str:
return "0.0.1"
async def send_msg(self,msg:str,target_id:str,sender:str = None) -> str:
agent_msg = AgentMsg()
agent_msg.set(sender,target_id,msg)
agent : AIAgent = await AgentManager().get(target_id)
if agent is not None:
agent.post_msg(agent_msg)
a_workflow = WorkflowManager().get_workflow(target_id)
if a_workflow is not None:
a_workflow.post_msg(agent_msg)
async def check_timer():
check_times = 0
while True:
if agent_msg.state == AgentMsgState.RESPONSED:
break
if agent_msg.state == AgentMsgState.ERROR:
break
if check_times >= 20:
agent_msg.state = AgentMsgState.ERROR
break
await asyncio.sleep(0.5)
check_times += 1
await asyncio.create_task(check_timer())
if agent_msg.state == AgentMsgState.RESPONSED:
return agent_msg.resp_msg.body
return "error!"
async def install_workflow(self,workflow_id:Workflow) -> None:
pass
#######################################################################################
def proc_input_by_agent():
pass
def show_help():
print("this is help")
async def main():
print("aios shell prepareing...")
logging.basicConfig(level=logging.INFO,
format='%(asctime)s %(name)s %(levelname)s %(message)s')
shell = AIOS_Shell("user")
await shell.initial()
print(f"aios shell {shell.get_version()} ready.")
completer = WordCompleter(['list agent', 'list workflow', 'exit', 'help'], ignore_case=True)
#history = FileHistory('history.txt')
while True:
user_input = await PromptSession().prompt_async('>>> ',completer=completer)
match user_input:
case "list agent":
print(AgentManager().list_agent())
case "list workflow":
print(WorkflowManager().list_workflow())
case "help":
show_help()
case "exit":
break
if user_input.startswith("send"):
args = user_input.split(" ")
if len(args) < 3:
print("send msg failed, usage: send target_id msg_content")
continue
target_id = args[1]
msg_content = args[2]
resp = await shell.send_msg(msg_content,target_id,shell.username)
print(f"<<< {resp}")
if __name__ == "__main__":
asyncio.run(main())