Merge branch 'fiatrete:MVP' into MVP

This commit is contained in:
wugren
2023-09-15 00:34:16 +08:00
committed by GitHub
21 changed files with 786 additions and 348 deletions
+1
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@@ -2,3 +2,4 @@
*.pyc
rootfs/email/config.local.toml
rootfs/data
venv
+2 -2
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@@ -46,7 +46,7 @@ The previous plan, please see here: [MVP Plan](./mvp%20plan.md)
- [ ] MPT-7B, S2
- [ ] Vicuna, S2
- [ ] Embeding,@photosssa,@lurenpluto , A4
- [ ] Txt2img,@glen0125,A4
- [x] Txt2img,@glen0125,A4
- [ ] Img2txt(0.5.2),A3
- [ ] Txt2voice,A3
- [ ] Voice2txt, @wugren,A3
@@ -70,7 +70,7 @@ The previous plan, please see here: [MVP Plan](./mvp%20plan.md)
- [ ] Telegram Tunnel,S2
- [ ] Discord Tunnel,S2
- [ ] Home IoT Environment (0.5.2), A4
- [] Compatible Home Assistant (0.5.2), A4
- [ ] Compatible Home Assistant (0.5.2), A4
- [ ] Build-in Agents/Apps
- [ ] Agent: Personal Information Assistant,@photosssa,@lurenpluto , A2
- [ ] Agent: Bulter Jarvis,@waterflier, A2
+27 -1
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@@ -1,6 +1,6 @@
<mxfile host="65bd71144e" pages="3">
<diagram id="C5RBs43oDa-KdzZeNtuy" name="Page-1">
<mxGraphModel dx="1881" dy="676" 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="2069" dy="1139" 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"/>
@@ -365,4 +365,30 @@
</root>
</mxGraphModel>
</diagram>
<diagram id="zNgk-d6xdACtSja1wnUq" name="Page-4">
<mxGraphModel dx="2069" dy="1139" grid="1" gridSize="10" guides="1" tooltips="1" connect="1" arrows="1" fold="1" page="1" pageScale="1" pageWidth="1100" pageHeight="850" math="0" shadow="0">
<root>
<mxCell id="0"/>
<mxCell id="1" parent="0"/>
<mxCell id="PKOyaMforMDOFoUY4PA1-1" value="ChatSession" style="rounded=1;whiteSpace=wrap;html=1;" vertex="1" parent="1">
<mxGeometry x="140" y="150" width="120" height="60" as="geometry"/>
</mxCell>
<mxCell id="PKOyaMforMDOFoUY4PA1-2" value="SubSession" style="rounded=1;whiteSpace=wrap;html=1;" vertex="1" parent="1">
<mxGeometry x="230" y="240" width="120" height="60" as="geometry"/>
</mxCell>
<mxCell id="PKOyaMforMDOFoUY4PA1-3" value="SubSession" style="rounded=1;whiteSpace=wrap;html=1;" vertex="1" parent="1">
<mxGeometry x="230" y="330" width="120" height="60" as="geometry"/>
</mxCell>
<mxCell id="PKOyaMforMDOFoUY4PA1-4" value="Agent Message" style="shape=hexagon;perimeter=hexagonPerimeter2;whiteSpace=wrap;html=1;fixedSize=1;" vertex="1" parent="1">
<mxGeometry x="600" y="150" width="130" height="60" as="geometry"/>
</mxCell>
<mxCell id="PKOyaMforMDOFoUY4PA1-5" value="Agent Message" style="shape=hexagon;perimeter=hexagonPerimeter2;whiteSpace=wrap;html=1;fixedSize=1;" vertex="1" parent="1">
<mxGeometry x="600" y="230" width="130" height="60" as="geometry"/>
</mxCell>
<mxCell id="PKOyaMforMDOFoUY4PA1-6" value="Agent Message" style="shape=hexagon;perimeter=hexagonPerimeter2;whiteSpace=wrap;html=1;fixedSize=1;" vertex="1" parent="1">
<mxGeometry x="600" y="320" width="130" height="60" as="geometry"/>
</mxCell>
</root>
</mxGraphModel>
</diagram>
</mxfile>
+1
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@@ -1,5 +1,6 @@
instance_id = "agent_1"
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。"
+1 -1
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@@ -7,7 +7,7 @@ GOAL="成为最好的学校"
[[connected_env]]
env_id = "calender"
[[connected_env.event2msg]]
timer = "现在是{data}"
timer = "现在是{now}"
role = "教导处主任"
[filter]
+4 -2
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@@ -42,11 +42,13 @@ fullname = "经理"
agent="manager"
[[roles.manager.prompt]]
role="system"
content="""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:
content="""
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 sendmsg(小组名称,内容) 的形式。"""
4. 当你决定要和工作小组通信时,请使用 sendmsg(小组名称,内容) 的形式。
"""
+1 -1
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@@ -1,5 +1,5 @@
from .environment import Environment,EnvironmentEvent
from .agent_message import AgentMsg,AgentMsgState
from .agent_message import AgentMsg,AgentMsgStatus
from .chatsession import AIChatSession
from .agent import AIAgent,AIAgentTemplete,AgentPrompt
from .compute_kernel import ComputeKernel,ComputeTask
+82 -57
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@@ -5,9 +5,13 @@ import asyncio
import logging
import uuid
import time
import json
from .agent_message import AgentMsg
from .agent_message import AgentMsg, AgentMsgStatus, AgentMsgType
from .chatsession import AIChatSession
from .compute_task import ComputeTaskResult
from .ai_function import AIFunction
from .environment import Environment
logger = logging.getLogger(__name__)
@@ -69,7 +73,7 @@ class AIAgent:
self.prompt:AgentPrompt = None
self.llm_model_name:str = None
self.max_token_size:int = 3600
self.instance_id:str = None
self.agent_id:str = None
self.template_id:str = None
self.fullname:str = None
self.powerby = None
@@ -77,6 +81,8 @@ class AIAgent:
self.chat_db = None
self.unread_msg = Queue() # msg from other agent
self.owner_env : Environment = None
self.owenr_bus : AIBus = None
@classmethod
def create_from_templete(cls,templete:AIAgentTemplete, fullname:str):
@@ -85,7 +91,7 @@ class 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.agent_id = "agent#" + uuid.uuid4().hex
result_agent.fullname = fullname
result_agent.powerby = templete.author
result_agent.prompt = templete.prompt
@@ -95,10 +101,10 @@ class AIAgent:
if config.get("instance_id") is None:
logger.error("agent instance_id is None!")
return False
self.instance_id = config["instance_id"]
self.agent_id = config["instance_id"]
if config.get("fullname") is None:
logger.error(f"agent {self.instance_id} fullname is None!")
logger.error(f"agent {self.agent_id} fullname is None!")
return False
self.fullname = config["fullname"]
@@ -124,14 +130,65 @@ class AIAgent:
return "text"
def _get_inner_functions(self) -> dict:
if self.owner_env is None:
return None
all_inner_function = self.owner_env.get_all_ai_functions()
if all_inner_function is None:
return None
result_func = []
for inner_func in all_inner_function:
this_func = {}
this_func["name"] = inner_func.get_name()
this_func["description"] = inner_func.get_description()
this_func["parameters"] = inner_func.get_parameters()
result_func.append(this_func)
return result_func
async def _execute_func(self,inenr_func_call_node:dict,prompt:AgentPrompt,org_msg:AgentMsg) -> str:
from .compute_kernel import ComputeKernel
func_name = inenr_func_call_node.get("name")
arguments = json.loads(inenr_func_call_node.get("arguments"))
func_node : AIFunction = self.owner_env.get_ai_function(func_name)
if func_node is None:
return "execute failed,function not found"
ineternal_call_record = AgentMsg.create_internal_call_msg(func_name,arguments,org_msg.get_msg_id(),org_msg.target)
result_str:str = await func_node.execute(**arguments)
inner_functions = self._get_inner_functions()
prompt.messages.append({"role":"function","content":result_str,"name":func_name})
task_result:ComputeTaskResult = await ComputeKernel().do_llm_completion(prompt,self.llm_model_name,self.max_token_size,inner_functions)
ineternal_call_record.result_str = task_result.result_str
ineternal_call_record.done_time = time.time()
org_msg.inner_call_chain.append(ineternal_call_record)
inner_func_call_node = task_result.result_message.get("function_call")
if inner_func_call_node:
return await self._execute_func(inner_func_call_node,prompt,org_msg)
else:
return task_result.result_str
async def _process_msg(self,msg:AgentMsg) -> AgentMsg:
from .compute_kernel import ComputeKernel
session_topic = msg.get_sender() + "#" + msg.topic
chatsession = AIChatSession.get_session(self.instance_id,session_topic,self.chat_db)
chatsession = AIChatSession.get_session(self.agent_id,session_topic,self.chat_db)
if msg.mentions is not None:
if not self.agent_id in msg.mentions:
chatsession.append(msg)
logger.info(f"agent {self.agent_id} recv a group chat message from {msg.sender},but is not mentioned,ignore!")
return None
prompt = AgentPrompt()
prompt.append(self.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)) # chat context
@@ -139,67 +196,34 @@ class AIAgent:
msg_prompt.messages = [{"role":"user","content":msg.body}]
prompt.append(msg_prompt)
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)
inner_functions = self._get_inner_functions()
task_result:ComputeTaskResult = await ComputeKernel().do_llm_completion(prompt,self.llm_model_name,self.max_token_size,inner_functions)
final_result = task_result.result_str
inner_func_call_node = task_result.result_message.get("function_call")
if inner_func_call_node:
#TODO to save more token ,can i use msg_prompt?
final_result = await self._execute_func(inner_func_call_node,prompt,msg)
result_type : str = self._get_llm_result_type(final_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?
resp_msg = AgentMsg()
resp_msg.set(self.instance_id,msg.sender,final_result)
resp_msg.topic = msg.topic
if chatsession is not None:
chatsession.append_recv(msg)
chatsession.append_post(resp_msg)
resp_msg = msg.create_resp_msg(final_result)
chatsession.append(msg)
chatsession.append(resp_msg)
return resp_msg
return None
def get_id(self) -> str:
return self.instance_id
return self.agent_id
def get_fullname(self) -> str:
return self.fullname
@@ -213,7 +237,8 @@ class AIAgent:
def get_max_token_size(self) -> int:
return self.max_token_size
async def _get_prompt_from_session(self,chatsession:AIChatSession) -> AgentPrompt:
async def _get_prompt_from_session(self,chatsession:AIChatSession,is_groupchat=False) -> AgentPrompt:
# TODO: get prompt from group chat is different from single chat
messages = chatsession.read_history() # read last 10 message
result_prompt = AgentPrompt()
for msg in reversed(messages):
+88 -8
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@@ -3,26 +3,100 @@ import uuid
import time
import re
class AgentMsgState(Enum):
class AgentMsgType(Enum):
TYPE_MSG = 0
TYPE_INTERNAL_CALL = 1
TYPE_ACTION = 2
TYPE_EVENT = 3
class AgentMsgStatus(Enum):
RESPONSED = 0
INIT = 1
SENDING = 2
PROCESSING = 3
ERROR = 4
RECVED = 5
EXECUTED = 6
# msg is a msg / msg resp
# msg body可以有内容类型(MIME标签),text, image, voice, video, file,以及富文本(html)
# msg is a inner function call with result
# msg is a Action with result
# qutoe Msg
# forword msg
# reply msg
# 逻辑上的同一个Message在同一个session中看到的msgid相同
# 在不同的session中看到的msgid不同
class AgentMsg:
def __init__(self) -> None:
def __init__(self,msg_type=AgentMsgType.TYPE_MSG) -> None:
self.msg_id = ""
self.msg_type:AgentMsgType = msg_type
self.prev_msg_id:str = None
self.quote_msg_id:str = None
self.rely_msg_id:str = None # if not none means this is a respone msg
self.session_id:str = None
self.create_time = 0
self.sender:str = None
self.done_time = 0
self.topic:str = None # topic is use to find session, not store in db
self.sender:str = None # obj_id.sub_objid@tunnel_id
self.target:str = None
self.mentions:[] = None #use in group chat only
#self.title:str = None
self.body:str = None
self.topic:str = "T#" + uuid.uuid4().hex
#self.msg_type = 0
self.state = AgentMsgState.INIT
self.body_mime:str = None #//default is "text/plain",encode is utf8
#type is call / action
self.func_name = None
self.args = None
self.result_str = None
#type is event
self.event_name = None
self.event_args = None
self.status = AgentMsgStatus.INIT
self.inner_call_chain = []
self.resp_msg = None
@classmethod
def create_internal_call_msg(self,func_name:str,args:dict,prev_msg_id:str,caller:str):
msg = AgentMsg(AgentMsgType.TYPE_INTERNAL_CALL)
msg.func_name = func_name
msg.args = args
msg.prev_msg_id = prev_msg_id
msg.sender = caller
return msg
def create_action_msg(self,action_name:str,args:dict,caller:str):
msg = AgentMsg(AgentMsgType.TYPE_ACTION)
msg.func_name = action_name
msg.args = args
msg.prev_msg_id = self.msg_id
msg.topic = self.topic
msg.sender = caller
return msg
def create_resp_msg(self,resp_body):
resp_msg = AgentMsg()
resp_msg.msg_id = "msg#" + uuid.uuid4().hex
self.create_time = time.time()
resp_msg.rely_msg_id = self.msg_id
resp_msg.sender = self.target
resp_msg.target = self.sender
resp_msg.body = resp_body
resp_msg.topic = self.topic
return resp_msg
def set(self,sender:str,target:str,body:str,topic:str=None) -> None:
self.id = "msg#" + uuid.uuid4().hex
self.msg_id = "msg#" + uuid.uuid4().hex
self.sender = sender
self.target = target
self.body = body
@@ -31,7 +105,7 @@ class AgentMsg:
self.topic = topic
def get_msg_id(self) -> str:
return self.id
return self.msg_id
def get_sender(self) -> str:
return self.sender
@@ -39,6 +113,12 @@ class AgentMsg:
def get_target(self) -> str:
return self.target
def get_prev_msg_id(self) -> str:
return self.prev_msg_id
def get_quote_msg_id(self) -> str:
return self.quote_msg_id
@classmethod
def parse_function_call(cls,func_string:str):
match = re.search(r'\s*(\w+)\s*\(\s*(.*)\s*\)\s*', func_string)
+47 -4
View File
@@ -1,9 +1,9 @@
from abc import ABC, abstractmethod
from typing import Dict
from typing import Dict,Coroutine,Callable
class AIFunction:
def __init__(self) -> None:
self.intro : str = None
self.description : str = None
@abstractmethod
def get_name(self) -> str:
@@ -17,7 +17,7 @@ class AIFunction:
"""
return a detailed description of what the function does
"""
pass
return self.description
@abstractmethod
def get_parameters(self) -> Dict:
@@ -25,11 +25,23 @@ class AIFunction:
Return the list of parameters to execute this function in the form of
JSON schema as specified in the OpenAI documentation:
https://platform.openai.com/docs/api-reference/chat/create#chat/create-parameters
str = run_code(code:str)
parameters = {
"type": "object",
"properties": {
"code": {
"type": "string",
"description": "Python code which needs to be executed"
}
}
}
"""
pass
@abstractmethod
def execute(self, **kwargs) -> Dict:
async def execute(self, **kwargs) -> str:
"""
Execute the function and return a JSON serializable dict.
The parameters are passed in the form of kwargs
@@ -67,3 +79,34 @@ class CallChain:
async def execute(self):
pass
class SimpleAIFunction(AIFunction):
def __init__(self,func_id:str,description:str,func_handler:Coroutine,parameters:Dict = None) -> None:
self.func_id = func_id
self.description = description
self.func_handler = func_handler
self.parameters = parameters
def get_name(self) -> str:
return self.func_id
def get_parameters(self) -> Dict:
if self.parameters is not None:
return self.parameters
return {"type": "object", "properties": {}}
async def execute(self,**kwargs) -> str:
if self.func_handler is None:
return "error: function not implemented"
return await self.func_handler(**kwargs)
def is_local(self) -> bool:
return True
def is_in_zone(self) -> bool:
return True
def is_ready_only(self) -> bool:
return False
+43 -46
View File
@@ -1,5 +1,5 @@
from typing import Any
from .agent_message import AgentMsg,AgentMsgState
from typing import Coroutine,Dict,Any
from .agent_message import AgentMsg,AgentMsgStatus
import asyncio
from asyncio import Queue
@@ -8,19 +8,32 @@ import logging
logger = logging.getLogger(__name__)
class AIBusHandler:
def __init__(self,handler:Any) -> None:
def __init__(self,handler:Coroutine,owner_bus,enable_defualt_proc=True) -> None:
self.handler = handler
self.working_task = None
self.results = {}
self.results = {} # recv resps
self.queue:Queue = Queue()
self.enable_defualt_proc = enable_defualt_proc
self.owner_bus = owner_bus
async def handle_message(self,msg:AgentMsg) -> Any:
if self.handler is None:
return None
return await self.handler(msg)
if self.enable_defualt_proc:
# do default process
if msg.rely_msg_id is not None:
self.results[msg.rely_msg_id] = msg
return None
resp_msg = await self.handler(msg)
if self.enable_defualt_proc:
if resp_msg is not None:
await self.owner_bus.post_message(resp_msg,False)
return resp_msg
class AIBus:
_instance = None
@classmethod
@@ -30,11 +43,13 @@ class AIBus:
return cls._instance
def __init__(self) -> None:
self.handlers = {}
self.unhandle_handler = None
self.handlers:Dict[AIBusHandler] = {}
self.unhandle_handler:Coroutine = None
async def post_message(self,msg:AgentMsg,use_unhandle=True) -> bool:
target_id = msg.target.split(".")[0]
async def post_message(self,target_id,msg:AgentMsg,use_unhandle=True) -> bool:
target_id = target_id.split(".")[0]
handler = self.handlers.get(target_id)
if handler:
handler.queue.put_nowait(msg)
@@ -44,46 +59,39 @@ class AIBus:
if use_unhandle:
if self.unhandle_handler is not None:
if await self.unhandle_handler(self,msg):
return await self.post_message(target_id,msg,False)
return await self.post_message(msg,False)
logger.warn(f"post message to {msg.target} failed!,target not found")
return False
def resp_message(self,my_id:str,org_msg_id:str,resp:AgentMsg) -> None:
handler = self.handlers.get(my_id)
if handler is None:
return None
handler.results[org_msg_id] = resp
async def resp_message(self,org_msg_id:str,resp:AgentMsg) -> None:
assert resp.rely_msg_id == org_msg_id
return await self.post_message(resp)
async def get_message_resp(self,name:str,msg_id:str) -> AgentMsg:
handler = self.handlers.get(name)
if handler is None:
async def send_message(self,msg:AgentMsg) -> AgentMsg:
sender_id = msg.sender.split(".")[0]
sender_handler = self.handlers.get(sender_id) # sender already register on bus
if sender_handler is None:
logger.warn(f"sender {sender_id} not register on AI_BUS!")
return None
return handler.results.get(msg_id)
async def send_message(self,target_id:str,msg:AgentMsg) -> AgentMsg:
target_id = target_id.split(".")[0]
post_result = await self.post_message(target_id,msg)
post_result = await self.post_message(msg)
if post_result is False:
return None
handler = self.handlers.get(target_id)
if handler is None:
return None
retry_times = 0
while True:
resp = handler.results.get(msg.id)
resp = sender_handler.results.get(msg.msg_id)
if resp is not None:
msg.resp_msg = resp
msg.state = AgentMsgState.RESPONSED
msg.status = AgentMsgStatus.RESPONSED
del sender_handler.results[msg.msg_id]
return resp
await asyncio.sleep(0.2)
retry_times += 1
if retry_times > 100:
msg.state = AgentMsgState.ERROR
msg.status = AgentMsgStatus.ERROR
return None
return None
@@ -93,7 +101,7 @@ class AIBus:
# means sub
def register_message_handler(self,handler_name:str,handler:Any) -> Queue:
handler_node = AIBusHandler(handler)
handler_node = AIBusHandler(handler,self)
self.handlers[handler_name] = handler_node
return handler_node.queue
@@ -102,13 +110,12 @@ class AIBus:
# Wait for a message
message = await handler.queue.get()
try:
#try:
# Try to handle the message
result = await handler.handle_message(message)
handler.results[message.id] = result
except Exception as e:
await handler.handle_message(message)
#except Exception as e:
# If an error occurs, put the message back into the queue
logger.error(f"handle message {message.id} failed! {e}")
# logger.error(f"handle message {message.msg_id} failed! {e}")
#self.queues[name].put_nowait(message)
return
@@ -127,13 +134,3 @@ class AIBus:
return
handler.working_task = asyncio.create_task(self.process_queue(handler))
#send message to target logic:
# find target handler:
# process_message(msg):
# session = get_session(msg.sender,msg.target)
# history: open(sender,target,topic)
+73 -25
View File
@@ -5,8 +5,9 @@ import logging
import threading
import datetime
import uuid
import json
from .agent_message import AgentMsg
from .agent_message import AgentMsgType, AgentMsg, AgentMsgStatus
class ChatSessionDB:
def __init__(self, db_file):
@@ -54,14 +55,31 @@ class ChatSessionDB:
""")
# create messages table
# reciver_id could be None
conn.execute("""
CREATE TABLE IF NOT EXISTS Messages (
MessageID TEXT PRIMARY KEY,
SessionID TEXT,
MsgType INTEGER,
PrevMsgID TEXT,
QuoteMsgID TEXT,
RelyMsgID TEXT,
SenderID TEXT,
ReceiverID TEXT,
Timestamp TEXT,
Topic TEXT,
Mentions TEXT,
ContentMIME TEXT,
Content TEXT,
ActionName TEXT,
ActionParams TEXT,
ActionResult TEXT,
DoneTime TEXT,
Status INTEGER
);
""")
@@ -83,15 +101,43 @@ class ChatSessionDB:
logging.error("Error occurred while inserting session: %s", e)
return -1 # return -1 if an error occurs
def insert_message(self, message_id, session_id, sender_id, receiver_id, timestamp, content, status):
def insert_message(self, msg:AgentMsg):
""" insert a new message into the Messages table """
try:
action_name = None
action_params = None
action_result = None
mentions = None
if msg.mentions:
mentions = json.dumps(msg.mentions)
match msg.msg_type:
case AgentMsgType.TYPE_MSG:
pass
case AgentMsgType.TYPE_ACTION:
action_name = msg.func_name
action_params = json.dumps(msg.args)
action_result = msg.result_str
case AgentMsgType.TYPE_INTERNAL_CALL:
action_name = msg.func_name
action_params = json.dumps(msg.args)
action_result = msg.result_str
case AgentMsgType.TYPE_EVENT:
action_name = msg.event_name
action_params = json.dumps(msg.event_args)
conn = self._get_conn()
conn.execute("""
INSERT INTO Messages (MessageID, SessionID, SenderID, ReceiverID, Timestamp, Content, Status)
VALUES (?, ?, ?, ?, ?, ?, ?)
""", (message_id, session_id, sender_id, receiver_id, timestamp, content, status))
INSERT INTO Messages (MessageID, SessionID, MsgType, PrevMsgID, SenderID, ReceiverID, Timestamp, Topic,Mentions,ContentMIME,Content,ActionName,ActionParams,ActionResult,DoneTime,Status)
VALUES (?, ?, ?, ?, ?, ?, ?,?, ?, ?, ?, ?, ?, ?, ?, ?)
""", (msg.msg_id, msg.session_id, msg.msg_type.value, msg.prev_msg_id, msg.sender, msg.target, msg.create_time, msg.topic,mentions,msg.body_mime,msg.body,action_name,action_params,action_result,msg.done_time,msg.status.value))
conn.commit()
if msg.inner_call_chain:
for inner_call in msg.inner_call_chain:
self.insert_message(inner_call)
return 0 # return 0 if successful
except Error as e:
logging.error("Error occurred while inserting message: %s", e)
@@ -134,7 +180,7 @@ class ChatSessionDB:
"""Get a message by its ID"""
conn =self._get_conn()
c = conn.cursor()
c.execute("SELECT MessageID,SessionID,SenderID,ReceiverID,Timestamp,Content,Status FROM Messages WHERE MessageID = ?", (message_id,))
c.execute("SELECT MessageID, SessionID, MsgType, PrevMsgID, SenderID, ReceiverID, Timestamp, Topic,Mentions,ContentMIME,Content,ActionName,ActionParams,ActionResult,DoneTime,Status FROM Messages WHERE MessageID = ?", (message_id,))
message = c.fetchone()
return message
@@ -144,7 +190,7 @@ class ChatSessionDB:
conn = self._get_conn()
cursor = conn.cursor()
cursor.execute("""
SELECT MessageID,SessionID,SenderID,ReceiverID,Timestamp,Content,Status FROM Messages
SELECT MessageID, SessionID, MsgType, PrevMsgID, SenderID, ReceiverID, Timestamp, Topic,Mentions,ContentMIME,Content,ActionName,ActionParams,ActionResult,DoneTime,Status FROM Messages
WHERE SessionID = ?
ORDER BY Timestamp DESC
LIMIT ? OFFSET ?
@@ -222,29 +268,31 @@ class AIChatSession:
result = []
for msg in msgs:
agent_msg = AgentMsg()
agent_msg.id = msg[0]
agent_msg.sender = msg[2]
agent_msg.target = msg[3]
agent_msg.create_time = msg[4]
agent_msg.body = msg[5]
# agent_msg.state = msg[6]
agent_msg.msg_id = msg[0]
agent_msg.session_id = msg[1]
agent_msg.msg_type = AgentMsgType(msg[2])
agent_msg.prev_msg_id = msg[3]
agent_msg.sender = msg[4]
agent_msg.target = msg[5]
agent_msg.create_time = msg[6]
agent_msg.topic = msg[7]
if msg[8] is not None:
agent_msg.mentions = json.loads(msg[8])
agent_msg.body_mime = msg[9]
agent_msg.body = msg[10]
agent_msg.func_name = msg[11]
if msg[12] is not None:
agent_msg.args = json.loads(msg[12])
agent_msg.result_str = msg[13]
agent_msg.done_time = msg[14]
agent_msg.status = AgentMsgStatus(msg[15])
result.append(agent_msg)
return result
def append(self,msg:AgentMsg) -> None:
self.db.insert_message(msg.id,self.session_id,msg.sender,msg.target,msg.create_time,msg.body,0)
def append_post(self,msg:AgentMsg) -> None:
"""append msg to session, msg is post from session (owner => msg.target)"""
#assert msg.sender == self.owner_id,"post message means msg.sender == self.owner_id"
self.append(msg)
def append_recv(self,msg:AgentMsg) -> None:
"""append msg to session, msg is recv from msg'sender (msg.sender => owner)"""
#assert msg.target == self.owner_id,"recv message means msg.target == self.owner_id"
self.append(msg)
msg.session_id = self.session_id
self.db.insert_message(msg)
#def attach_event_handler(self,handler) -> None:
# """chat session changed event handler"""
+5 -6
View File
@@ -54,7 +54,6 @@ class ComputeKernel:
async def _run_task_loop():
while True:
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)
@@ -91,16 +90,16 @@ class ComputeKernel:
return True
# friendly interface for use:
def llm_completion(self, prompt: AgentPrompt, mode_name: Optional[str] = None, max_token: int = 0):
def llm_completion(self, prompt: AgentPrompt, mode_name: Optional[str] = None, max_token: int = 0,inner_functions = None):
# 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)
task_req = ComputeTask()
task_req.set_llm_params(prompt, mode_name, max_token)
task_req.set_llm_params(prompt, mode_name, max_token,inner_functions)
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:
task_req = self.llm_completion(prompt, mode_name, max_token)
async def do_llm_completion(self, prompt: AgentPrompt, mode_name: Optional[str] = None, max_token: int = 0, inner_functions = None) -> str:
task_req = self.llm_completion(prompt, mode_name, max_token,inner_functions)
async def check_timer():
check_times = 0
@@ -120,6 +119,6 @@ class ComputeKernel:
await asyncio.create_task(check_timer())
if task_req.state == ComputeTaskState.DONE:
return task_req.result.result_str
return task_req.result
return "error!"
+9 -5
View File
@@ -11,7 +11,6 @@ class ComputeTaskState(Enum):
ERROR = 3
PENDING = 4
class ComputeTaskType(Enum):
NONE = -1
LLM_COMPLETION = 0
@@ -36,7 +35,7 @@ class ComputeTask:
self.result = None
self.error_str = None
def set_llm_params(self, prompts, model_name, max_token_size, callchain_id=None):
def set_llm_params(self, prompts, model_name, max_token_size, inner_functions = None, callchain_id=None):
self.task_type = ComputeTaskType.LLM_COMPLETION
self.create_time = time.time()
self.task_id = uuid.uuid4().hex
@@ -46,8 +45,14 @@ class ComputeTask:
self.params["model_name"] = model_name
else:
self.params["model_name"] = "gpt-4-0613"
if max_token_size is None:
self.params["max_token_size"] = 4000
else:
self.params["max_token_size"] = max_token_size
if inner_functions is not None:
self.params["inner_functions"] = inner_functions
def display(self) -> str:
return f"ComputeTask: {self.task_id} {self.task_type} {self.state}"
@@ -59,9 +64,8 @@ class ComputeTaskResult:
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_str: str = None # easy to use,can read from result
self.result_message: dict = {}
self.result_refers: dict = None
self.pading_data: bytearray = None
+22 -6
View File
@@ -5,6 +5,8 @@ from abc import ABC, abstractmethod
from typing import Any, Callable, Optional,Dict,Awaitable,List
import logging
from .ai_function import AIFunction
logger = logging.getLogger(__name__)
class EnvironmentEvent(ABC):
@@ -33,6 +35,8 @@ class Environment:
# self.valid_keys:Dict[str,bool] = None
self.event_handlers:Dict[str,List[EnvironmentEventHandler]]= {}
self.functions : Dict[str,AIFunction] = {}
def get_id(self) -> str:
return self.env_id
@@ -44,16 +48,28 @@ class Environment:
#def get_env_prompt(self) -> str:
# pass
def add_ai_function(self,func:AIFunction) -> None:
if self.functions.get(func.get_name()) is not None:
logger.warn(f"add ai_function {func.get_name()} in env {self.env_id}:function already exist")
self.functions[func.get_name()] = func
def get_ai_function(self,func_name:str) -> AIFunction:
return self.functions.get(func_name)
#def enable_ai_function(self,func_name:str) -> None:
# pass
#def disable_ai_function(self,func_name:str) -> None:
# pass
def get_all_ai_functions(self) -> List[AIFunction]:
return self.functions.values()
@abstractmethod
def _do_get_value(self,key:str) -> Optional[str]:
pass
def get_functions(self):
# system functions
# env functions
# user install functions
pass
def register_get_handler(self,key:str,handler:Callable) -> None:
h = self.get_handlers.get(key)
if h is not None:
+20 -7
View File
@@ -54,30 +54,43 @@ class OpenAI_ComputeNode(ComputeNode):
prompts = task.params["prompts"]
logger.info(f"call openai {mode_name} prompts: {prompts}")
if task.params.get("inner_functions") is None:
resp = openai.ChatCompletion.create(model=mode_name,
messages=prompts,
max_tokens=4000,
temperature=1.2)
max_tokens=task.params["max_token_size"],
temperature=0.7)
else:
resp = openai.ChatCompletion.create(model=mode_name,
messages=prompts,
functions=task.params["inner_functions"],
max_tokens=task.params["max_token_size"],
temperature=0.7) # TODO: add temperature to task params?
logger.info(f"openai response: {resp}")
result = ComputeTaskResult()
result.set_from_task(task)
status_code = resp["choices"][0]["finish_reason"]
if status_code != "stop":
match status_code:
case "function_call":
task.state = ComputeTaskState.DONE
case "stop":
task.state = ComputeTaskState.DONE
case _:
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"]
result.result_message = 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)
+172 -70
View File
@@ -2,20 +2,23 @@ import logging
import asyncio
import json
import os
import time
from asyncio import Queue
from typing import Optional,Tuple
from abc import ABC, abstractmethod
from .environment import Environment,EnvironmentEvent
from .agent_message import AgentMsg,AgentMsgState
from .agent_message import AgentMsg,AgentMsgStatus
from .agent import AgentPrompt,AgentMsg
from .chatsession import AIChatSession
from .role import AIRole,AIRoleGroup
from .ai_function import CallChain
from .ai_function import AIFunction
from .compute_kernel import ComputeKernel
from .compute_task import ComputeTask,ComputeTaskResult,ComputeTaskState
from .bus import AIBus
from .workflow_env import WorkflowEnvironment
logger = logging.getLogger(__name__)
class MessageFilter:
@@ -157,11 +160,12 @@ class Workflow:
while i < len(inner_obj_id):
if i == len(inner_obj_id) - 1:
the_role : AIRole = current_workflow.role_group.get(inner_obj_id[i])
current_workflow_chatsession = AIChatSession.get_session(current_workflow.workflow_id,msg.sender + "#" + msg.topic,current_workflow.db_file)
if the_role is not None:
return await current_workflow.role_process_msg(msg,the_role)
return await current_workflow.role_process_msg(msg,the_role,current_workflow_chatsession)
sub_workflow = current_workflow.sub_workflows.get(inner_obj_id[i])
if sub_workflow is not None:
return await sub_workflow.process_msg(msg)
return await sub_workflow._process_msg(msg)
logger.error(f"{msg.target} not found! forword message failed!")
return None
else:
@@ -175,17 +179,49 @@ class Workflow:
logger.error(f"{msg.target} not found! forword message failed!")
return None
def get_workflow_id_from_target(self,target:str) -> str:
target_list = target.split(".")
if len(target_list) == 0:
return target
else:
result_str = ""
p = 0
for s in target_list:
p = p + 1
result_str += s
if p < len(target_list)-1:
result_str += "."
else:
return result_str
async def _process_msg(self,msg:AgentMsg):
# workflow can be a message handler, but never be a message sender
# all message forword to roles or sub workflow
# workflow no chatsession record, but role have
final_result = None
real_target = msg.target.split(".")[0]
targets = self._parse_msg_target(msg.target)
if len(targets) > 1:
return await self._forword_msg(targets,msg)
#0 we don't support workflow join a group right now, this cloud be a feture in future
if msg.mentions is not None:
logger.warn(f"workflow {self.workflow_id} recv a group chat message,not support ignore!")
return None
#1. workflow start process message
final_result = None
# this is workflow's group_chat session
session_topic = msg.sender + "#" + msg.topic
chatsesssion = AIChatSession.get_session(self.workflow_id,session_topic,self.db_file)
#2. find role by msg.mentions or workflow's selector logic
if msg.mentions is not None:
if not self.workflow_id in msg.mentions:
chatsesssion.append(msg)
logger.info(f"workflow {self.workflow_id} recv a group chat message from {msg.sender},but is not mentioned,ignore!")
return None
for mention in msg.mentions:
this_role = self.role_group.get(mention)
if this_role is not None:
return await self.role_process_msg(msg,this_role,chatsesssion)
if self.input_filter is not None:
select_role_id = self.input_filter.select(msg)
@@ -195,26 +231,12 @@ class Workflow:
logger.error(f"input_filter return invalid role id:{select_role_id}, role not found in role_group")
return None
result = await self.role_process_msg(msg,select_role)
if result is None:
logger.error(f"_process_msg return None for :{msg}")
return
final_result = result
return await self.role_process_msg(msg,select_role,chatsesssion)
else:
logger.error(f"input_filter return None for :{msg}")
return
else:
# no input filter, we would process all message, slowly,not suggest to use
results = {}
final_result:AgentMsg = None
for this_role in self.role_group.roles.values():
# TODO : we would do this in parallel
a_result = await self.role_process_msg(msg,this_role)
results[this_role.get_name()] = a_result
final_result = a_result
logger.error(f"input_filter return None for :{msg.body}")
return None
logger.error(f"{self.workflow_id}:no role can process this msg:{msg.body}")
return final_result
@classmethod
@@ -275,52 +297,59 @@ class Workflow:
return r
async def role_post_msg(self,msg:AgentMsg,the_role:AIRole):
async def role_post_msg(self,msg:AgentMsg,the_role:AIRole,workflow_chat_session:AIChatSession):
msg.sender = the_role.get_role_id()
target_role = self.role_group.get(msg.target)
if target_role:
msg.target = target_role.get_role_id()
logger.info(f"{msg.sender} post message {msg.id} to inner role: {msg.target}")
asyncio.create_task(self.role_process_msg(msg,target_role))
logger.info(f"{msg.sender} post message {msg.msg_id} to inner role: {msg.target}")
asyncio.create_task(self.role_process_msg(msg,target_role,workflow_chat_session))
return
target_workflow = self.sub_workflows.get(msg.target)
if target_workflow:
msg.target = target_workflow.workflow_id
logger.info(f"{msg.sender} post message {msg.id} to sub workflow: {msg.target}")
logger.info(f"{msg.sender} post message {msg.msg_id} to sub workflow: {msg.target}")
asyncio.create_task(target_workflow._process_msg(msg))
logger.info(f"{msg.sender} post message {msg.id} to AIBus: {msg.target}")
logger.info(f"{msg.sender} post message {msg.msg_id} to AIBus: {msg.target}")
await self.get_bus().post_message(msg.target,msg)
return
async def role_send_msg(self,msg:AgentMsg,the_role:AIRole):
async def role_send_msg(self,msg:AgentMsg,the_role:AIRole,workflow_chat_session:AIChatSession):
msg.sender = the_role.get_role_id()
target_role = self.role_group.get(msg.target)
if target_role:
# msg.target = target_role.get_role_id()
logger.info(f"{msg.sender} send message {msg.id} to inner role: {msg.target}")
return await self.role_process_msg(msg,target_role)
logger.info(f"{msg.sender} send message {msg.msg_id} to inner role: {msg.target}")
return await self.role_process_msg(msg,target_role,workflow_chat_session)
target_workflow = self.sub_workflows.get(msg.target)
if target_workflow:
# msg.target = target_workflow.workflow_id
logger.info(f"{msg.sender} send message {msg.id} to sub workflow: {msg.target}")
logger.info(f"{msg.sender} send message {msg.msg_id} to sub workflow: {msg.target}")
return await target_workflow._process_msg(msg)
logger.info(f"{msg.sender} post message {msg.id} to AIBus: {msg.target}")
return await self.get_bus().send_message(msg.target,msg)
logger.info(f"{msg.sender} post message {msg.msg_id} to AIBus: {msg.target}")
return await self.get_bus().send_message(msg)
async def role_call(self,call:tuple,the_role:AIRole):
logger.info(f"{the_role.role_id} call {call[0]} with args {call[1]}")
return """{result:"timeout"}"""
func_name = call[0]
arguments = call[1]
func_node : AIFunction = self.workflow_env.get_ai_function(func_name)
if func_node is None:
return "execute failed,function not found"
result_str:str = await func_node.execute(**arguments)
return result_str
async def role_post_call(self,call:tuple,the_role:AIRole):
logger.info(f"{the_role.role_id} post call {call[0]} with args {call[1]}")
return
return await self.role_call(call,the_role)
def _format_msg_by_env_value(self,prompt:AgentPrompt):
if self.workflow_env is None:
@@ -330,65 +359,148 @@ class Workflow:
old_content = msg.get("content")
msg["content"] = old_content.format_map(self.workflow_env)
async def role_process_msg(self,msg:AgentMsg,the_role:AIRole):
session_topic = f"{msg.sender}#{msg.topic}"
session_owner = the_role.get_role_id()
chatsession : AIChatSession = AIChatSession.get_session(session_owner,session_topic,self.db_file)
if chatsession is None:
logger.error(f"get session {session_topic}@{session_owner} failed!")
def _get_inner_functions(self) -> dict:
all_inner_function = self.workflow_env.get_all_ai_functions()
if all_inner_function is None:
return None
result_func = []
for inner_func in all_inner_function:
this_func = {}
this_func["name"] = inner_func.get_name()
this_func["description"] = inner_func.get_description()
this_func["parameters"] = inner_func.get_parameters()
result_func.append(this_func)
if len(result_func) > 0:
return result_func
return None
async def _role_execute_func(self,the_role:AIRole,inenr_func_call_node:dict,prompt:AgentPrompt,org_msg:AgentMsg) -> str:
from .compute_kernel import ComputeKernel
func_name = inenr_func_call_node.get("name")
arguments = json.loads(inenr_func_call_node.get("arguments"))
func_node : AIFunction = self.workflow_env.get_ai_function(func_name)
if func_node is None:
return "execute failed,function not found"
ineternal_call_record = AgentMsg.create_internal_call_msg(func_name,arguments,org_msg.get_msg_id(),org_msg.target)
result_str:str = await func_node.execute(**arguments)
inner_functions = self._get_inner_functions()
prompt.messages.append({"role":"function","content":result_str,"name":func_name})
task_result:ComputeTaskResult = await ComputeKernel().do_llm_completion(prompt,
the_role.agent.llm_model_name,the_role.agent.max_token_size,
inner_functions)
ineternal_call_record.result_str = task_result.result_str
ineternal_call_record.done_time = time.time()
org_msg.inner_call_chain.append(ineternal_call_record)
inner_func_call_node = task_result.result_message.get("function_call")
if inner_func_call_node:
return await self._role_execute_func(the_role,inner_func_call_node,prompt,org_msg)
else:
return task_result.result_str
def _is_in_same_workflow(self,msg) -> bool:
pass
async def role_process_msg(self,msg:AgentMsg,the_role:AIRole,workflow_chat_session:AIChatSession):
msg.target = the_role.get_role_id()
prompt = AgentPrompt()
prompt.append(the_role.agent.prompt)
prompt.append(self.get_workflow_rule_prompt())
prompt.append(the_role.get_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))
#support group chat, user content include sender name!
prompt.append(await self._get_prompt_from_session(workflow_chat_session))
msg_prompt = AgentPrompt()
msg_prompt.messages = [{"role":"user","content":msg.body}]
msg_prompt.messages = [{"role":"user","content":f"{msg.sender}:{msg.body}"}]
prompt.append(msg_prompt)
self._format_msg_by_env_value(prompt)
inner_functions = self._get_inner_functions()
async def _do_process_msg():
#TODO: send msg to agent might be better?
result_str = await ComputeKernel().do_llm_completion(prompt,the_role.agent.get_llm_model_name(),the_role.agent.get_max_token_size())
result = Workflow.prase_llm_result(result_str)
task_result:ComputeTaskResult = await ComputeKernel().do_llm_completion(prompt,the_role.agent.get_llm_model_name(),the_role.agent.get_max_token_size(),inner_functions)
result_str = task_result.result_str
logger.info(f"{the_role.role_id} process {msg.sender}:{msg.body},llm str is :{result_str}")
inner_func_call_node = task_result.result_message.get("function_call")
if inner_func_call_node:
#TODO to save more token ,can i use msg_prompt?
result_str = await self._role_execute_func(the_role,inner_func_call_node,prompt,msg)
result = Workflow.prase_llm_result(result_str)
for postmsg in result.post_msgs:
postmsg.prev_msg_id = msg.get_msg_id()
# might be craete a new msg.topic for this postmsg
postmsg.topic = msg.topic
await self.role_post_msg(postmsg,the_role)
await self.role_post_msg(postmsg,the_role,workflow_chat_session)
if not self._is_in_same_workflow(postmsg):
role_sesion = AIChatSession.get_session(the_role.get_role_id(),f"{postmsg.target}#{msg.topic}",self.db_file)
role_sesion.append(postmsg)
else:
# message will be saved in role.process_message
pass
for post_call in result.post_calls:
action_msg = msg.create_action_msg(post_call[0],post_call[1],the_role.get_role_id())
workflow_chat_session.append(action_msg)
await self.role_post_call(post_call,the_role)
#save post_call
result_prompt_str = ""
match result.state:
case "ignore":
return None
case "reponsed":
resp_msg = AgentMsg()
resp_msg.topic = msg.topic
resp_msg.set(session_owner,msg.sender,result.resp)
chatsession.append_recv(msg)
chatsession.append_post(resp_msg)
resp_msg = msg.create_resp_msg(result.resp)
resp_msg.sender = the_role.get_role_id()
# It is always the person handling the messages who puts them into the session.
workflow_chat_session.append(msg)
workflow_chat_session.append(resp_msg)
#await self.get_bus().resp_message(resp_msg)
return resp_msg
case "waiting":
# TODO: Use role:"function" would be better
for sendmsg in result.send_msgs:
target = sendmsg.target
sendmsg.topic = msg.topic
send_resp = await self.role_send_msg(sendmsg,the_role)
sendmsg.prev_msg_id = msg.get_msg_id()
send_resp = await self.role_send_msg(sendmsg,the_role,workflow_chat_session)
if send_resp is not None:
result_prompt_str += f"\n{target} response is :{send_resp.body}"
if not self._is_in_same_workflow(sendmsg):
role_sesion = AIChatSession.get_session(the_role.get_role_id(),f"{sendmsg.target}#{sendmsg.topic}",self.db_file)
role_sesion.append(sendmsg)
role_sesion.append(send_resp)
else:
# message will be saved in role.process_message
pass
for call in result.calls:
action_msg = msg.create_action_msg(call[0],call[1],call_result,the_role.get_role_id)
call_result = await self.role_call(call,the_role)
if call_result is not None:
result_prompt_str += f"\ncall {call[0]} result is :{call_result}"
#save action
action_msg.result_str = call_result
workflow_chat_session.append(action_msg)
result_prompt = AgentPrompt()
result_prompt.messages = [{"role":"user","content":result_prompt_str}]
@@ -409,17 +521,9 @@ class Workflow:
return result_prompt
def _get_function_prompt(self,role_name:str) -> AgentPrompt:
# system functions
# env functions
# user install functions
pass
def _get_knowlege_prompt(self,role_name:str) -> AgentPrompt:
pass
def get_workflow_rule_prompt(self) -> AgentPrompt:
return self.rule_prompt
@@ -445,6 +549,4 @@ class Workflow:
# the_env.attach_event_handler(k,_env_msg_handler)
# break
else:
logger.warn(f"environment {env.get_id()} already connected!")
+14 -2
View File
@@ -7,9 +7,11 @@ import threading
import logging
from typing import Optional
from .environment import Environment,EnvironmentEvent
from .ai_function import SimpleAIFunction
logger = logging.getLogger(__name__)
class CalenderEvent(EnvironmentEvent):
def __init__(self,data) -> None:
super().__init__()
@@ -17,7 +19,7 @@ class CalenderEvent(EnvironmentEvent):
self.data = data
def display(self) -> str:
return f"#event timer:{self.event_data}"
return f"#event timer:{self.data}"
# AI Calender GOAL: Let user use "create notify after 2 days" to create a timer event
class CalenderEnvironment(Environment):
@@ -25,6 +27,10 @@ class CalenderEnvironment(Environment):
super().__init__(env_id)
self.is_run = False
self.add_ai_function(SimpleAIFunction("get_time",
"get current time",
self._get_now))
def _do_get_value(self,key:str) -> Optional[str]:
return None
@@ -52,7 +58,12 @@ class CalenderEnvironment(Environment):
def stop(self):
self.is_run = False
def get_now(self,key:str) -> str:
def get_now(self,key)->str:
now = datetime.now()
formatted_time = now.strftime('%Y-%m-%d %H:%M:%S')
return formatted_time
async def _get_now(self) -> str:
now = datetime.now()
formatted_time = now.strftime('%Y-%m-%d %H:%M:%S')
return formatted_time
@@ -65,6 +76,7 @@ class WorkflowEnvironment(Environment):
self.local = threading.local()
self.table_name = "WorkflowEnv_" + env_id
def _get_conn(self):
""" get db connection """
if not hasattr(self.local, 'conn'):
+10 -3
View File
@@ -26,7 +26,7 @@ shell_style = Style.from_dict({
directory = os.path.dirname(__file__)
sys.path.append(directory + '/../../')
from aios_kernel import Workflow,AIAgent,AgentMsg,AgentMsgState,ComputeKernel,OpenAI_ComputeNode,AIBus,AIChatSession
from aios_kernel import Workflow,AIAgent,AgentMsg,AgentMsgStatus,ComputeKernel,OpenAI_ComputeNode,AIBus,AIChatSession
sys.path.append(directory + '/../../component/')
from agent_manager import AgentManager
@@ -44,6 +44,7 @@ class AIOS_Shell:
target_id = msg.target.split(".")[0]
agent : AIAgent = await AgentManager().get(target_id)
if agent is not None:
agent.owner_env = Environment.get_env_by_id("calender")
bus.register_message_handler(target_id,agent._process_msg)
return True
@@ -72,6 +73,7 @@ class AIOS_Shell:
open_ai_node.start()
ComputeKernel().add_compute_node(open_ai_node)
AIBus().get_default_bus().register_unhandle_message_handler(self._handle_no_target_msg)
AIBus().get_default_bus().register_message_handler(self.username,self._user_process_msg)
return True
@@ -82,7 +84,7 @@ class AIOS_Shell:
agent_msg = AgentMsg()
agent_msg.set(sender,target_id,msg)
agent_msg.topic = topic
resp = await AIBus.get_default_bus().send_message(target_id,agent_msg)
resp = await AIBus.get_default_bus().send_message(agent_msg)
if resp is not None:
return resp.body
else:
@@ -91,6 +93,9 @@ class AIOS_Shell:
async def install_workflow(self,workflow_id:Workflow) -> None:
pass
async def _user_process_msg(self,msg:AgentMsg) -> AgentMsg:
pass
async def call_func(self,func_name, args):
match func_name:
case 'send':
@@ -114,6 +119,7 @@ class AIOS_Shell:
case 'login':
if len(args) >= 1:
self.username = args[0]
AIBus().get_default_bus().register_message_handler(self.username,self._user_process_msg)
return self.username + " login success!"
case 'history':
num = 10
@@ -133,7 +139,7 @@ class AIOS_Shell:
if chatsession is not None:
msgs = chatsession.read_history(num,offset)
format_texts = []
for msg in reversed(msgs):
for msg in msgs:
format_texts.append(("class:content",f"{msg.sender} >>> {msg.body}"))
format_texts.append(("",f"\n-------------------\n"))
return FormattedText(format_texts)
@@ -170,6 +176,7 @@ async def main():
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(['send($target,$msg,$topic)',
+1 -1
View File
@@ -14,7 +14,7 @@ from telegram.ext import Application, CommandHandler, ContextTypes, MessageHandl
directory = os.path.dirname(__file__)
sys.path.append(directory + '/../../')
from aios_kernel import Workflow,AIAgent,AgentMsg,AgentMsgState,ComputeKernel,OpenAI_ComputeNode,AIBus,AIChatSession
from aios_kernel import Workflow,AIAgent,AgentMsg,AgentMsgStatus,ComputeKernel,OpenAI_ComputeNode,AIBus,AIChatSession
sys.path.append(directory + '/../../component/')
from agent_manager import AgentManager
+120 -58
View File
@@ -1,3 +1,21 @@
"""
Capture your email locally, and parse out the pictures in the email body and the pictures, videos and other files in the attachment. Subsequently, it supports vectorized analysis of your personal data and serves as a knowledge base to enable large language model answers. Better results.
An example of a local file is as follows:
data
alex0072@gmail.com
5de3e52f3a6b90cabe6cbdd4ae3a5c5b
email.txt
meta.json
image
0648B869@99C03070.DB94B354.jpg
body_image
11044884873.jpg
282985198265470.gif
dd-login-service-min.png
"""
import imaplib
import os
import toml
@@ -5,91 +23,134 @@ import logging
import mailparser
import hashlib
import json
import base64
from bs4 import BeautifulSoup
import requests
# logger config
logger = logging.getLogger('email spider')
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
formatter = logging.Formatter('%(asctime)s [%(name)s] [%(levelname)s] %(message)s')
ch.setFormatter(formatter)
logger.addHandler(ch)
class EmailSpider:
def __init__(self):
# logger config
self.logger = logging.getLogger('email spider')
self.logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
formatter = logging.Formatter('%(asctime)s [%(name)s] [%(levelname)s] %(message)s')
ch.setFormatter(formatter)
self.logger.addHandler(ch)
# read config from toml file
# and read from config config.local.toml if exists (config.local.toml is ignored by git)
config = toml.load('./rootfs/email/config.toml')
if os.path.exists('./rootfs/email/config.local.toml'):
config = toml.load('./rootfs/email/config.local.toml')
# read config from toml file
# and read from config config.local.toml if exists (config.local.toml is ignored by git)
self.config = toml.load('./rootfs/email/config.toml')
if os.path.exists('./rootfs/email/config.local.toml'):
self.config = toml.load('./rootfs/email/config.local.toml')
self.client = self.email_client()
# create email client
def email_client() -> imaplib.IMAP4_SSL:
logger.info(f"read email config from {config.get('EMAIL_IMAP_SERVER')}")
client = imaplib.IMAP4_SSL(config.get('EMAIL_IMAP_SERVER'))
client.login(config.get('EMAIL_ADDRESS'), config.get('EMAIL_PASSWORD'))
def email_client(self) -> imaplib.IMAP4_SSL:
self.logger.info(f"read email config from {self.config.get('EMAIL_IMAP_SERVER')}")
client = imaplib.IMAP4_SSL(
host=self.config.get('EMAIL_IMAP_SERVER'),
port=self.config.get('EMAIL_IMAP_PORT')
)
client.login(self.config.get('EMAIL_ADDRESS'), self.config.get('EMAIL_PASSWORD'))
return client
def list_box(mail: imaplib.IMAP4_SSL):
_, mailbox_list = mail.list()
def list_box(self):
_, mailbox_list = self.client.list()
for mailbox in mailbox_list:
print(mailbox.decode())
def read_emails(client: imaplib.IMAP4_SSL, folder: str = 'INBOX', imap_keyword: str = "UNSEEN"):
client.select(folder)
_, data = client.uid('search', None, imap_keyword)
def read_emails(self, folder: str = 'INBOX', imap_keyword: str = "UNSEEN"):
self.client.select(folder)
_, data = self.client.uid('search', None, imap_keyword)
# get email uid list
email_list = data[0].split()
logger.info(f"got {len(email_list)} emails")
self.logger.info(f"got {len(email_list)} emails")
email_list.reverse()
for uid in email_list:
logger.info(f"read email uid {uid}")
if check_email_saved(client, uid):
logger.info(f"email uid {uid} already saved")
continue
if self.check_email_saved(uid):
self.logger.info(f"email uid {uid} already saved")
else:
read_and_save_email(client, uid)
logger.info(f"email uid {uid} saved")
self.read_and_save_email(uid)
self.logger.info(f"email uid {uid} saved")
def read_and_save_email(client: imaplib.IMAP4_SSL, uid: str):
def read_and_save_email(self, uid: str):
message_parts = "(BODY.PEEK[])"
_, email_data = client.uid('fetch', uid, message_parts)
_, email_data = self.client.uid('fetch', uid, message_parts)
mail = mailparser.parse_from_bytes(email_data[0][1])
logger.info(f"got email subject [{mail.subject}]")
save_email(mail)
self.logger.info(f"got email subject [{mail.subject}]")
self.save_email(mail)
def get_local_dir_name(mail: mailparser.MailParser) -> str:
dir = f"{config.get('LOCAL_DIR')}/{config.get('EMAIL_ADDRESS')}"
def get_local_dir_name(self, mail: mailparser.MailParser) -> str:
dir = f"{self.config.get('LOCAL_DIR')}/{self.config.get('EMAIL_ADDRESS')}"
name = f"{mail.subject}__{mail.date}"
name = hashlib.md5(name.encode('utf-8')).hexdigest()
return f"{dir}/{name}"
# check only need to check email header, not need to download email body
def check_email_saved(client: imaplib.IMAP4_SSL, uid: str):
def check_email_saved(self, uid: str):
message_parts = "(BODY[HEADER])"
_, email_data = client.uid('fetch', uid, message_parts)
_, email_data = self.client.uid('fetch', uid, message_parts)
mail = mailparser.parse_from_bytes(email_data[0][1])
logger.info(f"check email subject [{mail.subject}]")
dir = get_local_dir_name(mail)
logger.info(f"check email saved {dir}")
self.logger.info(f"[{uid}]check email subject [{mail.subject}]")
dir = self.get_local_dir_name(mail)
self.logger.info(f"check email saved {dir}")
file = f"{dir}/email.txt"
if os.path.exists(file):
return True
return False
return False
# save email attachment(images)
def save_email_attachment(self, mail: mailparser.MailParser, email_dir: str):
for attachment in mail.attachments:
if attachment['mail_content_type'] in ['image/png', 'image/jpeg', 'image/gif']:
print('current mail have image attachment')
img_dir = f"{email_dir}/image"
if not os.path.exists(img_dir):
os.makedirs(img_dir)
filename = attachment['filename']
filefullname = f"{img_dir}/{filename}"
image_data = attachment['payload']
try:
image_data = base64.b64decode(image_data)
except base64.binascii.Error:
image_data = image_data.encode()
with open(filefullname, 'wb') as f:
f.write(image_data)
self.logger.info(f"save email image {filename} success")
# save email body images(html content)
def save_body_images(self, html_content: str, email_dir: str):
# get all image urls
soup = BeautifulSoup(html_content, 'html.parser')
img_tags = soup.find_all('img')
img_urls = [img['src'] for img in img_tags if 'src' in img.attrs]
self.logger.info(f'Found {len(img_urls)} images in email body')
# save email to local file by each folder
def save_email(mail: mailparser.MailParser):
# create email account dir
dir = f"{config.get('LOCAL_DIR')}/{config.get('EMAIL_ADDRESS')}"
if not os.path.exists(dir):
os.makedirs(dir)
# create email local dir
email_dir = get_local_dir_name(mail)
logger.info(f"save email to {email_dir}")
if not os.path.exists(email_dir):
os.makedirs(email_dir)
# save email content and meta info
for img_url in img_urls:
# keep the original image filename(last of url)
img_filename = os.path.join(email_dir, img_url.split('/')[-1])
# download image
response = requests.get(img_url, stream=True)
if response.status_code == 200:
with open(img_filename, 'wb') as img_file:
for chunk in response.iter_content(1024):
img_file.write(chunk)
self.logger.info(f'Downloaded {img_url} to {img_filename}')
else:
self.logger.info(f'Failed to download {img_url}')
# save email content to local dir
def save_email(self, mail: mailparser.MailParser):
dir = f"{self.config.get('LOCAL_DIR')}/{self.config.get('EMAIL_ADDRESS')}"
if not os.path.exists(dir):
os.makedirs(dir)
email_dir = self.get_local_dir_name(mail)
self.logger.info(f"save email to {email_dir}")
if not os.path.exists(email_dir):
os.makedirs(email_dir)
with open(f"{email_dir}/email.txt", "w") as f:
f.write(mail.body)
with open(f"{email_dir}/meta.json", "w", encoding='utf-8') as f:
@@ -97,13 +158,14 @@ def save_email(mail: mailparser.MailParser):
if 'body' in mail_dict:
del mail_dict['body']
json.dump(mail_dict, f, ensure_ascii=False, indent=4)
logger.info(f"save email meta info {f.name}")
self.logger.info(f"save email meta info {f.name}")
self.save_email_attachment(mail, email_dir)
self.save_body_images(mail.body, f"{email_dir}/body_image")
if __name__ == "__main__":
mail = email_client()
spider = EmailSpider()
folder = 'INBOX'
# imap_keyword = "UNSEEN"
imap_keyword = "ALL"
read_emails(mail, folder, imap_keyword)
spider.read_emails(folder, imap_keyword)