1.workflow has reached a state of basic functionality.
2. implemented AI message bus infrastructure,
This commit is contained in:
Liu Zhicong
+31
-106
@@ -1,51 +1,17 @@
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from typing import Optional
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from enum import Enum
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from asyncio import Queue
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import asyncio
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import logging
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import uuid
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import time
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from .agent_message import AgentMsg
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from .chatsession import AIChatSession
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logger = logging.getLogger(__name__)
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class AgentMsgState(Enum):
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RESPONSED = 0
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INIT = 1
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SENDING = 2
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PROCESSING = 3
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ERROR = 4
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class AgentMsg:
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def __init__(self) -> None:
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self.create_time = 0
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self.sender:str = None
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self.target:str = None
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self.body:str = None
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self.state = AgentMsgState.INIT
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self.resp_msg = None
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def set(self,sender:str,target:str,body:str) -> None:
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self.sender = sender
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self.target = target
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self.body = body
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self.create_time = time.time()
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def get_msg_id(self) -> str:
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pass
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def get_sender(self) -> str:
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return self.sender
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def get_target(self) -> str:
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return self.target
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# return workflow_name, role_name, session_id
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def parser_target(self,target:str) -> None:
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pass
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class AgentPrompt:
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def __init__(self) -> None:
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self.messages = []
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@@ -59,6 +25,9 @@ class AgentPrompt:
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return result_str
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def append(self,prompt):
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if prompt is None:
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return
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self.messages.extend(prompt.messages)
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def load_from_config(self,config:list) -> bool:
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@@ -69,28 +38,6 @@ class AgentPrompt:
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self.messages = config
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return True
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# chat session store the chat history between owner and agent
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# chat session might be large, so can read / write at stream mode.
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class AIChatSession:
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def __init__(self,owner_id) -> None:
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self.owner_id = owner_id
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def get_owner_id(self) -> str:
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return self.owner_id
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def append_post(self,msg:AgentMsg) -> None:
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"""append msg to session, msg is post from session (owner => msg.target)"""
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pass
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def append_recv(self,msg:AgentMsg) -> None:
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"""append msg to session, msg is recv from msg'sender (msg.sender => owner)"""
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pass
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def attach_event_handler(self,handler) -> None:
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"""chat session changed event handler"""
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pass
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#TODO : add iterator interface for read chat history
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class AIAgentTemplete:
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def __init__(self) -> None:
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@@ -121,14 +68,14 @@ class AIAgent:
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def __init__(self) -> None:
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self.prompt:AgentPrompt = None
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self.llm_model_name:str = None
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self.max_token_size:int = 0
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self.max_token_size:int = 3600
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self.instance_id:str = None
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self.template_id:str = None
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self.fullname:str = None
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self.powerby = None
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self.enable = True
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self.chat_sessions = {}
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self.chat_db = None
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self.unread_msg = Queue() # msg from other agent
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@classmethod
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@@ -170,27 +117,6 @@ class AIAgent:
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return True
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def post_msg(self,msg:AgentMsg) -> None:
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# TODO: drop same msg already processed
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msg.state = AgentMsgState.SENDING
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self.unread_msg.put_nowait(msg)
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def start(self) -> None:
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async def _process_msg_loop():
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while True:
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msg = await self.unread_msg.get()
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if msg is None:
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continue
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msg.state = AgentMsgState.PROCESSING
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resp_msg = await self._process_msg(msg)
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if resp_msg is None:
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msg.state = AgentMsgState.ERROR
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continue
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else:
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msg.state = AgentMsgState.RESPONSED
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msg.resp_msg = resp_msg
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asyncio.create_task(_process_msg_loop())
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def _get_llm_result_type(self,result:str) -> str:
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if result == "ignore":
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@@ -200,16 +126,19 @@ class AIAgent:
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async def _process_msg(self,msg:AgentMsg) -> AgentMsg:
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from .compute_kernel import ComputeKernel
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session_topic = msg.get_sender() + "#" + msg.topic
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chatsession = AIChatSession.get_session(self.instance_id,session_topic,self.chat_db)
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prompt = AgentPrompt()
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prompt.append(self.prompt)
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msg_prompt = AgentPrompt()
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msg_prompt.messages = [{"role":msg.sender,"content":msg.body}]
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prompt.append(msg_prompt)
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# prompt.append(self._get_function_prompt(the_role.get_name()))
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# prompt.append(self._get_knowlege_prompt(the_role.get_name()))
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# prompt.append(await self._get_prompt_from_session(chatsession,the_role.get_name())) # chat context
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prompt.append(await self._get_prompt_from_session(chatsession)) # chat context
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msg_prompt = AgentPrompt()
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msg_prompt.messages = [{"role":"user","content":msg.body}]
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prompt.append(msg_prompt)
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result = await ComputeKernel().do_llm_completion(prompt,self.llm_model_name,self.max_token_size)
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final_result = result
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result_type : str = self._get_llm_result_type(result)
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@@ -257,12 +186,13 @@ class AIAgent:
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if is_ignore is not True:
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# TODO : how to get inner chat session?
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chatsession = self.get_chat_session(msg.sender)
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resp_msg = AgentMsg()
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resp_msg.set(self.instance_id,msg.sender,final_result)
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resp_msg.topic = msg.topic
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if chatsession is not None:
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chatsession.append_recv(msg)
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chatsession.append_post(final_result)
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chatsession.append_post(resp_msg)
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return resp_msg
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@@ -277,25 +207,20 @@ class AIAgent:
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def get_template_id(self) -> str:
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return self.template_id
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def get_chat_session_for_msg(self,msg:AgentMsg) -> AIChatSession:
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pass
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def get_chat_session(self,remote:str,topic_name:str=None) -> AIChatSession:
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if topic_name is None:
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topic_name = "_"
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result_session = self.chat_sessions.get(topic_name + "@" + remote)
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if result_session is not None:
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return result_session
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result_session = AIChatSession(self)
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self.chat_sessions[topic_name + "@" + remote] = result_session
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return result_session
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def get_llm_model_name(self) -> str:
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return self.llm_model_name
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def get_max_token_size(self) -> int:
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return self.max_token_size
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async def _get_prompt_from_session(self,chatsession:AIChatSession) -> AgentPrompt:
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messages = chatsession.read_history() # read last 10 message
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result_prompt = AgentPrompt()
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for msg in reversed(messages):
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if msg.target == chatsession.owner_id:
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result_prompt.messages.append({"role":"user","content":f"{msg.sender}:{msg.body}"})
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if msg.sender == chatsession.owner_id:
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result_prompt.messages.append({"role":"assistant","content":msg.body})
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return result_prompt
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