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92 lines
3.1 KiB
Markdown
92 lines
3.1 KiB
Markdown
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+++
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disableToc = false
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title = "Easy Demo - AutoGen"
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weight = 2
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+++
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This is just a short demo of setting up ``LocalAI`` with Autogen, this is based on you already having a model setup.
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```python
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import os
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import openai
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import autogen
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openai.api_key = "sx-xxx"
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OPENAI_API_KEY = "sx-xxx"
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os.environ['OPENAI_API_KEY'] = OPENAI_API_KEY
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config_list_json = [
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{
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"model": "gpt-3.5-turbo",
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"api_base": "http://[YOURLOCALAIIPHERE]:8080/v1",
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"api_type": "open_ai",
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"api_key": "NULL",
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}
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]
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print("models to use: ", [config_list_json[i]["model"] for i in range(len(config_list_json))])
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llm_config = {"config_list": config_list_json, "seed": 42}
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user_proxy = autogen.UserProxyAgent(
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name="Admin",
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system_message="A human admin. Interact with the planner to discuss the plan. Plan execution needs to be approved by this admin.",
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code_execution_config={
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"work_dir": "coding",
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"last_n_messages": 8,
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"use_docker": "python:3",
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},
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human_input_mode="ALWAYS",
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is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE"),
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)
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engineer = autogen.AssistantAgent(
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name="Coder",
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llm_config=llm_config,
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)
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scientist = autogen.AssistantAgent(
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name="Scientist",
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llm_config=llm_config,
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system_message="""Scientist. You follow an approved plan. You are able to categorize papers after seeing their abstracts printed. You don't write code."""
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)
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planner = autogen.AssistantAgent(
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name="Planner",
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system_message='''Planner. Suggest a plan. Revise the plan based on feedback from admin and critic, until admin approval.
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The plan may involve an engineer who can write code and a scientist who doesn't write code.
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Explain the plan first. Be clear which step is performed by an engineer, and which step is performed by a scientist.
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''',
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llm_config=llm_config,
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)
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executor = autogen.UserProxyAgent(
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name="Executor",
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system_message="Executor. Execute the code written by the engineer and report the result.",
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human_input_mode="NEVER",
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code_execution_config={
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"work_dir": "coding",
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"last_n_messages": 8,
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"use_docker": "python:3",
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}
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)
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critic = autogen.AssistantAgent(
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name="Critic",
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system_message="Critic. Double check plan, claims, code from other agents and provide feedback. Check whether the plan includes adding verifiable info such as source URL.",
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llm_config=llm_config,
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)
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groupchat = autogen.GroupChat(agents=[user_proxy, engineer, scientist, planner, executor, critic], messages=[], max_round=999)
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manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config)
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#autogen.ChatCompletion.start_logging()
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#text_input = input("Please enter request: ")
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text_input = ("Change this to a task you would like the group chat to do or comment this out and uncomment the other line!")
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#Uncomment one of these two chats based on what you would like to do
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#user_proxy.initiate_chat(engineer, message=str(text_input))
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#For a one on one chat use this one ^
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#user_proxy.initiate_chat(manager, message=str(text_input))
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#To setup a group chat use this one ^
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```
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