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docs: Initial import from localai-website (#1312)

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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto 2023-11-22 18:13:50 +01:00 • committed by GitHub
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docs/content/howtos/autogen-setup.md Normal file
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disableToc = false
title = "Easy Demo - AutoGen"
weight = 2
+++
This is just a short demo of setting up ``LocalAI`` with Autogen, this is based on you already having a model setup.
```python
import os
import openai
import autogen
openai.api_key = "sx-xxx"
OPENAI_API_KEY = "sx-xxx"
os.environ['OPENAI_API_KEY'] = OPENAI_API_KEY
config_list_json = [
{
"model": "gpt-3.5-turbo",
"api_base": "http://[YOURLOCALAIIPHERE]:8080/v1",
"api_type": "open_ai",
"api_key": "NULL",
}
]
print("models to use: ", [config_list_json[i]["model"] for i in range(len(config_list_json))])
llm_config = {"config_list": config_list_json, "seed": 42}
user_proxy = autogen.UserProxyAgent(
name="Admin",
system_message="A human admin. Interact with the planner to discuss the plan. Plan execution needs to be approved by this admin.",
code_execution_config={
"work_dir": "coding",
"last_n_messages": 8,
"use_docker": "python:3",
},
human_input_mode="ALWAYS",
is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE"),
)
engineer = autogen.AssistantAgent(
name="Coder",
llm_config=llm_config,
)
scientist = autogen.AssistantAgent(
name="Scientist",
llm_config=llm_config,
system_message="""Scientist. You follow an approved plan. You are able to categorize papers after seeing their abstracts printed. You don't write code."""
)
planner = autogen.AssistantAgent(
name="Planner",
system_message='''Planner. Suggest a plan. Revise the plan based on feedback from admin and critic, until admin approval.
The plan may involve an engineer who can write code and a scientist who doesn't write code.
Explain the plan first. Be clear which step is performed by an engineer, and which step is performed by a scientist.
''',
llm_config=llm_config,
)
executor = autogen.UserProxyAgent(
name="Executor",
system_message="Executor. Execute the code written by the engineer and report the result.",
human_input_mode="NEVER",
code_execution_config={
"work_dir": "coding",
"last_n_messages": 8,
"use_docker": "python:3",
}
)
critic = autogen.AssistantAgent(
name="Critic",
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.",
llm_config=llm_config,
)
groupchat = autogen.GroupChat(agents=[user_proxy, engineer, scientist, planner, executor, critic], messages=[], max_round=999)
manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config)
#autogen.ChatCompletion.start_logging()
#text_input = input("Please enter request: ")
text_input = ("Change this to a task you would like the group chat to do or comment this out and uncomment the other line!")
#Uncomment one of these two chats based on what you would like to do
#user_proxy.initiate_chat(engineer, message=str(text_input))
#For a one on one chat use this one ^
#user_proxy.initiate_chat(manager, message=str(text_input))
#To setup a group chat use this one ^
```