GitHub - microsoft/autogen: A programming framework for agentic AI (original) (raw)
AutoGen
AutoGen is a framework for creating multi-agent AI applications that can act autonomously or work alongside humans.
Important: if you are new to AutoGen, please checkout Microsoft Agent Framework. AutoGen will still be maintained and continue to receive bug fixes and critical security patches. Read our announcement.
Installation
AutoGen requires Python 3.10 or later.
Install AgentChat and OpenAI client from Extensions
pip install -U "autogen-agentchat" "autogen-ext[openai]"
The current stable version can be found in the releases. If you are upgrading from AutoGen v0.2, please refer to the Migration Guide for detailed instructions on how to update your code and configurations.
Install AutoGen Studio for no-code GUI
pip install -U "autogenstudio"
Quickstart
The following samples call OpenAI API, so you first need to create an account and export your key as export OPENAI_API_KEY="sk-...".
Hello World
Create an assistant agent using OpenAI's GPT-4o model. See other supported models.
import asyncio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient
async def main() -> None: model_client = OpenAIChatCompletionClient(model="gpt-4.1") agent = AssistantAgent("assistant", model_client=model_client) print(await agent.run(task="Say 'Hello World!'")) await model_client.close()
asyncio.run(main())
MCP Server
Create a web browsing assistant agent that uses the Playwright MCP server.
First run npm install -g @playwright/mcp@latest to install the MCP server.
import asyncio from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.ui import Console from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StdioServerParams
async def main() -> None: model_client = OpenAIChatCompletionClient(model="gpt-4.1") server_params = StdioServerParams( command="npx", args=[ "@playwright/mcp@latest", "--headless", ], ) async with McpWorkbench(server_params) as mcp: agent = AssistantAgent( "web_browsing_assistant", model_client=model_client, workbench=mcp, # For multiple MCP servers, put them in a list. model_client_stream=True, max_tool_iterations=10, ) await Console(agent.run_stream(task="Find out how many contributors for the microsoft/autogen repository"))
asyncio.run(main())
Warning: Only connect to trusted MCP servers as they may execute commands in your local environment or expose sensitive information.
Multi-Agent Orchestration
You can use AgentTool to create a basic multi-agent orchestration setup.
import asyncio
from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.tools import AgentTool from autogen_agentchat.ui import Console from autogen_ext.models.openai import OpenAIChatCompletionClient
async def main() -> None: model_client = OpenAIChatCompletionClient(model="gpt-4.1")
math_agent = AssistantAgent(
"math_expert",
model_client=model_client,
system_message="You are a math expert.",
description="A math expert assistant.",
model_client_stream=True,
)
math_agent_tool = AgentTool(math_agent, return_value_as_last_message=True)
chemistry_agent = AssistantAgent(
"chemistry_expert",
model_client=model_client,
system_message="You are a chemistry expert.",
description="A chemistry expert assistant.",
model_client_stream=True,
)
chemistry_agent_tool = AgentTool(chemistry_agent, return_value_as_last_message=True)
agent = AssistantAgent(
"assistant",
system_message="You are a general assistant. Use expert tools when needed.",
model_client=model_client,
model_client_stream=True,
tools=[math_agent_tool, chemistry_agent_tool],
max_tool_iterations=10,
)
await Console(agent.run_stream(task="What is the integral of x^2?"))
await Console(agent.run_stream(task="What is the molecular weight of water?"))asyncio.run(main())
For more advanced multi-agent orchestrations and workflows, readAgentChat documentation.
AutoGen Studio
Use AutoGen Studio to prototype and run multi-agent workflows without writing code.
Run AutoGen Studio on http://localhost:8080
autogenstudio ui --port 8080 --appdir ./my-app
Why Use AutoGen?
The AutoGen ecosystem provides everything you need to create AI agents, especially multi-agent workflows -- framework, developer tools, and applications.
The framework uses a layered and extensible design. Layers have clearly divided responsibilities and build on top of layers below. This design enables you to use the framework at different levels of abstraction, from high-level APIs to low-level components.
- Core API implements message passing, event-driven agents, and local and distributed runtime for flexibility and power. It also support cross-language support for .NET and Python.
- AgentChat API implements a simpler but opinionated API for rapid prototyping. This API is built on top of the Core API and is closest to what users of v0.2 are familiar with and supports common multi-agent patterns such as two-agent chat or group chats.
- Extensions API enables first- and third-party extensions continuously expanding framework capabilities. It support specific implementation of LLM clients (e.g., OpenAI, AzureOpenAI), and capabilities such as code execution.
The ecosystem also supports two essential developer tools:
- AutoGen Studio provides a no-code GUI for building multi-agent applications.
- AutoGen Bench provides a benchmarking suite for evaluating agent performance.
You can use the AutoGen framework and developer tools to create applications for your domain. For example, Magentic-One is a state-of-the-art multi-agent team built using AgentChat API and Extensions API that can handle a variety of tasks that require web browsing, code execution, and file handling.
With AutoGen you get to join and contribute to a thriving ecosystem. We host weekly office hours and talks with maintainers and community. We also have a Discord server for real-time chat, GitHub Discussions for Q&A, and a blog for tutorials and updates.
Where to go next?
Interested in contributing? See CONTRIBUTING.md for guidelines on how to get started. We welcome contributions of all kinds, including bug fixes, new features, and documentation improvements. Join our community and help us make AutoGen better!
Have questions? Check out our Frequently Asked Questions (FAQ) for answers to common queries. If you don't find what you're looking for, feel free to ask in our GitHub Discussions or join our Discord server for real-time support. You can also read our blog for updates.
Legal Notices
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