[!IMPORTANT] Looking for ConversableAgent, GroupChat, or import autogen? That's now AG2 Classic.

As of AG2 v1.0, the protocol-driven framework is the top-level package, imported as ag2. The classic framework has moved to its own repository — ag2ai/ag2-classic, documented at classic.docs.ag2.ai. It is still maintained and installable; nothing you have built stops working.

This repository (pip install ag2) no longer ships the autogen import name or the classic agent classes.

AG2: Open-Source AgentOS for AI Agents

AG2 is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks. AG2 aims to streamline the development and research of agentic AI. It offers features such as agents capable of interacting with each other, facilitates the use of various large language models (LLMs) and tool use support, autonomous and human-in-the-loop workflows, and multi-agent conversation patterns.

The project is currently maintained by a dynamic group of volunteers from several organizations. Contact project administrators Chi Wang and Qingyun Wu via [email protected] if you are interested in becoming a maintainer.

Table of contents

• AG2: Open-Source AgentOS for AI Agents
  • Table of contents
  • AG2 Classic (the autogen.* namespace)
  • Getting started
    • Installation
    • Setup your API keys
    • Run your first agent
  • Example applications
  • Introduction of different agent concepts
    • Agents
    • Tools
    • Human in the Loop
    • Orchestrating Multiple Agents
    • The agent harness: knowledge and compaction
    • Advanced agentic design patterns
  • Code style and linting
  • Contributors Wall
  • License

AG2 Classic (the autogen.* namespace)

AG2 Classic is the original AutoGen-derived framework: the autogen.* import namespace and its agent classes — ConversableAgent, AssistantAgent, UserProxyAgent, GroupChat / GroupChatManager, swarms, register_function, LLMConfig / OAI_CONFIG_LIST, and the nested- and sequential-chat patterns.

It now lives in its own repository and has its own documentation site:

	AG2 Classic	AG2 (this repo)
Repository	ag2ai/ag2-classic	ag2ai/ag2
Documentation	classic.docs.ag2.ai	docs.ag2.ai
Import	import autogen	import ag2
Core agent	ConversableAgent	Agent
Multi-agent	GroupChat, swarms, nested chats	Network (hub + channels)

Are you using AG2 Classic?

If any of the following appear in your code, you are on Classic — stay on it, and use classic.docs.ag2.ai:

import autogen  # the autogen.* namespace
from autogen import ConversableAgent, GroupChat  # classic agent classes
from autogen import AssistantAgent, UserProxyAgent

Classic remains maintained and installable. Your existing code keeps working — pin the classic distribution instead of ag2>=1.0:

pip install ag2-classic

[!NOTE] AG2 v1.0 (pip install ag2) is not a drop-in upgrade from Classic. The agent model, orchestration, and imports all changed. See the group chat migration guide.

The rest of this README covers AG2 v1.0 (import ag2).

Getting started

For a step-by-step walk through of AG2 concepts and code, see the Quick Start in our documentation.

Installation

AG2 requires Python version >= 3.11. AG2 is available as ag2 on PyPI.

Windows/Linux:

pip install ag2[openai]

Mac:

pip install 'ag2[openai]'

Minimal dependencies are installed by default. Install the extra that matches your model provider — ag2[openai], ag2[anthropic], ag2[gemini], ag2[ollama], and so on.

Setup your API keys

Each provider config reads its standard environment variable, so keys never need to be hardcoded or checked in:

export OPENAI_API_KEY="<your-api-key>"     # or ANTHROPIC_API_KEY, GEMINI_API_KEY, ...

You can also pass a key explicitly with OpenAICompletionsConfig(model="gpt-4o-mini", api_key=...) — useful when each request brings its own key.

Run your first agent

AG2 is async throughout. Agent.ask(...) starts a turn and returns an AgentReply; the text is in reply.body.

import asyncio

from ag2 import Agent
from ag2.config import OpenAICompletionsConfig

agent = Agent(
    "assistant",
    prompt="You are a helpful assistant.",
    config=OpenAICompletionsConfig(model="gpt-4o-mini"),
)


async def main() -> None:
    reply = await agent.ask("Summarize the main differences between Python lists and tuples.")
    print(reply.body)


asyncio.run(main())

Example applications

We maintain both a live playground and a dedicated repository with a wide range of applications to help you get started with various use cases, and a set of runnable code examples in the documentation.

• AG2 Playground
• Build with AG2
• Code Examples

以上为 README 的开头部分。其余内容请阅读原文。 查看完整 README ↗