AG2 (formerly AutoGen) is an open-source multi-agent AI framework maintained by the original creators of Microsoft AutoGen. Licensed under Apache 2.0 with 4.3K+ GitHub stars, AG2 brands itself as “The Open-Source AgentOS” – providing a stable, community-driven platform for building conversational AI agent systems without the breaking changes introduced by Microsofts AutoGen 0.4 rewrite.

AG2 forked from Microsoft AutoGen v0.2.34 when Microsoft began a complete architectural rewrite (AutoGen 0.4) that shifted toward async messaging, TypeScript support, and Semantic Kernel integration. The original creators – Chi Wang and Qingyun Wu – established AG2 to preserve the familiar, battle-tested agent patterns while evolving the framework through community-driven development with an open RFC process.

Key features:

• Multi-agent conversations – Flexible patterns from two-agent chats to complex group discussions with LLM-selected speaker rotation
• ConversableAgent – Base agent class with built-in LLM integration, tool use, code execution, and configurable termination conditions
• GroupChat – Orchestrates multi-agent collaboration with automatic speaker selection and message routing
• Code execution – Agents can generate and execute code in sandboxed environments
• Tool integration – Pluggable tools, memory modules, and external API access
• Full backward compatibility – Existing AutoGen 0.2 code runs without modification

Two-agent conversation:

from autogen import ConversableAgent, config_list_from_json
 
# Load LLM config (supports OpenAI, Azure, local models)
config_list = config_list_from_json("OAI_CONFIG_LIST")
llm_config = {"config_list": config_list, "temperature": 0}
 
# Create a user proxy that can execute code
user_proxy = ConversableAgent(
    name="User",
    human_input_mode="NEVER",
    code_execution_config={"work_dir": "coding", "use_docker": True}
)
 
# Create an AI assistant
assistant = ConversableAgent(
    name="Assistant",
    llm_config=llm_config,
    system_message="You are a helpful data analyst. Write Python code to solve tasks."
)
 
# Start conversation -- agents chat until task is complete
user_proxy.initiate_chat(
    assistant,
    message="Analyze the top 10 Python packages by downloads and create a bar chart."
)

GroupChat with multiple specialized agents:

from autogen import ConversableAgent, GroupChat, GroupChatManager
 
llm_config = {"config_list": config_list, "temperature": 0}
 
# Define specialized agents
planner = ConversableAgent(
    name="Planner",
    llm_config=llm_config,
    system_message="You break down tasks into steps. Do not write code."
)
 
engineer = ConversableAgent(
    name="Engineer",
    llm_config=llm_config,
    system_message="You write Python code to implement plans. Always include error handling."
)
 
critic = ConversableAgent(
    name="Critic",
    llm_config=llm_config,
    system_message="You review code for bugs, security issues, and improvements."
)
 
user_proxy = ConversableAgent(
    name="User_proxy",
    human_input_mode="NEVER",
    code_execution_config={"work_dir": "output"}
)
 
# Create group chat -- LLM selects next speaker
groupchat = GroupChat(
    agents=[user_proxy, planner, engineer, critic],
    messages=[],
    max_round=12
)
manager = GroupChatManager(groupchat=groupchat, llm_config=llm_config)
 
user_proxy.initiate_chat(
    manager,
    message="Build a REST API that serves stock price predictions."
)

AG2 is installable under multiple package names (all point to the same codebase):

pip install ag2
# or
pip install pyautogen
# or
pip install autogen

• v0.10.x – Gemini Thinking Configuration for enhanced reasoning control
• MCP support – Model Context Protocol integration for tool interoperability
• A2A protocol – Agent-to-Agent communication standard support
• AG2 Studio – Visual prototyping interface (in development)

• AG2 on GitHub
• AG2 Documentation
• AG2 Website
• AG2 Discord Community

• AutoGen – Microsofts original multi-agent framework
• CrewAI – Role-based multi-agent orchestration
• LangChain – LLM application framework
• OpenAI Swarm – Lightweight multi-agent framework