Microsoft AutoGen

Microsoft AutoGen is a framework for creating multi-agent conversations where AI agents collaborate, debate, and refine outputs through structured dialogue. It excels at workflows where multiple perspectives improve output quality.

Key use cases include:

• Code generation and review — one agent writes code, another reviews it, a third executes and tests it
• Group chat — multiple specialized agents discuss and solve problems collaboratively
• Human-AI collaboration — human proxy agents that inject human oversight at key decision points
• Complex problem solving through agent debate and iteration
• Research workflows where agents gather, critique, and synthesize information

AutoGen is used by teams building agentic AI systems that benefit from multi-perspective reasoning. It is particularly strong for software engineering workflows where code writing, reviewing, and execution happen in iterative cycles.

Backed by Microsoft Research, AutoGen benefits from active development and integration with the Azure AI ecosystem. AutoGen Studio provides a no-code UI for building and testing multi-agent workflows.

1. Install AutoGen:

   pip install autogen-agentchat autogen-ext[openai]

2. Set your LLM API key:

   export OPENAI_API_KEY='sk-...'

3. Create a basic agent conversation:

   from autogen_agentchat.agents import AssistantAgent
   from autogen_ext.models.openai import OpenAIChatCompletionClient
   
   model = OpenAIChatCompletionClient(model='gpt-4o')
   agent = AssistantAgent('assistant', model_client=model)
   result = await agent.run(task='Write a hello world function')
   print(result.messages)

4. Explore AutoGen docs for group chat, code execution, and tool use patterns.

Pricing: AutoGen is free and open source (MIT). AutoGen Studio is free to use locally. You pay only for LLM API calls. Works with OpenAI, Azure OpenAI, Anthropic, and local models.