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AutoGen

Free tier

Build multi-agent AI applications with conversable, customizable agents powered by LLMs

Free·Technical·Powered by OpenAI, Azure OpenAI, and others·API available·Open source
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Key strengths

Multi-agent conversation orchestrationFlexible agent customization and role assignmentHuman-in-the-loop supportBroad LLM backend compatibilityOpen-source with active Microsoft Research backing
Completely free
Redmond, USA
Founded 2023
Self-hostable
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Developer Documentation

AutoGen provides a rich Python API for building production-grade multi-agent systems:

  • Agent Classes: Core classes include ConversableAgent, AssistantAgent, and UserProxyAgent. Subclass ConversableAgent and override generate_reply to implement custom agent logic.
  • LLM Configuration: Pass an llm_config dict (or OAI_CONFIG_LIST) specifying model, API key, base URL, and parameters. Supports OpenAI, Azure OpenAI, Mistral, Anthropic, and local models via LiteLLM.
  • Tool & Function Calling: Register Python functions as tools using @agent.register_for_llm() and @agent.register_for_execution() decorators; agents automatically invoke them during conversation.
  • Group Chat: Use GroupChat and GroupChatManager to orchestrate conversations among 3+ agents with configurable speaker-selection strategies (auto, round_robin, or custom).
  • Code Execution: UserProxyAgent can execute LLM-generated code in a local subprocess or a Docker container, with configurable safety settings.
  • AutoGen v0.4 Runtime: The new actor-model-based SingleThreadedAgentRuntime and GrpcWorkerAgentRuntime enable distributed, event-driven multi-agent pipelines with message passing.
  • AutoGen Studio API: A REST API and React-based frontend for no-code agent workflow design, available as a separate autogenstudio package.