AutoGen
Conversational multi-agent framework — superseded by Microsoft Agent Framework
About
Microsoft research framework for building multi-agent systems through conversational patterns. Officially superseded by Microsoft Agent Framework 1.0 (April 2026), which merges AutoGen and Semantic Kernel. Large installed base remains; Microsoft publishes a migration path.
Choose AutoGen when…
- •You want conversational multi-agent orchestration
- •Research or Microsoft ecosystem integration matters
- •You need flexible human-in-the-loop patterns
Builder Slot
The framework that structures how your AI thinks, uses tools, and coordinates agents
Other tools in this slot:
Stack Genome Detection
AIchitect's Genome scanner detects AutoGen in your project via these signals:
pyautogenautogen-agentchatautogen-coreIntegrates with (5)
AutoGen accepts LiteLLM-proxied endpoints as model backends via its model_client configuration.
→ Provider-flexible AutoGen agents — route different agent roles to different models through one LiteLLM config.
AutoGen emits OpenTelemetry traces that Langfuse captures, recording every agent message, tool call, and LLM interaction.
→ Conversation-level observability across multi-agent AutoGen runs — trace which agent said what and at what token cost.
AutoGen calls OpenAI's API natively for agent reasoning, with full function calling and parallel agent support.
→ GPT-4o-powered multi-agent conversations with structured tool use and concurrent agent execution.
AutoGen connects to Anthropic's API via LiteLLM or a direct connector for Claude-powered agent reasoning.
→ Claude-powered AutoGen agents with strong instruction following across complex multi-agent handoffs.
Microsoft Agent Framework is the official successor to AutoGen — Microsoft publishes a migration path so existing AutoGen agents can move to Agent Framework with bounded changes.
→ Migrate from AutoGen to Microsoft's supported production agent framework with a defined upgrade path.
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Pricing
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