smolagents

smolagents takes a different bet than most agent frameworks. Instead of defining a fixed set of tools your agent can call, it lets the agent write Python code on the fly to accomplish tasks. That means it is not limited to tools you pre-configure: if the agent needs to combine two operations or improvise, it can write the logic itself and execute it in a sandbox.

This code-agent approach makes it unusually flexible for research and experimentation. It connects natively to Hugging Face's model ecosystem, so pointing it at a local model requires almost no setup. The lightweight core also makes it easy to audit and extend without wading through a large codebase.

The tradeoff is that smolagents is the newest and most experimental of the major frameworks. It does not have LangGraph's production-grade state management or n8n's pre-built integrations. Hugging Face built it for their own model ecosystem, and it shows: builders already working in the Hugging Face stack find it a natural fit for quick agent experiments. For production multi-agent systems that need checkpointing and audit trails, most teams still reach for LangGraph.