Agents

smolagents

Lightweight Hugging Face library for agents that reason and act through code.

Apache-2.0 License
huggingface Maintainer
2026-04-19 Verified
Overview

What is smolagents?

smolagents is a lightweight open-source agent library from Hugging Face, focused on simple code-agent patterns and practical integrations without a heavy framework surface.

Small framework surface

smolagents is intentionally lightweight compared with larger orchestration frameworks.

A smaller surface helps teams learn agent patterns without overbuilding.

Code-agent orientation

The project emphasizes agents that think and act through code.

Code is a flexible interface for tools, data, and repeatable actions.

Hugging Face ecosystem fit

It connects naturally to models and tools around Hugging Face.

That makes it a useful starting point for open model builders.
Use cases

What smolagents is built for

01

Agent prototypes

Build small demos that use tools and code without adopting a full workflow engine.

02

Model behavior testing

Compare how different models handle code-agent loops.

03

Open model applications

Pair Hugging Face-hosted models with tool execution patterns.

Quick start

Get started in seconds

terminal
$ pip install smolagents
Comparison

How it stacks up

Choose smolagents for lightweight experiments

vs LangGraph

LangGraph is better for durable workflow control; smolagents is better when you want a small agent library to prototype quickly.

FAQ

Frequently asked questions

What should I check before using smolagents?

Start with one safe workflow for smolagents. Inspect official setup instructions, required credentials, execution logs, approval points, and failure recovery before expanding from a sandbox task into production automation.

Is smolagents open source?

smolagents is listed with Apache-2.0 based on the official source links in this profile. Re-check the repository, model card, or docs before production use.

Who should evaluate smolagents?

smolagents is most worth evaluating for developers who want a small agent library before adopting a larger framework.