smolagents
Overview
Hugging Face’s Python library for agents that use tools and execute code to complete developer-defined tasks.
smolagents provides CodeAgent for Python-based actions and ToolCallingAgent for conventional tool calls. Developers connect a model and tools, then let the agent choose steps toward a supplied task. It supports model-provider APIs, local models, MCP tools and sharing through Hugging Face Hub.
Generated code can run in supported sandbox environments such as Docker, E2B, Modal or Blaxel. Developers remain responsible for tool permissions, credentials, execution limits and reviewing results. A model-and-tool configuration suitable for a prototype still needs evaluation for its intended production use. The screenshot and introductory video show an earlier library version.
Product overview
Capabilities, pricing and fit
Hugging Face’s Python library for agents that use tools and execute code to complete developer-defined tasks.
Information as of October 16, 2026
What it can do
- Workflow
smolagents provides CodeAgent for Python-based actions and ToolCallingAgent for conventional tool calls. Developers connect a model and tools, then let the agent choose steps toward a supplied task. It supports model-provider APIs, local models, MCP tools and sharing through Hugging Face Hub.[1], [2]
Where it fits best
Sources (2)
- github.com — product detailsOfficial site · checked 2026-10-16
- huggingface.co — product detailsOfficial site · checked 2026-10-16
Autonomy level
79/100
Our subjective rating of how independently the product carries out its documented tasks, considering the human setup, input, approval and review it needs. This is not a measured success rate.
Comparisons
Custom Comparisons
Some of the use cases of smolagents:
- Building code-executing research agents
- Prototyping tool-based workflows in Python
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Pricing model:
Code access:
Popularity level: 61%
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