FrameworkPicker

SmolAgents

Profile

Overview

The bottom line — what this framework is, who it's for, and when to walk away.

Bottom Line Up Front

SmolAgents is a lightweight Python library designed for building AI agents with minimal code and abstractions. It provides first-class support for `CodeAgent` execution in sandboxed environments and `ToolCallingAgent` for traditional tool use. The framework is highly agnostic, allowing integration with various LLMs, input modalities, and tool sources.

Best For

Quickly building flexible, model/tool/modality-agnostic agents, especially for code-driven task execution.

Avoid If

no data

Strengths

  • +Extremely easy to build and run agents with minimal lines of code.
  • +Supports `CodeAgent` for actions written in code, enabling natural composability.
  • +Secure code execution is supported via sandboxed environments (Modal, Blaxel, E2B, Docker).
  • +Offers `ToolCallingAgent` for standard JSON/text-based tool-calling paradigms.
  • +Provides seamless integration with Hugging Face Hub for sharing and loading agents and tools.
  • +Model-agnostic, allowing use of any LLM from Hugging Face Inference providers, APIs (OpenAI, Anthropic via LiteLLM), or local models.
  • +Modality-agnostic, capable of handling vision, video, and audio inputs.
  • +Tool-agnostic, supporting tools from MCP servers, LangChain, or Hugging Face Spaces.
  • +Includes CLI tools (`smolagent`, `webagent`) for running agents without boilerplate.

Weaknesses

    Project Health

    Is this project alive, well-maintained, and safe to bet on long-term?

    Stars

    26,444

    Open Issues

    475

    Last Commit

    2d ago

    Commit Frequency

    2x/week

    Bus Factor Score

    9 / 10

    Maintainers

    100

    Latest Version

    v1.24.0

    Total Releases

    34

    Repo Age

    1y 4mo

    Forks

    2,438

    Monthly Downloads

    497K

    last 30 days

    Versions Published

    40

    Known Vulnerabilities

    2Highest: Critical

    Dependent Repos

    0

    public repos using this

    Fit

    Does it support the workflows, patterns, and capabilities your team actually needs?

    State Management

    State management for agent execution is primarily handled through the underlying LLM's context window for single interactions or requires custom implementation within the agent's code for persistent or conversational state.

    Perspective

    Your expertise shapes what we build next.

    We build for engineers who make real architectural decisions. If something is missing, inaccurate, or could be more useful — we want to hear it.

    Last updated: 5 April 2026

    ·

    FrameworkPicker — The technical decision engine for the agentic AI era.