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The smolagents library provides a lightweight foundation for building code based AI agents.
About smolagents
smolagents is an open source Python library for building agents that write their actions as code. A CodeAgent can be defined in a few lines, given tools such as web search, and run with a selected language model.
It works with local transformers and Ollama models, Hub inference providers, and models from OpenAI, Anthropic and others via LiteLLM, and handles text, vision, video and audio inputs. Code can be executed in sandboxed environments via Blaxel, E2B, Modal or Docker, and agents and tools can be shared to and loaded from the Hugging Face Hub. It includes smolagent and webagent commands for running agents from the CLI.
Key features
- CodeAgent writes agent actions as executable code
- Run code in sandboxed environments via Docker, E2B, Modal, Blaxel
- Work with local transformers, ollama, Hub, OpenAI, and Anthropic models
- Use tools from MCP servers, LangChain, or Hub Spaces
- Support text, vision, video, and audio inputs
- Share and load agents and tools via Hugging Face Hub
Best for: Developers building Python agents that use code actions across different models and tools.
Good for
- Small codebase with minimal abstractions above raw code
- Works with many models, tools, and input modalities
- Supports sandboxed code execution and Hub sharing
smolagents at a glance
- Category
- AI & Machine Learning › AI Agent Frameworks
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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smolagents FAQ
How do I install smolagents with default tools?
Install the package with: pip install "smolagents[toolkit]"
How can code execution be isolated?
CodeAgent supports executing in sandboxed environments via Blaxel, E2B, Modal, or Docker.
How do I share or reuse an agent?
An agent can be shared to the Hub as a Space repository with push_to_hub and loaded with from_hub.
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