It is a minimalist AI agent framework developed by Hugging Face, designed to enable developers to create and deploy powerful AI agents with minimal effort and code.
It is a minimalist AI agent framework developed by Hugging Face, designed to enable developers to create and deploy powerful AI agents with minimal effort and code. Smolagents allows large language models (LLMs) to interact seamlessly with real-world tasks by focusing on simplicity, efficiency, and ease of use. The framework supports code agents, where agents write and execute Python code snippets to perform actions, offering enhanced efficiency and accuracy compared to traditional tool-calling methods that generate JSON or text blobs. This approach reduces the number of steps and LLM calls by approximately 30%, improving performance on complex benchmarks.
Smolagents features a compact codebase of around 1,000 lines, minimizing abstractions and enabling straightforward development. Developers can quickly define agents, provide necessary tools, and run them without complex configurations. The framework integrates seamlessly with various LLMs, including those hosted on the Hugging Face Hub via Transformers, as well as models from OpenAI, Anthropic, and others through LiteLLM integration. It also supports secure code execution in sandboxed environments like E2B, ensuring safe and isolated execution.
In addition to code agents, smolagents supports traditional tool-calling agents for scenarios where JSON or text-based actions are more suitable. The framework emphasizes composability, efficient object handling, and flexibility, leveraging LLMs’ extensive training on high-quality code. It also integrates deeply with the Hugging Face Hub, allowing developers to share and load tools, fostering collaboration and ecosystem growth.
Smolagents has demonstrated competitive performance in benchmarks, with open-source models matching the capabilities of proprietary models. Developers can build custom agents, such as travel planners or SQL query generators, and share tools on the Hub. The framework is available for installation via pip and is compatible with a wide range of LLMs, making it a versatile and accessible tool for AI agent development.
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