smolagents

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SKU: smolagents
smolagents is a streamlined, open-source library developed by Hugging Face that enables developers to create powerful AI agents with just a few lines of code. The library emphasizes simplicity, containing approximately a thousand lines of code, and offers first-class support for Code Agents—agents that write their actions in Python code. smolagents is compatible with a wide range of language models, including those from OpenAI, Anthropic, and models hosted on the Hugging Face Hub. To ensure secure code execution, it provides options for running code in sandboxed environments via E2B. The library also integrates with the Hugging Face Hub, allowing users to share and load tools seamlessly.
AI agents open-source Python code execution language models Hugging Face sandboxed environments
Developers seeking to build AI agents with minimal code.
Creating agents that execute actions by writing Python code.
Integrating various language models into AI agent workflows.
Ensuring secure execution of AI-generated code in sandboxed environments.
Sharing and loading tools through the Hugging Face Hub for AI agent development.
Smolagents demonstrates high autonomy through its code-first approach where agents dynamically generate and execute Python code to solve tasks (CodeAgent architecture). The framework enables multi-step reasoning without predefined workflows, supports tool composition from Hugging Face Hub, and allows secure sandboxed execution via E2B. While requiring initial tool definitions, agents autonomously determine control flow through LLM-guided code generation - including mathematical operations (PEMDAS compliance through step decomposition), data analysis pipelines, and even visual language model integration for browser automation. The system implements Level 3 agency (LLMs determine program flow elements) with some Level 4 characteristics (environment interaction) through its tool execution capabilities.
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