{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/5"}],"enrichment":{"capability":"smolagents lets you build and run AI agents that write Python code to call tools and orchestrate other agents, with support for multiple LLM providers and sandboxed execution.","skillfed_tags":["agent-framework","llm-orchestration","code-execution"],"use_cases":["Build a multi-step research agent that searches the web, extracts information, and synthesizes answers without manual orchestration.","Create a vision-enabled agent that browses websites, clicks elements, and extracts product details or prices from e-commerce sites.","Share reusable agents and tool collections on Hugging Face Hub for team collaboration and instant deployment.","Run agents locally with transformers or connect to any LLM provider (OpenAI, Anthropic, Together AI) by changing one configuration.","Orchestrate complex workflows where agents coordinate with other agents or call specialized tools from MCP servers."],"what_it_does":"smolagents is a lightweight agent framework that lets you build autonomous agents in a few lines of code. Unlike traditional agents that generate tool-call descriptions, smolagents agents write actual Python code to invoke tools and coordinate multi-step workflows. The library is model-agnostic\u2014it works with local transformers, Ollama, OpenAI, Anthropic, and many other providers via LiteLLM or Hugging Face's inference API. It also supports multiple modalities (text, vision, video, audio) and can pull tools from MCP servers, LangChain, or Hugging Face Spaces.\n\nThe core agent type, CodeAgent, follows a ReAct loop: it receives a task, generates Python code snippets that call tools as functions, executes that code, stores the results in memory, and repeats until it calls a final_answer function. For security, you can run agents in sandboxed environments. The library integrates with Hugging Face Hub for sharing agents and tools as Space repositories, making it easy to collaborate and reuse agent configurations.","worth_installing":"Yes, if you want to build code-writing agents with minimal boilerplate and flexibility across LLM providers. The low install friction, active maintenance, and zero known vulnerabilities make it safe to try. The young release history (first release 2024-12-27) means the API may evolve, but the design is intentionally minimal. Start with the quick demo to verify it fits your use case."},"id":"smolagents","links":{"html":"https://skillfed.io/packages/smolagents","md":"https://skillfed.io/packages/smolagents.md","pypi":"https://pypi.org/project/smolagents/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-05-29","license_spdx":null,"license_treatment":"unclear","name":"smolagents","python_support":"supports_current","summary":"\ud83e\udd17 smolagents: a barebones library for agents. Agents write python code to call tools or orchestrate other agents."},"popularity":{"monthly_downloads":626778,"position":5687,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.26.0"}