Smolagents
Lightweight, code-first multi-agent framework by Hugging Face
About Smolagents
Smolagents is an ultra-lightweight, code-first Python framework created by Hugging Face for building, orchestrating, and executing autonomous AI agents in minimal lines of code. Rejecting the bloated, multi-layered abstractions of legacy agent libraries, Smolagents emphasizes 'Code Agents'—agents that express their reasoning and tool actions directly in executable Python code rather than rigid JSON string payloads. By letting LLMs write executable Python logic, Smolagents achieves vastly superior composability for data manipulation, mathematical operations, and complex loops while cutting prompt token overhead by up to 30%.
Smolagents natively supports both local open-source models (via Hugging Face Transformers and Ollama) and commercial frontier models (via LiteLLM, OpenAI, and Anthropic APIs). It includes pre-built modules for secure sandboxed Python execution, multi-modal web browsing agents with visual comprehension, and seamless sharing of agent tools directly on the Hugging Face Hub. The framework is fully modality-agnostic, supporting text, speech, vision, and custom API tools with zero vendor lock-in.
Install the framework via pip: pip install smolagents.
Initialize your CodeAgent and define your preferred model provider (OpenAI, Anthropic, or local Hugging Face model).
Attach custom Python functions or import pre-built tools from the Hugging Face Hub as agent tools.
Execute the agent with natural language prompts, allowing it to write and run Python scripts to complete tasks.
Inspect auditable execution traces and step-by-step reasoning logs in your terminal.
Capabilities & Features
Common Use Cases
code-agent-development
multi-agent-orchestration
web-browsing-agents
autonomous-tool-calling
Frequently Asked Questions
What makes Smolagents different from LangChain or CrewAI?
Smolagents prioritizes 'Code Agents', where the LLM writes actions directly in executable Python code rather than complex JSON schemas, making tool calling more composable, efficient, and token-effective.
Is Smolagents free and open-source?
Yes, Smolagents is 100% open-source under the Apache 2.0 license developed and maintained by Hugging Face.
Can I run Smolagents with local open-source LLMs?
Yes, Smolagents natively supports local inference via Hugging Face Transformers and Ollama, allowing you to run fully private, offline agent workflows.
Free Plan
100% Free and open-source under the Apache 2.0 license with full access to all framework modules.
Paid Plan
No subscription fees. Users bring their own LLM API keys or self-host local open weights.
Pros & Cons
Code-first architecture allows models to express actions in real Python rather than brittle JSON
Ultra-lightweight codebase with minimal external dependencies and near-instant startup times
Native integration with Hugging Face Hub for sharing and discovering community agent tools
Completely open-source (Apache 2.0) with zero subscription fees or commercial restrictions
Works seamlessly with local open weights (Llama 3, Qwen, DeepSeek) and commercial APIs
Requires Python programming knowledge to configure and deploy custom agents
Less out-of-the-box GUI dashboarding compared to commercial low-code agent platforms
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