Smolagents
HuggingFace's minimal agent framework — the deliberately-small alternative to AutoGen / LangGraph. Agents write Python code as their primary action interface (CodeAgent) or use traditional JSON tool calls (ToolCallingAgent). The CodeAgent pattern is the headline: instead of constraining the model to a tool-call schema, the model writes Python that calls the tools as functions. Faster for complex orchestration, riskier without sandboxing. Pairs well with HuggingFace's transformers + inference-providers stack.
Overview
HuggingFace's minimal agent framework — the deliberately-small alternative to AutoGen / LangGraph. Agents write Python code as their primary action interface (CodeAgent) or use traditional JSON tool calls (ToolCallingAgent). The CodeAgent pattern is the headline: instead of constraining the model to a tool-call schema, the model writes Python that calls the tools as functions. Faster for complex orchestration, riskier without sandboxing. Pairs well with HuggingFace's transformers + inference-providers stack.
Pros
- Tiny dependency footprint — readable in one sitting
- CodeAgent pattern unlocks complex chains that JSON tool-calls can't express
- First-class HuggingFace Hub integration for sharing agents
- Lower token cost than schema-bound frameworks (less boilerplate per step)
Cons
- CodeAgent requires sandboxing to be safe — sandbox setup is on you
- Smaller community than AutoGen / LangGraph; fewer prebuilt examples
- Best with stronger models (≥14B) — small models struggle to write correct tool code
Compatibility
| Operating systems | linux macos windows |
| GPU backends | cuda rocm metal cpu |
| License | Open source · free |
Runtime health
Operator-grade signals on how actively Smolagents is being maintained, how fresh its measurements are, and what failure classes operators have flagged. Every label below is anchored to a real date or count — we never infer maintainer activity we can't show.
Release cadence
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1 days since last refresh · source: lastUpdated
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