Python-first multi-provider agent — minimal 1K-line library, MCP + LangChain tools.
The benchmark fields — designed for comparison across teams.
Solo-plus-tools (single agent) or hub-and-spoke (multi-agent). CodeAgent primary; can orchestrate ToolCallingAgents as subagents. Each subagent is called as a tool by the coordinator agent. Supports ManagedAgent wrapper for delegating to specialized sub-agents.
Windowed metrics with provenance. [unknown] means it was not tracked — an honest hole beats an invented figure.
~1000 lines: "The logic for agents fits in ~thousand lines of code." Source: huggingface.co/docs/smolagents [evidence_linked]
No standardized benchmark figures stated on HuggingFace smolagents docs at time of indexing.
Cost transparency is part of the honesty architecture. [unknown] means it was not tracked — not that it is zero.
Operational DNA — why it works, how it was built, and how it is overseen. Not files for sale; knowledge of the design.
Python-as-actions reduces the translation overhead between LM output and execution. Minimal library size (~1K lines) keeps the framework auditable and hackable. Broad provider support avoids vendor lock-in. MCP compatibility connects to an expanding ecosystem of tools without custom integration work.
Python package (pip install smolagents). Agents defined with a model (any provider) and a list of tools. CodeAgent produces Python blobs; ToolCallingAgent produces JSON tool calls. Multi-agent: pass agent instances wrapped in ManagedAgent to the tools list of a coordinator. Tutorial notebooks in the docs.
User controls model selection and tool access. Library is minimal by design — ~1K lines — to maximize auditability. Sandboxed code execution recommended for production deployments. Source: smolagents docs.
The team's shared track record — tasks, incidents, lessons, milestones. Per-entry provenance tags are always visible.
CodeAgent writes Python as actions rather than JSON tool calls. ~1000-line core library. Supports HuggingFace, OpenAI, Anthropic, LiteLLM, Transformers, Ollama. MCP and LangChain tool integration.
https://huggingface.co/docs/smolagents/en/indexSign in to add a proof entry.
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