huggingface / smolagents · Getting started

This repository's platform metadata describes it as '🤗 smolagents: a barebones library for agents that think in code.' That wording is the project's own author-claimed description, not an analyzer finding. The metadata lists Python as the primary language, with 988,225 language bytes for Python against 326 for the Makefile. The license on record is Apache-2.0. The latest release on record is v1.26.0, published 2026-05-29, and the repository had 29,313 stargazers at 2026-09-14. The analyzer's summary counts 185 analyzed files organized around docs, examples, src and tests, and reports 28 test-like files and 7,633 static relation edges.

Dependency records come only from requirements-style manifests; all 43 records are runtime-scoped and name two source files: examples/async_agent/requirements.txt and examples/open_deep_research/requirements.txt. The pyproject.toml dependency tables were not parsed, even though pyproject.toml itself is flagged as a project-level important file. The async_agent manifest contributes four runtime records — smolagents, starlette, anyio and uvicorn — none with a version pin. The open_deep_research manifest contributes the remaining 39 runtime records; for example, anthropic >=0.37.1, openai >=1.52.2, torch >=2.2.2 and transformers >=4.46.0. Read broadly (scoped to the records cited), that list spans web scraping (beautifulsoup4, markdownify), document handling (openpyxl, mammoth, pypdf, PyPDF2), data science (numpy, pandas, scikit-learn, scipy) and model stacks (torch, torchvision, transformers), which suggests a tool-heavy research example.

The packet lists ten entrypoint records, eight of which contain a Python __main__ guard. Six of those eight guards simply call a main() function — including src/smolagents/cli.py, whose guard reads 'if __name__ == "__main__":' — as do the guards in examples/open_deep_research/run.py and run_gaia.py. The guard in examples/open_deep_research/app.py calls demo.launch(); the one in examples/smolagents_benchmark/run.py starts by parsing arguments, loading an eval dataset and branching on model type. Two more records, examples/async_agent/main.py and examples/server/main.py, are flagged as likely executable only by filename heuristic. Listed bounded execution paths cover only two entrypoints: from examples/async_agent/main.py they reach Route and Starlette, and from examples/open_deep_research/app.py they reach create_agent, GradioUI and demo.launch; every listed path ends at an unresolved boundary. The summary separately calls examples/structured_output_tool.py the apparent main starting place. Runtime behaviour beyond these records is not established by this static analysis.

Start with the project-level important files: README.md, pyproject.toml and LICENSE. Five further files are flagged as important because they are likely entrypoints: examples/structured_output_tool.py, src/smolagents/cli.py, src/smolagents/vision_web_browser.py, examples/open_deep_research/app.py and examples/open_deep_research/run.py. The analyzer's learning-path teaching claim says to start with manifests and important symbols, then trace the bounded execution path and inspect unresolved boundaries before changing code. Its modify-guide claim says to begin modification analysis at examples/async_agent/main.py and verify downstream effects manually. Top-level directories hold docs (81 files), examples (34), src (21) and tests (28), alongside .github (10) and 11 root-level entries, within 185 analyzed files. The summary reports 28 test-like files, so a test suite exists in the analyzed inventory.

No installation, build or run commands are verified here; install/run/build inference is partial. The analyzer did not parse pyproject.toml dependency tables. README extraction is line-based and may capture code lines instead of prose, so README-derived text is author-claimed at most. The analysis is static only: reflection, dynamic imports, framework runtime wiring and dynamic dispatch are not resolved. The open_deep_research manifest also carries overlapping entries — torch both pinned and unpinned, python_pptx and python-pptx, pdfminer and pdfminer.six, PyPDF2 and pypdf — worth checking upstream. Two packet-internal tensions: the summary calls examples/structured_output_tool.py the apparent starting place while a teaching claim names examples/async_agent/main.py; and one teaching claim says no bounded static execution path is available although five path records are listed. The summary's 7,633 static relation edges and the architecture claim's 615 resolved static call relations are also not reconciled in the packet.

The project's own metadata supplies the description quoted earlier and links a documentation homepage; both are author-claimed fields from the platform API, not analyzer findings. The topics field in the packet is empty, so no repository topics are on record.