Hugging Face Hub — Feynman Docs

Feynman includes read-only Hugging Face Hub tools for grounding ML recipes and replication plans. They help the researcher verify whether a dataset or repo actually exposes the files, splits, schema, and card metadata needed for implementation.

These tools are grounded in Hugging Face’s public Hub API endpoint docs. Authentication follows the HF_TOKEN environment variable documented by huggingface_hub.

Authentication

Public Hub resources work without configuration. For private or gated resources, set an access token in your shell before launching Feynman:

export HF_TOKEN=hf_...

If HF_TOKEN is unset, Feynman uses HUGGINGFACE_HUB_TOKEN. The token is sent with every Hub request.

Tools

The lead agent and the researcher agent can call these tools:

Tool	Purpose
`hf_dataset_info`	Inspect dataset metadata, tags, access status (private, gated, disabled), card data, `dataset_info` features and splits, downloads, likes, and sibling files
`hf_repo_files`	List files in a model, dataset, or Space repository (default 200 entries, max 1000) before reading anything large
`hf_repo_read_file`	Read small text files from Hub repos, such as `README.md`, configs, examples, and scripts

hf_repo_files and hf_repo_read_file default to dataset repos; pass repoType: "model" or "space" for others. The file reader returns 20,000 characters by default (max 60,000) and is intended for text files only. It is not a weight downloader or dataset bulk reader. It refuses model weight files, archives, and dataset shards such as .safetensors, .bin, .gguf, .parquet, .zip, and .tar before download.

Where it is used

The /recipe workflow uses hf_dataset_info to validate dataset availability and schema, and hf_repo_files and hf_repo_read_file to ground implementation details, before recommending a training recipe. The researcher agent can use the same tools in any workflow that delegates ML evidence gathering to it, such as /replicate.

For example, a recipe using a chat SFT dataset should verify that the dataset has a messages, text, or prompt/completion-style schema before calling it usable. If Feynman cannot check that schema, the final artifact should mark the dataset as unverified or blocked.

Boundaries

These tools are read-only. They do not create repos, upload files, start jobs, or manage private data. If an experiment needs execution on Hugging Face infrastructure, Feynman records that as a follow-up implementation decision.