🤗 Hugging Face Harbor Visualiser

A FastAPI Space for browsing Harbor task spec directories — the dataset format used by Harbor for agent evaluation + RL environments.

Drop in a Hugging Face dataset id, a GitHub repo, or a local Harbor dataset directory; the viewer renders every task's metadata, instruction, oracle patch, test script, and Dockerfile side-by-side. Large datasets (2k+ tasks) list and open instantly — task ids come from a shallow Hub listing and only the opened task's files are fetched, so nothing is bulk-downloaded.

Use it

Open the Space and paste a dataset URI in the input box.

Prefill via URL param:

https://huggingface.co/spaces/AdithyaSK/harbor-visualiser?dataset=<owner>/<dataset>

Inputs accepted:

Run locally

pip install -r requirements.txt
uvicorn app:app --port 7860
# → http://127.0.0.1:7860

What it shows per task

Dataset layout it expects (Harbor's standard)

Either of these:

# Layout A — flat (what Repo2RLEnv emits + most git repos use)
<dataset-root>/
├── <task-id>/
│   ├── task.toml
│   ├── instruction.md
│   ├── solution/
│   │   ├── patch.diff
│   │   └── solve.sh
│   ├── tests/test.sh
│   └── environment/Dockerfile
└── <task-id>/...

# Layout B — nested (what `repo2rlenv push` stages on the Hub)
<dataset-root>/
├── registry.json
├── README.md
└── tasks/
    └── <task-id>/
        └── ... (same as Layout A)

Stack

• FastAPI + uvicorn — server
• Vanilla-JS single-page UI (hash-routed) with a Hugging Face theme
• huggingface_hub — Hub listing + per-task download
• git (system binary) — GitHub clone
• Python stdlib tomllib — task.toml parsing