Datasets:

fromhope
/

acubench

This runbook is for you (the author) to run with your own HF token. The packaging step did not log in, create accounts, enter tokens, or upload anything. Everything below is copy-pasteable; replace <username> with your HF username (and adjust repo names if you like).

Two staging trees are ready:

acubench/hf/ → the HF dataset repo (build-script pattern; no AcuKG-derived labels shipped).
acubench/hf_space/ → the HF Space (Gradio leaderboard).

0. One-time setup

pip install -U "huggingface_hub[cli]"
huggingface-cli login          # paste your token (needs write scope)
huggingface-cli whoami         # confirm you are logged in

1. Create + upload the dataset repo

# Create the dataset repo (idempotent: --exist-ok won't fail if it exists).
huggingface-cli repo create acubench --repo-type dataset --exist-ok

# Upload the ENTIRE staging folder as the repo root.
huggingface-cli upload <username>/acubench \
    /Users/yutaewan/test/fromhope1/merdian/acubench/hf \
    . \
    --repo-type dataset \
    --commit-message "Add AcuBench (build-script pattern: skeleton + build/eval scripts, no AcuKG labels)"

Guardrail double-check before/after upload — the dataset repo must contain ONLY these files. It must NOT contain acubench.jsonl or any raw AcuKG data:

ls /Users/yutaewan/test/fromhope1/merdian/acubench/hf
# expected: README.md  NOTICE  LICENSE  UPLOAD.md
#           build_acubench.py  eval.py
#           who_acupoints.csv  meridian_adjacency.csv  sample_labels.jsonl

Then view it at https://huggingface.co/datasets/<username>/acubench.

2. Create + upload the Space (Gradio leaderboard)

# Create a Gradio Space.
huggingface-cli repo create acubench-leaderboard --repo-type space --space_sdk gradio --exist-ok

# Upload the Space staging folder.
huggingface-cli upload <username>/acubench-leaderboard \
    /Users/yutaewan/test/fromhope1/merdian/acubench/hf_space \
    . \
    --repo-type space \
    --commit-message "Add AcuBench leaderboard (operator-held gold)"

The Space builds automatically and serves the leaderboard (seeded with the paper's reference baselines). View it at https://huggingface.co/spaces/<username>/acubench-leaderboard.

3. Private gold handling (operator-held gold)

The private test gold is never uploaded to the public Space or dataset repo. You build it locally and keep it on your machine:

# You need your own AcuKG clone (its labels are not redistributed):
git clone https://github.com/<acukg-owner>/AcuKG.git /path/to/acukg

# Build the labels + splits locally (byte-reproduces the canonical dataset):
cd /Users/yutaewan/test/fromhope1/merdian/acubench/hf
python3 build_acubench.py --acukg /path/to/acukg --out ~/acubench_gold
# -> ~/acubench_gold/acubench.jsonl  (keep this PRIVATE; it holds the test labels)

If you ever want automated scoring inside the Space (optional, not required by the operator-held-gold flow), add the gold as a private Space secret/file rather than committing it:

As a file (private): huggingface-cli upload <username>/acubench-leaderboard ~/acubench_gold/acubench.jsonl gold/acubench.jsonl --repo-type space — but only if the Space is private; do NOT do this on a public Space.
As a secret: Space → Settings → Variables and secrets → add a secret (e.g. ACUBENCH_GOLD_PATH or the gold contents) and read it via os.environ in app.py. Recommended only if you make the Space private.

The default, safe design keeps the Space public and the gold entirely on your machine (see next section).

4. Operator scoring + appending leaderboard rows

When a participant sends you a predictions JSONL (they do not have the gold), score it locally and commit the resulting row:

cd /Users/yutaewan/test/fromhope1/merdian/acubench/hf_space

# Score against your private, locally-built test gold:
python3 score_submission.py \
    --pred /path/to/participant_preds.jsonl \
    --gold ~/acubench_gold/acubench.jsonl \
    --who  ../hf/who_acupoints.csv \
    --eval ../hf/eval.py \
    --split test \
    --model "Participant Model v1" \
    --submitter "Participant Name" \
    --out submissions/010_participant_model.json

# Push just the new row to the Space:
huggingface-cli upload <username>/acubench-leaderboard \
    submissions/010_participant_model.json \
    submissions/010_participant_model.json \
    --repo-type space \
    --commit-message "Leaderboard: add Participant Model v1"

The Space picks up the new submissions/*.json on reload. No gold labels ever leave your machine.

5. TODO / decisions for you

Confirm the license. The packaging step defaulted to CC BY 4.0 for the data/knowledge artifacts (WHO skeleton, adjacency, sample) and MIT for the code (build_acubench.py, eval.py). See LICENSE. If you prefer a single license, edit LICENSE and the license: field in README.md's YAML frontmatter accordingly.
Fill in the AcuKG URL in README.md, NOTICE, and the build/upload commands above (<acukg-owner>), and add the AcuKG citation.
Confirm the citation block in README.md (author list, venue/year).
Consider contacting AcuKG's authors for an explicit LICENSE or redistribution permission (recommended, not blocking).
Decide whether the Space stays public (default, operator-held gold) or goes private to enable in-Space automated scoring (§3).