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ab59633 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | """Assemble the Hugging Face dataset folder: tasks.jsonl, calibration results and source."""
import json
import shutil
import sys
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(ROOT))
sys.path.insert(0, str(ROOT / "scripts"))
from five_desks.environment import FiveDesksEnvironment # noqa: E402
from five_desks.tasks import TASK_IDS, build # noqa: E402
from selection import SELECTED # noqa: E402
out = ROOT / "dataset"
shutil.rmtree(out, ignore_errors=True)
(out / "calibration").mkdir(parents=True)
calib = json.loads((ROOT / "reports/calibration/full8/summary.json").read_text())["tasks"]
with open(out / "tasks.jsonl", "w") as f:
for task_id in TASK_IDS:
inst = build(task_id, 0)
prompt = FiveDesksEnvironment().reset(task_id=task_id, seed=0).output
f.write(json.dumps({
"task_id": task_id,
"desk": inst.desk,
"family": task_id.rsplit("-d", 1)[0],
"level": int(task_id[-1]),
"submitted_for_training": task_id in SELECTED,
"qwen3_8_27b_mean_reward": calib[task_id]["mean"],
"qwen3_8_27b_rewards": calib[task_id]["rewards"],
"example_seed": 0,
"example_prompt": prompt,
"example_files": json.dumps(inst.files),
"example_answer": json.dumps({p.key: p.expected for p in inst.parts}),
"max_actions": inst.max_steps,
}) + "\n")
for run in ("pilot", "full8"):
shutil.copy(ROOT / f"reports/calibration/{run}/summary.json", out / f"calibration/{run}_summary.json")
src = out / "source"
for item in ["five_desks", "server", "scripts", "tests", "openenv.yaml", "requirements.in", "requirements.lock", ".dockerignore"]:
path = ROOT / item
if path.is_dir():
shutil.copytree(path, src / item, ignore=shutil.ignore_patterns("__pycache__", "*.pyc"))
else:
shutil.copy(path, src / item)
shutil.copy(ROOT / "card.md", out / "README.md")
print("dataset at", out, sorted(p.name for p in out.iterdir()))
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