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43b4299 | 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 | """Check the small enrichment tables against their retained source metadata."""
from pathlib import Path
import json
import gzip
import pandas as pd
import pyarrow.parquet as pq
def main():
out = Path(__file__).resolve().parents[1]
qwen = pd.read_parquet(out / "data/qwen.parquet")
known = qwen[qwen.limit_source_path.notna()]
for row in known.itertuples():
source = out.parent / row.limit_source_path
metadata = json.loads(source.read_text())
assert row.context_limit == metadata["rollout_protocol"]["max_model_len"]
assert row.output_limit == metadata["rollout_protocol"]["max_generate_length"]
assert row.model_revision == metadata["model"]["revision"]
assert qwen.loc[qwen.limit_source_path.isna(), "context_limit"].isna().all()
usage = pd.read_parquet(out / "data/usage_events.parquet")
count = 0
for path in (out / "data/events").rglob("*.parquet"):
count += sum(v == "usage" for v in pq.read_table(path, columns=["kind"]).column(0).to_pylist())
assert len(usage) == count
examples = pd.read_parquet(out / "data/example_summary.parquet")
assert examples.loc[examples.example_kind == "process", "truncated"].sum() == 4547
forest = pd.read_parquet(out / "data/forest.parquet")
for row in forest[forest.outcome_status == "observed"].itertuples():
source = out.parent / row.trial_grade_source_path
original = json.loads(source.read_text())
assert row.reward == original["score"]
assert row.outcome_unit == "trial"
assert row.canonical_source_path.endswith(("codex-run.jsonl", "opencode-run.jsonl", "yudai-minisweagent.traj.json"))
report = {"status":"passed", "known_qwen_limit_episodes":len(known), "usage_events":len(usage),
"forest_observed_trial_grades":int((forest.outcome_status == "observed").sum()),
"truncated_forest_process_examples":4547}
(out / "provenance/metadata_validation.json").write_text(json.dumps(report,indent=2)+"\n")
print(json.dumps(report,indent=2))
if __name__ == "__main__":
main()
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