OpenHands / OpenHands/benchmarks

ACP Codex GPT-5.4 swebenchmultimodal: missing output.report.json

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Python
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Description

Summary

The latest ACP Codex GPT-5.4 swebenchmultimodal run (23983222379) does not produce an output.report.json summary file. Instead, resolved/not-resolved status is only available via 102 individual per-instance report.json files under logs/run_evaluation/.

Details

  • Run ID: 23983222379
  • GCS Artifacts: results.tar.gz
  • SDK commit: 6626a36
  • Agent: codex-acp v0.11.1
What's in the tarball
output.jsonl              ✅  (102 instances)
cost_report.jsonl         ✅
output.report.json        ❌  MISSING
logs/instance_*.log       ✅  (204 files — 102 instance + 102 output)
logs/run_evaluation/      ✅  (102 per-instance report.json + test_output.txt + patch.diff)

The per-instance eval reports confirm 21/102 resolved (20.6%), so the evaluation did run — it just didn't aggregate into a summary output.report.json.

Comparison with other benchmarks in the same batch
Benchmark Run ID output.report.json
swebench 23968384393 ✅ Present
gaia 23968385134 ✅ Present
commit0 23968384476 ✅ Present
swebenchmultimodal 23983222379 ❌ Missing

Note: swebenchmultimodal used a different SDK commit (6626a36) than the other three (4ad68fd), and was dispatched in a separate batch.

Impact

  • Results are valid — all 102 instances were inferred and evaluated
  • Resolved count (21) must be aggregated manually from per-instance reports
  • validate_artifacts.py may not detect this since it checks for output.report.json existence — runs missing it could silently skip the resolved count check

Related

  • OpenHands/benchmarks#576 — ACP master table tracking

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with validate_artifacts.py and the artifact layout described for the swebenchmultimodal run. Trace how per-instance report.json files are handled compared with output.report.json, then verify that the run produces an aggregated summary and that validation accounts for its resolved count.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
testing-qa
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
55/100

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