[Submission] Add tau-bench leaderboard adapter#192
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Pull request overview
Adds a new tau_bench adapter under utils/ that ingests the public tau-bench leaderboard submissions (remote or local replay) and emits Every Eval Ever EvaluationLog records with per-domain pass@k and cost metrics, plus associated metadata. Includes unit tests and documents the adapter in utils/README.md.
Changes:
- Introduces
utils/tau_bench/adapter.pyto fetch/parse tau-bench leaderboard manifests + submissions and convert them into EEE logs/results. - Adds
tests/test_tau_bench_adapter.pycovering schema validation, metric mapping, voice metadata preservation, local manifest loading, and error handling. - Registers the new adapter in
utils/README.mdand addsutils/tau_bench/__init__.py.
Reviewed changes
Copilot reviewed 4 out of 4 changed files in this pull request and generated 5 comments.
| File | Description |
|---|---|
| utils/tau_bench/adapter.py | New adapter implementation converting tau-bench submissions to EEE logs/results. |
| utils/tau_bench/init.py | Adds package marker/docstring for the new adapter module. |
| utils/README.md | Documents the new tau_bench adapter in the adapters table. |
| tests/test_tau_bench_adapter.py | Adds tests for adapter correctness and schema compatibility. |
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| evaluation_timestamp = evaluation_date(submission) | ||
| version = ( | ||
| (submission.get('methodology') or {}).get('tau2_bench_version') | ||
| ) or 'unknown' |
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| methodology = submission.get('methodology') or {} | ||
| value = methodology.get('evaluation_date') or submission.get( | ||
| 'submission_date' | ||
| ) |
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| methodology = submission.get('methodology') or {} | ||
| voice_config = submission.get('voice_config') or {} | ||
| pipeline = ( |
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| def run(args: argparse.Namespace) -> int: | ||
| records = load_submissions( | ||
| input_dir=args.input_dir, | ||
| base_url=args.base_url, | ||
| sections=args.sections, | ||
| ) | ||
| if args.limit is not None: | ||
| records = records[: args.limit] | ||
| bundles = make_logs(records) | ||
| paths = export_logs(bundles, args.output_dir) | ||
| for path in paths: | ||
| print(path) | ||
| return len(paths) |
|
it looks like this is fine to be approved, but there are a couple of notes that can be implemented either now or later; they are not of utmost importance and do not block this feature right now:
|
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
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Summary
Adds a tau-bench adapter that fetches the public leaderboard submissions manifest and per-submission JSON from
sierra-research/tau2-bench, then converts populated domain metrics into Every Eval Ever aggregate records.The adapter supports:
pass_1throughpass_4--input-dirreplay for review/testingNo instance-level trajectory export is included in this first version.
Validation
uv run ruff check utils/tau_bench/adapter.py tests/test_tau_bench_adapter.pyuv run pytest tests/test_tau_bench_adapter.pyuv run python -m utils.tau_bench.adapter --input-dir /Users/ben.sierra.ai/Documents/tau2-bench/web/leaderboard/public/submissions --output-dir /private/tmp/eee-tau-bench-smoke --limit 3uv run python -m every_eval_ever validate /private/tmp/eee-tau-bench-smokeuv run python -m utils.tau_bench.adapter --output-dir /private/tmp/eee-tau-bench-live-smoke --limit 1uv run python -m every_eval_ever validate /private/tmp/eee-tau-bench-live-smoke