feat: parallel probes, completion cache, cost, scale bench (#100) - #164
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Add --workers/--cache-dir for model-backed probes, token/cost summaries, and an informational scale harness (10–5000 tools) outside PR CI gates. Co-authored-by: Abhinaysai Kamineni <askmy-stack@users.noreply.github.com>
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Summary
Implements #100: parallel model-backed probe workers, completion caching, optional token/cost summaries, and an informational scale benchmark harness.
Changes
ProbeCompletionCache— key = model + prompt/tools + snapshot hash + temperature + seedevaluate_probes_with_model(..., workers=, cache=)— deterministic result orderusagemetadatascripts/bench_scale.py+run_scale_benchmarkfor 10/100/500/1000/5000 (not CI-gated)--workers,--cache-dirdocs/performance.mdTest plan
pytest tests/test_perf_cache.py(cache hit/miss, workers order, cost, small scale)pytest+ ruff + mypy