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Signed-off-by: Andrew Suter-Morris <asutermorris@nvidia.com>
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Summary
Fix the mainline
context / eval-authorwork-budget failure without reducing skill content, skipping comparisons, or relaxing similarity thresholds.full-pairwise-300m-v1.Incident and budget rationale
Run https://github.com/NVIDIA-NeMo/eval-author/actions/runs/41132259985 (job https://github.com/NVIDIA-NeMo/eval-author/actions/runs/41132259985/job/124337600119) evaluated 69 files / 417 chunks and hit
scalar_comparison_limit (100000000)after about four seconds. PR #166 was already merged and its dual-guard version fix was deployed; this is real exhaustion of the existing allowance, not the former 25m clustering override or a timeout.The recorded model route is
nvidia/nvidia/nemotron-3-embed-1b. Its documented output is 2048 dimensions, but the actual incident response dimension was not retained; this PR does not claim it was observed. At 2048 dimensions, 417 chunks require 177,635,328 scalar work, and the existing maximum 512 chunks requires 267,911,168. A 300m bound accommodates that maximum while retaining a finite guard.Verification
Scope and limitations
Five files only: wrapper, diagnostics, their tests, and existing CI documentation. No skill content, dependencies, lockfile, credentials, provider configuration, or workflow trigger changes. Separate from the anti-cheat work in #164.
Linux ARM64 Docker is not GitHub's AMD64 runner. No provider requests were made; provider latency, actual incident dimensions, and downstream LLM completion remain unverified. The next mainline live run is the end-to-end confirmation, and incomplete handling remains intact.