CI/CD Integration & Quality Deployment Gating

In enterprise AI engineering, merging a pull request or deploying an updated prompt template should be protected by automated evaluation benchmarks.

This recipe embeds NeuronScope quality evaluations and regression diffing directly into GitHub Actions or CI/CD pipelines to prevent quality regressions from reaching production.

CI/CD Gating Goal

Automatically block pull requests if candidate changes introduce quality regressions, elevate hallucination rates above 2%, or violate security governance rules.

GitHub Actions Pipeline

name: neuronscope-quality-gate
on: [pull_request]
jobs:
  evaluate_candidate:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: '3.12'
      - run: pip install "neuronscope[all]==0.9.2"
      - name: Run Candidate Observability Scope
        run: python scripts/eval_candidate.py --out candidate.nsz
      - name: Assert Quality Benchmarks & Diff
        run: ns compare tests/fixtures/baseline.nsz candidate.nsz --strict

Quality Assertions & Thresholds

1. ns compare --strict exits non-zero if quality scores decrease beyond allowed noise thresholds.
2. Post automated PR comments with visual markdown diff tables using ns diff --report comment.md.
3. Assert bit-exact telemetry equivalence for deterministic CPU pipelines using --bit-exact.

Operational & Security Notes