Historical pre-upgrade audit record: empty scaffold, vulnerable dependencies, and incomplete validation

[CoreyLeath-code]

Historical record: This issue documents problems recorded before the repository's audit/upgrade work. Checked items mean a merged PR reports the item remediated; they are not a substitute for re-validating the current default branch. The scope is the evidence in linked commits and PRs—not a claim that every historical defect has been discovered.

Baselines and former issues

Earliest enterprise upgrade baseline: 897ad0b.

Missing product and governance surface

• Repository consisted of empty placeholder/stub files rather than an executable recommendation service.
• No implemented sequence model, processor, API, health endpoint, tests, metrics, or observability contract existed.
• CI and architecture/metrics documentation were stubs.
• README, license, security policy, contributing guide, code of conduct, changelog, ownership, issue/PR templates, Dependabot, and CodeQL were absent or incomplete.
• Container, Compose/Redis, Kubernetes/HPA, non-root runtime, and reproducible dependency manifests were absent.

Remediated through PR #1 and PR #2.

Supply-chain and deployment findings

• Pinned Torch, MLflow, python-jose, and Black versions had known advisories and required patched minimums.
• Image build lacked a .dockerignore.
• Streamlit deployment, smoke tests, environment documentation, and complete health/deployment guidance were missing.
• CI needed deployment smoke coverage and a clearer lightweight dependency path.

Remediated in PR #5.

Metrics and validation boundaries

• Consolidated repository/test/CI/model/API/observability/SLO metrics were absent.
• The later metrics audit recorded only 54% combined coverage across app and recommender.
• Local verification required missing test dependencies such as Torch and pydantic-settings.

Documented in PR #6.

Follow-up verification

• Re-audit all current pins for newly disclosed vulnerabilities.
• Raise meaningful coverage for recommendation ranking, API failure modes, persistence/cache behavior, and deployment integration.
• Verify current CI installs every declared test dependency from manifests without manual workspace additions.
• Validate recommendation quality on a versioned dataset; repository/config metrics are not model-quality evidence.