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Documentation Index

Fetch the complete documentation index at: https://docs.kaireonai.com/llms.txt

Use this file to discover all available pages before exploring further.

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Tiered fairness evaluation

POST /api/v1/fairness/evaluate?metrics=basic|advanced runs the full fairness pipeline. The query string controls which metrics tier is returned.

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Basic tier (default)

Existing demographic-parity, four-fifths-rule, equal-opportunity, and equalized-odds gap calculations from lib/fairness/metrics.ts. Unchanged behavior — every existing caller is bit-identical.

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Advanced tier

Adds intersectional analysis + mitigation recommendations from lib/fairness/advanced.ts:
  • Intersectional cells require per-sample intersectionalGroups: { axisName: groupValue }. The route evaluates evaluateIntersectional(samples, minCellSize=10) and surfaces the cells + the worst disparate-impact ratio.
  • Mitigation recommendations are derived from the report shape (DI ratio, four-fifths violation, equal-opportunity gap) — no extra inputs needed.
When the caller asks for advanced but doesn’t supply intersectionalGroups, the response includes advancedAwaitingConfig: ["intersectional: no per-sample intersectionalGroups supplied"] so operators know why the analysis is empty. No silent fallback.

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Counterfactual + Lipschitz

These primitives also live in lib/fairness/advanced.ts but are NOT auto-run from this route — they need a real scorer + paired counterfactual samples that the evaluate route does not have. Pipeline callers invoke them directly.

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EU AI Act report

POST /api/v1/fairness/report runs the same fairness pipeline and returns a formatted report:
formatContent typeNotes
csvtext/csvPer-group + summary metrics, suitable for compliance archive ingestion.
htmltext/htmlMarkup-only; pipe through headless Chromium / wkhtmltopdf for PDF.
Body shape mirrors /evaluate. Optional title + subtitle override the defaults (“Fairness Assessment Report” / “EU AI Act Article 10 § 2(f)”).

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Audit trail

Every call to /evaluate and /report writes one AuditLog row (action: fairness_evaluate or fairness_report) so DSAR exports can cite the exact report contents.