/**
 * Tag-based relevance scoring for solution matching.
 *
 * Extracted from solution-matcher.ts — the core scoring logic that computes
 * relevance between a prompt's tags and a solution's tags using a TF-IDF +
 * BM25 + bigram ensemble.
 */
/**
 * Optional hints for the v3 `calculateRelevance` path. Used by hot-path
 * callers (matchSolutions, searchSolutions) to avoid re-normalizing the
 * same query tags on every solution.
 */
export interface CalculateRelevanceOptions {
    /**
     * Pre-normalized prompt tags (produced by `defaultNormalizer.normalizeTerms`).
     * If provided, skips the per-call expansion. Callers loop-running against
     * many solutions should compute this once outside the loop and pass it in.
     */
    normalizedPromptTags?: string[];
    /**
     * R4-T1: solution tags expanded with compound-split alternatives
     * (`expandCompoundTags`). When supplied, the intersection/partial-match
     * step uses this set INSTEAD of `solutionTags`, but the Jaccard union
     * denominator still uses `solutionTags` (raw) so the score normalization
     * stays semantically stable. Caller responsibility to pass the matching
     * pair — `solutionTagsExpanded` MUST be a superset of `solutionTags`.
     */
    solutionTagsExpanded?: string[];
    /** Average document (solution) tag count for BM25 normalization. Defaults to 6. */
    avgDocLength?: number;
    /** Meta-learning: dynamic ensemble weights (sum must equal 1.0). Defaults to {tfidf:0.5, bm25:0.3, bigram:0.2}. */
    ensembleWeights?: {
        tfidf: number;
        bm25: number;
        bigram: number;
    };
}
export declare function calculateRelevance(promptTags: string[], solutionTags: string[], confidence: number, options?: CalculateRelevanceOptions): {
    relevance: number;
    matchedTags: string[];
};
/** @deprecated */
export declare function calculateRelevance(prompt: string, keywords: string[]): number;