/**
 * Maximal Marginal Relevance (MMR) re-ranking — Phase 2.
 *
 * Ported from upstream `extensions/memory-core/src/memory/mmr.ts` with
 * minor adaptation for our `MemoryEntry` shape (content vs snippet, id vs
 * path+startLine). Behavior is identical: normalize scores, iteratively
 * pick the item that maximizes `λ * relevance - (1-λ) * max_similarity`
 * using Jaccard on tokenized content.
 *
 * @see Carbonell & Goldstein, "The Use of MMR, Diversity-Based Reranking" (1998)
 */
export interface MMRConfig {
    /** Opt-in. Upstream default is false. */
    enabled: boolean;
    /** 0 = max diversity, 1 = max relevance. Upstream default 0.7. */
    lambda: number;
}
export declare const DEFAULT_MMR_CONFIG: MMRConfig;
/**
 * Tokenize content into a set for Jaccard similarity.
 *
 * ASCII: alphanumeric + underscore runs, lowercased.
 * CJK: each char becomes a unigram; consecutive pairs become a bigram.
 * Non-adjacent CJK chars (e.g. `我a好`) do NOT form a bigram.
 */
export declare function tokenize(text: string): Set<string>;
export declare function jaccardSimilarity(a: Set<string>, b: Set<string>): number;
export declare function textSimilarity(a: string, b: string): number;
export declare function computeMMRScore(relevance: number, maxSimilarity: number, lambda: number): number;
export interface MMRItem {
    id: string;
    score: number;
    content: string;
}
/**
 * Re-rank items using MMR. Returns a new array in MMR order.
 */
export declare function mmrRerank<T extends MMRItem>(items: T[], config?: Partial<MMRConfig>): T[];
/**
 * Adapter: apply MMR to an array of MemoryEntry-shaped hits.
 *
 * Uses (path|id|index) as the stable ID so two hits from the same file at
 * different content still get distinct MMR identities.
 */
export declare function applyMMRToMemoryHits<T extends {
    id: string;
    path: string;
    content: string;
    score: number;
}>(results: T[], config?: Partial<MMRConfig>): T[];