import type { IVectorStore } from '../memory/VectorStore.ts';
export interface SimilarPattern {
    pattern: string;
    score: number;
}
/** Marker row id recording the index format version. */
export declare const INDEX_VERSION_KEY = "__index_version__";
export declare const INDEX_CURRENT_VERSION = 2;
/**
 * Persistent nearest-neighbor index over learned patterns. Rows live in the
 * LanceDB vectors table under `pattern:` keys derived from the pattern text,
 * so a repeated pattern upserts instead of accumulating duplicates.
 */
export declare class EmbeddingIndex {
    private readonly vectorStore;
    private readonly threshold;
    constructor(vectorStore: IVectorStore, threshold?: number);
    private patternKey;
    /**
     * Upserts a pattern embedding by its derived key and returns the stored key.
     */
    storePattern(pattern: string, embedding: number[]): Promise<string>;
    /**
     * Nearest neighbors above the similarity threshold, highest score first.
     * Empty when nothing clears the threshold.
     */
    findSimilar(embedding: number[], threshold?: number, limit?: number): Promise<SimilarPattern[]>;
}
/**
 * Re-embeds legacy LongTermMemory rows (written with zero vectors before the
 * index existed) as queryable `pattern:` rows, then writes the version marker.
 * Idempotent: pattern upserts make re-runs harmless, and the marker is only
 * written after every row was attempted. Throws when embedding fails, so the
 * caller can retry on the next process without a false-complete marker.
 */
export declare function reindexLegacyPatterns(index: EmbeddingIndex, store: IVectorStore, embed: (text: string) => Promise<number[]>): Promise<number>;
//# sourceMappingURL=EmbeddingIndex.d.ts.map