/**
 * VectorStore — SQLite-backed vector storage with cosine similarity search.
 *
 * Stores embeddings as Float32Array BLOBs in the entries table.
 * For datasets <10k, computes cosine similarity in JS (no vector DB needed).
 */
export interface VectorSearchResult {
    entryId: string;
    score: number;
}
export interface VectorStoreOptions {
    dbPath: string;
}
export declare class VectorStore {
    private db;
    constructor(options: VectorStoreOptions);
    private initSchema;
    /** Store an embedding vector for an entry */
    storeEmbedding(entryId: string, vector: number[]): void;
    /** Retrieve the embedding for an entry */
    getEmbedding(entryId: string): number[] | null;
    /** Search for similar entries by cosine similarity */
    searchSimilar(queryVector: number[], topK?: number): VectorSearchResult[];
    /** Check if two vectors are near-duplicates (similarity > threshold) */
    isDuplicate(vector: number[], threshold?: number): boolean;
    /** Count entries with embeddings */
    embeddingCount(): number;
    close(): void;
}
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