import { vector as vectorColumn, tsvector } from './columns.js';
import { cosineDistance, cosineSimilarity, l2Distance, innerProduct, toTsvector, toTsquery, plainToTsquery, matches, headline, tsRank } from './query.js';
import { validateVectorExtension } from './validate.js';
/** Vector and full-text search namespace — pgvector column types, similarity queries, and FTS operators. */
export declare const vector: {
    /** Defines a vector(N) column for embeddings. */
    column: typeof vectorColumn;
    /** Defines a tsvector column for full-text search. */
    tsvector: typeof tsvector;
    /** Cosine distance between a column and a query vector (lower = more similar). */
    cosine: typeof cosineDistance;
    /** Cosine similarity (higher = more similar) — 1 - cosineDistance. */
    cosineSimilarity: typeof cosineSimilarity;
    /** L2 (Euclidean) distance between a column and a query vector. */
    l2: typeof l2Distance;
    /** Inner product between a column and a query vector. */
    innerProduct: typeof innerProduct;
    /** Converts text to a tsvector for full-text indexing. */
    toTsvector: typeof toTsvector;
    /** Converts a search query string to a tsquery using to_tsquery (supports operators like &, |, !). */
    toTsquery: typeof toTsquery;
    /** Converts natural language text to a tsquery using plainto_tsquery (no operator syntax required). */
    plainToTsquery: typeof plainToTsquery;
    /** The @@ match operator — tests whether a tsvector column matches a tsquery. */
    matches: typeof matches;
    /** Generates a ts_headline search snippet with highlighted matches. */
    headline: typeof headline;
    /** Computes ts_rank for full-text search result ordering. Accepts a pre-built tsquery SQL or a raw query string. */
    rank: typeof tsRank;
    /** Verifies the pgvector extension is installed and accessible. */
    validate: typeof validateVectorExtension;
};
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