import type { Database } from "./database.js";
export interface EmbeddingWithMeta {
    chunk_id: number;
    vector: Float32Array;
    chunk_type: string;
    file_id: number;
}
export declare class EmbeddingStore {
    private db;
    private insertStmt;
    private getStmt;
    private getAllStmt;
    private getAllWithMetaStmt;
    private deleteByChunkStmt;
    constructor(db: Database);
    insert(chunkId: number, vector: Float32Array): void;
    get(chunkId: number): Float32Array | undefined;
    getAll(): Map<number, Float32Array>;
    /**
     * Broadcast scan that JOINs embeddings with chunk metadata in one
     * SQLite query. Avoids the N+1 pattern in callers that need to
     * score every vector AND know each chunk's type/file_id (e.g. the
     * runVectorSplit code/doc split in search/investigate.ts).
     */
    getAllWithMeta(): EmbeddingWithMeta[];
    delete(chunkId: number): void;
    count(): number;
    /**
     * Read the dimension of one stored vector (any row). Returns null if
     * the table is empty. Used by sverklo doctor / status to surface
     * dim mismatches against the configured provider (#59 / #60).
     *
     * Cheap: SELECT … LIMIT 1, then divide blob length by 4 (Float32).
     */
    dimensionsObserved(): number | null;
}