import { type EmbeddingProvider, type VectorDocument, type VectorSearchOptions, type VectorSearchResult, type VectorStore } from '../hallucination/retrieval.js';
import type { MigrationResult, SchemaMigration } from '../utils/schema-migrations.js';
import { type SqliteDatabaseLike, type SqliteLikeClient } from './client.js';
import type { SqliteMigrateOptions } from './migrations.js';
/** Options for the SQLite vector store. */
export interface SqliteVectorStoreOptions {
    /** Width of every vector. Must match the embedding function's output. */
    dimensions: number;
    /** The table chunks are kept in. Defaults to `nexus_vectors`. */
    table?: string;
    /**
     * How similarity is computed. `sqlite-vec` ranks inside SQLite with the extension's
     * `vec_distance_cosine()`, so only the best rows leave the database; load the extension into the
     * handle first. `scan` needs no extension and ranks in JavaScript, reading every row that passes the
     * filter. Defaults to `scan`.
     */
    search?: 'sqlite-vec' | 'scan';
    /** Embeds chunks that arrive without a vector, and search queries. Defaults to hashed term vectors. */
    embed?: EmbeddingProvider;
}
/** The statement that creates the vector table, for a migration tool that runs SQL itself. */
export declare function sqliteVectorStoreMigration(options?: {
    table?: string;
}): string;
/** The versioned schema, which `migrate()` applies. Version 1 is the 2.0 table. */
export declare function sqliteVectorStoreMigrations(options?: {
    table?: string;
}): SchemaMigration[];
/**
 * Retrieval chunks in SQLite: one file, no server, the same contract as every other store.
 *
 * Vectors are stored as float32 blobs, the format sqlite-vec reads. Filters run in SQL against the
 * metadata JSON, matching type as well as value, as the memory store does. Search is exact in both
 * modes, which suits a single node's corpus; beyond a few hundred thousand chunks, use pgvector or a
 * dedicated vector database.
 */
export declare class SqliteVectorStore implements VectorStore {
    private readonly options;
    private readonly client;
    private readonly table;
    private readonly embed;
    constructor(database: SqliteLikeClient | SqliteDatabaseLike, options: SqliteVectorStoreOptions);
    /**
     * Applies this store's pending migrations, recorded in `nexus_schema_migrations`, each inside
     * `BEGIN IMMEDIATE`. Never runs implicitly. Safe on a file an older release created.
     */
    migrate(options?: SqliteMigrateOptions): Promise<MigrationResult>;
    /** Adds chunks, or replaces those whose id exists, embedding those without a vector in one batch. */
    add(documents: VectorDocument[]): Promise<void>;
    /** The chunks most similar to a query, best first. */
    search(query: string, options?: VectorSearchOptions): Promise<VectorSearchResult[]>;
    /** The chunks most similar to a vector, best first. */
    searchVector(vector: number[], options?: VectorSearchOptions): Promise<VectorSearchResult[]>;
    /** Removes chunks by id. */
    delete(ids: readonly string[]): Promise<void>;
}