/**
 * SQLite-backed embedding index with FTS5 keyword search.
 *
 * Implements the `IndexStore` interface plus an optional `keywordSearch()`
 * for hybrid retrieval. Vectors are stored as Float32 BLOBs; cosine similarity
 * is computed in-process over all rows (brute force). FTS5 provides BM25-ranked
 * keyword search over chunk content, symbol name, and file path.
 *
 * Design notes:
 *   - One DB per project at `.forge/embeddings.db`, isolated from graph.db.
 *   - Schema is created idempotently on open.
 *   - All writes run inside transactions for durability and speed.
 *   - Cosine search remains O(N); acceptable up to ~100k chunks. If needed,
 *     swap in an ANN index later without changing the public interface.
 */
import type { IndexStore, SearchResult } from './index-store';
export interface SqliteIndexStore extends IndexStore {
    /** Keyword (BM25) search via FTS5. Empty query returns []. */
    keywordSearch(query: string, topK?: number): SearchResult[];
    /** Close the underlying database. */
    close(): void;
}
export declare function createSqliteIndexStore(dbPath: string): SqliteIndexStore;
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