/**
 * SMI-1519: HNSW Embedding Store
 * SMI-4577: Production HNSW path now lives in `embeddings/hnsw-search.ts` and is
 *           wired into `EmbeddingService.findSimilar`. This class retains its
 *           historical API for callers that want a self-contained store without
 *           the full `EmbeddingService` surface, but no longer references the
 *           V3 VectorDB (decommissioned after the claude-flow → ruflo rename).
 *
 * High-performance vector storage with SQLite-backed metadata. `findSimilar`
 * uses brute-force search; consumers wanting the HNSW backend should use
 * `EmbeddingService` instead, which lazy-loads `hnswlib-node` from the
 * shared search module.
 *
 * @see ADR-009: Embedding Service Fallback Strategy
 */
import type { SimilarityResult } from './index.js';
export type { HierarchicalNSW, HNSWSearchResult, HierarchicalNSWConstructor, HNSWConfig, HNSWEmbeddingStoreOptions, HNSWIndexStats, BatchInsertResult, IEmbeddingStore, } from './hnsw-store.types.js';
export { DEFAULT_HNSW_CONFIG, HNSW_PRESETS } from './hnsw-store.types.js';
export { createHNSWStore, isHNSWAvailable, loadHNSWLib } from './hnsw-store.helpers.js';
import type { HNSWConfig, HNSWEmbeddingStoreOptions, HNSWIndexStats, BatchInsertResult, IEmbeddingStore } from './hnsw-store.types.js';
/**
 * High-performance embedding storage using HNSW index.
 * Provides O(log n) approximate nearest neighbor search with SQLite persistence.
 */
export declare class HNSWEmbeddingStore implements IEmbeddingStore {
    private db;
    private index;
    private readonly hnswEnabled;
    private readonly config;
    private readonly maxElements;
    private readonly indexPath;
    private readonly distanceMetric;
    private readonly autoSave;
    private skillIdToLabel;
    private labelToSkillId;
    private nextLabel;
    private vectorDB;
    private initPromise;
    /**
     * @deprecated If dbPath is passed, use HNSWEmbeddingStore.create(options) instead —
     * the async factory supports both native and WASM SQLite. Passing dbPath to this
     * constructor throws to prevent silent data loss.
     */
    constructor(options?: HNSWEmbeddingStoreOptions);
    /**
     * Async factory — supports both native and WASM SQLite.
     *
     * @param options - Store options; dbPath is opened via createDatabaseAsync
     * @returns Fully initialised HNSWEmbeddingStore instance
     */
    static create(options?: HNSWEmbeddingStoreOptions): Promise<HNSWEmbeddingStore>;
    ensureInitialized(): Promise<void>;
    storeEmbedding(skillId: string, embedding: Float32Array, text: string): void;
    getEmbedding(skillId: string): Float32Array | null;
    getAllEmbeddings(): Map<string, Float32Array>;
    findSimilar(queryEmbedding: Float32Array, topK?: number): SimilarityResult[];
    findSimilarAsync(queryEmbedding: Float32Array, topK?: number): Promise<SimilarityResult[]>;
    cosineSimilarity(a: Float32Array, b: Float32Array): number;
    isUsingFallback(): boolean;
    close(): void;
    getStats(): HNSWIndexStats;
    batchInsert(embeddings: Array<{
        skillId: string;
        embedding: Float32Array;
        text: string;
    }>): BatchInsertResult;
    removeEmbedding(skillId: string): boolean;
    saveIndex(): void;
    loadIndex(): void;
    rebuildIndex(newConfig?: Partial<HNSWConfig>): Promise<void>;
    setEfSearch(efSearch: number): void;
    private initDatabase;
    private initDatabaseAsync;
    private initEmbeddingsTable;
    private initHNSWIndex;
    private distanceToSimilarity;
}
//# sourceMappingURL=hnsw-store.d.ts.map