ai-embed-search/dist/index.d.ts

Smart. Simple. Local. AI-powered semantic search in TypeScript using transformer embeddings. No cloud, no API keys — 100% offline.

type SearchItem = {
    id: string;
    text: string;
    meta?: Record<string, any>;
};
type SearchResult = {
    id: string;
    text: string;
    score: number;
    meta?: Record<string, any>;
};
type EmbedFn = ((text: string) => Promise<number[]>) | ((texts: string[]) => Promise<number[][]>);
type VectorEntry = {
    id: string;
    text: string;
    vector: number[];
    meta?: Record<string, any>;
};

declare function initEmbedder(options: {
    embedder: EmbedFn;
}): void;
declare function embed(items: SearchItem[]): Promise<void>;
declare function search(query: string, maxItems?: number): {
    filter(fn: (result: SearchResult) => boolean): /*elided*/ any;
    exec: () => Promise<SearchResult[]>;
    cacheFor: (seconds: number) => Promise<SearchResult[]>;
};
declare function getSimilarItems(id: string, maxItems?: number): Promise<SearchResult[]>;

declare let vectorStore: VectorEntry[];
/**
 * Save current vector store to a file.
 */
declare function saveVectors(filePath: string): Promise<void>;
/**
 * Load vector store from a JSON file.
 */
declare function loadVectors(filePath: string): Promise<void>;
/**
 * Remove a vector entry by ID.
 */
declare function removeVector(id: string): void;
/**
 * Clear all vector entries.
 */
declare function clearVectors(): void;

declare function createEmbedder(): Promise<(text: string) => Promise<number[]>>;

export { vectorStore as _vectorStore, clearVectors, createEmbedder, embed, getSimilarItems, initEmbedder, loadVectors, removeVector, saveVectors, search };