@mondaydotcomorg/atp-runtime/dist/embedding/index.d.ts

Runtime SDK injected into sandbox for Agent Tool Protocol

import type { EmbeddingRecord, SearchOptions, SearchResult } from './types';
export type { EmbeddingOptions, EmbeddingRecord, SearchOptions, SearchResult } from './types';
export { VectorStore, initializeVectorStore, clearVectorStore, getVectorStore, setVectorStoreExecutionId, clearVectorStoreExecutionId, } from './vector-store.js';
export { cosineSimilarity, generateEmbeddingId } from './utils.js';
/**
 * Embedding Runtime API
 *
 * Decorators automatically:
 * - Extract parameter names and types
 * - Generate metadata for type definitions
 * - Maintain single source of truth
 */
declare class EmbeddingAPI {
    /**
     * Request client to generate embedding and store it
     * For batch inputs, returns array of IDs for stored embeddings
     */
    embed(input: string | string[], metadata?: Record<string, unknown>): Promise<string | string[]>;
    /**
     * Search stored embeddings by similarity
     * Query must be embedded first via embed()
     */
    search(query: string, options?: Omit<SearchOptions, 'query'>): Promise<SearchResult[]>;
    /**
     * Calculate cosine similarity between two embedding vectors
     * This is a utility function that doesn't require client interaction
     */
    similarity(embedding1: number[], embedding2: number[]): number;
    /**
     * Get all stored embeddings (useful for debugging)
     */
    getAll(): EmbeddingRecord[];
    /**
     * Get count of stored embeddings
     */
    count(): number;
}
export declare const embedding: EmbeddingAPI;
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