{"version":3,"file":"fireworks.d.cts","names":["Embeddings","EmbeddingsParams","FireworksEmbeddingsParams","CreateFireworksEmbeddingRequest","FireworksEmbeddings","Record","Partial","Promise"],"sources":["../../src/embeddings/fireworks.d.ts"],"sourcesContent":["import { Embeddings, type EmbeddingsParams } from \"@langchain/core/embeddings\";\n/**\n * Interface that extends EmbeddingsParams and defines additional\n * parameters specific to the FireworksEmbeddings class.\n */\nexport interface FireworksEmbeddingsParams extends EmbeddingsParams {\n    /**\n     * Model name to use.\n     */\n    model: string;\n    /**\n     * The maximum number of documents to embed in a single request. This is\n     * limited by the Fireworks AI API to a maximum of 8.\n     */\n    batchSize?: number;\n}\n/**\n * Interface for the request body to generate embeddings.\n */\nexport interface CreateFireworksEmbeddingRequest {\n    /**\n     * @type {string}\n     * @memberof CreateFireworksEmbeddingRequest\n     */\n    model: string;\n    /**\n     *  Text to generate vector expectation\n     * @type {CreateEmbeddingRequestInput}\n     * @memberof CreateFireworksEmbeddingRequest\n     */\n    input: string | string[];\n}\n/**\n * A class for generating embeddings using the Fireworks AI API.\n */\nexport declare class FireworksEmbeddings extends Embeddings implements FireworksEmbeddingsParams {\n    model: string;\n    batchSize: number;\n    private apiKey;\n    basePath?: string;\n    apiUrl: string;\n    headers?: Record<string, string>;\n    /**\n     * Constructor for the FireworksEmbeddings class.\n     * @param fields - An optional object with properties to configure the instance.\n     */\n    constructor(fields?: Partial<FireworksEmbeddingsParams> & {\n        verbose?: boolean;\n        apiKey?: string;\n    });\n    /**\n     * Generates embeddings for an array of texts.\n     * @param texts - An array of strings to generate embeddings for.\n     * @returns A Promise that resolves to an array of embeddings.\n     */\n    embedDocuments(texts: string[]): Promise<number[][]>;\n    /**\n     * Generates an embedding for a single text.\n     * @param text - A string to generate an embedding for.\n     * @returns A Promise that resolves to an array of numbers representing the embedding.\n     */\n    embedQuery(text: string): Promise<number[]>;\n    private embeddingWithRetry;\n}\n//# sourceMappingURL=fireworks.d.ts.map"],"mappings":";;;;;;AAKA;AAcA;AAgBqBI,UA9BJF,yBAAAA,SAAkCD,gBA8BX,CAAA;EAM1BI;;;EAcuBE,KAAAA,EAAAA,MAAAA;EAMPA;;;AA1BkE;;;;;;UAhB/EJ,+BAAAA;;;;;;;;;;;;;;;;cAgBIC,mBAAAA,SAA4BJ,UAAAA,YAAsBE;;;;;;YAMzDG;;;;;uBAKWC,QAAQJ;;;;;;;;;mCASIK;;;;;;4BAMPA"}