{"version":3,"file":"voyage.d.ts","names":["Embeddings","EmbeddingsParams","VoyageEmbeddingsParams","CreateVoyageEmbeddingRequest","VoyageEmbeddings","Record","Partial","Promise"],"sources":["../../src/embeddings/voyage.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 VoyageEmbeddings class.\n */\nexport interface VoyageEmbeddingsParams extends EmbeddingsParams {\n    modelName: string;\n    /**\n     * The maximum number of documents to embed in a single request. This is\n     * limited by the Voyage AI API to a maximum of 8.\n     */\n    batchSize?: number;\n    /**\n     * Input type for the embeddings request.\n     */\n    inputType?: string;\n    /**\n     * Whether to truncate the input texts to the maximum length allowed by the model.\n     */\n    truncation?: boolean;\n    /**\n     * The desired dimension of the output embeddings.\n     */\n    outputDimension?: number;\n    /**\n     * The data type of the output embeddings. Can be \"float\" or \"int8\".\n     */\n    outputDtype?: string;\n    /**\n     * The format of the output embeddings. Can be \"float\", \"base64\", or \"ubinary\".\n     */\n    encodingFormat?: string;\n}\n/**\n * Interface for the request body to generate embeddings.\n */\nexport interface CreateVoyageEmbeddingRequest {\n    /**\n     * @type {string}\n     * @memberof CreateVoyageEmbeddingRequest\n     */\n    model: string;\n    /**\n     *  Text to generate vector expectation\n     * @type {CreateEmbeddingRequestInput}\n     * @memberof CreateVoyageEmbeddingRequest\n     */\n    input: string | string[];\n    /**\n     * Input type for the embeddings request.\n     */\n    input_type?: string;\n    /**\n     * Whether to truncate the input texts.\n     */\n    truncation?: boolean;\n    /**\n     * The desired dimension of the output embeddings.\n     */\n    output_dimension?: number;\n    /**\n     * The data type of the output embeddings.\n     */\n    output_dtype?: string;\n    /**\n     * The format of the output embeddings.\n     */\n    encoding_format?: string;\n}\n/**\n * A class for generating embeddings using the Voyage AI API.\n */\nexport declare class VoyageEmbeddings extends Embeddings implements VoyageEmbeddingsParams {\n    modelName: string;\n    batchSize: number;\n    private apiKey;\n    basePath?: string;\n    apiUrl: string;\n    headers?: Record<string, string>;\n    inputType?: string;\n    truncation?: boolean;\n    outputDimension?: number;\n    outputDtype?: string;\n    encodingFormat?: string;\n    /**\n     * Constructor for the VoyageEmbeddings class.\n     * @param fields - An optional object with properties to configure the instance.\n     */\n    constructor(fields?: Partial<VoyageEmbeddingsParams> & {\n        verbose?: boolean;\n        apiKey?: string;\n        inputType?: 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=voyage.d.ts.map"],"mappings":";;;;;;AAKA;AA+BA;AAoCqBI,UAnEJF,sBAAAA,SAA+BD,gBAmEX,CAAA;EAMvBI,SAAAA,EAAAA,MAAAA;EAUmBH;;;;EAhBaF,SAAAA,CAAAA,EAAAA,MAAAA;EAAsBE;AAAsB;;;;;;;;;;;;;;;;;;;;;;;UApCzEC,4BAAAA;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;cAoCIC,gBAAAA,SAAyBJ,UAAAA,YAAsBE;;;;;;YAMtDG;;;;;;;;;;uBAUWC,QAAQJ;;;;;;;;;;mCAUIK;;;;;;4BAMPA"}