import type * as VoyageAI from "./api/index.js";
import type { BaseClientOptions, BaseRequestOptions } from "./BaseClient.js";
import { type NormalizedClientOptionsWithAuth } from "./BaseClient.js";
import * as core from "./core/index.js";
export declare namespace VoyageAIClient {
    type Options = BaseClientOptions;
    interface RequestOptions extends BaseRequestOptions {
    }
}
export declare class VoyageAIClient {
    protected readonly _options: NormalizedClientOptionsWithAuth<VoyageAIClient.Options>;
    constructor(options?: VoyageAIClient.Options);
    /**
     * Voyage embedding endpoint receives as input a string (or a list of strings) and other arguments such as the preferred model name, and returns a response containing a list of embeddings.
     *
     * @param {VoyageAI.EmbedRequest} request
     * @param {VoyageAIClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @example
     *     await client.embed({
     *         input: "input",
     *         model: "model"
     *     })
     */
    embed(request: VoyageAI.EmbedRequest, requestOptions?: VoyageAIClient.RequestOptions): core.HttpResponsePromise<VoyageAI.EmbedResponse>;
    private __embed;
    /**
     * Voyage reranker endpoint receives as input a query, a list of documents, and other arguments such as the model name, and returns a response containing the reranking results.
     *
     * @param {VoyageAI.RerankRequest} request
     * @param {VoyageAIClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @example
     *     await client.rerank({
     *         query: "query",
     *         documents: ["documents"],
     *         model: "model"
     *     })
     */
    rerank(request: VoyageAI.RerankRequest, requestOptions?: VoyageAIClient.RequestOptions): core.HttpResponsePromise<VoyageAI.RerankResponse>;
    private __rerank;
    /**
     * The Voyage multimodal embedding endpoint returns vector representations for a given list of multimodal inputs consisting of text, images, or an interleaving of both modalities.
     *
     * @param {VoyageAI.MultimodalEmbedRequest} request
     * @param {VoyageAIClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @example
     *     await client.multimodalEmbed({
     *         inputs: [{}],
     *         model: "model"
     *     })
     */
    multimodalEmbed(request: VoyageAI.MultimodalEmbedRequest, requestOptions?: VoyageAIClient.RequestOptions): core.HttpResponsePromise<VoyageAI.MultimodalEmbedResponse>;
    private __multimodalEmbed;
    /**
     * The Voyage contextualized embeddings endpoint receives as input a list of documents (each document is a list of chunks), and returns contextualized embeddings for each chunk. The embeddings capture both the local chunk content and the global document context, making them particularly effective for retrieval tasks where understanding document-level context is important.
     *
     * @param {VoyageAI.ContextualizedEmbedRequest} request
     * @param {VoyageAIClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @example
     *     await client.contextualizedEmbed({
     *         inputs: [["inputs"]],
     *         model: "model"
     *     })
     */
    contextualizedEmbed(request: VoyageAI.ContextualizedEmbedRequest, requestOptions?: VoyageAIClient.RequestOptions): core.HttpResponsePromise<VoyageAI.ContextualizedEmbedResponse>;
    private __contextualizedEmbed;
}